U.S. patent number RE48,913 [Application Number 16/535,080] was granted by the patent office on 2022-02-01 for spatially addressable molecular barcoding.
This patent grant is currently assigned to Becton, Dickinson and Company. The grantee listed for this patent is Becton, Dickinson and Company. Invention is credited to Geoffrey Facer, Christina Fan, Stephen P. A. Fodor, Glenn Fu.
United States Patent |
RE48,913 |
Fodor , et al. |
February 1, 2022 |
Spatially addressable molecular barcoding
Abstract
The disclosure provides for methods, compositions, systems,
devices, and kits for determining the number of distinct targets in
distinct spatial locations within a sample. In some examples, the
methods include: stochastically barcoding the plurality of targets
in the sample using a plurality of stochastic barcodes, wherein
each of the plurality of stochastic barcodes comprises a spatial
label and a molecular label; estimating the number of each of the
plurality of targets using the molecular label; and identifying the
spatial location of each of the plurality of targets using the
spatial label. The method can be multiplexed.
Inventors: |
Fodor; Stephen P. A. (Franklin
Lakes, NJ), Fan; Christina (Franklin Lakes, NJ), Fu;
Glenn (Franklin Lakes, NJ), Facer; Geoffrey (Franklin
Lakes, NJ) |
Applicant: |
Name |
City |
State |
Country |
Type |
Becton, Dickinson and Company |
Franklin Lakes |
NJ |
US |
|
|
Assignee: |
Becton, Dickinson and Company
(Franklin Lakes, NJ)
|
Family
ID: |
1000005764861 |
Appl.
No.: |
16/535,080 |
Filed: |
August 8, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
|
|
62162471 |
May 15, 2015 |
|
|
|
|
62126230 |
Feb 27, 2015 |
|
|
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Reissue of: |
15055445 |
Feb 26, 2016 |
9727810 |
Aug 8, 2017 |
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
C12Q
1/6816 (20130101); C12Q 1/6813 (20130101); G06K
19/06103 (20130101); C12Q 1/6813 (20130101); C12Q
2525/179 (20130101); C12Q 2543/10 (20130101); C12Q
2563/155 (20130101); C12Q 1/6816 (20130101); C12Q
2525/179 (20130101); C12Q 2543/10 (20130101); C12Q
2563/155 (20130101) |
Current International
Class: |
G06K
19/06 (20060101); C12Q 1/6813 (20180101); C12Q
1/6816 (20180101) |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
|
|
|
|
|
|
|
2474509 |
|
Feb 2003 |
|
CA |
|
102008025656 |
|
Dec 2009 |
|
DE |
|
0 799 897 |
|
Oct 1997 |
|
EP |
|
1473080 |
|
Nov 2004 |
|
EP |
|
1647600 |
|
Apr 2006 |
|
EP |
|
1845160 |
|
Oct 2007 |
|
EP |
|
2036989 |
|
Mar 2009 |
|
EP |
|
1379693 |
|
May 2009 |
|
EP |
|
2204456 |
|
Jul 2010 |
|
EP |
|
2431465 |
|
Mar 2012 |
|
EP |
|
2203749 |
|
Aug 2012 |
|
EP |
|
2511708 |
|
Oct 2012 |
|
EP |
|
2538220 |
|
Dec 2012 |
|
EP |
|
2623613 |
|
Aug 2013 |
|
EP |
|
1745155 |
|
Oct 2014 |
|
EP |
|
2805769 |
|
Nov 2014 |
|
EP |
|
2556171 |
|
Sep 2015 |
|
EP |
|
2970958 |
|
Dec 2017 |
|
EP |
|
3263715 |
|
Jan 2018 |
|
EP |
|
3136103 |
|
Aug 2018 |
|
EP |
|
2954102 |
|
Dec 2018 |
|
EP |
|
3428290 |
|
Jan 2019 |
|
EP |
|
2970957 |
|
Apr 2019 |
|
EP |
|
3058092 |
|
May 2019 |
|
EP |
|
3256606 |
|
May 2019 |
|
EP |
|
3327123 |
|
Aug 2019 |
|
EP |
|
2293238 |
|
Mar 1996 |
|
GB |
|
H04108385 |
|
Apr 1992 |
|
JP |
|
2001078768 |
|
Mar 2001 |
|
JP |
|
2005233974 |
|
Sep 2005 |
|
JP |
|
2007504831 |
|
Mar 2007 |
|
JP |
|
2008256428 |
|
Oct 2008 |
|
JP |
|
2013039275 |
|
Feb 2013 |
|
JP |
|
WO1989001050 |
|
Feb 1989 |
|
WO |
|
WO1996024061 |
|
Aug 1996 |
|
WO |
|
WO1997010365 |
|
Mar 1997 |
|
WO |
|
WO1999015702 |
|
Apr 1999 |
|
WO |
|
WO1999028505 |
|
Jun 1999 |
|
WO |
|
WO2000058516 |
|
Oct 2000 |
|
WO |
|
WO2001048242 |
|
Jul 2001 |
|
WO |
|
WO2001053539 |
|
Jul 2001 |
|
WO |
|
WO2002018643 |
|
Mar 2002 |
|
WO |
|
WO2002046472 |
|
Jun 2002 |
|
WO |
|
WO2002056014 |
|
Jul 2002 |
|
WO |
|
WO2002059355 |
|
Aug 2002 |
|
WO |
|
WO2002070684 |
|
Sep 2002 |
|
WO |
|
WO2002072772 |
|
Sep 2002 |
|
WO |
|
WO2002079490 |
|
Oct 2002 |
|
WO |
|
WO2002083922 |
|
Oct 2002 |
|
WO |
|
WO2002101358 |
|
Dec 2002 |
|
WO |
|
WO2003035829 |
|
May 2003 |
|
WO |
|
WO2004017374 |
|
Feb 2004 |
|
WO |
|
WO2004021986 |
|
Mar 2004 |
|
WO |
|
WO2004033669 |
|
Apr 2004 |
|
WO |
|
WO2004066185 |
|
Aug 2004 |
|
WO |
|
WO2004081225 |
|
Sep 2004 |
|
WO |
|
WO2005017206 |
|
Feb 2005 |
|
WO |
|
WO2005021731 |
|
Mar 2005 |
|
WO |
|
WO2005042759 |
|
May 2005 |
|
WO |
|
WO2005071110 |
|
Aug 2005 |
|
WO |
|
WO2005080604 |
|
Sep 2005 |
|
WO |
|
WO2005111242 |
|
Nov 2005 |
|
WO |
|
WO2005111243 |
|
Nov 2005 |
|
WO |
|
WO2006026828 |
|
Mar 2006 |
|
WO |
|
WO2006071776 |
|
Jul 2006 |
|
WO |
|
WO2006102264 |
|
Sep 2006 |
|
WO |
|
WO2006137932 |
|
Dec 2006 |
|
WO |
|
WO 2007/087310 |
|
Aug 2007 |
|
WO |
|
WO 2007/087312 |
|
Aug 2007 |
|
WO |
|
WO2007087310 |
|
Aug 2007 |
|
WO |
|
WO2007087312 |
|
Aug 2007 |
|
WO |
|
WO2007147079 |
|
Dec 2007 |
|
WO |
|
WO2008047428 |
|
Apr 2008 |
|
WO |
|
WO2008051928 |
|
May 2008 |
|
WO |
|
WO2008057163 |
|
May 2008 |
|
WO |
|
WO2008096318 |
|
Aug 2008 |
|
WO |
|
WO2008104380 |
|
Sep 2008 |
|
WO |
|
WO2008147428 |
|
Dec 2008 |
|
WO |
|
WO2008150432 |
|
Dec 2008 |
|
WO |
|
WO2009048530 |
|
Apr 2009 |
|
WO |
|
WO 2009/148560 |
|
Dec 2009 |
|
WO |
|
WO 2009/152928 |
|
Dec 2009 |
|
WO |
|
WO2009148560 |
|
Dec 2009 |
|
WO |
|
WO2009152928 |
|
Dec 2009 |
|
WO |
|
WO2010059820 |
|
May 2010 |
|
WO |
|
WO2010117620 |
|
Oct 2010 |
|
WO |
|
WO2011091393 |
|
Jul 2011 |
|
WO |
|
WO2011106738 |
|
Sep 2011 |
|
WO |
|
WO2011123246 |
|
Oct 2011 |
|
WO |
|
WO2011127099 |
|
Oct 2011 |
|
WO |
|
WO2011143659 |
|
Nov 2011 |
|
WO |
|
WO2011155833 |
|
Dec 2011 |
|
WO |
|
WO 20118155833 |
|
Dec 2011 |
|
WO |
|
WO2012038839 |
|
Mar 2012 |
|
WO |
|
WO 2012/042374 |
|
Apr 2012 |
|
WO |
|
WO 2012/047297 |
|
Apr 2012 |
|
WO |
|
WO 2012/048341 |
|
Apr 2012 |
|
WO |
|
WO2012041802 |
|
Apr 2012 |
|
WO |
|
WO2012042374 |
|
Apr 2012 |
|
WO |
|
WO2012047297 |
|
Apr 2012 |
|
WO |
|
WO2012048341 |
|
Apr 2012 |
|
WO |
|
WO2012083225 |
|
Jun 2012 |
|
WO |
|
WO2012099896 |
|
Jul 2012 |
|
WO |
|
WO2012103154 |
|
Aug 2012 |
|
WO |
|
WO2012108864 |
|
Aug 2012 |
|
WO |
|
WO2012112804 |
|
Aug 2012 |
|
WO |
|
WO2012129363 |
|
Sep 2012 |
|
WO |
|
WO 2012/140224 |
|
Oct 2012 |
|
WO |
|
WO 2012/142213 |
|
Oct 2012 |
|
WO |
|
WO2012140224 |
|
Oct 2012 |
|
WO |
|
WO2012142213 |
|
Oct 2012 |
|
WO |
|
WO 2012/149042 |
|
Nov 2012 |
|
WO |
|
WO2012148477 |
|
Nov 2012 |
|
WO |
|
WO2012148497 |
|
Nov 2012 |
|
WO |
|
WO2012149042 |
|
Nov 2012 |
|
WO |
|
WO2012156744 |
|
Nov 2012 |
|
WO |
|
WO2012162267 |
|
Nov 2012 |
|
WO |
|
WO2013019075 |
|
Feb 2013 |
|
WO |
|
WO2013070990 |
|
May 2013 |
|
WO |
|
WO2013096802 |
|
Jun 2013 |
|
WO |
|
WO2013117595 |
|
Aug 2013 |
|
WO |
|
WO2013130674 |
|
Sep 2013 |
|
WO |
|
WO2013148525 |
|
Oct 2013 |
|
WO |
|
WO2013173394 |
|
Nov 2013 |
|
WO |
|
WO2013176767 |
|
Nov 2013 |
|
WO |
|
WO2013177206 |
|
Nov 2013 |
|
WO |
|
WO2013188831 |
|
Dec 2013 |
|
WO |
|
WO2013188872 |
|
Dec 2013 |
|
WO |
|
WO2013191775 |
|
Dec 2013 |
|
WO |
|
WO2014015084 |
|
Jan 2014 |
|
WO |
|
WO2014015098 |
|
Jan 2014 |
|
WO |
|
WO2014018093 |
|
Jan 2014 |
|
WO |
|
WO2014018460 |
|
Jan 2014 |
|
WO |
|
WO2014028537 |
|
Feb 2014 |
|
WO |
|
WO 2014/071361 |
|
May 2014 |
|
WO |
|
WO2014065756 |
|
May 2014 |
|
WO |
|
WO2014093676 |
|
Jun 2014 |
|
WO |
|
WO2014108850 |
|
Jul 2014 |
|
WO |
|
WO 2014/124336 |
|
Aug 2014 |
|
WO |
|
WO 2014/124338 |
|
Aug 2014 |
|
WO |
|
WO 2014/126937 |
|
Aug 2014 |
|
WO |
|
WO2014124046 |
|
Aug 2014 |
|
WO |
|
WO2014124336 |
|
Aug 2014 |
|
WO |
|
WO2014124338 |
|
Aug 2014 |
|
WO |
|
WO2014126937 |
|
Aug 2014 |
|
WO |
|
WO2014144495 |
|
Sep 2014 |
|
WO |
|
WO2014145458 |
|
Sep 2014 |
|
WO |
|
WO2014176575 |
|
Oct 2014 |
|
WO |
|
WO2014200767 |
|
Dec 2014 |
|
WO |
|
WO2014201273 |
|
Dec 2014 |
|
WO |
|
WO2014204939 |
|
Dec 2014 |
|
WO |
|
WO2014210223 |
|
Dec 2014 |
|
WO |
|
WO2014210225 |
|
Dec 2014 |
|
WO |
|
WO2014210353 |
|
Dec 2014 |
|
WO |
|
WO2015002908 |
|
Jan 2015 |
|
WO |
|
WO2015031691 |
|
Mar 2015 |
|
WO |
|
WO2015035087 |
|
Mar 2015 |
|
WO |
|
WO2015044428 |
|
Apr 2015 |
|
WO |
|
WO2015047186 |
|
Apr 2015 |
|
WO |
|
WO2015057985 |
|
Apr 2015 |
|
WO |
|
WO2014071361 |
|
May 2015 |
|
WO |
|
WO2015061844 |
|
May 2015 |
|
WO |
|
WO2015103339 |
|
Jul 2015 |
|
WO |
|
WO2015117163 |
|
Aug 2015 |
|
WO |
|
WO2015134787 |
|
Sep 2015 |
|
WO |
|
WO2015168161 |
|
Nov 2015 |
|
WO |
|
WO2015179339 |
|
Nov 2015 |
|
WO |
|
WO2015200869 |
|
Dec 2015 |
|
WO |
|
WO2015200893 |
|
Dec 2015 |
|
WO |
|
WO2016044227 |
|
Mar 2016 |
|
WO |
|
WO2016049418 |
|
Mar 2016 |
|
WO |
|
WO2016061517 |
|
Apr 2016 |
|
WO |
|
WO2016100976 |
|
Jun 2016 |
|
WO |
|
WO2016118915 |
|
Jul 2016 |
|
WO |
|
WO2016130578 |
|
Aug 2016 |
|
WO |
|
WO2016160965 |
|
Aug 2016 |
|
WO |
|
WO2016138496 |
|
Sep 2016 |
|
WO |
|
WO2016138500 |
|
Sep 2016 |
|
WO |
|
WO2016145409 |
|
Sep 2016 |
|
WO |
|
WO2016149418 |
|
Sep 2016 |
|
WO |
|
WO2016160844 |
|
Oct 2016 |
|
WO |
|
WO2016168825 |
|
Oct 2016 |
|
WO |
|
WO2016172373 |
|
Oct 2016 |
|
WO |
|
WO2016190795 |
|
Dec 2016 |
|
WO |
|
WO2016191272 |
|
Dec 2016 |
|
WO |
|
WO2017032808 |
|
Mar 2017 |
|
WO |
|
WO2017040306 |
|
Mar 2017 |
|
WO |
|
WO2017044574 |
|
Mar 2017 |
|
WO |
|
WO2017053905 |
|
Mar 2017 |
|
WO |
|
WO2017079593 |
|
May 2017 |
|
WO |
|
WO2017097939 |
|
Jun 2017 |
|
WO |
|
WO2017117358 |
|
Jul 2017 |
|
WO |
|
WO2017125508 |
|
Jul 2017 |
|
WO |
|
WO2017139690 |
|
Aug 2017 |
|
WO |
|
WO2017164936 |
|
Sep 2017 |
|
WO |
|
WO2017173328 |
|
Oct 2017 |
|
WO |
|
WO2017205691 |
|
Nov 2017 |
|
WO |
|
WO2018017949 |
|
Jan 2018 |
|
WO |
|
WO2018020489 |
|
Feb 2018 |
|
WO |
|
WO2018031631 |
|
Feb 2018 |
|
WO |
|
WO2018058073 |
|
Mar 2018 |
|
WO |
|
WO2018064640 |
|
Apr 2018 |
|
WO |
|
WO2018075693 |
|
Apr 2018 |
|
WO |
|
WO2018111872 |
|
Jun 2018 |
|
WO |
|
WO2018115852 |
|
Jun 2018 |
|
WO |
|
WO2018119447 |
|
Jun 2018 |
|
WO |
|
WO2018140966 |
|
Aug 2018 |
|
WO |
|
WO2018144240 |
|
Aug 2018 |
|
WO |
|
WO2018144813 |
|
Aug 2018 |
|
WO |
|
WO2018174827 |
|
Sep 2018 |
|
WO |
|
WO2018217862 |
|
Nov 2018 |
|
WO |
|
WO2018218222 |
|
Nov 2018 |
|
WO |
|
WO2018222548 |
|
Dec 2018 |
|
WO |
|
WO2018226293 |
|
Dec 2018 |
|
WO |
|
WO2019055852 |
|
Mar 2019 |
|
WO |
|
WO2019076768 |
|
Apr 2019 |
|
WO |
|
WO2019113457 |
|
Jun 2019 |
|
WO |
|
WO2019113499 |
|
Jun 2019 |
|
WO |
|
WO2019113506 |
|
Jun 2019 |
|
WO |
|
WO2019113533 |
|
Jun 2019 |
|
WO |
|
WO2019118355 |
|
Jun 2019 |
|
WO |
|
WO2019126789 |
|
Jun 2019 |
|
WO |
|
WO2019157529 |
|
Aug 2019 |
|
WO |
|
WO2013137737 |
|
Sep 2019 |
|
WO |
|
WO2019178164 |
|
Sep 2019 |
|
WO |
|
WO2019213237 |
|
Nov 2019 |
|
WO |
|
WO2019213294 |
|
Nov 2019 |
|
WO |
|
WO2020028266 |
|
Feb 2020 |
|
WO |
|
WO2020033164 |
|
Feb 2020 |
|
WO |
|
WO2020037065 |
|
Feb 2020 |
|
WO |
|
WO2020046833 |
|
Mar 2020 |
|
WO |
|
WO2020072380 |
|
Apr 2020 |
|
WO |
|
WO2020097315 |
|
May 2020 |
|
WO |
|
WO2020123384 |
|
Jun 2020 |
|
WO |
|
WO2020154247 |
|
Jul 2020 |
|
WO |
|
WO2020167920 |
|
Aug 2020 |
|
WO |
|
WO2020214642 |
|
Oct 2020 |
|
WO |
|
WO2021146207 |
|
Jul 2021 |
|
WO |
|
WO2021146219 |
|
Jul 2021 |
|
WO |
|
WO2021146636 |
|
Jul 2021 |
|
WO |
|
WO2021155057 |
|
Aug 2021 |
|
WO |
|
WO2021155284 |
|
Aug 2021 |
|
WO |
|
Other References
10X Genomics, Inc., 2019, User Guide: Visium Spatial Gene
Expression Reagent Kits, www.10xGenomics.com, 76 pp. cited by
applicant .
2018 Top 10 Innovations, The Scientist Magazine.RTM. (2018).
Available at:
https://www.thescientist.com/features/2018-top-10-innovations-65140,
16 pp. cited by applicant .
Achim et al., "High-throughput spatial mapping of single-cell
RNA-seq data to tissue of origin," Nature Biotechnology 2015,
33(5), 503-511. cited by applicant .
Advisory Action dated Nov. 29, 2019 in U.S. Appl. No. 15/084,307.
cited by applicant .
Advisory Action dated Dec. 2, 2019 in U.S. Appl. No. 15/055,407.
cited by applicant .
Advisory Action dated Aug. 25, 2020 in U.S. Appl. No. 15/084,307.
cited by applicant .
Agasti et al., "Photocleavable DNA barcode-antibody conjugates
allow sensitive and multiplexed protein analysis in single cell," J
Am Chem Soc. 2012, 134(45), 18499-18502. cited by applicant .
Alexandra M. Ewing of Richards, Layton and Finger, P.A., Entry of
Appearance dated Jan. 18, 2019 in the USDC District of Delaware,
C.A. No. 18-1800-RGA, 1 pp. cited by applicant .
Alkan et al., "Personalized copy number and segmental duplication
maps using next-generation sequencing," Nat Genet. 2009,
41(10):1061-1067. cited by applicant .
Anderson, "Study Describes RNA Sequencing Applications for
Molecular Indexing Methods," GenomeWeb 2014, 5 pp. cited by
applicant .
Ansorge, "Next-generation DNA sequencing techniques," New
Biotechnology 2009, 25(4), 195-203. cited by applicant .
Applied Biosystems, Apr. 2008, SOLiD.TM. System Barcoding,
Application Note, 4 pp. cited by applicant .
Argrawal et al., "Counting Single Native Biomolecules and Intact
Viruses with Color-Coded Nanoparticles," Analytical Chemistry 2006,
78, 1061-1070. cited by applicant .
Arslan et al., "An efficient algorithm for the stochastic
simulation of the hybridization of DNA to microarrays," BMC
Bioinformatics 2009, 10(411), 1-17. cited by applicant .
Atanur et al., "The genome sequence of the spontaneously
hypertensive rat: Analysis and functional significance." Genome
Res. 2010, 20(6), 791-803. cited by applicant .
Audic et al., "The Significance of Digital Gene Expression
Profiles," Genome Res. 1997, 7, 986-995. cited by applicant .
Baek et al., "Development of Hydrogel TentaGel Shell-Core Beads for
Ultra-high Throughput Solution Phase Screening of Encoded OBOC
Combinatorial Small Molecule Libraries," J. Comb Chem. 2009, 11(1),
91-102. cited by applicant .
BD Life Sciences, 2018, BD AbSeq antibody-oligo conjugates,
www.bd.com/genomics, 2 pp. cited by applicant .
BD Life Sciences, 2018, BD AbSeq on the BD Rhapsody system:
Exploration of single-cell gene regulation by simultaneous digital
mRNA and protein quantification, www.bd.com/genomics, 7 pp. cited
by applicant .
Bendall et al., "Single-Cell Mass Cytometry of Differential Immune
and Drug Responses Across a Human Hematopoietic Continuum," Science
2011, 332(6030), 687-696. cited by applicant .
Bionumbers, Aug. 21, 2010, "Useful fundamental numbers in molecular
biology," http://bionumbers.hms.harvard.edu/KeyNumbers/aspx, 1-4.
cited by applicant .
Biosciences Product Catalogue, Dynal.RTM. Catalog 1999, Oslo,
Norway, 49-51. cited by applicant .
Bioscribe "Massively parallel sequencing technology for single-cell
gene expression published" (press release), PhysOrg 2015, 1-2.
cited by applicant .
Blainey, "The future is now: single-cell genomics of bacteria and
archaea," FEMS Microbiol Rev. 2013, 37(3), 407-427. cited by
applicant .
Bogdanova et al., "Normalization of full-length enriched cDNA,"
Molecular Biosystems 2008, 4(3), 205-212. cited by applicant .
Bonaldo et al., "Normalization and Subtraction: Two Approaches to
facilitate Gene Discovery," Genome Res. 1996, 6, 791-806. cited by
applicant .
Bontoux et al., "Integrating whole transcriptome assays on a
lab-on-a-chip for single cell gene profiling", Lab on a Chip 2008,
8(3), 443-450. cited by applicant .
Bose et al., "Scalable microfluidics for single-cell RNA printing
and sequencing," Genome Biology 2015, 16(120), 1-16. cited by
applicant .
Brady et al., "Construction of cDNA libraries form single cells",
Methods in Enzymology 1993, (225), 611-623. cited by applicant
.
Braha et al., "Simultaneous stochastic sensing of divalent metal
ions," Nature Biotechnology 2000, 18, 1005-1007. cited by applicant
.
Bratke et al., "Differential expression of human granzymes A, B,
and K in natural killer cells and during CD8+ T cell
differentiation in peripheral blood," Eur J Immunol. 2005, 35,
2608-2616. cited by applicant .
Brenner et al., "Gene expression analysis by massively parallel
signature sequencing (MPSS) on microbead arrays," Nature
Biotechnology 2000, 18, 630-634. cited by applicant .
Brenner et al., "In vitro cloning of complex mixtures of DNA on
microbeads: Physical separation of differentially expressed cDNAs,"
PNAS 2000, 97(4), 1665-1670. cited by applicant .
Brinza et al., "Detection of somatic mutations at 0.1% frequency
from cfDNA in peripheral blood with a multiplex next-generation
sequencing assay," Conference Poster, AACR 107th Annual Meeting,
Apr. 16-20, 2016, 1 p. cited by applicant .
Brisco et al., "Quantification of RNA integrity and its use for
measurement of transcript number," Nucleic Acids Research 2012,
40(18), e144, 1-9. cited by applicant .
Brodin et al., "Challenges with Using Primer IDs to Improve
Accuracy of Next Generation Sequencing," PLoS One 2015, 19(3),
1-12. cited by applicant .
Buggenum et al., "A covalent and cleavable antibody DNA conjugation
strategy for sensitive protein detection via immunoPCR," Scientific
Reports 2016, 6(22675), 1-12. cited by applicant .
Buschmann et al., Enhancing the detection of barcoded reads in high
throughput DNA sequencing DNA by controlling the false discovery
rate, BMC Bioinformatics, 15(1), 264, 1-16. 2014. cited by
applicant .
Bustin, "Absolute quantification of mRNA using real-time reverse
transcription polymerase chain reaction assays," Journal of
Molecular Endocrinology 2000, 25, 169-193. cited by applicant .
Butkus, "Cellular research set to launch first gene expression
platform using `molecular indexing` technology," GenomeWeb 2014,
1-5. cited by applicant .
Cai, "Turning single cells in microarrays by super-resolution
bar-coding," Briefings in Functional Genomics 2012, 12(2), 75-80.
cited by applicant .
Cao et al., "Comprehensive single-cell transcriptional profiling of
a multicellular organism," Science 2017, 357, 661-667. cited by
applicant .
Carr et al., "Inferring relative proportions of DNA variants from
sequencing electropherograms," Bioinformatics 2009, 25(24),
3244-3250. cited by applicant .
Caruccio et al., "Nextera (TM) Technology for NGS DNA Library
Preparation: Simultaneous Fragmentation and Tagging by in Vitro
Transposition," EpiBio 2009, 16(3), 4-6. cited by applicant .
Casbon et al., "A method for counting PCR template molecules with
application to next-generation sequencing," Nucleic Acids Res.
2011, 39(12), e81, 1-8. cited by applicant .
Castellarnau et al., "Stochastic particle barcoding for single-cell
tracking and multiparametric analysis," Small 2015, 11(4), 489-498.
cited by applicant .
Castle et al., "DNA copy number, including telomeres and
mitochondria, assayed using next-generation sequencing," BMC
Genomics 2010, 11(244), 1-11. cited by applicant .
Chamberlain et al., "Deletion screening of the Duchenne muscular
dystrophy locus via multiplex DNA amplification," Nucleic Acids
Res. 1988, 16(23), 11141-11156. cited by applicant .
Chang et al., "Detection of Allelic Imbalance in Ascitic
Supernatant by Digital Single Nucleotide Polymorphism Analysis,"
Clinical Cancer Research, 8, 2580-2585, 2002. cited by applicant
.
Chapin et al., "Rapid microRNA Profiling on Encoded Gel
Microparticles," Angew Chern Int Ed Engl. 2011, 50(10), 2289-2293.
cited by applicant .
Chee et al., "Accessing genetic information with high-density DNA
arrays," Science 1996, 274, 610-614. cited by applicant .
Chee, "Enzymatic multiplex DNA sequencing," Nucleic Acids Research
1991, 19(12), 3301-3305. cited by applicant .
Chen et al., "Spatially resolved, highly multiplexed RNA profiling
in single cells," Science Express 2015, 348(6233), aaa6090, 1-36.
cited by applicant .
Church et al., "Multiplex DNA sequencing," Science 1988, 240(4849),
185-188. cited by applicant .
Civil Cover Sheet filed Nov. 15, 2018 in the USDC for the District
of Delaware, C.A. 18-1800-RGA, 1 pp. cited by applicant .
Clontech Laboratories, Inc., "Smart.TM. PCR cDNA Synthesis Kit User
Manual," Clontech 2007, 1-39. cited by applicant .
Cloonan et al., "Stem cell transcriptome profiling via
massive-scale mRNA sequencing", Nature Methods 2008, 5(7), 613-619.
cited by applicant .
Combined Search and Examination Report dated Aug. 6, 2014 in UK
Patent Application No. 1408829.8. cited by applicant .
Combined Search and Examination Report dated Feb. 21, 2017 in UK
Patent Application No. 1609740.4. cited by applicant .
Communication of a Notice of Opposition dated Jul. 21, 2016 in
European Patent Application No. EP 10762102.1. cited by applicant
.
Complaint filed in Becton, Dickinson and Company and Cellular
Research Inc. v. 10X Genomics, Inc. dated Nov. 15, 2018 in the USDC
for the District of Delaware, C.A. 18-1800-RGA, 141 pp. cited by
applicant .
Costa et al., "Single-Tube Nested Real-Time PCR as a New Highly
Sensitive Approach to Trace Hazelnut," Journal of Agricultural and
Food Chemistry 2012, 60, 8103-8110. cited by applicant .
Costello et al., "Discovery and characterization of artefactual
mutations in deep coverage targeted capture sequencing data due to
oxidative DNA damage during sample preparation," Nucleic Acids Res
2013, 41(6), e67, 1-12. cited by applicant .
Cotten et al., "Selection of proteins with desired properties from
natural proteome libraries using mRNA display," Nature Protocols
2011, 6, 1163-1182. cited by applicant .
Cox, "Bar coding objects with DNA," Analyst 2001, 126, 545-547.
cited by applicant .
Craig et al., "Identification of genetic variants using bar-coded
multiplexed sequencing," Nat Methods 2008, 5(10), 887-893. cited by
applicant .
Cusanovich et al., "Multiplex single-cell profiling of chromatin
accessibility by combinatorial cellular indexing," Science 2015,
348(6237), 910-914. cited by applicant .
Custom Antibody Services, Precision Antibody, accessed Apr. 16,
2014, 2 pp. cited by applicant .
Daines et al., "High-throughput multiplex sequencing to discover
copy number variants in Drosophila," Genetics 2009, 182(4), 182,
935-941. cited by applicant .
Dalerba et al., "Single-cell dissection of transcriptional
heterogeneity in human colon tumors," Nat Biotechnol. 2011, 29(12),
1120-1127. cited by applicant .
D'Antoni et al., "Rapid quantitative analysis using a single
molecule counting approach," Anal Biochem. 2006, 352, 97-109. cited
by applicant .
Daser et al., "Interrogation of genomes by molecular copy-number
counting (MCC)," Nature Methods 2006, 3(6), 447-453. cited by
applicant .
Day et al., "Immobilization of polynucleotides on magnetic
particles," Biochem. J. 1991, 278, 735-740. cited by applicant
.
Decision of Refusal dated Aug. 21, 2017 in Japanese Patent
Application No. 2014-558975. cited by applicant .
Defendant 10X Genomics, Inc.'s Letter to Judge Andrews in Response
to Plaintiff's Letter of Supplemental Authority, dated Jul. 11,
2019 in the USDC for the District of Delaware, C.A. 18-1800-RGA, 2
pp. cited by applicant .
Defendant 10X Genomics Motion for Admission Pro Hac Vice of Paul
Ehrlich, Azra Hadzimehmedovic and Aaron Nathan, Pursuant to Local
Rule 83.5, dated May 1, 2019 in the USDC for the District of
Delaware, C.A. 18-1800-RGA, 5 pp. cited by applicant .
Defendant 10X Genomics, Inc.'s Motion for Admission Pro Hac Vice
Pursuant to Local Rule 83.5, dated Jan. 18, 2019 in the USDC
District of Delaware, C.A. No. 18-1800-RGA, 5 pp. cited by
applicant .
Defendant 10X Genomics, Inc.'s Motion to Dismiss Pursuant to
Federal Rule of Civil Procedure 12(b)(6), dated Jan. 18, 2019 in
the USDC for the District of Delaware, C.A. 18-1800-RGA, 1 pp.
cited by applicant .
Defendant 10X Genomics, Inc.'s Motion to Dismiss the First Amended
Complaint Pursuant to Federal Rule of Civil Procedure 12(b)(6),
dated Mar. 1, 2019 in the USDC for the District of Delaware, C.A.
18-1800-RGA, 1 pp. cited by applicant .
Defendant 10X Genomics Notice of Service for Initial Disclosures
served to Opposing Counsel, dated Jun. 7, 2019 in the USDC for the
District of Delaware, C.A. 18-1800-RGA, 2 pp. cited by applicant
.
Defendant 10X Genomic Inc.'s Notice of Service for Initial Requests
for Production and Interrogatories Served to Becton, Dickinson, and
Company and Cellular Research, Inc., dated May 31, 2019 in the USDC
for the District of Delaware, C.A. 18-1800-RGA, 2 pp. cited by
applicant .
Defendant 10X Genomics Inc's, Notice of Service of Technical
Documents, dated Jul. 8, 2019 in the USDC for the District of
Delaware, C.A. 18-1800-RGA, 2 pp. cited by applicant .
Defendant 10X Genomics, Inc.'s Opening Brief in Support of Its
Motion to Dismiss Pursuant to Federal Rule of Civil Procedure
12(b)(6), dated Jan. 18, 2019 in the USDC District of Delaware,
C.A. No. 1:18-cv-01800-RGA, 25 pp. cited by applicant .
Defendant 10X Genomics, Inc.'s Opening Brief in Support of Its
Motion to Dismiss Pursuant to Federal Rule of Civil Procedure
12(b)(6), dated Mar. 1, 2019 in the USDC District of Delaware, C.A.
No. 18-1800 RGA, 26 pp. cited by applicant .
Defendant 10X Genomics, Inc.'s [Proposed] Order for Partial
Dismissal Pursuant to Federal Rules of Civil Procedure 12(b)(6),
dated Jan. 18, 2019 in the USDC District of Delaware, C.A. No.
18-1800-RGA, 1 pp. cited by applicant .
Defendant 10X Genomics, Inc's Proposed Order for Dismissal pursuant
to Federal Rules of Civil Procedure 12(b)(6), filed Mar. 1, 2019 in
the USDC for the District of Delaware, C.A. 18-1800-RGA, 1 pp.
cited by applicant .
Defendant 10X Genomics Reply Brief in Support of its Motion to
Dismiss Pursuant to Federal Rule of Civil Procedure 12(b)(6), dated
Apr. 12, 2019 in the USDC for the District of Delaware, C.A. No.
18-1800-RGA, 15 pp. cited by applicant .
Defendant 10X Genomics Request for Oral Argument Under D. Del. LR
7.1.4, dated Apr. 18, 2019 in the USDC for the District of
Delaware, C.A. 18-1800-RGA 2 pp. cited by applicant .
Defendant 10X Genomics Response Letter to Judge Richard G. Andrews
re Request for a Rule 16, dated Apr. 16, 2019 in the USDC for the
District of Delaware, C.A. 18-1800-RGA, 2 pp. cited by applicant
.
Defendant 10X Genomics, Inc.'s Rule 7.1 Disclosure Statement, dated
Jan. 18, 2019 in the USDC District of Delaware, C.A. No.
18-1800-RGA, 1 pp. 1. cited by applicant .
Delley et al., "Combined aptamer and transcriptome sequencing of
single cells," bioRxiv2017, 1-10. cited by applicant .
De Saizieu et al., "Bacterial transcript imaging by hybridization
of total RNA to oligonucleotide arrays," Nature Biotechnology 1988,
16, 45-48. cited by applicant .
Di Carlo et al., "Dynamic single-cell analysis for quantitative
biology," Analytical Chemistry 2006, 78(23), 7918-7925. cited by
applicant .
Dirks et al., Triggered amplification by hybridization chain
reaction., Proc Natl Acad Sci 2014, 101(43), 15275-15278. cited by
applicant .
Dube et al., "Mathematical Analysis of Copy Number Variation in a
DNA Sample Using Digital PCR on a Nanofluidic Device," PLoS One
2008, 3(8) e2876. cited by applicant .
Eberwine et al., "Analysis of gene expression in single live
neurons," Proc. Natl. Acad. Sci. 1992, 89, 3010-3014. cited by
applicant .
Evanko et al., "Hybridization chain reaction," Nature Methods 2004,
1(3), 186-187. cited by applicant .
Examination Report dated Oct. 24, 2017 in Australian Patent
Application No. 2013226081. cited by applicant .
Examination Report dated Jul. 20, 2018 in Australian Patent
Application No. 2014312208. cited by applicant .
Examination Report dated May 12, 2020 in Australian Patent
Application No. 2018220004. cited by applicant .
Examination Report dated Apr. 10, 2017 in European Patent
Application No. 14761937.3. cited by applicant .
Examination Report dated Oct. 10, 2017 in European Patent
Application No. 14761937.3. cited by applicant .
Examination Report dated Mar. 16, 2018 in European Patent
Application No. 13754428.4. cited by applicant .
Examination Report dated Sep. 5, 2018 in European Patent
Application No. 16710357.1. cited by applicant .
Examination Report dated Sep. 26, 2018 in European Patent
Application No. 16714081.3. cited by applicant .
Examination Report dated Dec. 12, 2018 in European Patent
Application No. 16719706.0. cited by applicant .
Examination Report dated Jan. 2, 2019 in European Patent
Application No. 16757986.1. cited by applicant .
Examination Report dated Feb. 6, 2019 in European Patent
Application No. 13754428.4. cited by applicant .
Examination Report dated Apr. 26, 2019 in European Patent
Application No. 16710357.1. cited by applicant .
Examination Report dated Jun. 18, 2019 in European Patent
Application No. 16710551.9. cited by applicant .
Examination Report dated Jul. 24, 2019 in European Patent
Application No. 16714081.3. cited by applicant .
Examination Report dated Aug. 2, 2019 in European Patent
Application No. 17202409.3. cited by applicant .
Examination Report dated Oct. 11, 2019 in European Patent
Application No. 16757986.1. cited by applicant .
Examination Report dated Dec. 4, 2019 in European Patent
Application No. 16719706.0. cited by applicant .
Examination Report dated Feb. 19, 2020 in European Patent
Application No. 16710551.9. cited by applicant .
Examination Report dated Mar. 18, 2020 in European Patent
Application No. 17202409.3. cited by applicant .
Examination Report dated Jul. 6, 2020 in European Patent
Application No. 17781265.8. cited by applicant .
Examination Report dated Sep. 21, 2020 in European Patent
Application No. 18703156.2. cited by applicant .
Examination Report dated Mar. 18, 2019 in Singapore Patent
Application No. 11201405274W. cited by applicant .
Examination Report dated Jan. 27, 2016 in United Kingdom Patent
Application No. 1408829.8. cited by applicant .
Examination Report dated Feb. 19, 2016 in United Kingdom Patent
Application No. GB1511591.8. cited by applicant .
Examination Report dated Jun. 8, 2016 in United Kingdom Patent
Application No. 1408829.8. cited by applicant .
Examination Report dated Jun. 15, 2016 in United Kingdom Patent
Application No. GB1511591.8. cited by applicant .
Examination Report dated Jan. 3, 2018 in United Kingdom Patent
Application No. 1609740.4. cited by applicant .
Exhibit A filed Jul. 10, 2019 in the USDC for the District of
Delaware, C.A. 18-1800-RGA, 25 pp. cited by applicant .
Exhibits 12-32 filed Feb. 8, 2019 in the USDC for the District of
Delaware, C.A. 18-1800-RGA, 795 pp. cited by applicant .
Exhibits A-D filed Jan. 18, 2019 in the USDC District of Delaware,
C.A. No. 1:18-cv-01800-RGA, 47 pp. cited by applicant .
Exhibits A-E filed Mar. 1, 2019 in the USDC District of Delaware,
C.A. No. 18-1800 RGA, 75 pp. cited by applicant .
Extended European Search Report dated Jul. 17, 2015 in European
Patent Application No. 13755319.4. cited by applicant .
Extended European Search Report dated Dec. 14, 2015 in European
Patent Application No. 13754428.4. cited by applicant .
Extended European Search Report dated Feb. 8, 2018 in European
Patent Application No. 17202409.3. cited by applicant .
Extended European Search Report dated Jun. 11, 2018 in European
Patent Application No. 16740872.3. cited by applicant .
Extended European Search Report dated Mar. 22, 2019 in European
Patent Application No. 18195513.9. cited by applicant .
Fan et al., "Parallel Genotyping of Human SNPs Using Generic
High-density Oligonucleotide Tag Arrays," Genome Research 2000, 10,
853-860. cited by applicant .
Fan et al., "Microfluidic digital PCR enables rapid prenatal
diagnosis of fetal aneuploidy," Am Obstet Gynecol. 2009, 200,
543e1-543e7. cited by applicant .
Fan, "Molecular counting: from noninvasive prenatal diagnostics to
whole-genome haplotyping," Doctoral Dissertation, Stanford
University 2010, 1-185. cited by applicant .
Fan et al., "Non-invasive Prenatal Measurement of the Fetal
Genome," Nature 2012, 487(7407), 320-324. cited by applicant .
Fan et al., "Combinatorial labeling of single cells for gene
expression cytometry," Science 2015, 347(6222), 1258366-1258369.
cited by applicant .
Feldhaus et al., "Oligonucleotide-conjugated beads for
transdominant genetic experiments," Nucleic Acids Res. 2000, 28(2),
534-543. cited by applicant .
Final Office Action dated Sep. 1, 2015 for U.S. Appl. No.
14/540,029. cited by applicant .
Final Office Action dated Sep. 24, 2015 for U.S. Appl. No.
14/540,007. cited by applicant .
Final Office Action dated Oct. 6, 2015 in U.S. Appl. No.
14/540,018. cited by applicant .
Final Office Action dated Apr. 11, 2016 for U.S. Appl. No.
14/800,526. cited by applicant .
Final Office Action dated Jul. 20, 2016 for U.S. Appl. No.
14/281,706. cited by applicant .
Final Office Action dated Aug. 12, 2016 in U.S. Appl. No.
14/381,488. cited by applicant .
Final Office Action dated Feb. 13, 2017 in U.S. Appl. No.
14/381,488. cited by applicant .
Final Office Action dated May 8, 2017 in U.S. Appl. No. 15/224,460.
cited by applicant .
Final Office Action dated Oct. 16, 2017 in U.S. Appl. No.
15/409,355. cited by applicant .
Final Office Action dated Nov. 16, 2017 in U.S. Appl. No.
14/381,488. cited by applicant .
Final Office Action dated Jan. 25, 2018 in U.S. Appl. No.
14/381,526. cited by applicant .
Final Office Action dated May 3, 2018 in U.S. Appl. No. 15/046,225.
cited by applicant .
Final Office Action dated May 10, 2018 in U.S. Appl. No.
14/381,488. cited by applicant .
Final Office Action dated Jul. 5, 2018 in U.S. Appl. No.
15/004,618. cited by applicant .
Final Office Action dated Jul. 20, 2018 in U.S. Appl. No.
15/217,886. cited by applicant .
Final Office Action dated Nov. 16, 2018 in U.S. Appl. No.
15/134,967. cited by applicant .
Final Office Action dated Feb. 19, 2019 in U.S. Appl. No.
14/381,526. cited by applicant .
Final Office Action dated Mar. 1, 2019 in U.S. Appl. No.
16/012,584. cited by applicant .
Final Office Action dated Apr. 22, 2019 in U.S. Appl. No.
15/987,851. cited by applicant .
Final Office Action dated May 2, 2019 in U.S. Appl. No. 16/012,635.
cited by applicant .
Final Office Action dated May 3, 2019 in U.S. Appl. No. 15/937,713.
cited by applicant .
Final Office Action dated Sep. 18, 2019 in U.S. Appl. No.
15/055,407. cited by applicant .
Final Office Action dated Oct. 2, 2019 in U.S. Appl. No.
15/084,307. cited by applicant .
Final Office Action dated Dec. 4, 2019 in U.S. Appl. No.
15/596,364. cited by applicant .
Final Office Action dated Jan. 8, 2020 in U.S. Appl. No.
15/459,977. cited by applicant .
Final Office Action dated Jan. 16, 2020 in U.S. Appl. No.
16/012,584. cited by applicant .
Final Office Action dated Jan. 29, 2020 in U.S. Appl. No.
14/381,488. cited by applicant .
Final Office Action dated Feb. 4, 2020 in U.S. Appl. No.
15/715,028. cited by applicant .
Final Office Action dated Mar. 9, 2020 in U.S. Appl. No.
15/987,851. cited by applicant .
Final Office Action dated Apr. 28, 2020 in U.S. Appl. No.
15/134,967. cited by applicant .
Final Office Action dated Jun. 5, 2020 in U.S. Appl. No.
15/084,307. cited by applicant .
Final Office Action dated Aug. 19, 2020 in U.S. Appl. No.
15/875,816. cited by applicant .
Final Office Action dated Sep. 14, 2020 in U.S. Appl. No.
16/789,358. cited by applicant .
Final Office Action dated Sep. 22, 2020 in U.S. Appl. No.
16/789,311. cited by applicant .
Final Office Action dated Sep. 25, 2020 in U.S. Appl. No.
15/055,407. cited by applicant .
Final Office Action dated Dec. 7, 2020 in U.S. Appl. No.
16/012,584. cited by applicant .
First Action Interview Pilot Program Pre-Interview Communication
dated Oct. 15, 2018 in U.S. Appl. No. 15/987,851. cited by
applicant .
First Action Interview Office Action Summary dated Jan. 25, 2019 in
U.S. Appl. No. 15/987,851. cited by applicant .
Flanigon et al., "Multiplex protein detection with DNA readout via
mass spectrometry," N Biotechnol. 2013, 30(2), 153-158. cited by
applicant .
Forster et al., "A human gut bacterial genome and culture
collection for improved metagenomic analyses," Nature Biotechnology
2019, 37, 186-192. cited by applicant .
Fox-Walsh et al., "A multiplex RNA-seq strategy to profile poly(A+)
RNA: application to analysis of transcription response and 3' end
formation," Genomics 2011, 98, 266-721. cited by applicant .
Fu et al., "Counting individual DNA molecules by the stochastic
attachment of diverse labels," Proc Natl Acad Sci 2011, 108(22),
9026-9031. cited by applicant .
Fu et al., Digital Encoding of Cellular mRNAs Enabling Precise and
Absolute Gene Expression Measurement by Single-Molecule Counting.
Anal Chem. 2014, 86, 2867-2870. cited by applicant .
Fu et al., "Molecular indexing enables quantitative targeted RNA
sequencing and reveals poor efficiencies in standard library
preparation," PNAS 2014, 111(5), 1891-1896. cited by applicant
.
Gerry et al., "Universal DNA Microarray Method for Multiplex
Detection of Low Abundance Point Mutations," Journal of Molecular
Biology 1999, 292, 251-262. cited by applicant .
Gillespie, "Exact Stochastic Simulation of Coupled Chemical
Reactions," Journal of Physical Chemistry 1977, 81(25), 2340-2361.
cited by applicant .
Gong et al., "Massively parallel detection of gene expression in
single cells using subnanolitre wells," Lab Chip 2010, 10,
2334-2337. cited by applicant .
Gong et al., "Simple Method Prepare Oligonucleotide-Conjugated
Antibodies and Its Application in Multiplex Protein Detection in
Single Cells," Bioconjugate Chem. 2016, 27, 217-225. cited by
applicant .
Grant et al., "SNP genotyping on a genome-wide amplified DOP-PCR
template," Nucleic Acids Res 2002, 30(22), e25, 1-6. cited by
applicant .
Gu et al., "Complete workflow for detection of low frequency
somatic mutations from cell-free DNA using Ion Torrent.TM.
platforms," Conference Poster, AACR 107th Annual Meeting, Apr.
16-20, 2016, 1 p. cited by applicant .
Gu et al., "Depletion of abundant sequences by hybridization (DSH):
using Cas9 to remove unwanted high-abundance species in sequencing
libraries and molecular counting applications," Genome Biology
2016, 17(41) 1-13. cited by applicant .
Gunderson et al., "Decoding Randomly Ordered DNA Arrays," Genome
Research 2004, 14, 870-877. cited by applicant .
Gundry et al., "Direct, genome-wide assessment of DNA mutations in
single cells," Nucleic Acids Research 2011, 40(5), 2032-2040. cited
by applicant .
Gundry et al., "Direct mutation analysis by high-throughput
sequencing: from germline to low-abundant, somatic variants," Mutat
Res. 2012, 729(1-2), 1-15. cited by applicant .
Hacia et al., "Determination of ancestral alleles for human
single-nucleotide polymorphisms using high-density oligonucleotide
arrays," Nature Genetics 1999, 22, 164-167. cited by applicant
.
Haff, "Improved Quantitative PCR Using Nested Primers," PCR Methods
and Applications 1994, 3, 332-337. cited by applicant .
Hamady et al., "Error-correcting barcoded primers for
pyrosequencing hundreds of samples in multiplex," Nat Methods 2008,
5(3), 235-237. cited by applicant .
Han et al., "An approach to multiplexing an immunosorbent assay
with antibody-oligonucleotide conjugates," Bioconjug Chem. 2010,
21(12), 2190-2196. cited by applicant .
Harbers, "The current status of cDNA cloning," Genomics 2008, 91,
232-242. cited by applicant .
Harrington et al., Cross-sectional characterization of HIV-1 env
compartmentalization in cerebrospinal fluid over the full disease
course, AIDS 2009, 23(8), 907-915. cited by applicant .
Hartmann, "Gene expression profiling of single cells on large-scale
oligonucleotide arrays", Nucleic Acids Research, (Oct. 2006) vol.
34, No. 21, p. e143, 1-12. cited by applicant .
Hashimshony et al., "CEL-Seq: Single-Cell RNA-Seq by Multiplexed
Linear Amplification," Cell Rep. 2012, 2(3), 666-673. cited by
applicant .
Hensel et al., "Simultaneous identification of bacterial virulence
genes by negative selection," Science 1995, 269(5222), 400-403.
cited by applicant .
Hiatt et al., "Parallel, tag-directed assembly of locally derived
short sequence reads," Nat Methods 2010, 7(2), 119-122. cited by
applicant .
Hiatt et al., "Single molecule molecular inversion probes for
targeted, high-accuracy detection of low-frequency variation,"
Genome Res. 2013, 23(5), 843-854. cited by applicant .
Holcomb et al., "Abstract 1853: Single-cell multiplexed profiling
of protein-level changes induced by EGFR inhibitor gefitinib,"
Cancer Res 2016, 76(14 Suppl), Abstract 1853. cited by applicant
.
Hollas et al., "A stochastic approach to count RNA molecules using
DNA sequencing methods," Algorithms in Bioinformatics. WABI 2003,
Lecture Notes in Computer Science, 2812, 55-62. cited by applicant
.
How many species of bacteria are there? Wisegeek.org, accessed Jan.
21, 2014, 2 pp. cited by applicant .
Hu et al., "Dissecting Cell-Type Composition and Activity-Dependent
Transcriptional State in Mammalian Brains by Massively Parallel
Single-Nucleus RNA-Seq," Molecular Cell 2017, 68, 1006-1015. cited
by applicant .
Hu et al., "Single Cell Multi-Omics Technology: Methodology and
Application," Frontiers in Cell and Developmental Biology 2018,
6(28), 1-13. cited by applicant .
Hug et al., Measure of the Number of Molecular of a Single mRNA
Species in a Complex mRNA Preparation, Journal of Theoretical
Biology 2003, 221, 615-624. cited by applicant .
Ingolia et al., Genome-Wide Analysis in Vivo of Translation with
Nucleotide Resolution Using Ribosome Profiling, Science 2009,
324(5924), 218-223. cited by applicant .
International Preliminary Report on Patentability dated Mar. 26,
2019 in PCT Application No. PCT/US2017/053331. cited by applicant
.
International Preliminary Report on Patentability dated Aug. 6,
2019 in PCT Application No. PCT/US2018/014385. cited by applicant
.
International Preliminary Report on Patentability dated Nov. 3,
2020 in PCT Application No. PCT/US2019/030175. cited by applicant
.
International Preliminary Report on Patentability dated Nov. 3,
2020 in PCT Application No. PCT/US2019/030245. cited by applicant
.
International Search Report and Written Opinion dated May 7, 2012
for PCT Application No. PCT/IB2011/003160. cited by applicant .
International Search Report and Written Opinion dated Jun. 6, 2012
in PCT Application No. PCT/US2011/065291. cited by applicant .
International Search Report and Written Opinion dated Jun. 14, 2013
in PCT Application No. PCT/US2013/028103. cited by applicant .
International Search Report and Written Opinion dated Aug. 16, 2013
for PCT Application No. PCT/US2013/027891. cited by applicant .
International Search Report and Written Opinion dated Dec. 19, 2014
in PCT Application No. PCT/US2014/059542. cited by applicant .
International Search Report and Written Opinion dated Feb. 3, 2015
in PCT Application No. PCT/US2014/053301. cited by applicant .
International Search Report and Written Opinion dated May 3, 2016
in PCT Application No. PCT/US2016/018354. cited by applicant .
International Search Report and Written Opinion dated Jun. 9, 2016
in PCT Application No. PCT/US2016/022712. cited by applicant .
International Search Report and Written Opinion dated Jun. 17, 2016
in PCT Application No. PCT/US2016/019962. cited by applicant .
International Search Report and Written Opinion dated Jun. 20, 2016
in PCT Application No. PCT/US2016/014612. cited by applicant .
International Search Report and Written Opinion dated Aug. 9, 2016
in PCT Application No. PCT/US2016/019971. cited by applicant .
International Search Report and Written Opinion dated Sep. 27, 2016
in PCT Application No. PCT/US2016/034473. cited by applicant .
International Search Report and Written Opinion dated Sep. 28, 2016
in PCT Application No. PCT/US2016/028694. cited by applicant .
International Search Report and Written Opinion dated Dec. 5, 2016
in PCT Application No. PCT/US2016/024783. cited by applicant .
International Search Report and Written Opinion dated Jan. 31, 2017
in PCT Application No. PCT/US2016/050694. cited by applicant .
International Search Report and Written Opinion dated Aug. 7, 2017
in PCT Application No. PCT/US2017/034576. cited by applicant .
International Search Report and Written Opinion dated Sep. 8, 2017
in PCT Application No. PCT/US2017/030097. cited by applicant .
International Search Report and Written Opinion dated Mar. 20, 2018
in PCT Application No. PCT/US2017/053331. cited by applicant .
International Search Report and Written Opinion dated Mar. 28, 2018
in PCT Application No. PCT/US2018/014385. cited by applicant .
International Search Report and Written Opinion dated Jul. 16, 2018
in PCT Application No. PCT/US2018/024602. cited by applicant .
International Search Report and Written Opinion dated Jun. 24, 2019
in PCT Application No. PCT/US2019/030175. cited by applicant .
International Search Report and Written Opinion dated Oct. 8, 2019
in PCT Application No. PCT/US2019/043949. cited by applicant .
International Search Report and Written Opinion dated Oct. 16, 2019
in PCT Application No. PCT/US2019/030245. cited by applicant .
International Search Report and Written Opinion dated Nov. 27, 2019
in PCT Application No. PCT/US2019/046549. cited by applicant .
International Search Report and Written Opinion dated Dec. 4, 2019
in PCT Application No. PCT/US2019/053868. cited by applicant .
International Search Report and Written Opinion dated Jan. 27, 2020
in PCT Application No. PCT/US2019/048179. cited by applicant .
International Search Report and Written Opinion dated Mar. 30, 2020
in PCT Application No. PCT/US2019/060243. cited by applicant .
International Search Report and Written Opinion dated Mar. 30, 2020
in PCT Application No. PCT/US2019/065237. cited by applicant .
International Search Report and Written Opinion dated May 18, 2020
in PCT Application No. PCT/US2020/014339. cited by applicant .
International Search Report and Written Opinion dated Jun. 30, 2020
in PCT Application No. PCT/US2020/017890. cited by applicant .
International Search Report and Written Opinion dated Nov. 12, 2020
in PCT Application No. PCT/US2020/042880. cited by applicant .
Invitation to Pay Fees dated Mar. 16, 2016 in PCT Application No.
PCT/US2016/019971. cited by applicant .
Invitation to Pay Fees dated May 16, 2018 in PCT Application No.
PCT/US2018/024602. cited by applicant .
Invitation to Pay Fees dated Nov. 26, 2019 in PCT Application No.
PCT/US2019/048179. cited by applicant .
Invitation to Pay Additional Search Fees dated May 7, 2020 in PCT
Application No. PCT/US2020/017890. cited by applicant .
Invitation to Respond to Written Opinion dated May 26, 2017 in
Singapore Patent Application No. 11201405274W. cited by applicant
.
Islam et al., "Characterization of the single-cell transcriptional
landscape by highly multiplex RNA-seq," Genome Research 2011, 21,
1160-1167. cited by applicant .
Islam et al., "Highly multiplexed and strand specific single-cell
RNA 5' end sequencing," Nature Protocols 2012, 7(5), 813-828. cited
by applicant .
Islam et al., "Quantitative single-cell RNA-seq with unique
molecular identifiers," Nature Methods 2014, 11(2), 163-168. cited
by applicant .
Jabara, "Capturing the cloud: High throughput sequencing of
multiple individual genomes from a retroviral population," Biology
Lunch Bunch Series, Training Initiatives in Biomedical &
Biological Sciences of the University of North Carolina at Chapel
Hill 2010. cited by applicant .
Jabara et al., "Accurate sampling and deep sequencing of the HIV-1
protease gene using a Primer ID," PNAS 2011, 108(50), 20166-20171.
cited by applicant .
Jason J. Rawnsley of Richards, Layton and Finger, P.A., Entry of
Appearance dated Jan. 18, 2019 in the USDC District of Delaware,
C.A. No. 18-1800-RGA, 1 pp. cited by applicant .
Jiang et al., "Synthetic spike-in standards for RNA-seq
experiments," Genome Res. 2011, 21, 1543-1551. cited by applicant
.
Joint Stipulation and Order to Extend Time to Respond to
Plaintiff's First Amended Complaint, dated Feb. 21, 2019 in the
USDC for the District of Delaware, C.A. 18-1800-RGA, 2 pp. cited by
applicant .
Joint Stipulation and Order to Request Extended Time to File
Opposition to Defendant's Motion to Dismiss dated, Mar. 8, 2019 in
the USDC District of Delaware, C.A. No. 18-1800 RGA, 2 pp. cited by
applicant .
Joint Stipulation and Order to Request Extended Time to Submit a
proposed Protective Order, dated Jun. 7, 2019 in the USDC for the
District of Delaware, C.A. 18-1800-RGA, 1 pp. cited by applicant
.
Joint Stipulation and Order to Extended Time to Submit Agreed
Document Production Protocol, filed Jun. 28, 2019 in the USDC for
the District of Delaware, C.A. 18-1800 (RGA), 1 pp. cited by
applicant .
Joint Stipulation and Order to Request Extended Time to Submit
Agreed Document Production Protocol, dated Jul. 11, 2019 in the
USDC for the District of Delaware, C.A. 18-1800 (RGA), 1 pp. cited
by applicant .
Junker et al., "Single-Cell Transcriptomics Enters the Age of Mass
Production," Molecular Cell 2015, 58, 563-564. cited by applicant
.
Kanagawa, "Bias and artifacts in multi-template polymerase chain
reactions (PCR)," Journal of Bioscience and Bioengineering 2003,
96(4), 317-323. cited by applicant .
Kang et al., "Targeted sequencing with enrichment PCR: a novel
diagnostic method for the detection of EGFR mutations," Oncotarget
2015, 6(15), 13742-13749. cited by applicant .
Kang et al., "Application of multi-omics in single cells," Ann
Biotechnol. 2018, 2(1007), 1-8. cited by applicant .
Karrer et al., "In situ isolation of mRNA from individual plant
cells: creation of cell-specific cDNA libraries," Proc. Natl. Acad.
Sci. USA 1995, 92, 3814-3818. cited by applicant .
Kausch et al., "Organelle Isolation by Magnetic Immunoabsorption,"
BioTechniques 1999, 26(2), 336-343. cited by applicant .
Kebschull et al., "Sources of PCR-induced distortions in
high-throughput sequencing data sets," Nucleic Acids Research 2015,
1-15. cited by applicant .
Keys et al., Primer ID Informs Next-Generation Sequencing Platforms
and Reveals Preexisting Drug Resistance Mutations in the HIV-1
Reverse Transcriptase Coding Domain, AIDS Research and Human
Retroviruses 2015, 31(6), 658-668. cited by applicant .
Kim et al., Polony Multiplex Analysis of Gene Expression (PMAGE) in
Mouse Hypertrophic Cardiomyopathy, Science 2007, 316(5830),
1481-1484. cited by applicant .
Kinde et al., "Detection and quantification of rare mutations with
massively parallel sequencing," Proc. Natl Acad Sci 2011, 108(23),
9530-0535. cited by applicant .
Kirsebom et al., "Stimuli-Responsive Polymers in the 21st Century:
Elaborated Architecture to Achieve High Sensitivity, Fast Response,
and Robust Behavior," Journal of Polymer Science: Part B: Polymer
Physics 2011, 49, 173-178. cited by applicant .
Kivioja et al., "Counting absolute numbers of molecules using
unique molecular identifiers," Nature Proceedings 2011, 1-18. cited
by applicant .
Klein et al., Droplet Barcoding for Single-Cell Transcriptomics
Applied to Embryonic Stem Cells, Cell 2015, 161, 1187-1201. cited
by applicant .
Ko et al., "RNA-conjugated template-switching RT-PCR method for
generating an Escherichia coli cDNA library for small RNAs,"
Journal of Microbiological Methods 2006, 64, 297-304. cited by
applicant .
Koboldt et al., "VarScan: variant detection in massively parallel
sequencing of individual and pooled samples," Bioinformatics 2009,
25(17), 2283-2285. cited by applicant .
Kolodziejczyk et al., The Technology and Biology of Single-Cell RNA
Sequencing, Molecular Cell 2015, 58, 610-620. cited by applicant
.
Konig et al., "iCLIP reveals the function of hnRNAP particles in
splicing at individual nucleotide resolution," Nature Structural
& Molecular Biology 2010, 17(7), 909-916. cited by applicant
.
Kooiker & Xue, "cDNA Library Preparation," Cereal Genomics
2013, 1099, 29-40. cited by applicant .
Kotake et al., "A simple nested RT-PCR method for quantitation of
the relative amounts of multiple cytokine mRNAs in small tissue
samples," Journal of Immunological Methods 1996, 199, 193-203.
cited by applicant .
Kozarewa & Turner, "96-Plex Molecular Barcoding for the
Illumina Genome Analyzer," High-Throughput Next Generation
Sequencing. Methods in Molecular Biology (Methods and Applications)
2011, 733, 24 pp. DOI: 10.1007/978-1-61779-089-8_20. cited by
applicant .
Kozlov et al., "A high-complexity, multiplexed solution-phase assay
for profiling protease activity on microarrays," Comb Chern High
Throughput Screen 2008, 11(1), 24-35. cited by applicant .
Kurimoto et al., "An improved single-cell cDNA amplification method
for efficient high-density oligonucleotide microarray analysis,"
Nucleic Acids Res. 2006, 34(5), e42, 1-17. cited by applicant .
Kurimoto et al., "Global single-cell cDNA amplification to provide
a template for representative high-density oligonucleotide
microarray analysis," Nature Protocols 2007, 2(3), 739-752. cited
by applicant .
Lamble et al., "Improved workflows for high throughput library
preparation using the transposome-based nextera system," BMC
Biotechnology 2013, 13, 104, 1-10. cited by applicant .
Larson et al., "A single molecule view of gene expression," Trends
Cell Biol. 2009, 19(11), 630-637. cited by applicant .
Lass-Napiorkowska et al., "Detection methodology based on target
molecule-induced sequence-specific binding to a single-stranded
oligonucleotide," Anal Chem. 2012, 84(7), 3382-3389. cited by
applicant .
Leamon et al., A massively parallel PicoTiterPlate based platform
for discrete picoliter-scale polymerase chain reactions,
Electrophoresis 2003, 24, 3769-3777. cited by applicant .
Lee et al., "Large-scale arrays of picolitre chambers for
single-cell analysis of large cell populations," Lab Chip 2010, 10,
2952-2958. cited by applicant .
Lee et al., "Highly Multiplexed Subcellular RNA Sequencing in
Situ," Science 2014, 343, 1360-1363. cited by applicant .
Lee et al., "Universal process-inert encoding architecture for
polymer microparticles," Nature Materials 2014, 13(5), 524-529.
cited by applicant .
Letter regarding the opposition procedure dated Jul. 22, 2015 for
European Patent Application No. 11810645.9. cited by applicant
.
Letter to Judge Richard G. Andrews Requesting a Rule 16 Conference,
dated Apr. 15, 2019 in the USDC for the District of Delaware, C.A.
18-1800 (RGA), 1 pp. cited by applicant .
Letter to Judge Andrews regarding Agreement on Proposed Scheduling
Order, dated May 7, 2019 in the USDC for the District of Delaware,
C.A. 18-1800-RGA, 1 pp. cited by applicant .
Letter to Judge Andrews regarding Notice of Supplemental Authority,
dated Jul. 10, 2019 in the USDC for the District of Delaware, C.A.
18-1800(RGA), 2pp. cited by applicant .
Lin et al., "Self-Assembled Combinatorial Encoding Nanoarrays for
Multiplexed Biosensin," Nano Lett. 2007, 7 (2), 507-512. cited by
applicant .
Liu et al., "Single-cell transcriptome sequencing: recent advances
and remaining challenges," F1000Research 2016, 5(F1000 Faculty
Rev)(182), 1-9. cited by applicant .
Lizardi et al., "Mutation detection and single-molecule counting
using isothermal rolling-circle amplification," Nat Genet. 1998,
19, 225-232. cited by applicant .
Lockhart et al., "Expression monitoring by hybridization to
high-density oligonucleotide arrays," Nature Biotechnology 1996,
14, 1675-1680. cited by applicant .
Lovatt et al., "Transcriptome in vivo analysis (TIVA) of spatially
defined single cells in live tissue," Nat Methods 2014, 11(2),
190-196. cited by applicant .
Loy et al., "A rapid library preparation method with custom assay
designs for detection of variants at 0.1% allelic frequency in
liquid biopsy samples," Oct. 2, 2018, 1 p. cited by applicant .
Lucito et al., "Representational Oligonucleotide Microarray
Analysis: A High-Resolution Method to Detect Genome Copy Number
Variation," Genome Research 2003, 13, 2291-2305. cited by applicant
.
Lundberg et al., "Practical innovations for high-throughput
amplicon sequencing," Nature Methods 2013, 10(10), 999-1007. cited
by applicant .
Lundberg et al., "Supplementary Information for: Practical
innovations for high-throughput amplicon sequencing," Nature
Methods 2013, 1-24. cited by applicant .
Maamar et al., "Noise in Gene Expression Determines Cell Fate in
Bacillus subtilis," Science 2007, 317, 526-529. cited by applicant
.
Macaulay et al., "Single Cell Genomics: Advances and Future
Perspectives," PLoS Genetics 2014, 10(1), 1-9. cited by applicant
.
Macaulay et al., "G&T-seq: parallel sequencing of single-cell
genomes and transcriptomes," Nature Methods 2015, 1-7. cited by
applicant .
Macosko et al., "Highly parallel genome-wide expression profiling
of individual cells using nanoliter droplets," Cell 2015, 161,
1202-1214. cited by applicant .
Maeda et al., "Development of a DNA barcode tagging method for
monitoring dynamic changes in gene expression by using an ultra
high-throughput sequencer," BioTechniques 2008, 45(1), 95-97. cited
by applicant .
Makrigiorgos et al., "A PCR-Based amplification method retaining
quantities difference between two complex genomes," Nature Biotech
2002, 20(9), 936-939. cited by applicant .
Marcus et al., "Microfluidic single-cell mRNA isolation and
analysis," Anal Chem. 2006, 78, 3084-3089. cited by applicant .
Mardis, "Next-generation DNA sequencing methods", Annu. Rev.
Genomics Hum. Genet. 2008, 9, 387-402. cited by applicant .
Marguerat et al., "Next-generation sequencing: applications beyond
genomes," Biochem. Soc. Trans. 2008, 36(5), 1091-1096. cited by
applicant .
Marguiles et al., Genome sequencing in microfabricated high-density
picolitre reactors, Nature 2005, 437, 376-380. cited by applicant
.
Martinez et al., "A microfluidic approach to encapsulate living
cells in uniform alginate hydrogel microparticles," Macromol.
Biosci 2012, 12, 946-951. cited by applicant .
Massachusetts General Hospital, Overview of Illumina Chemistry,
http://nextgen.mgh.harvard.edu/IlluminaChemistry.html, downloaded
Jan. 28, 2020, 2 pp. cited by applicant .
McCloskey et al., "Encoding PCR products with batch-stamps and
barcodes," Biochem Genet. 2007, 45(11-12), 761-767. cited by
applicant .
Medvedev et al., "Detecting copy number variation with mated short
reads," Genome Res. 2010, 20, 1613-1622. cited by applicant .
Mei et al., "Identification of recurrent regions of Copy-Number
Variants across multiple individuals," BMC Bioinformatics 2010, 11,
147, 1-14. cited by applicant .
Meyer et al., "Parallel tagged sequencing on the 454 platform,"
Nature Protocols 2008, 3(2), 267-278. cited by applicant .
Miller et al., Directed evolution by in vitro compartmentalization,
Nature Methods 2006, 3(7), 561-570. cited by applicant .
Miner et al., "Molecular barcodes detect redundancy and
contamination in hairpin-bisulfite PCR," Nucleic Acids Research
2004, 32(17), e135, 1-4. cited by applicant .
Mortazavi et al., "Mapping and quantifying mammalian transcriptomes
by RNA-Seq," Nat. Methods 2008, 5(7), 621-628. cited by applicant
.
Motion and Order for Admission Pro Hac Vice Pursuant to Local Rule
83.5, dated Jan. 24, 2019 in the USDC District of Delaware, C.A.
No. 18-1800-RGA, 7 pp. cited by applicant .
Nadai et al., Protocol for nearly full-length sequencing of HIV-1
RNA from plasma, PLoS One 2008, 3(1), e1420, 1-6. cited by
applicant .
Nagai et al., "Development of a microchamber array for picoleter
PCR," Anal. Chem. 2001, 73, 1043-1047. cited by applicant .
Navin et al., "The first five years of single-cell cancer genomics
and beyond," Genome Research 2015, 25, 1499-1507. cited by
applicant .
Newell et al., Cytometry by time-of-flight shows combinatorial
cytokine expression and virus-specific cell niches within a
continuum of CD8+ T cell phenotypes. Immunity 2012, 36(1), 142-152.
cited by applicant .
Non-Final Office Action dated Oct. 3, 2013 in U.S. Appl. No.
12/969,581. cited by applicant .
Non-Final Office Action dated Feb. 18, 2015 for U.S. Appl. No.
14/540,007. cited by applicant .
Non-Final Office Action dated Feb. 26, 2015 for U.S. Appl. No.
14/540,029. cited by applicant .
Non-Final Office Action dated Mar. 19, 2015 in U.S. Appl. No.
14/540,018. cited by applicant .
Non-Final Office Action dated May 7, 2015 for U.S. Appl. No.
13/327,526. cited by applicant .
Non-Final Office Action dated Dec. 3, 2015 for U.S. Appl. No.
14/281,706. cited by applicant .
Non-Final Office Action dated Dec. 31, 2015 for U.S. Appl. No.
14/800,526. cited by applicant .
Non-Final Office Action dated Apr. 11, 2016 in U.S. Appl. No.
14/472,363. cited by applicant .
Non-Final Office Action dated May 10, 2016 in U.S. Appl. No.
14/381,488. cited by applicant .
Non-Final Office Action dated May 13, 2016 in U.S. Appl. No.
14/508,911. cited by applicant .
Non-Final Office Action dated Aug. 17, 2016 for U.S. Appl. No.
14/800,526. cited by applicant .
Non-Final Office Action dated Sep. 26, 2016 in U.S. Appl. No.
15/167,807. cited by applicant .
Non-Final Office Action dated Oct. 11, 2016 in U.S. Appl. No.
15/224,460. cited by applicant .
Non-Final Office Action dated Jan. 19, 2017 in U.S. Appl. No.
15/055,445. cited by applicant .
Non-Final Office Action dated Mar. 24, 2017 in U.S. Appl. No.
15/409,355. cited by applicant .
Non-Final Office Action dated Jun. 2, 2017 in U.S. Appl. No.
14/381,526. cited by applicant .
Non-Final Office Action dated Jun. 7, 2017 in U.S. Appl. No.
14/381,488. cited by applicant .
Non-Final Office Action dated Jul. 28, 2017 in U.S. Appl. No.
14/975,441. cited by applicant .
Non-Final Office Action dated Sep. 8, 2017 in U.S. Appl. No.
15/046,225. cited by applicant .
Non-Final Office Action dated Sep. 8, 2017 in U.S. Appl. No.
15/134,967. cited by applicant .
Non-Final Office Action dated Nov. 1, 2017 in U.S. Appl. No.
15/667,125. cited by applicant .
Non-Final Office Action dated Nov. 9, 2017 in U.S. Appl. No.
15/004,618. cited by applicant .
Non-Final Office Action dated Jan. 9, 2018 in U.S. Appl. No.
15/217,896. cited by applicant .
Non-Final Office Action dated Jan. 12, 2018 in U.S. Appl. No.
15/217,886. cited by applicant .
Non-Final Office Action dated Mar. 8, 2018 in U.S. Appl. No.
15/608,780. cited by applicant .
Non-Final Office Action dated Apr. 6, 2018 in U.S. Appl. No.
15/603,239. cited by applicant .
Non-Final Office Action dated Jul. 25, 2018 in U.S. Appl. No.
15/108,268. cited by applicant .
Non-Final Office Action dated Oct. 4, 2018 in U.S. Appl. No.
15/260,106. cited by applicant .
Non-Final Office Action dated Oct. 25, 2018 in U.S. Appl. No.
16/012,584. cited by applicant .
Non-Final Office Action dated Nov. 5, 2018 in U.S. Appl. No.
16/038,790. cited by applicant .
Non-Final Office Action dated Nov. 26, 2018 in U.S. Appl. No.
15/937,713. cited by applicant .
Non-Final Office Action dated Jan. 7, 2019 in U.S. Appl. No.
15/055,407. cited by applicant .
Non-Final Office Action dated Jan. 14, 2019 in U.S. Appl. No.
16/219,553. cited by applicant .
Non-Final Office Action dated Mar. 19, 2019 in U.S. Appl. No.
15/046,225. cited by applicant .
Non-Final Office Action dated May 15, 2019 in U.S. Appl. No.
15/084,307. cited by applicant .
Non-Final Office Action dated May 23, 2019 in U.S. Appl. No.
15/459,977. cited by applicant .
Non-Final Office Action dated Jun. 17, 2019 in U.S. Appl. No.
14/381,488. cited by applicant .
Non-Final Office Action dated Jul. 9, 2019 in U.S. Appl. No.
15/596,364. cited by applicant .
Non-Final Office Action dated Aug. 20, 2019 for U.S. Appl. No.
15/715,028. cited by applicant .
Non-Final Office Action dated Sep. 18, 2019 in U.S. Appl. No.
16/194,819. cited by applicant .
Non-Final Office Action dated Nov. 29, 2019 in U.S. Appl. No.
15/937,713. cited by applicant .
Non-Final Office Action dated Jan. 17, 2020 in U.S. Appl. No.
15/084,307. cited by applicant .
Non-Final Office Action dated Feb. 5, 2020 in U.S. Appl. No.
15/875,816. cited by applicant .
Non-Final Office Action dated Mar. 12, 2020 in U.S. Appl. No.
16/789,358. cited by applicant .
Non-Final Office Action dated Mar. 17, 2020 in U.S. Appl. No.
15/055,407. cited by applicant .
Non-Final Office Action dated Mar. 26, 2020 in U.S. Appl. No.
16/012,635. cited by applicant .
Non-Final Office Action dated Mar. 26, 2020 in U.S. Appl. No.
16/789,311. cited by applicant .
Non-Final Office Action dated Jun. 8, 2020 in U.S. Appl. No.
15/715,028. cited by applicant .
Non-Final Office Action dated Aug. 4, 2020 in U.S. Appl. No.
15/459,977. cited by applicant .
Non-Final Office Action dated Aug. 19, 2020 in U.S. Appl. No.
16/374,626. cited by applicant .
Non-Final Office Action dated Aug. 25, 2020 in U.S. Appl. No.
14/381,488. cited by applicant .
Non-Final Office Action dated Dec. 4, 2020 in U.S. Appl. No.
16/677,012. cited by applicant .
Non-Final Office Action dated Dec. 9, 2020 in U.S. Appl. No.
16/788,743. cited by applicant .
Notice of Allowability dated Jun. 19, 2014 for U.S. Appl. No.
12/969,581. cited by applicant .
Notice of Allowance dated Dec. 21, 2015 in U.S. Appl. No.
14/540,018. cited by applicant .
Notice of Allowance dated Jan. 9, 2019 in U.S. Appl. No.
15/603,239. cited by applicant .
Notice of Allowance dated Mar. 20, 2019 in U.S. Appl. No.
16/219,553. cited by applicant .
Notice of Allowance dated Mar. 21, 2019 in U.S. Appl. No.
15/993,468. cited by applicant .
Notice of Allowance dated May 28, 2019 in U.S. Appl. No.
16/219,553. cited by applicant .
Notice of Allowance dated Sep. 24, 2019 in U.S. Appl. No.
15/217,886. cited by applicant .
Notice of Allowance dated Nov. 11, 2019 in Japanese Patent
Application No. 2017-245295. cited by applicant .
Notice of Allowance dated Nov. 29, 2019 in U.S. Appl. No.
16/012,635. cited by applicant .
Notice of Allowance dated Dec. 27, 2019 in U.S. Appl. No.
15/260,106. cited by applicant .
Notice of Allowance dated Mar. 5, 2020 in U.S. Appl. No.
15/217,886. cited by applicant .
Notice of Allowance dated Mar. 27, 2020 in U.S. Appl. No.
15/596,364. cited by applicant .
Notice of Allowance dated Mar. 30, 2020 in U.S. Appl. No.
15/937,713. cited by applicant .
Notice of Allowance dated Apr. 15, 2020 in U.S. Appl. No.
16/012,635. cited by applicant .
Notice of Allowance dated Sep. 23, 2020 in Korean Patent
Application No. 10-2016-7008144. cited by applicant .
Notice of Allowance dated Oct. 29, 2020 in U.S. Appl. No.
15/987,851. cited by applicant .
Notice, Consent, and Reference of a Civil Action to a Magistrate
Judge (Rule 73.1), filed Nov. 15, 2018 in the USDC for the District
of Delaware, C.A. 18-1800-RGA, 3 pp. cited by applicant .
Notice of Opposition dated Jul. 9, 2015 for European Patent
Application No. 11810645.9. cited by applicant .
Notice of Opposition dated Jul. 27, 2016 for European Patent
Application No. 10762102.1. cited by applicant .
Notice of Reasons for Rejection dated Dec. 28, 2016 in Japanese
Patent Application No. 2014-558975. cited by applicant .
Notice of Reasons for Rejection dated Apr. 2, 2018 in Japanese
Patent Application No. 2014-558975. cited by applicant .
Notice of Reasons for Rejection dated Jul. 30, 2018 in Japanese
Patent Application No. 2016-537867. cited by applicant .
Notice of Reasons for Rejection dated Aug. 31, 2018 in Japanese
Patent Application No. 2016-520632. cited by applicant .
Notice of Reasons for Rejection dated Dec. 5, 2018 in Japanese
Patent Application No. 2017-245295. cited by applicant .
Notice of Reason for Rejection dated Nov. 21, 2019 in Korean Patent
Application No. 10-2016-7008144. cited by applicant .
Notice of Reasons for Rejection dated Feb. 25, 2020 in Japanese
Patent Application No. 2019-014564. cited by applicant .
Notice of Reasons for Rejection dated May 11, 2020 in Japanese
Patent Application No. 2017-549390. cited by applicant .
Notice of Service of Disclosures to Opposing Counsel, dated Jun.
10, 2019 in the USDC for the District of Delaware, C.A. 18-1800
(RGA), 3 pp. cited by applicant .
Notice of Service of Interrogatories and First Request of Documents
and Things to Defendant 10X Genomics, Inc., dated Jul. 5, 2019 in
the USDC for the District of Delaware, C.A. 18-1800 (RGA), 3 pp.
cited by applicant .
Notification Prior to Examination dated Nov. 27, 2019 in Israeli
Patent Application No. 265478. cited by applicant .
Novak et al., "Single-Cell Multiplex Gene Detection and Sequencing
with Microfluidically Generated Agarose Emulsions," Angew. Chem.
Int. Ed. 2011, 50, 390-395. cited by applicant .
Office Action dated Jun. 6, 2016 in Chinese Patent Application No.
201380022187.9. cited by applicant .
Office Action dated Dec. 27, 2016 in Chinese Patent Application No.
201380022187.9. cited by applicant .
Office Action dated Jul. 14, 2017 in Chinese Patent Application No.
201380022187.9. cited by applicant .
Office Action dated Dec. 19, 2017 in Chinese Patent Application No.
201480061859.1. cited by applicant .
Office Action dated Feb. 15, 2018 in Canadian Patent Application
No. 2,865,575. cited by applicant .
Office Action dated Sep. 7, 2018 in Chinese Patent Application No.
201480061859.1. cited by applicant .
Office Action dated Dec. 13, 2018 in Canadian Patent Application
No. 2,865,575. cited by applicant .
Office Action dated Jan. 2, 2019 in Chinese Patent Application No.
201480059505.3. cited by applicant .
Office Action dated Mar. 4, 2020 in Canadian Patent Application No.
2,865,575. cited by applicant .
Office Action dated Jun. 22, 2020 in Chinese Patent Application No.
201680007351.2. cited by applicant .
Office Action dated Jun. 22, 2020 in Chinese Patent Application No.
201680007652.5. cited by applicant .
Office Action dated Jun. 23, 2020 in Chinese Patent Application No.
2016800157452. cited by applicant .
Office Action dated Jul. 20, 2020 in Japanese Patent Application
No. 2018-512152. cited by applicant .
Office Action dated Oct. 29, 2020 in Chinese Patent Application No.
2018800377201. cited by applicant .
Office Action dated Nov. 12, 2020 in European Patent Application
No. 18716877.8. cited by applicant .
Office Action dated Dec. 3, 2020 in European Patent Application No.
16719706.0. cited by applicant .
Office Action dated Jan. 4, 2021 in Japanese Patent Application No.
2017-549390. cited by applicant .
Ogino et al., "Quantification of PCR bias caused by a single
nucleotide polymorphism in SMN gene dosage analysis," J Mol Diagn.
2002, 4(4), 185-190. cited by applicant .
Opposition to Defendant's Motion to Dismiss Pursuant to Federal
Rule of Civil Procedure 12(b)(6) dated Feb. 15, 2019, in the USDC
for the District of Delaware, C.A. 18-800-RGA, 3 pp. cited by
applicant .
Oral Order by Judge Andrews Canceling Scheduling Conference set for
May 8, 2019. cited by applicant .
Order Setting Rule 16(b) Conference as Ordered by Judge Andrews
Pursuant to Fed. R. Civ. P. 16(b), ruling dated Apr. 17, 2019 in
the USDC District of Delaware, C.A. 18-1800-RGA, 1 pp. cited by
applicant .
Order Scheduling ADR Mediation Teleconference, filed May 13, 2019
in the USDC for the District of Delaware, C.A. 18-1800-RGA, 4pp.
cited by applicant .
Ozkumur et al., "Inertial Focusing for Tumor Antigen-Dependent
and--Independent Sorting of Rare Circulating Tumor Cells," Science
Translational Medicine 2013, 5(179), 1-20. cited by applicant .
Parameswaran et al., "A pyrosequencing-tailored nucleotide barcode
design unveils opportunities for large-scale sample multiplexing,"
Nucleic Acids Res. 2007, 35(19), e130, 1-9. cited by applicant
.
Park et al., "Discovery of common Asian copy number variants using
integrated high-resolution array CGH and massively parallel DNA
sequencing," Nat Genet. 2010, 42(5), 400-405. cited by applicant
.
Patanjali et al., "Construction of a uniform-abundance (normalized)
CNDA library," Proceedings of the National Academy of Sciences
1991, 88(5), 1943-1947. cited by applicant .
Peng et al., "Reducing amplification artifacts in high multiplex
amplicon sequencing by using molecular barcodes," BMC Genomics
2015, 16(589), 1-12. cited by applicant .
Perez-Rentero et al., "Synthesis of Oligonucleotides Carrying Thiol
Groups Using a Simple Reagent Derived from Threoninol," Molecules
2012, 17, 10026-10045. cited by applicant .
Peterson et al., "Multiplexed quantification of proteins and
transcripts in single cells," Nature Biotechnology 2017, 35,
936-939. cited by applicant .
Pfaffl et al., "Determination of stable housekeeping genes,
differentially regulated target genes and sample integrity:
BestKeepe--Excel-based tool using pair-wise correlations,"
Biotechnology Letters, 26(6), 505-515, 2004. cited by applicant
.
Picelli et al., "Tn5 transposase and tagmentation procedures for
massively scaled sequencing projects," Genome Research 2014,
24(12), 2033-2040. cited by applicant .
Picelli et al., "Single-cell RNA-sequencing: The future of genome
biology is now," RNA Biology 2017, 14(5), 637-650. cited by
applicant .
Pihlak et al., "Rapid genome sequencing with short universal tiling
probes," Nature Biotechnology 2008, 26, 1-9. cited by applicant
.
Pinkel et al., "Comparative Genomic Hybridization," Annual Review
of Genomics and Human Genetics 2005, 6, 331-354. cited by applicant
.
Plaintiff's Brief in Opposition to Defendant's Motion to Dismiss
Pursuant to Fed. R. Civ. P. 12(b)(6), filed Mar. 29, 2019 in the
USDC District of Delaware, C.A. No. 18-1800 (RGA), 27 pp. cited by
applicant .
Plaintiff's First Amended Complaint filed on Feb. 8, 2019, in the
USDC for the District of Delaware, C.A. 18-1800-RGA, 178 pp. cited
by applicant .
Pleasance et al., "A small-cell lung cancer genome with complex
signatures of tobacco exposure," Nature 2010, 463(7278), 184-190.
cited by applicant .
Plessy et al., "Population transcriptomics with single-cell
resolution: a new field made possible by microfluidics: a
technology for high throughput transcript counting and data-driven
definition of cell types," Bioessays 2012, 35, 131-140. cited by
applicant .
Pre-interview communication dated Nov. 27, 2018 in U.S. Appl. No.
16/012,635. cited by applicant .
Preissl et al., "Single-nucleus analysis of accessible chromatin in
developing mouse forebrain reveals cell-type-specific
transcriptional regulation," Nature Neuroscience 2018, 21(3),
432-439. cited by applicant .
Proposed Stipulated Protective Order Pursuant to Rule 26(c) of the
Federal Rules of Civil Procedure, filed Jun. 20, 2019 In the USDC
for the District of Delaware, C.A. 18-1800 (RGA), 26 pp. cited by
applicant .
Qiu et al., "DNA Sequence-Based "BarCodes" for Tracking the Origins
of Expressed Sequence Tags from a Maize cDNA Library Constructed
Using Multiple mRNA Sources," Plant Physiol. 2003, 133, 475-481.
cited by applicant .
Raj et al., "Stochastic mRNA synthesis in mammalian cells," PLoS
Biol. 2006, 4(10) 1707-1719. cited by applicant .
Raj et al., "Imaging individual mRNA molecules using multiple
singly labeled probes," Nature Methods 2008, 5(10), 877-879. cited
by applicant .
Raj et al., "Single-Molecule Approaches to Stochastic Gene
Expression," Annu Rev Biophys 2009, 38, 255-270. cited by applicant
.
Rajeevan et al., "Global amplification of sense RNA: a novel method
to replicate and archive mRNA for gene expression analysis,"
Genomics 2003, 82, 491-497. cited by applicant .
Report on the Filing or Determination of an Action Regarding a
Patent or Trademark filed Nov. 15, 2018 in the USDC for the
District of Delaware, C.A. 18-1800-RGA, 2 pp. cited by applicant
.
Restriction Requirement dated Mar. 29, 2019 in U.S. Appl. No.
15/715,028. cited by applicant .
Restriction Requirement dated Jun. 19, 2019 in U.S. Appl. No.
15/596,364. cited by applicant .
Restriction Requirement dated Sep. 20, 2019 in U.S. Appl. No.
15/875,816. cited by applicant .
Rhee et al., "Simultaneous detection of mRNA and protein stem cell
markers in live cells," BMC Biotechnology 2009, 9(30), 1-10. cited
by applicant .
Roche Diagnostics GmbH, "Genome Sequencer 20 System: First to the
Finish," 2006, 1-40. cited by applicant .
Rule 7.1 Disclosure Statement dated Nov. 15, 2018 in the USDC for
the District of Delaware, C.A. 18-1800-RGA, 1 pp. cited by
applicant .
Sah et al., "Complete Genome Sequence of a 2019 Novel Coronavirus
(SARS-CoV-2) Strain Isolated in Nepal," Microbiol Resour Announc.
2020, 9(11), e00169-20, 3 pp. cited by applicant .
Sano et al., "Immuno-PCR: Very Sensitive Antigen Detection by Means
of Specific Antibody--DNA Conjugates," Science 1992, 258, 120-122.
cited by applicant .
Sasagawa et al., "Quartz-Seq: a highly reproducible and sensitive
single-cell RNA sequencing method, reveals non-genetic
gene-expression heterogeneity," Genome Biology 2013, 14, R31. cited
by applicant .
Sasuga et al., Single-cell chemical lysis method for analyses of
intracellular molecules using an array of picoliter-scale
microwells, Anal Chem 2008, 80(23), 9141-9149. cited by applicant
.
Satija et al., Spatial reconstruction of single-cell gene
expression data, Nature Biotechnology 2015, 33(5), 495-508. cited
by applicant .
Scheduling Order pursuant to Local Rule 16.1(b), filed May 7, 2019
in the USDC for the District of Delaware, C.A. 18-1800-RGA, 10 pp.
cited by applicant .
Scheduling Order Signed by Judge Andrews, dated May 8, 2019 in the
USDC for the District of Delaware, C.A. 18-1800-RGA, 10 pp. cited
by applicant .
Schmitt et al., "Detection of ultra-rare mutations by
next-generation sequencing," Proc Natl Acad Sci 2012, 109(36), 1-6.
cited by applicant .
Search and Examination Report dated Aug. 26, 2015 in United Kingdom
Patent Application No. 1511591.8. cited by applicant .
Search Report and Written Opinion dated Jan. 26, 2016 in Singapore
Patent Application No. 1120140527W. cited by applicant .
Search Report and Written Opinion dated Aug. 26, 2020 in Singapore
Patent Application No. 10201806890V. cited by applicant .
Sebat et al., "Large-Scale Copy Number Polymorphism in the Human
Genome," Science 2004, 305, 525-528. cited by applicant .
Shahi et al., "Abseq: ultrahigh-throughput single cell protein
profiling with droplet microfluidic barcoding," Scientific Reports
2017, 7(44447), 1-10. cited by applicant .
Shalek et al., "Single-cell transcriptomics reveals bimodality in
expression and splicing in immune cells," Nature 2013, 498(7453),
236-240. cited by applicant .
Shendure et al., "Next-generation DNA sequencing," Nature
Biotechnology 2008, 26(10), 1135-1145. cited by applicant .
Shiroguchi et al., "Digital RNA sequencing minimizes
sequence-dependent bias and amplification noise with optimized
single-molecule barcodes," Proc Natl Acad Sci 2012,
109(4):1347-1352. cited by applicant .
S.H.KO, "An `equalized cDNA library` by the reassociation of short
double-stranded cDNAs," Nucleic Acids Res. 1990, 18(19), 5705-5711.
cited by applicant .
Shoemaker et al., "Quantitative phenotypic analysis of yeast
deletion mutants using a highly parallel molecular bar-coding
strategy," Nature Genetics 1996, 14, 450-456. cited by applicant
.
Shortreed et al., "A thermodynamic approach to designing
structure-free combinatorial DNA word sets," Nucleic Acids Res.
2005, 33(15), 4965-4977. cited by applicant .
Shum et al., "Quantitation of mRNA Transcripts and Proteins Using
the BD Rhapsody.TM. Single-Cell Analysis System," Adv Exp Med Biol.
2019,1129, 63-79. cited by applicant .
Simpson et al., "Copy number variant detection in inbred strains
from short read sequence data," Bioinformatics 2010, 26(4),
565-567. cited by applicant .
Smith et al., "Highly-multiplexed barcode sequencing: an efficient
method for parallel analysis of pooled samples," Nucleic Acids
Research 2010, 38(13), e142, 1-7. cited by applicant .
Soares et al., "Construction and characterization of a normalized
cDNA library," Proc. Natl., Acad. Sci. 1994, 91, 9228-9232. cited
by applicant .
Sogin et al., "Microbial diversity in the deep sea and the
underexplored "rare biosphere"," PNAS 2008, 103(32), 12115-12120.
cited by applicant .
Sommer et al., "Minimal homology requirements for PCR primers,"
Nucleic Acids Research 1989, 17(16), 6749. cited by applicant .
Song et al., "Design rules for size-based cell sorting and
sheathless cell focusing by hydrophoresis," Journal of
Chromatography A 2013, 1302, 191-196. cited by applicant .
Soumillon et al., "Characterization of directed differentiation by
high-throughput single-cell RNA-Seq," bioRxiv 2014, 1-13. cited by
applicant .
Speicher et al., "The new cytogenetics: blurring the boundaries
with molecular biology," Nature Reviews Genetics 2005, 6(10),
782-792. cited by applicant .
Statement of Opposition of Strawman Limited filed against European
Patent No. EP2414548B1 on Jul. 19, 2016. cited by applicant .
Statement of Opposition dated Jul. 21, 2016 filed against European
Patent No. EP2414548B1. cited by applicant .
Statement of Opposition filed against European Patent No.
EP2414548B1 on Jul. 26, 2016. cited by applicant .
Statement regarding Third-Party Submission filed on Jun. 6, 2018
for U.S. Appl. No. 15/847,752. cited by applicant .
Stipulated Protective Order Pursuant to Rule 26(c) of the Federal
Rules of Civil Procedure, dated Jun. 21, 2019 in the USDC for the
District of Delaware, C.A. 18-1800 (RGA), 26 pp. cited by applicant
.
Stipulation and Order to Extend Time to File Opposition to Motion
to Dismiss, and Reply in Support of the Motion, dated Jan. 28, 2019
in the USDC for the District of Delaware, C.A. 18-1800-RGA, 2 pp.
cited by applicant .
Stoeckius et al., "Large-scale simultaneous measurement of epitopes
and transcriptomes in single cells," Nature Methods 2017, 14(9),
865-868. cited by applicant .
Stratagene 1988 Catalog, Gene Characterization Kits, 39. cited by
applicant .
Subkhankulova et al., "Comparative evaluation of linear and
exponential amplification techniques for expression profiling at
the single cell level," Genome Biology 2006, 7(3), 1-16. cited by
applicant .
Submission dated Jan. 15, 2018 in preparation for upcoming oral
proceedings in opposition against European Patent No. EP2414548B1.
cited by applicant .
Summons in a Civil Action to Defendant 10X Genomics, Inc. filed
Nov. 16, 2018 in the USDC for the District of Delaware, Civil
Action No. 18-1800, 2 pp. cited by applicant .
Summons to Attend Oral Proceedings dated Nov. 16, 2020 in European
Patent Application No. 17202409.3. cited by applicant .
Sun et al., "Ultra-deep profiling of alternatively spliced
Drosophila Dscam isoforms by circularization-assisted multi-segment
sequencing," EMBO J. 2013, 32(14), 2029-2038. cited by applicant
.
Takahashi et al., "Novel technique of quantitative nested real-time
PCR assay for mycobacterium tuberculosis DNA," Journal of Clinical
Microbiology 2006, 44, 1029-1039. cited by applicant .
Tan et al., "Genome-wide comparison of DNA hydroxymethylation in
mouse embryonic stem cells and neural progenitor cells by a new
comparative hMeDIP-seq method," Nucleic Acids Res. 2013, 41(7),
e84, 1-12. cited by applicant .
Tang et al., "RNA-Seq analysis to capture the transcriptome
landscape of a single cell," Nature Protocols 2010, 5(3), 516-535.
cited by applicant .
Taudien et al., "Haplotyping and copy number estimation of the
highly polymorphic human beta-defensin locus on 8p23 by 454
amplicon sequencing," BMC Genomics 2010, 11, 252, 1-14. cited by
applicant .
The Tibbs Times, UNC bioscience newsletter, Apr. 2010, 1-17. cited
by applicant .
Third-Party Submission filed on May 21, 2018 for U.S. Appl. No.
15/847,752. cited by applicant .
Tomaz et al., "Differential methylation as a cause of allele
dropout at the imprinted GNAS locus," Genet Test Mol Biomarkers
2010, 14(4), 455-460. cited by applicant .
Treutlein et al., Reconstructing lineage hierarchies of the distal
lung epithelium using single-cell RNA-seq, Nature 2014, 509,
371-375. cited by applicant .
Ullal et al., "Cancer cell profiling by barcoding allows
multiplexed protein analysis in fine needle aspirates," Sci Transl
Med. 2014, 6(219), 22 pp. cited by applicant .
Unopposed Motion to Extend Time for Defendant's Response, dated
Dec. 4, 2018 in the USDC for the District of Delaware, C.A.
18-1800-(RGA), 2 pp. cited by applicant .
Vandesompele et al., "Accurate normalization of real-time
quantitative RT-PCR data by geometric averaging of multiple
internal control genes," Genome Biology 2002, 3(7), 1-12. cited by
applicant .
Velculescu et al., "Serial Analysis of Gene Expression," Science
1995, 270(5235), 484-487. cited by applicant .
Velculescu et al., "Characterization of the Yeast Transcriptome,"
Cell 1997, 88, 243-251. cited by applicant .
Vogelstein et al., "Digital PCR," Proc. Natl. Acad. Sci. 1999, 96,
9236-9241. cited by applicant .
Vollbrecht et al., "Validation and comparison of two NGS assays for
the detection of EGFR T790M resistance mutation in liquid biopsies
of NSCLC patients," Oncotarget 2018, 9(26), 18529-18539. cited by
applicant .
Walker et al., "Isothermal in vitro amplification of DNA by a
restriction enzyme/DNA polymerase system," Proc Natl Acad Sci 1992,
89, 392-396. cited by applicant .
Walsh et al., "Detection of inherited mutations for breast and
ovarian cancer using genomic capture and massively parallel
sequencing," Proc Natl Acad Sci 2010, 107(28), 12629-12633. cited
by applicant .
Wang et al., "Combining Gold Nanoparticles with Real-Time
Immuno-PCR for Analysis of HIV p24 Antigens," Proceedings of ICBBE
2007, 1198-1201. cited by applicant .
Wang et al., "RNA-Seq: a revolutionary tool for transcriptomics,"
Nature Reviews Genetics 2009, 10(1), 57-63. cited by applicant
.
Wang et al., "iCLIP predicts the dual splicing effects of TIA-RNA
interactions," PLoS Biol 2010, 8(10), e1000530, 1-16. cited by
applicant .
Wang et al., "Advances and applications of single-cell sequencing
technologies," Molecular Cell 2015, 58, 598-609. cited by applicant
.
Warren et al., "Transcription factor profiling in individual
hematopoietic progenitors by digital RT-PCR," PNAS 2006, 103(47),
17807-17812. cited by applicant .
Weber et al., "A real-time polymerase chain reaction assay for
quantification of allele ratios and correction of amplification
bias," Anal Biochem. 2003, 320, 252-258. cited by applicant .
Weibrecht et al., "Proximity ligation assays: a recent addition to
the proteomics toolbox," Expert Rev. Proteomics 2010, 7(3),
401-409. cited by applicant .
Weiner et al., "Kits and their unique role in molecular biology: a
brief retrospective," BioTechniques 2008, 44(5), 701-704. cited by
applicant .
White et al., "High-throughput microfluidic single-cell RT-qPCR,"
PNAS 2011, 108(34), 13999-14004. cited by applicant .
Wittes et al., "Searching for Evidence of Altered Gene Expression:
a Comment on Statistical Analysis of Microarray Data," Journal of
the National Cancer Institute 1999, 91 (5), 400-401. cited by
applicant .
Wodicka et al., "Genome-wide expression monitoring in Saccharomyces
cerevisiae," Nature Biotechnology 1997, 15, 1359-1367. cited by
applicant .
Wojdacz et al., "Primer design versus PCR bias in methylation
independent PCR amplifications," Epigenetics 2009, 4(4), 231-234.
cited by applicant .
Wood et al., "Using next-generation sequencing for high resolution
multiplex analysis of copy number variation from nanogram
quantities of DNA from formalin-fixed paraffin-embedded specimens,"
Nucleic Acids Res. 2010, 38(14), 1-14. cited by applicant .
Written Submission of Publications dated Jun. 14, 2018 in Japanese
Patent Application No. 2016-537867. cited by applicant .
Wu et al., "Quantitative assessment of single-cell RNA-sequencing
methods," Nat Methods 2014, 11(1), 41-46. cited by applicant .
Yandell et al., "A probabilistic disease-gene finder for personal
genomes," Genome Res. 2011, 21(9), 1529-1542. cited by applicant
.
Ye et al., Fluorescent microsphere-based readout technology for
multiplexed human single nucleotide polymorphism analysis and
bacterial identification, Human Mutation 2001, 17(4), 305-316.
cited by applicant .
Yoon et al., Sensitive and accurate detection of copy number
variants using read depth of coverage, Genome Res. 2009, 19,
1586-1592. cited by applicant .
Zagordi et al., "Error correction of next-generation sequencing
data and reliable estimation of HIV quasispecies," Nucleic Acids
Research 2010, 38(21), 7400-7409. cited by applicant .
Zhang et al., "The impact of next-generation sequencing on
genomics," J Genet Genomics 2011, 38(3), 95-109. cited by applicant
.
Zhang et al., "DNA-based hybridization chain reaction for amplified
bioelectronic signal and ultrasensitive detection of proteins,"
Anal Chem. 2012, 84, 5392-5399. cited by applicant .
Zhao et al., "Homozygous Deletions and Chromosome Amplifications in
Human Lung Carcinomas Revealed by Single Nucleotide Polymorphism
Array Analysis," Cancer Research 2005, 65(13), 5561-5570. cited by
applicant .
Zheng et al., "Haplotyping germline and cancer genomes with
high-throughput linked-read sequencing," Nature Biotechnology 2016,
34(3), 303-311. cited by applicant .
Zhou et al., "Counting alleles reveals a connection between
chromosome 18q loss and vascular invasion," Nature Biotechnology
2001, 19, 78-81. cited by applicant .
Zhou et al., "Photocleavable Peptide-Oligonucleotide Conjugates for
Protein Kinase Assays by MALDI-TOF MS," Mol. BioSyst. 2012, 8,
2395-2404. cited by applicant .
Zhu et al., "Reverse Transcriptase Template Switching: A Smart
Approach for Full-Length cDNA Library Construction," BioTechniques
2001, 30(4), 892-897. cited by applicant .
Examination Report dated Mar. 25, 2021 in European Patent
Application No. 17781265.8. cited by applicant .
Final Office Action dated Feb. 11, 2021 in U.S. Appl. No.
15/134,967. cited by applicant .
Final Office Action dated Mar. 16, 2021 in U.S. Appl. No.
15/715,028. cited by applicant .
Final Office Action dated Mar. 25, 2021 in U.S. Appl. No.
16/374,626. cited by applicant .
GenBank Accession No. NM_000518.5 for Homo sapiens hemoglobin
subunit beta (HBB), mRNA. Mar. 22, 2021 [online], [retrieved on
Apr. 27, 2021], retrieved from the Internet: <URL:
www.ncbi.nlm.nih.gov/nuccore/NM_000518.5?report=Genbank (Year:
2021). cited by applicant .
International Preliminary Report on Patentability dated Feb. 9,
2021 in PCT Application No. PCT/US2019/043949. cited by applicant
.
International Preliminary Report on Patentability dated Feb. 23,
2021 in PCT Application No. PCT/US2019/046549. cited by applicant
.
International Preliminary Report on Patentability dated Mar. 2,
2021 in PCT Application No. PCT/US2019/048179. cited by applicant
.
International Search Report and Written Opinion dated Jan. 19, 2021
in PCT Application No. PCT/US2020/059419. cited by applicant .
International Search Report and Written Opinion dated Apr. 9, 2021
in PCT Application No. PCT/US2021/013137. cited by applicant .
International Search Report and Written Opinion dated Apr. 21, 2021
in PCT Application No. PCT/US2021/015571. cited by applicant .
New COVID-19 Variants, Centers for Disease Control and Prevention
2021, accessed Jan. 21, 2021, 3 pp. cited by applicant .
Non-Final Office Action dated Jan. 19, 2021 in U.S. Appl. No.
16/836,750. cited by applicant .
Non-Final Office Action dated Feb. 25, 2021 in U.S. Appl. No.
15/055,407. cited by applicant .
Non-Final Office Action dated Feb. 25, 2021 in U.S. Appl. No.
15/084,307. cited by applicant .
Non-Final Office Action dated Mar. 29, 2021 in U.S. Appl. No.
16/789,358. cited by applicant .
Non-Final Office Action dated Apr. 14, 2021 in U.S. Appl. No.
16/789,311. cited by applicant .
Non-Final Office Action dated Apr. 20, 2021 in U.S. Appl. No.
15/875,816. cited by applicant .
Notice of Allowance dated Jan. 13, 2021 in U.S. Appl. No.
14/381,488. cited by applicant .
Notice of Allowance dated Jan. 13, 2021 in U.S. Appl. No.
15/459,977. cited by applicant .
Notice of Allowance dated Apr. 26, 2021 in Japanese Patent
Application No. 2019-014564. cited by applicant .
Office Action dated Jan. 6, 2021 in Chinese Patent Application No.
201680052330.2. cited by applicant .
Office Action dated Jan. 14, 2021 in Japanese Patent Application
No. 2019-014564. cited by applicant .
Office Action dated Jan. 15, 2021 in Korean Patent Application No.
10-2020-7033213. cited by applicant .
Office Action dated Jan. 26, 2021 in Chinese Patent Application No.
201680007351.2. cited by applicant .
Office Action dated Feb. 4, 2021 in Canadian Patent Application No.
2,865,575. cited by applicant .
Office Action dated Feb. 20, 2021 in Chinese Patent Application No.
201680022865.5. cited by applicant .
Office Action dated Mar. 1, 2021 in Chinese Patent Application No.
201680007652.5. cited by applicant .
Office Action dated Mar. 2, 2021 in Chinese Patent Application No.
2016800157452. cited by applicant .
Office Action dated Mar. 8, 2021 in Japanese Patent Application No.
2018-512152. cited by applicant .
Office Action dated Mar. 16, 2021 in Chinese Patent Application No.
2018800377201. cited by applicant .
Stoeckius et al., "Cell Hashing with barcoded antibodies enables
multiplexing and doublet detection for single cell genomics,"
Genome Biology 2018, 19(224), 1-12. cited by applicant .
TotalSeq.TM.-A0251 anti-human Hashtag 1 Antibody, BioLegend.RTM.,
Jul. 2018, 1-10. cited by applicant .
Vestheim et al., "Application of Blocking Oligonucleotides to
Improve Signal-to-Noise Ratio in a PCR," Methods in Molecular
Biology 2011, 687, 265-274. cited by applicant .
Zeberg et al., "The major genetic risk factor for severe COVID-19
is inherited from Neanderthals," Nature 2020, 587(7835), 1-13.
cited by applicant .
Extended European Search Report dated May 6, 2021 in European
Patent Application No. 20207621.2. cited by applicant .
Extended European Search Report dated May 28, 2021 in European
Patent Application No. 20209777.0. cited by applicant .
Final Office Action dated Jun. 15, 2021 in U.S. Appl. No.
15/084,307. cited by applicant .
Final Office Action dated Jul. 15, 2021 in U.S. Appl. No.
16/836,750. cited by applicant .
Final Office Action dated Aug. 10, 2021 in U.S. Appl. No.
16/012,584. cited by applicant .
Fitzgerald and Grivel, "A Universal Nanoparticle Cell Secretion
Capture Assay," Cytometry Part A 2012, 83A(2), 205-211. cited by
applicant .
Gratton et al., "Cell-permeable peptides improve cellular uptake
and therapeutic gene delivery of replication-deficient viruses in
cells and in vivo," Nature Medicine 2003, 9(3), 357-362. cited by
applicant .
International Search Report and Written Opinion dated May 4, 2021
in PCT Application No. PCT/US2021/013109. cited by applicant .
International Search Report and Written Opinion dated May 11, 2021
in PCT Application No. PCT/US2021/013748. cited by applicant .
International Search Report and Written Opinion dated Jul. 15, 2021
in PCT Application No. PCT/US2021/019475. cited by applicant .
International Search Report and Written Opinion dated Jul. 20, 2021
in PCT Application No. PCT/US2021/015898. cited by applicant .
Invitation to Pay Fees dated May 25, 2021 in PCT Application No.
PCT/US2021/01598. cited by applicant .
Invitation to Provide Informal Clarification dated Jun. 9, 2021 in
PCT Application No. PCT/US2021/019475. cited by applicant .
Non-Final Office Action dated Jun. 9, 2021 in U.S. Appl. No.
16/588,405. cited by applicant .
Non-Final Office Action dated Aug. 17, 2021 in U.S. Appl. No.
16/551,620. cited by applicant .
Notice of Allowance dated Jun. 10, 2021 in Chinese Patent
Application No. 2018800377201. cited by applicant .
Notice of Allowance dated Aug. 16, 2021 in Japanese Patent
Application No. 2018-512152. cited by applicant .
Novus Biologicals, "Fixation and Permeability in ICC IF," Novus
Biologicals 2021, 1-3. cited by applicant .
Office Action dated May 10, 2021 in Japanese Patent Application No.
2019-566787. cited by applicant .
Office Action dated May 21, 2021 in Chinese Patent Application No.
201680007351.2. cited by applicant .
Office Action dated Jul. 26, 2021 in Korean Patent Application No.
10-2019-7011635. cited by applicant .
Office Action dated Jul. 28, 2021 in Korean Patent Application No.
10-2020-7033213. cited by applicant .
Prevette et al., "Polycation-Induced Cell Membrane Permeability
Does Not Enhance Cellular Uptake or Expression Efficiency of
Delivered DNA," Molecular Pharmaceutics 2010, 7(3), 870-883. cited
by applicant .
Restriction Requirement dated May 5, 2021 in U.S. Appl. No.
16/400,886. cited by applicant .
Restriction Requirement dated May 28, 2021 in U.S. Appl. No.
16/781,814. cited by applicant .
Restriction Requirement dated Jun. 4, 2021 in U.S. Appl. No.
16/551,620. cited by applicant .
Cai, Mar. 2013, Turning single cells in microarrays by
super-resolution bar-coding, Brief Funct Genomics, 12(2):75-80.
cited by applicant .
Castellarnau et al., Jan. 2015, Stochastic particle barcoding for
single-cell tracking and multiparametric analysis, Small,
11(4):489-498. cited by applicant .
Dalerba et al., 2011, Single-cell dissection of transcriptional
heterogeneity in human colon tumors, Nat Biotechnol.,
29(12):1120-1127 and Supplementary Material. cited by applicant
.
Fan, Nov. 2010, Molecular counting: from noninvasive prenatal
diagnostics to whole-genome haplotyping, doctoral dissertation,
Stanford University, 185 pp. cited by applicant .
Gong et al., 2010, Massively parallel detection of gene expression
in single cells using subnanolitre wells, Lab Chip, 10:2334-2337.
cited by applicant .
Haff, 1994, Improved quantitative PCR using nested primers, PCR
Methods and Applications, 3:332-337. cited by applicant .
Kebschull et al., Jul. 17, 2015, Sources of PCR-induced distortions
in high-throughput sequencing data sets, Nucleic Acids Research, 15
pp. cited by applicant .
Kim et al., Jun. 8, 2007, Polony multiplex analysis of gene
expression (PMAGE) in mouse hypertrophic cardiomyopathy, Science,
316(5830):1481-1484. cited by applicant .
Kotake et al., 1996, A simple nested RT-PCR method for quantitation
of the relative amounts of multiple cytokine mRNAs in small tissue
samples, Journal of Immunological Methods, 199:193-203. cited by
applicant .
Kurimoto et al., Mar. 17 2006, An improved single-cell cDNA
amplification method for efficient high-density oligonucleotide
microarray analysis, Nucleic Acids Res., 34(5):e42. cited by
applicant .
Lee et al., 2010, Large-scale arrays of picolitre chambers for
single-cell analysis of large cell populations, Lab Chip,
10:2952-2958. cited by applicant .
Marcus et a., 2006, Microfluidic single-cell mRNA isolation and
analysis, Ana. Chem. 78:3084-3089. cited by applicant .
Nagai et al., 2001, Development of a microchamber array for
picoleter PCR, Anal. Chem., 73:1043-1047. cited by applicant .
Picelli et al., Jul. 30, 2014, Tn5 transposase and tagmentation
procedures for massively scaled sequencing projects, Genome
Research 24(12):2033-2040. cited by applicant .
Soumillon et al., Mar. 5, 2014, Characterization of directed
differentiation by high-throughput single-cell RNA-Seq, bioRxiv
preprint,
http://biorxiv.org/content/early/2014/03/05/003236.full.pdf, 13 pp.
cited by applicant .
Speicher et al., Oct. 2005, The new cytogenetics: blurring the
boundaries with molecular biology, Nature Reviews Genetics,
6(10):782-792. cited by applicant .
Takahashi et al., Mar. 2006, Novel technique of quantitative nested
real-time PCR assay for Mycobacterium tuberculosis DNA, Journal of
Clinical Microbiology, 44(3):1029-1039. cited by applicant .
Wang et al., May 21, 2015, Advances and applications of single-cell
sequencing technologies, Molecular Cell, 58(4):598-609. cited by
applicant .
Warren et al., Nov. 21, 2006, Transcription factor profiling in
individual hematopoietic progenitors by digital RT-PCR, PNAS,
103(47):17807-17812. cited by applicant .
White et al., Aug. 23, 2011, High-throughput microfluidic
single-cell RT-qPCR, PNAS, 108(34):13999-14004. cited by applicant
.
Zheng et al., Feb. 2016, Haplotyping germline and cancer genomes
with high-throughput linked-read sequencing, Nature Biotechnology,
34(3):303-311. cited by applicant .
International Search Report and Written Opinion dated May 3, 2016
in PCT/US16/018354. cited by applicant .
Office action dated Jul. 20, 2016 for U.S. Appl. No. 14/281,706.
cited by applicant .
Office Action dated May 10, 2016 in U.S. Appl. No. 14/381,488.
cited by applicant .
Office Action dated Aug. 12, 2016 in U.S. Appl. No. 14/381,488.
cited by applicant .
Second Office Action dated Jun. 6, 2016 in Chinese patent
application No. 201380022187.9. cited by applicant .
Examination report dated Jul. 12, 2016 in European patent
application No. 13755319.4. cited by applicant .
Examination Report dated Jun. 8, 2016 in GB patent application No.
1408829.8. cited by applicant .
Office action dated Aug. 17, 2016 for U.S. Appl. No. 14/800,526.
cited by applicant .
Examination Report dated Jun. 15, 2016 in Great Britain patent
application No. GB1511591.8. cited by applicant .
Office Action dated May 13, 2016 in U.S. Appl. No. 14/508,911.
cited by applicant .
International Search Report and Written Opinion dated Jun. 20, 2016
in PCT/US16/14612. cited by applicant .
International Search Report and Written Opinion dated Jun. 17, 2016
in PCT/US16/019962. cited by applicant .
Written Opinion dated Jul. 5, 2016 in PCT/US16/019962. cited by
applicant .
Invitation to Pay Additional Search Fees dated Jun. 2, 2016 in
PCT/US16/019971. cited by applicant .
ISR and WO dated Aug. 9, 2016 in PCT/US16/019971. cited by
applicant .
International Search Report and Written Opinion dated Jun. 9, 2016
in PCT/US16/022712. cited by applicant .
Anderson, Feb. 11, 2014, Study describes RNA sequencing
applications for molecular indexing methods, genomeweb.com, 5 pp.
cited by applicant .
Bioscribe, Feb. 5, 2015, Massively parallel sequencing technology
for single-cell gene expression published (press release), 3 pp.
cited by applicant .
Brisco et al., Jun. 25, 2012, Quantification of RNA integrity and
its use for measurement of transcript number, Nucleic Acids
Research, 40(18):e144. cited by applicant .
Butkus, Feb. 6, 2014, Cellular research set to launch first gene
expression platform using `molecular indexing` technology,
genomeweb.com, 5 pp. cited by applicant .
Junker et al., May 21, 2015, Single-cell transcriptomics enters the
age of mass production, Molecular Cell, 58:563-564. cited by
applicant .
Klein et al., May 21, 2015, Droplet barcoding for single-cell
transcriptomics applied to embryonic stem cells, Cell,
161:1187-1201. cited by applicant .
Kolodziejczyk et al., May 21, 2015, The technology and biology of
single-cell RNA sequencing, Molecular Cell, 58:610-620. cited by
applicant .
Lamble et al., Nov. 20, 2013, Improved workflows for high
throughput library preparation using the transposome-based nextera
system, BMC Biotechnology, 13(1):104. cited by applicant .
Liu et al., Single-cell transcriptome sequencing: recent advances
and remaining challenges, F1000Research 2016, 5(F1000 Faculty
Rev):182, 9 pp. cited by applicant .
Martinez et al., Jul. 2012, A microfluidic approach to encapsulate
living cells in uniform alginate hydrogel microparticles, Macromol.
Biosci, 12(7):946-951. cited by applicant .
Nadai et al., 2008, Protocol for nearly full-length sequencing of
HIV-1 RNA from plasma, PLoS One, 3(1):e1420. cited by applicant
.
Navin et al., 2015, The first five years of single-cell cancer
genomics and beyond, Genome Research, 25(10):1499-1507. cited by
applicant .
Pfaffl et al., Mar. 2004, Determination of stable housekeeping
genes, differentially regulated target genes and sample integrity:
BestKeeper--Excel-based tool using pair-wise correlations,
Biotechnology Letters, 26(6):505-515. cited by applicant .
Rajeevan et al., Oct. 2003, Global amplification of sense RNA: a
novel method to replicate and archive mRNA for gene expression
analysis, Genomics, 82(4):491-497. cited by applicant .
Stratagene 1998 Catalog, Gene Characterization Kits, p. 39. cited
by applicant .
Vandesompele et al., Jun. 18, 2002, Accurate normalization of
real-time quantitative RT-PCR data by geometric averaging of
multiple internal control genes, Genome Biology, 3(7). cited by
applicant .
Weiner et al., Apr. 2008, Kits and their unique role in molecular
biology: a brief retrospective, BioTechniques, 44:701-704. cited by
applicant .
Office Action dated Oct. 11, 2016 in U.S. Appl. No. 15/224,460.
cited by applicant .
Office Action dated Oct. 25, 2015 in U.S. Appl. No. 14/872,337.
cited by applicant .
Office action dated Sep. 26, 2016 in U.S. Appl. No. 15/167,807.
cited by applicant .
Written Opinion dated Sep. 27, 2016 in PCT/US16/019962. cited by
applicant .
International Search Report and Written Opinion dated Sep. 28, 2016
in PCT/US16/028694. cited by applicant .
International Search Report and Written Opinion dated Sep. 27, 2016
in PCT/US16/034473. cited by applicant .
Achim et al., May 2015, High-throughput spatial mapping of
single-cell RNA-seq data to tissue of origin. Nature Biotechnology,
33(5):503-511. cited by applicant .
Alkan et al., Oct. 2009, Personalized copy number and segmental
duplication maps using next-generation sequencing. Nat Genet.,
41(10):1061-1067. cited by applicant .
Ansorge, 2009, Next-generation DNA sequencing techniques. New
Biotechnology, 25(4):195-203. cited by applicant .
Atanur et al., Jun. 2010, The genome sequence of the spontaneously
hypertensive rat: Analysis and functional significance. Genome
Res., 20(6):791-803. cited by applicant .
Audic et al., 1997, The Significance of Digital Gene Expression
Profiles. Genome Research, 7:986-995. cited by applicant .
Bendall et al., May 6, 2011, Single-cell mass cytometry of
differential immune and drug responses across a human hematopoietic
continuum. Science, 332(6030):687-696. cited by applicant .
Bionumbers, Aug. 21, 2010, Useful fundamental numbers in molecular
biology, http://bionumbers.hms.harvard.edu/KeyNumbers/aspx, 4 pp.
cited by applicant .
Blainey, May 2013, The future is now: single-cell genomics of
bacteria and archaea, FEMS Microbiol Rev., 37(3):407-427. cited by
applicant .
Bonaldo et al., Sep. 1996, Normalization and subtraction: two
approaches to facilitate gene discovery. Genome Res., 6(9):791-806.
cited by applicant .
Braha et al., 2000, Simultaneous stochastic sensing of divalent
metal ions. Nature Biotechnology, 18:1005-1007. cited by applicant
.
Bratke et al., Sep. 2005, Differential expression of human
granzymes A, B, and K in natural killer cells and during CD8+ T
cell differentiation in peripheral blood. Eur J Immunol.,
35(9):2608-2616. cited by applicant .
Brenner et al., 2000, Gene expression analysis by massively
parallel signature sequencing (MPSS) on microbead arrays. Nature
Biotechnology, 18:630-634. cited by applicant .
Brenner et al., Feb. 15, 2000, In vitro cloning of complex mixtures
of DNA on microbeads: physical separation of differentially
expressed cDNAs. Proc Natl Acad Sci, 97(4):1665-1670. cited by
applicant .
Brodin et al., 2015, Challenges with using primer IDs to improve
accuracy of next generation sequencing, 19(3):1-12. cited by
applicant .
Carr et al., Dec. 15, 2009, Inferring relative proportions of DNA
variants from sequencing electropherograms. Bioinformatics,
25(24):3244-3250. cited by applicant .
Casbon et al., Jul. 2011, A method for counting PCR template
molecules with application to next-generation sequencing. Nucleic
Acids Res., 39(12):e81. cited by applicant .
Castle et al., Apr. 16, 2010, DNA copy number, including telomeres
and mitochondria, assayed using next-generation sequencing. BMC
Genomics, 11:244. doi: 10.1186/1471-2164-11-244. cited by applicant
.
Chamberlain et al., Dec. 9, 1988, Deletion screening of the
Duchenne muscular dystrophy locus via multiplex DNA amplification.
Nucleic Acids Res., 16(23):11141-11156. cited by applicant .
Chang et al., Aug. 2002, Detection of allelic imbalance in ascitic
supernatant by digital single nucleotide polymorphism analysis.
Clin Cancer Res., 8(8):2580-2585. cited by applicant .
Chee et al., 1996, Accessing genetic information with high-density
DNA arrays, Science, 274:610-614. cited by applicant .
Chee, 1991, Enzymatic multiplex DNA sequencing. Nucleic Acids
Research, 19(12): 3301-3305. cited by applicant .
Chen et al., Apr. 9, 2015, Spatially resolved, highly multiplexed
RNA profiling in single cells. Science Express, pp. 1-21. cited by
applicant .
Church et al., 1988, Multiplex DNA sequencing. Science,
240:185-188. cited by applicant .
Costello et al., Apr. 1, 2013, Discovery and characterization of
artifactual mutations in deep coverage targeted capture sequencing
data due to oxidative DNA damage during sample preparation. Nucleic
Acids Res, 41(6):e67. cited by applicant .
Cox. May 2001, Bar coding objects with DNA. Analyst,
126(5):545-547. cited by applicant .
Craig et al., Oct. 2008, Identification of genetic variants using
bar-coded multiplexed sequencing. Nat Methods, 5(10):887-893. cited
by applicant .
Cusanovich et al., May 7, 2014, Multiplex single-cell profiling of
chromatin accessibility by combinatorial cellular indexing. Science
Express, pp. 1-9. cited by applicant .
Daines et al., Aug. 2009, High-throughput multiplex sequencing to
discover copy number variants in Drosophila. Genetics,
182(4):935-941. cited by applicant .
D'Antoni et al., May 1, 2006, Rapid quantitative analysis using a
single molecule counting approach. Anal Biochem. 352(1):97-109.
cited by applicant .
Daser et al., 2006, Interrogation of genomes by molecular
copy-number counting (MCC). Nature Methods, 3(6):447-453. cited by
applicant .
De Saizieu et al., 1998, Bacterial transcript imaging by
hybridization of total RNA to oligonucleotide arrays. Nature
Biotechnology, 16:45-48. cited by applicant .
Dirks et al., Oct. 26, 2004, Triggered amplification by
hybridization chain reaction., Proc Natl Acad Sci U S A,
101(43),15275-15278. cited by applicant .
Fan et al., Feb. 6, 2015, Combinatorial labeling of single cells
for gene expression cytometry. Science, 347(6222):1258367-8. cited
by applicant .
Fan et al., 2000, Parallel Genotyping of Human SNPs Using Generic
High-density Oligonucleotide Tag Arrays. Genome Research,
10:853-860. cited by applicant .
Fan et al., 2009, Microfluidic digital PCR enables rapid prenatal
diagnosis of fetal aneuploidy. Am Obstet Gynecol.
200:543.e1-543.e7. cited by applicant .
Fan et al., Jul. 19, 2012, Non-invasive prenatal measurement of the
fetal genome. Nature, 487(7407):320-324. cited by applicant .
Feldhaus et al., Jan. 15, 2000, Oligonucleotide-conjugated beads
for transdominant genetic experiments, Nucleic Acids Res.,
28(2):534-543. cited by applicant .
Fox-Walsh et al., Oct. 2011, A multiplex RNA-seq strategy to
profile poly(A+) RNA: application to analysis of transcription
response and 3' end formation., Genomics, 98(4),266-721. cited by
applicant .
Fu et al., Marcy 18, 2014, Digital encoding of cellular mRNAs
enabling precise and absolute gene expression measurement by
single-molecule counting. Anal Chem., 86(6):2867-2870. cited by
applicant .
Fu et al., May 31, 2011, Counting individual DNA molecules by the
stochastic attachment of diverse labels. Proc Natl Acad Sci,
108(22):9026-9031. cited by applicant .
Gerry et al., 1999, Universal DNA microarray method for multiplex
detection of low abundance point mutations. Journal of Molecular
Biology, 292(2): 251-262. cited by applicant .
Gillespie, 1977, Exact stochastic simulation of coupled chemical
reactions. The Journal of Physical Chemistry, 81(25):2340-2361.
cited by applicant .
Grant et al., Nov. 15, 2002, SNP genotyping on a genome-wide
amplified DOP-PCR template. Nucleic Acids Res, 30(22):e125. cited
by applicant .
Gunderson et al., May 2004, Decoding randomly ordered DNA arrays.
Genome Res. 14(5):870-877. cited by applicant .
Gundry et al., Jan. 3, 2012, Direct mutation analysis by
high-throughput sequencing: from germline to low-abundant, somatic
variants. Mutat Res. 729(1-2):1-15. cited by applicant .
Gundry et al., Mar. 2012, Direct, genome-wide assessment of DNA
mutations in single cells. Nucleic Acids Res., 40(5):2032-40. cited
by applicant .
Hacia et al., 1999, Determination of ancestral alleles for human
single-nucleotide polymorphisms using high-density oligonucleotide
arrays. Nature Genetics, 22:164-167. cited by applicant .
Hamady et al., Mar. 2008, Error-correcting barcoded primers for
pyrosequencing hundreds of samples in multiplex. Nat Methods,
5(3):235-237. cited by applicant .
Harrington et al.,2009, Cross-sectional characterization of HIV-1
env compartmentalization in cerebrospinal fluid over the full
disease course, AIDS, 23(8) 907-915. cited by applicant .
Hashimshony et al., Sep. 27, 2012, CEL-Seq: single-cell RNA-Seq by
multiplexed linear amplification Cell Rep. 2(3):666-673. cited by
applicant .
Hensel et al., Jul. 21, 1995, Simultaneous identification of
bacterial virulence genes by negative selection. Science.
269(5222):400-403. cited by applicant .
Hiatt et al., Feb. 2010, Parallel, tag-directed assembly of locally
derived short sequence reads. Nat Methods, 7(2):119-122. cited by
applicant .
Hiatt et al., May 2013, Single molecule molecular inversion probes
for targeted, high-accuracy detection of low-frequency variation.
Genome Res., 23(5):843-854. cited by applicant .
Hollas et al., 2003, A stochastic approach to count RNA molecules
using DNA sequencing methods. Lecture Notes in Computer Science,
2812:55-62. cited by applicant .
Hug et al., 2003, Measure of the number of molecular of a single
mRNA species in a complex mRNA preparation, Journal of Theoretical
Biology, 221:615-624. cited by applicant .
Ingolia et al., Apr. 10, 2009, Genome-wide analysis in vivo of
translation with nucleotide resolution using ribosome profiling.
Science, 324(5924):218-223. cited by applicant .
Islam et al., 2011, Characterization of the single-cell
transcriptional landscape by highly multiplex RNA-seq. Genome
Research, 21:1160-1167. cited by applicant .
Islam et al., 2014, Quantitative single-cell RNA-seq with unique
molecular identifiers, Nature Methods, 11(2):163-168. cited by
applicant .
Jabara et al., Dec. 3, 2011, Accurate sampling and deep sequencing
of the HIV-1 protease gene using a Primer ID, PNAS,
108(50):20166-20171. cited by applicant .
Jabara, Apr. 23, 2010, Capturing the cloud: High throughput
sequencing of multiple individual genomes from a retroviral
population. Biology Lunch Bunch Series, Training Initiatives in
Biomedical & Biological Sciences of the University of North
Carolina at Chapel Hill. cited by applicant .
Kanagawa, 2003, Bias and artifacts in multitemplate polymerase
chain reactions (PCR), Journal of Bioscience and Bioengineering,
96(4):317-323. cited by applicant .
Keys et al., Jun. 2015, Primer ID informs next-generation
sequencing platforms and reveals preexisting drug resistance
mutations in the HIV-1 reverse transcriptase coding domain, AIDS
Research and Human Retroviruses, 31(6):658-668. cited by applicant
.
Kinde et al., Jun. 7, 2011, Detection and quantification of rare
mutations with massively parallel sequencing, Proc. Natl Acad Sci,
108(23):9530-0535. cited by applicant .
Kivioja et al., Jan. 2012, Counting absolute numbers of molecules
using unique molecular identifiers. Nature Methods, 9(1):72-76.
cited by applicant .
Koboldt et al., Sep. 1, 2009, VarScan: variant detection in
massively parallel sequencing of individual and pooled samples.
Bioinformatics. 25(17):2283-2285. cited by applicant .
Konig et al., Jul. 2010, iCLIP reveals the function of hnRNAP
particles in splicing at individual nucleotide resolution, Nature
Structural & Molecular Biology, 17(7):909-916. cited by
applicant .
Larson et al., Nov. 2009, A single molecule view of of gene
expression. Trends Cell Biol. 19(11):630-637. cited by applicant
.
Leamon et al., Nov. 2003, A massively parallel PicoTiterPlate based
platform for discrete picoliter-scale polymerase chain reactions,
Electrophoresis, 24(21):3769-3777. cited by applicant .
Lee et al., Mar. 21, 2014, Highly multiplexed subcellular RNA
sequencing in situ. Science. 343(6177):1360-1363. cited by
applicant .
Lizardi et al., Jul. 1998, Mutation detection and single-molecule
counting using isothermal rolling-circle amplification. Nat Genet.
19(3):225-32. cited by applicant .
Lockhart et al., 1996, Expression monitoring by hybridization to
high-density oligonucleotide arrays. Nature Biotechnology,
14:1675-1680. cited by applicant .
Lovatt et al., Feb. 2014, Transcriptome in vivo analysis (TIVA) of
spatially defined single cells in live tissue. Nat Methods.
11(2):190-196. cited by applicant .
Lucito et al., 1996, Representational Oligonucleotide Microarray
Analysis: A High-Resolution Method to Detect Genome Copy Number
Variation. Genome Research, 13: 2291-2305. cited by applicant .
Maamar et al., 2007, Noise in Gene Expression Determines Cell Fate
in Bacillus subtilis. Science, 317:526-529. cited by applicant
.
Macaulay et al., 2015, G&T-seq: parallel sequencing of
single-cell genomes and transcriptomes. Nature Methods, pp. 1-7.
cited by applicant .
Macosko et al., 2015, Highly parallel genome-wide expression
profiling of individual cells using nanoliter droplets, Cell
161:1202-1214 (and supplemental information). cited by applicant
.
Makrigiorgos et al., Sep. 2002, A PCR-Based amplification method
retaining quantative difference between two complex genomes. Nature
Biotech, 20(9):936-939. cited by applicant .
Margulies et al., Sep. 15, 2005 Genome sequencing in
microfabricated high-density picolitre reactors, Nature,
437:376-380. cited by applicant .
McCloskey et al., Dec. 2007, Encoding PCR products with
batch-stamps and barcodes. Biochem Genet. 45(11-12):761-767. cited
by applicant .
Medvedev et al., Nov. 2010, Detecting copy number variation with
mated short reads. Genome Res. 20(11):1613-1622. cited by applicant
.
Mei et al., Mar. 22, 2010, Identification of recurrent regions of
Copy-Number Variants across multiple individuals. BMC
Bioinformatics. 11:147. cited by applicant .
Merriam-Webster, definition of associate,:
http://www.merriam-webster.com/dictionary/associate, accessed Apr.
5, 2016. cited by applicant .
Miller et al., 2006, Directed evolution by in vitro
compartmentalization, Nature Methods, 3:561-570. cited by applicant
.
Miner et al., 2004, Molecular barcodes detect redundancy and
contamination in hairpin-bisulfite PCR, Nucleic Acids Research,
32(17):e135. cited by applicant .
Mortazavi et al., 2008, Mapping and quantifying mammalian
transcriptomes by RNA-Seq. Nat. Methods. 5:621-628. cited by
applicant .
Newell et al., Jan. 27, 2012, Cytometry by time-of-flight shows
combinatorial cytokine expression and virus-specific cell niches
within a continuum of CD8+ T cell phenotypes. Immunity.
36(1):142-152. cited by applicant .
Novak et al., Jan. 20, 2011, Single-cell multiplex gene detection
and sequencing with microfluidically generated agarose emulsions,
Angew Chem Int Ed Engl., 50(2):390-395. cited by applicant .
Ogino et al., Nov. 2002, Quantification of PCR bias caused by a
single nucleotide polymorphism in SMN gene dosage analysis. J Mol
Diagn. 4(4):185-190. cited by applicant .
Parameswaran et al., 2007, A pyrosequencing-tailored nucleotide
barcode design unveils opportunities for large-scale sample
multiplexing. Nucleic Acids Res. 35(19):e130. cited by applicant
.
Park et al., May 2010, Discovery of common Asian copy number
variants using integrated high-resolution array CGH and massively
parallel DNA sequencing. Nat Genet. 42(5):400-405. cited by
applicant .
Pihlak et al., 2008, Rapid genome sequencing with short universal
tiling probes. Nature Biotechnology, 26:676-684. cited by applicant
.
Pinkel et al., 2005, Comparative Genomic Hybridization. Annual
Review of Genomics and Human Genetics, 6:331-354. cited by
applicant .
Pleasance et al., Jan. 14, 2010, A small-cell lung cancer genome
with complex signatures of tobacco exposure. Nature.
463(7278):184-190. cited by applicant .
Plessy et al., Feb. 2013, Population transcriptomics with
single-cell resolution: a new field made possible by micorfluidics:
a technology for high throughput transcript counting and
data-driven definition of cell types, Bioessays, 35(2):131-140.
cited by applicant .
Qiu et al., Oct. 2003, DNA sequence-based "bar codes" for tracking
the origins of expressed sequence tags from a maize cDNA library
constructed using multiple mRNA sources. Plant Physiol.
133(2):475-481. cited by applicant .
Roche Diagnostics GmbH, 2006, Genome Sequencer 20 System: First to
the Finish (product brochure), 40 pp. cited by applicant .
Sasagawa et al., 2013, Quartz-Seq: a highly reproducible and
sensitive single-cell RNA sequencing method, reveals non-genetic
gene-expression heterogeneity. Genome Biology, 14:R31. cited by
applicant .
Sasuga et al., Dec. 2008, Single-cell chemical lysis method for
analyses of intracellular molecules using an array of
picoliter-scale microwells, Anal Chem, 80(23):9141-9149. cited by
applicant .
Satija et al., May 2015, Spatial reconstruction of single-cell gene
expression data. Nature Biotechnology, 33(5):495-508. cited by
applicant .
Schmitt et al., Sep. 4, 2012, Detection of ultra-rare mutations by
next-generation sequencing. Proc Natl Acad Sci U S A.
109(36):14508-14513. cited by applicant .
Sebat et al., 2004, Large-Scale Copy Number Polymorphism in the
Human Genome. Science, 305:525-528. cited by applicant .
Shalek et al., Jun. 13, 2013, Single-cell transcriptomics reveals
bimodality in expression and splicing in immune cells. Nature.
498(7453):236-240. cited by applicant .
Shiroguchi et al., Jan. 24, 2012, Digital RNA sequencing minimizes
sequence-dependent bias and amplification noise with optimized
single-molecule barcodes. Proc Natl Acad Sci U S A.
109(4):1347-1352. cited by applicant .
Shoemaker et al., 1996, Quantitative phenotypic analysis of yeast
deletion mutants using a highly parallel molecular bar-coding
strategy. Nature Genetics, 14:450-456. cited by applicant .
Simpson et al., Feb. 15, 2010, Copy Number variant detection in
inbred strains from short read sequence data. Bioinformatics.
26(4):565-567. cited by applicant .
Smith et al., 2010, Highly-multiplexed barcode sequencing: an
efficient method for parallel analysis of pooled samples. Nucleic
Acids Research, 38(13):e142. cited by applicant .
Tan et al., Apr. 2013, Genome-wide comparison of DNA
hydroxymethylation in mouse embryonic stem cells and neural
progenitor cells by a new comparative hMeDIP-seq method. Nucleic
Acids Res. 41(7):e84. cited by applicant .
Taudien et al., Apr. 19, 2010, Haplotyping and copy number
estimation of the highly polymorphic human beta-defensin locus on
8p23 by 454 amplicon sequencing. BMC Genomics. 11:252. cited by
applicant .
The Tibbs Times, UNC bioscience newsletter, Apr. 2010, 17 pp. cited
by applicant .
Tomaz et al., Aug. 2010, Differential methylation as a cause of
allele dropout at the imprinted GNAS locus. Genet Test Mol
Biomarkers. 14(4):455-460. cited by applicant .
Treutlein et al., May 15, 2014, Reconstructing lineage hierarchies
of the distal lung epithelium using single-cell RNA-seq. Nature.
509(7500):371-375. cited by applicant .
Velculescu et al., 1995, Serial Analysis of Gene Expression.
Science, 270:484-487. cited by applicant .
Velculescu et al., 1997, Characterization of the Yeast
Transcriptome. Cell, 88:243-251. cited by applicant .
Vogelstein et al., 1999, Digital PCR. Proc. Natl. Acad. Sci.,
96(16):9236-9241. cited by applicant .
Walker et al., Jan. 1, 1992, Isothermal in vitro amplification of
DNA by a restriction enzyme/DNA polymerase system. Proc Natl Acad
Sci U S A., 89(1):392-396. cited by applicant .
Walsh et al., Jul. 13, 2010, Detection of inherited mutations for
breast and ovarian cancer using genomic capture and massively
parallel sequencing. Proc Natl Acad Sci U S A. 107(28):12629-12633.
cited by applicant .
Wang et al., 2009, RNA-Seq: a revolutionary tool for
transcriptomics. Nature Reviews Genetics, 10:57-63. cited by
applicant .
Wang et al., Oct. 2010, iCLIP predicts the dual splicing effects of
TIA-RNA interactions, PLoS Biol, 8(10):e1000530. cited by applicant
.
Weber et al., Sep. 15, 2003, A real-time polymerase chain reaction
assay for quantification of allele ratios and correction of
amplification bias. Anal Biochem. 320(2):252-258. cited by
applicant .
Wittes et al., 1999, Searching for Evidence of Altered Gene
Expression: a Comment on Statistical Analysis of Microarray Data.
Journal of the National Cancer Institute, 91(5):400-401. cited by
applicant .
Wodicka et al., 1997, Genome-wide expression monitoring in
Saccharomyces cerevisiae. Nature Biotechnology, 15:1359-1367. cited
by applicant .
Wojdacz et al., May 16, 2009, Primer design versus PCR bias in
methylation independent PCR amplifications. Epigenetics.
4(4):231-234. cited by applicant .
Wood et al., Aug. 2010, Using next-generation sequencing for high
resolution multiplex analysis of copy number variation from
nanogram quantities of DNA from formalin-fixed paraffin-embedded
specimens. Nucleic Acids Res. 38(14):e151. cited by applicant .
Wu et al., Jan. 2014, Quantitative assessment of single-cell
RNA-sequencing methods. Nat Methods. 11(1):41-46. cited by
applicant .
Yandell et al., Sep. 2011, A probabilistic disease-gene finder for
personal genomes. Genome Res. 21(9):1529-1542. cited by applicant
.
Ye et al., 2001, Fluorescent microsphere-based readout technology
for multiplexed human single nucleotide polymorphism analysis and
bacterial identification. Human Mutation, 17(4):305-316. cited by
applicant .
Yoon et al., Sep. 2009, Sensitive and accurate detection of copy
number variants using read depth of coverage. Genome Res.
19(9):1586-1592. cited by applicant .
Zhang et al., Jun. 19, 2012, DNA-based hybridization chain reaction
for amplified bioelectronic signal and ultrasensitive detection of
proteins., Anal Chem., 84(12),5392-5399. cited by applicant .
Zhang et al., Mar. 20, 2011, The impact of next-generation
sequencing on genomics. J Genet Genomics. 38(3):95-109. cited by
applicant .
Zhao et al., 2005, Homozygous Deletions and Chromosome
Amplifications in Human Lung Carcinomas Revealed by Single
Nucleotide Polymorphism Array Analysis. Cancer Research,
65:5561-5570. cited by applicant .
Zhou et al., 2001, Counting alleles reveals a connection between
chromosome 18q loss and vascular invasion. Nature Biotechnology,
19:78-81. cited by applicant .
Chapin et al., 2011, Rapid microRNA profiling on encoded gel
microparticles, Angew. Chem. Int. Ed., 50:2289-2293. cited by
applicant .
Lee et al., May 2014, Universal process-inert encoding architecture
for polymer microparticles, Nature Materials, 13:524-529. cited by
applicant .
Office action dated Oct. 3, 2013 for U.S. Appl. No. 12/969,581.
cited by applicant .
Response with allowed claims dated Mar. 4, 2014 for U.S. Appl. No.
12/969,581. cited by applicant .
Notice of allowance dated Mar. 21, 2014 for U.S. Appl. No.
12/969,581. cited by applicant .
Notice of allowance dated Jun. 19, 2014 for U.S. Appl. No.
12/969,581. cited by applicant .
Notice of allowance dated Aug. 22, 2014 for U.S. Appl. No.
12/969,581. cited by applicant .
Office action dated Dec. 3, 2015 for U.S. Appl. No. 14/281,706.
cited by applicant .
Office Action dated May 7, 2015 for U.S. Appl. No. 13/327,526.
cited by applicant .
Notice of allowance dated Jan. 21, 2016 for U.S. Appl. No.
13/327,526. cited by applicant .
Office action dated Feb. 18, 2015 for U.S. Appl. No. 14/540,007.
cited by applicant .
Office action dated Sep. 24, 2015 for U.S. Appl. No. 14/540,007.
cited by applicant .
Notice of allowance dated Dec. 15, 2015 for U.S. Appl. No.
14/540,007. cited by applicant .
Office action dated Mar. 19, 2015 for U.S. Appl. No. 14/540,018.
cited by applicant .
Office action dated Oct. 6, 2015 for U.S. Appl. No. 14/540,018.
cited by applicant .
Notice of allowance dated Dec. 21, 2015 for U.S. Appl. No.
14/540,018. cited by applicant .
Office Action dated Feb. 26, 2015 for U.S. Appl. No. 14/540,029.
cited by applicant .
Office action dated Sep. 1, 2015 for U.S. Appl. No. 14/540,029.
cited by applicant .
International Search Report and Written Opinion dated Jun. 6, 2012
in PCT/US11/065291. cited by applicant .
Restriction Requirement dated Mar. 15, 2016 in U.S. Appl. No.
14/381,488. cited by applicant .
International Search Report and Written Opinion dated Sep. 6, 2013
in PCT/US13/028103. cited by applicant .
European search report and search opinion dated Jul. 17, 2015 for
EP Application No. 13755319.4. cited by applicant .
Search and Examination Report dated Aug. 6, 2014 for GB patent
application No. 1408829.8. cited by applicant .
Search and Examination Report dated Jan. 27, 2016 in GB patent
application No. 1408829.8. cited by applicant .
Search Report and Written Opinion mailed Mar. 1, 2016 in Singapore
patent application No. 1120140527W. cited by applicant .
International search report and written opinion dated Aug. 16, 2013
for PCT/US2013/027891. cited by applicant .
Extended European Search Report dated Dec. 15, 2015 in European
patent application No. 13754428.4. cited by applicant .
Restriction Requirement dated Mar. 17, 2016 in U.S. Appl. No.
14/472,363. cited by applicant .
Office Action dated Apr. 11, 2016 in U.S. Appl. No. 14/472,363.
cited by applicant .
Office action dated Dec. 31, 2015 for U.S. Appl. No. 14/800,526.
cited by applicant .
Office action dated Apr. 11, 2016 for U.S. Appl. No. 14/800,526.
cited by applicant .
International Search Report and Written Opinion dated Feb. 3, 2015
in PCT/US/14/053301. cited by applicant .
Search and Examination Report dated Aug. 26, 2015 in GB patent
application No. 1511591.8. cited by applicant .
Examination Report dated Feb. 19, 2016 in Great Britain patent
application No. GB1511591.8. cited by applicant .
International search report and written opinion dated Dec. 19, 2014
for PCT Application No. US2014/059542. cited by applicant .
International search report and written opinion dated May 7, 2012
for PCT/IB2011/003160. cited by applicant .
Notice of opposition dated Jul. 22, 2015 for EP Application No.
11810645.9. cited by applicant .
Notice of opposition dated Jul. 9, 2015 for EP Application No.
11810645.9. cited by applicant .
Bogdanova et al., Jan. 2008, Normalization of full-length enriched
cDNA, Molecular Biosystems, 4(3):205. cited by applicant .
Patanjali et al., Mar. 1991, Construction of a uniform-abundance
(normalized) CNDA library, Proceedings of the National Academy of
Sciences, 88(5):1943-1947. cited by applicant .
Office Action dated Feb. 13, 2017 in U.S. Appl. No. 14/381,488.
cited by applicant .
Office Action dated Feb. 17, 2017 in Canadian patent application
No. 2,865,575. cited by applicant .
Third Office Action dated Dec. 27, 2016 in Chinese patent
application No. 201380022187.9. cited by applicant .
Official Action dated Dec. 28, 2016 in Japanese patent application
No. 2014-558975. cited by applicant .
Combined Search and Examination Report dated Feb. 21, 2017 in GB
patent application No. 1609740.4. cited by applicant .
Office Action dated Mar. 24, 2017 in U.S. Appl. No. 15/409,355.
cited by applicant .
International Search Report and Written Opinion dated Dec. 5, 2016
in PCT/US16/024783. cited by applicant .
International Search Report and Written Opinion dated Jan. 31, 2017
in PCT/US16/050694. cited by applicant.
|
Primary Examiner: Diamond; Alan D
Attorney, Agent or Firm: Sheppard, Mullin, Richter &
Hampton LLP
Parent Case Text
RELATED APPLICATIONS
The present application .Iadd.is a reissue of U.S. Pat. No.
9,727,810, issued on Aug. 8, 2017 from U.S. patent application Ser.
No. 15/055,445, filed on Feb. 26, 2016, which .Iaddend.claims
priority under 35 U.S.C. .sctn.119(e) to U.S. Provisional
Application No. 62/126,230, filed on Feb. 27, 2015, and U.S.
Provisional Application No. 62/162,471, filed on May 15, 2015. The
content of .Iadd.each of .Iaddend.these related applications
.Iadd.and the patent .Iaddend.is herein expressly incorporated by
reference in its entirety.
Claims
What is claimed is:
1. A method for determining spatial locations of a plurality of
single cells, comprising: stochastically barcoding the plurality of
single cells using a plurality of synthetic particles, wherein each
of the plurality of synthetic particles comprises a plurality of
stochastic barcodes, a first group of optical labels, and a second
group of optical labels, wherein each of the plurality of
stochastic barcodes comprises a cellular label and a molecular
label, wherein each optical label in the first group of optical
labels comprises a first optical moiety and each optical label in
the second group of optical labels comprises a second optical
moiety, and wherein each of the plurality of synthetic particles is
associated with an optical barcode comprising the first optical
moiety and the second optical moiety; detecting the optical barcode
of each of the plurality of synthetic particles to determine the
location of each of the plurality of synthetic particles; and
determining the spatial locations of the plurality of single cells
based on the locations of the plurality of synthetic particles.
2. The method of claim 1, wherein the first optical moiety and the
second optical moiety are selected from a group .[.comprising.].
.Iadd.consisting of .Iaddend.two or more spectrally-distinct
optical moieties.
3. The method of claim 1, wherein stochastically barcoding the
plurality of single cells using the plurality of synthetic
particles comprises contacting the plurality of single cells with
the plurality of synthetic particles.
4. The method of claim 3, wherein a synthetic particle of the
plurality of synthetic particles is in close proximity to a single
cell or a small number of cells.
5. The method of claim 3, wherein each of the plurality of single
cells comprises a plurality of targets, wherein stochastically
barcoding the plurality of single cells further comprises
hybridizing the plurality of stochastic barcodes with the plurality
of targets to generate stochastically barcoded targets, and wherein
at least one of the plurality of targets is hybridized to one of
the plurality of stochastic barcodes.
6. The method of claim 1, wherein cellular labels of at least two
stochastic barcodes of the plurality of stochastic barcodes on one
synthetic particle have the same sequence, and wherein cellular
labels of at least two stochastic barcodes of the plurality of
stochastic barcodes on different synthetic particles have different
sequences.
7. The method of claim 1, wherein molecular labels of at least two
stochastic barcodes of the plurality of stochastic barcodes on one
synthetic particle have different sequences.
8. The method of claim 1, wherein the molecular labels are selected
from a group .[.comprising.]. .Iadd.consisting of .Iaddend.at least
100 molecular labels with unique sequences.
9. The method of claim 1, wherein the molecular labels are selected
from a group .[.comprising.]. .Iadd.consisting of .Iaddend.at least
1000 molecular labels with unique sequences.
10. The method of claim 1, wherein detecting the optical barcode of
each of the plurality of synthetic particles to determine the
location of each of the plurality of synthetic particles comprises
generating an optical image showing the optical barcodes and the
locations of the plurality of synthetic particles.
11. The method of claim 1, wherein the plurality of single cells
comprises cells distributed across a microwell array comprising
microwells.
12. The method of claim 11, .Iadd.wherein each of the plurality of
single cells comprises a plurality of targets, the method
.Iaddend.comprising: lysing the plurality of single cells; and
generating an indexed library of stochastically barcoded targets,
.Iadd.wherein generating an indexed library of stochastically
barcoded targets comprises hybridizing the plurality of stochastic
barcodes with the plurality of targets to generate stochastically
barcoded targets, wherein the molecular label comprises a molecular
label sequence, wherein the cellular label comprises a cellular
label sequence, and .Iaddend. wherein each of the stochastically
barcoded targets comprises a cellular label sequence, a molecular
label sequence, and at least a portion of .[.the.]. .Iadd.a
.Iaddend.complementary sequence of one of the plurality of
targets.
13. The method of claim 12, comprising: amplifying the
stochastically barcoded targets of the indexed library to generate
amplified stochastically barcoded targets; and sequencing the
amplified stochastically barcoded targets to determine the number
of amplified stochastically barcoded targets with unique molecular
label sequences and identical complementary sequence, wherein the
number of amplified stochastically barcoded targets with unique
molecular label sequences and identical complementary sequence is
substantially the same as the occurrences of targets with sequences
complementary of the identical complementary sequence in the single
cell or the small number of cells.
14. The method of claim 13, wherein the labeled target molecules
are amplified using bridge amplification, amplification with a gene
specific primer, amplification with a universal primer,
amplification with an oligo(dT) primer, or any combination
thereof.
15. The method of claim 1, wherein the plurality of single cells
comprises a tissue, a cell monolayer, fixed cells, a tissue
section, or any combination thereof.
16. The method of claim 1, wherein a synthetic particle of the
plurality of synthetic .[.particle.]. .Iadd.particles .Iaddend.is a
bead.
17. The method of claim 16, wherein the bead is selected from the
group .[.comprising.]. .Iadd.consisting of .Iaddend.streptavidin
beads, agarose beads, magnetic beads, conjugated beads, protein A
conjugated beads, protein G conjugated beads, protein A/G
conjugated beads, protein L conjugated beads, oligo(dT) conjugated
beads, silica beads, silica-like beads, anti-biotin microbead,
anti-fluorochrome microbead, and any combination thereof.
18. The method of claim 1, wherein a synthetic particle of the
plurality of synthetic particles comprises a material selected from
the group .[.comprising.]. .Iadd.consisting of
.Iaddend.polydimethylsiloxane (PDMS), polystyrene, glass,
polypropylene, agarose, hydrogel, paramagnetic, ceramic, plastic,
glass, methylstyrene, acrylic polymer, titanium, latex, sepharose,
cellulose, nylon, silicone, and any combination thereof.
19. A .[.synthetic particle.]. .Iadd.composition.Iaddend.,
comprising: .Iadd.a synthetic particle; .Iaddend. a plurality of
stochastic barcodes, wherein each of the plurality of stochastic
barcodes comprises a cellular label and a molecular label; a first
group of optical labels; and a second group of optical labels,
.Iadd.wherein the plurality of stochastic barcodes, the first group
of optical labels, and the second group of optical labels are
attached to the surface of the synthetic particle, .Iaddend.
wherein each optical label in the first group of optical labels
comprises a first optical moiety and each optical label in the
second group of optical labels comprises a second optical moiety,
and wherein .[.each of the plurality of synthetic particles.].
.Iadd.the synthetic particle .Iaddend.is associated with an optical
barcode comprising the first optical moiety and the second optical
moiety.
20. The .[.synthetic particle.]. .Iadd.composition .Iaddend.of
claim 19, wherein the molecular labels of the plurality of
stochastic barcodes are different from one another, and the
molecular labels are selected from a group .[.comprising.].
.Iadd.consisting of .Iaddend.at least 100 molecular labels with
unique sequences.
21. The .[.synthetic particle.]. .Iadd.composition .Iaddend.of
claim 19, wherein cellular labels of at least two stochastic
barcodes of the plurality of stochastic barcodes have the same
sequence.
22. The .[.synthetic particle.]. .Iadd.composition .Iaddend.of
claim 19, wherein molecular labels of at least two stochastic
barcodes of the plurality of stochastic barcodes have different
sequences.
23. The .[.synthetic particle.]. .Iadd.composition .Iaddend.of
claim 19, wherein molecular labels of the plurality of stochastic
barcodes are selected from a group .[.comprising.].
.Iadd.consisting of .Iaddend.at least 100 molecular labels with
unique sequences.
24. The .[.synthetic particle.]. .Iadd.composition .Iaddend.of
claim 19, wherein molecular labels of the plurality of stochastic
barcodes are selected from a group .[.comprising.].
.Iadd.consisting of .Iaddend.at least 1000 molecular labels with
unique sequences.
25. The .[.synthetic particle.]. .Iadd.composition .Iaddend.of
claim 19, wherein the first optical moiety and the second optical
moiety are selected from a group .[.comprising.]. .Iadd.consisting
.Iaddend.two or more spectrally-distinct optical moieties.
26. The .[.synthetic particle.]. .Iadd.composition .Iaddend.of
claim 19, wherein each of the plurality of stochastic barcodes
comprises a spatial label, and wherein spatial labels of at least
two stochastic barcodes of the plurality of stochastic barcodes
differ from each other by at least one nucleotide.
27. The .[.synthetic particle.]. .Iadd.composition .Iaddend.of
claim 19, wherein each of the plurality of stochastic barcodes
further comprises a universal label, and wherein universal labels
of at least two stochastic barcodes of the plurality of stochastic
barcodes have the same sequence.
28. The .[.synthetic particle.]. .Iadd.composition .Iaddend.of
claim 19, wherein the synthetic particle is a bead.
29. The .[.synthetic particle.]. .Iadd.composition .Iaddend.of
claim 28, wherein the bead is selected from the group
.[.comprising.]. .Iadd.consisting of .Iaddend.streptavidin beads,
agarose beads, magnetic beads, conjugated beads, protein A
conjugated beads, protein G conjugated beads, protein A/G
conjugated beads, protein L conjugated beads, oligo(dT) conjugated
beads, silica beads, silica-like beads, anti-biotin microbead,
anti-fluorochrome microbead, and any combination thereof.
30. The .[.synthetic particle.]. .Iadd.composition .Iaddend.of
claim 19, wherein the synthetic particle comprises a material
selected from the group .[.comprising.]. .Iadd.consisting of
.Iaddend.polydimethylsiloxane (PDMS), polystyrene, glass,
polypropylene, agarose, hydrogel, paramagnetic, ceramic, plastic,
glass, methylstyrene, acrylic polymer, titanium, latex, sepharose,
cellulose, nylon, silicone, and any combination thereof.
.Iadd.31. A method for determining the number and spatial locations
of a plurality of targets in a sample, comprising: providing a
solid support comprising a plurality of synthetic particles
associated with a plurality of stochastic barcodes, wherein each of
the plurality of stochastic barcodes comprises a spatial label and
a molecular label; decoding the solid support by contacting the
solid support with a plurality of decoding nucleic acids labeled
with a decoding label and detecting the presence of the decoding
label, wherein at least some portion of each of the plurality of
stochastic barcodes is single stranded to allow hybridization to a
decoding nucleic acid, and wherein decoding comprises two or more
sequential hybridizations of decoding nucleic acids to each of the
plurality of stochastic barcodes; stochastically barcoding the
plurality of targets in the sample by hybridizing the plurality of
stochastic barcodes with the plurality of targets to generate
stochastically barcoded targets; identifying the spatial location
of each of the plurality of targets by correlating the spatial
labels of the plurality of the stochastic barcodes with the spatial
locations of the plurality of targets in the sample; and estimating
the number of each of the plurality of targets by determining
sequences of the spatial labels and molecular labels of the
plurality of the stochastic labels and counting the number of the
molecular labels with distinct sequences..Iaddend.
.Iadd.32. The method of claim 31, wherein the sample comprises a
plurality of cells, and wherein the plurality of targets is
associated with the plurality of cells..Iaddend.
.Iadd.33. The method of claim 31, wherein the sample comprises a
tissue, a cell monolayer, fixed cells, a tissue section, or any
combination thereof..Iaddend.
.Iadd.34. The method of claim 31, wherein the sample is physically
divided during stochastically barcoding the plurality of targets in
the sample..Iaddend.
.Iadd.35. The method of claim 31, wherein the spatial locations of
the plurality of targets in the sample are on a surface of the
sample, inside the sample, subcellularly in the sample, or any
combination thereof..Iaddend.
.Iadd.36. The method of claim 31, wherein stochastic barcoding the
plurality of targets in the sample is performed on the surface of
the sample, subcellularly in the sample, inside the sample, or any
combination thereof..Iaddend.
.Iadd.37. The method of claim 31, wherein the plurality of targets
comprises ribonucleic acids (RNAs), messenger RNAs (mRNAs),
microRNAs, small interfering RNAs (siRNAs), RNA degradation
products, RNAs each comprising a poly(A) tail, and any combination
thereof..Iaddend.
.Iadd.38. The method of claim 31, further comprising visualizing
the plurality of targets in the sample..Iaddend.
.Iadd.39. The method of claim 38, wherein visualizing the plurality
of targets in the sample comprises mapping the plurality of targets
onto a map of the sample..Iaddend.
.Iadd.40. The method of claim 31, wherein the synthetic particles
are beads..Iaddend.
.Iadd.41. The method of claim 40, wherein the beads are silica gel
beads, controlled pore glass beads, magnetic beads, dynabeads,
sephadex/sepharose beads, cellulose beads, polystyrene beads,
hydrogel beads, or any combination thereof..Iaddend.
.Iadd.42. The method of claim 31, wherein the molecular labels of
different stochastic barcodes are different from one
another..Iaddend.
.Iadd.43. The method of claim 31, wherein the sample is intact
during stochastically barcoding the plurality of targets in the
sample..Iaddend.
Description
BACKGROUND
Field
The present disclosure relates generally to the field of molecular
biology and more particularly to molecular barcoding.
Description of the Related Art
Methods and techniques such as in situ hybridization and
immunohistochemistry allow the visualization of the locations of
target molecules within the sample. Methods and techniques for
labeling target molecules for amplification and sequencing, for
example stochastic barcoding, are useful for determining the
identities of the target molecules. Determining the identities and
locations of the targets molecules in the sample is important for
clinical applications, diagnostics, and biomedical research. Thus,
there is a need for methods and techniques capable of correlating
the identities of the target molecules with the locations of target
molecules within the sample.
SUMMARY
Disclosed herein are methods for determining the number and spatial
locations of a plurality of targets in a sample. In some
embodiment, the methods include: stochastically barcoding the
plurality of targets in the sample using a plurality of stochastic
barcodes, wherein each of the plurality of stochastic barcodes
comprises a spatial label and a molecular label; estimating the
number of each of the plurality of targets using the molecular
label; and identifying the spatial location of each of the
plurality of targets using the spatial label. The method can be
multiplexed.
In some embodiments, stochastically barcoding the plurality of
targets in the sample can include hybridizing the plurality of
stochastic barcodes with the plurality of targets to generate
stochastically barcoded targets, and at least one of the plurality
of targets is hybridized to one of the plurality of stochastic
barcodes. Stochastically barcoding the plurality of targets in the
sample can include comprises generating an indexed library of the
stochastically barcoded targets. The molecular labels of different
stochastic barcodes can be different from one another. The sample
can be physically divided or is intact during stochastically
barcoding the plurality of targets in the sample. The spatial
locations of the plurality of targets in the sample can be on a
surface of the sample, inside the sample, subcellularly in the
sample, or any combination thereof. Stochastic barcoding the
plurality of targets in the sample can be performed on the surface
of the sample, subcellularly in the sample, inside the sample, or
any combination thereof.
In some embodiments, the spatial label can include 5-20
nucleotides. The molecular label can include 5-20 nucleotides.
Estimating the number of the plurality of targets using the
molecular label can include determining sequences of the spatial
labels and molecular labels of the plurality of the stochastic
labels and counting the number of the molecular labels with
distinct sequences. Determining the sequences of the spatial labels
and the molecular labels of the plurality of the stochastic
barcodes can include sequencing some or all of the plurality of
stochastic barcodes. Sequencing some or all of the plurality of
stochastic barcodes can include generating sequences each with a
read length of 100 or more bases. Identifying the spatial locations
of the plurality of targets can include correlating the spatial
labels of the plurality of the stochastic barcodes with the spatial
locations of the plurality of targets in the sample.
In some embodiments, the methods can include comprising visualizing
the plurality of targets in the sample. Visualizing the plurality
of targets in the sample can include mapping the plurality of
targets onto a map of the sample. Mapping the plurality of targets
onto the map of the sample can include generating a two dimensional
map or a three dimensional map of the sample. The two dimensional
map and the three dimensional map can be generated prior to or
after stochastically barcoding the plurality of targets in the
sample. In some embodiments, the two dimensional map and the three
dimensional map can be generated before or after lysing the sample.
Lysing the sample before or after generating the two dimensional
map or the three dimensional map can include heating the sample,
contacting the sample with a detergent, changing the pH of the
sample, or any combination thereof.
In some embodiments, the sample can include a plurality of cells
and the plurality of targets can be associated with the plurality
of cells. The plurality of cells can include one or more cell
types. At least one of the one or more cell types can be brain
cell, heart cell, cancer cell, circulating tumor cell, organ cell,
epithelial cell, metastatic cell, benign cell, primary cell,
circulatory cell, or any combination thereof. The plurality of
targets can include ribonucleic acids (RNAs), messenger RNAs
(mRNAs), microRNAs, small interfering RNAs (siRNAs), RNA
degradation products, RNAs each comprising a poly(A) tail, and any
combination thereof. Stochastically barcoding the plurality of
targets in the sample can be performed with a solid support
including the plurality of stochastic barcodes. In some
embodiments, the methods can include decoding the solid support.
The solid support can include a plurality of synthetic particles
associated with the plurality of stochastic barcodes. The spatial
labels of the plurality of stochastic barcodes on different solid
supports can differ by at least one nucleotide.
In some embodiments, each of the plurality of stochastic barcodes
can include one or more of a universal label and a cellular label,
wherein universal labels can be the same for the plurality of
stochastic barcodes on the solid support and cellular labels can be
the same for the plurality of stochastic barcodes on the solid
support. The universal label can include 5-20 nucleotides. The
cellular label can include 5-20 nucleotides. The solid support can
include the plurality of stochastic barcodes in two dimensions or
three dimensions. The synthetic particles can be beads. The beads
can be silica gel beads, controlled pore glass beads, magnetic
beads, Dynabeads, Sephadex/Sepharose beads, cellulose beads,
polystyrene beads, or any combination thereof. Solid support can
include a polymer, a matrix, a hydrogel, a needle array device, an
antibody, or any combination thereof.
Disclosed herein are methods for determining spatial locations of a
plurality of targets in a sample. In some embodiments, the methods
include: stochastically barcoding the plurality of targets in the
sample at one or more time points using a plurality of stochastic
barcodes, wherein each of the plurality of stochastic barcodes
comprises a spatial label; and identifying the spatial location of
each of the plurality of targets using the spatial label.
In some embodiments, stochastically barcoding the plurality of
targets in the sample using the plurality of stochastic barcodes
can include stochastically barcoding the plurality of targets in
the sample at different time points using the plurality of
stochastic barcodes. Each of the plurality of stochastic barcodes
can include a dimension label, and the dimension labels of the
plurality of stochastic barcodes used for stochastic barcoding the
plurality of targets at the different time points can be different.
The dimension labels can correlate with the different time
points.
In some embodiments, stochastically barcoding the plurality of
targets in the sample can include contacting the sample with a
device. The device can be a needle, a needle array, a tube, a
suction device, an injection device, an electroporation device, a
fluorescent activated cell sorter device, a microfluidic device, or
any combination thereof. The device can contact sections of the
sample at a specified rate. The specified rate can correlate the
spatial locations of the plurality of targets with the one or more
time points. Stochastically barcoding the plurality of targets in
the sample can be performed with a solid support including a
plurality of synthetic particles associated with the plurality of
stochastic barcodes.
Disclosed herein are synthetic particles. In some embodiments, each
synthetic particle, include: a plurality of stochastic barcodes,
wherein each of the plurality of stochastic barcodes comprises a
cellular label and a molecular label; a first group of optical
labels; a second group of optical labels, wherein each optical
label in the first group of optical labels comprises a first
optical moiety and each optical label in the second group of
optical labels comprises a second optical moiety, and wherein each
of the plurality of synthetic particles is associated with an
optical barcode comprising the first optical moiety and the second
optical moiety.
In some embodiments, the molecular labels of the plurality of
stochastic barcodes are different from one another, and the
molecular labels are selected from a group comprising at least 100
molecular labels with unique sequences. The cellular labels of the
plurality of stochastic barcodes can be same. The first optical
moiety and the second optical moiety are selected from a group
comprising two or more spectrally-distinct optical moieties. Each
of the plurality of stochastic barcodes can include a spatial
label, wherein the spatial labels of the plurality of stochastic
barcodes differ from one another by at least one nucleotide.
In some embodiments, each of the plurality of stochastic barcodes
further comprises a universal label, wherein universal labels of
all stochastic barcodes on the particle are the same. The synthetic
particle can be a bead or a magnetic bead. The bead can be a silica
gel bead, a controlled pore glass beads, a magnetic beads, a
Dynabead, a Sephadex/Sepharose bead, a cellulose beads, a
polystyrene bead, or any combination thereof.
Disclosed herein are methods for determining spatial locations of a
plurality of targets in a sample. In some embodiments, the methods
include: stochastically barcoding the plurality of targets in the
sample using a plurality of stochastic barcodes, wherein each of
the plurality of stochastic barcodes comprises a pre-spatial label;
concatenating one or more spatial label blocks onto the pre-spatial
label to generate a spatial label; and identifying the spatial
location of each of the plurality of targets using the spatial
label.
In some embodiments, stochastically barcoding the plurality of
targets in the sample can include hybridizing the plurality of
stochastic barcodes with the plurality of targets to generate
stochastically barcoded targets, and at least one of the plurality
of targets is hybridized to one of the plurality of stochastic
barcodes. Stochastically barcoding the plurality of targets in the
sample can include generating an indexed library of the
stochastically barcoded targets. The spatial label can include 5-20
nucleotides. The sample can include a plurality of cells and the
plurality of targets that can be associated with the plurality of
cells. The plurality of targets can include ribonucleic acids
(RNAs), messenger RNAs (mRNAs), microRNAs, small interfering RNAs
(siRNAs), RNA degradation products, RNAs each comprising a poly (A)
tail, and any combination thereof. Stochastically barcoding the
plurality of targets in the sample can be performed with a solid
support comprising the plurality of stochastic barcodes. In some
embodiments, the methods can include decoding the solid support.
The solid support can include a plurality of synthetic particles
associated with the plurality of stochastic barcodes. The synthetic
particles can be beads.
Disclosed herein can be methods for determining spatial locations
of a plurality of targets in a sample. In some embodiments, the
methods include: imaging the sample to generate a sample image;
stochastically barcoding the plurality of targets in the sample
using a plurality of stochastic barcodes to generate stochastically
barcoded targets, wherein each of the plurality of stochastic
barcodes can include a spatial label; and identifying the spatial
location of each of the plurality of targets using the spatial
label.
In some embodiments, identifying the spatial location of each of
the plurality of targets using the spatial label can include
correlating the sample image with the spatial labels of the
plurality of targets in the sample. Imaging the sample can include
staining the sample with a stain, wherein the stain can be a
fluorescent stain, a negative stain, an antibody stain, or any
combination thereof. Imaging the sample can include imaging the
sample using optical microscopy, electron microscopy, confocal
microscopy, fluorescence microscopy, or any combination
thereof.
In some embodiments, the sample can include a tissue, a cell
monolayer, fixed cells, a tissue section, or any combination
thereof. Correlating the sample image with the spatial labels of
the plurality of targets in the sample can include overlaying the
sample image with the spatial labels of the plurality of targets in
the sample. The sample can include a biological sample, a clinical
sample, an environmental sample, a biological fluid, a tissue, or a
cell from a subject. The subject can be a human, a mouse, a dog, a
rat, or a vertebrate.
In some embodiments, the methods can include determining genotype,
phenotype, or one or more genetic mutations of the subject based on
the spatial labels of the plurality of targets in the sample. In
some embodiments, the methods can include predicting susceptibility
of the subject to one or more diseases. At least one of the one or
more diseases can be cancer or a hereditary disease. The sample can
include a plurality of cells and the plurality of targets can be
associated with the plurality of cells. The plurality of cells can
include one or more cell types. In some embodiments, the methods
can include determining cell types of the plurality of cells in the
sample. The drug can be chosen based on predicted responsiveness of
the cell types of the plurality of cells in the sample.
Disclosed herein are methods for determining spatial locations of a
plurality of singles cells. In some embodiments, the methods can
include: stochastically barcoding the plurality of singe cells
using a plurality of synthetic particles, wherein each of the
plurality of synthetic particles can include a plurality of
stochastic barcodes, a first group of optical labels, and a second
group of optical labels, wherein each of the plurality of
stochastic barcodes can include a cellular label and a molecular
label, wherein each optical label in the first group of optical
labels can include a first optical moiety and each optical label in
the second group of optical labels can include a second optical
moiety, and wherein each of the plurality of synthetic particles
can be associated with an optical barcode including the first
optical moiety and the second optical moiety; detecting the optical
barcode of each of the plurality of synthetic particles to
determine the location of each of the plurality of synthetic
particles; and determining the spatial locations of the plurality
of single cells based on the locations of the plurality of
synthetic particles.
In some embodiments, stochastically barcoding the plurality of
single cells using the plurality of synthetic particles can include
contacting the plurality of single cells with the plurality of
synthetic particles, and each of the plurality of synthetic
particles can be in close proximity to a single cell or a small
number of cells. Each of the plurality of single cells can include
a plurality of targets, and stochastically barcoding the plurality
of single cells can include hybridizing the plurality of stochastic
barcodes with the plurality of targets to generate stochastically
barcoded targets, and at least one of the plurality of targets can
be hybridized to one of the plurality of stochastic barcodes.
In some embodiments, the cellular labels of the plurality of
stochastic barcodes on one synthetic particle can have the same
sequence and the cellular labels of the plurality of stochastic
barcodes on different synthetic particles can have different
sequences. The molecular labels of the plurality of stochastic
barcodes on one synthetic barcode can be different from one
another, and the molecular labels can be selected from a group
including at least 100 molecular labels with unique sequences. The
first optical moiety and the second optical moiety can be selected
from a group including two or more spectrally-distinct optical
moieties. Determining the optical barcodes of the plurality of
synthetic particles and determining the optical barcodes of the
plurality of synthetic particles can include generating an optical
image showing the optical barcodes and the locations of the
plurality of synthetic particles.
In some embodiments, the plurality of single cells can include
cells distributed across a well array including wells, and each of
a majority of the wells in the well array contains at most one
single cell. In some embodiments, the methods can include lysing
the plurality of single cells; and generating an indexed library of
stochastically barcoded targets, wherein each of the stochastically
barcoded targets can include a cellular label sequence, a molecular
label sequence, and at least a portion of the complementary
sequence of one of the plurality of targets. The methods can
include amplifying the stochastically barcoded targets of the
indexed library to generate amplified stochastically barcoded
targets; and sequencing the amplified stochastically barcoded
targets to determine the number of amplified stochastically
barcoded targets with unique molecular label sequences and
identical complementary sequence, wherein the number of amplified
stochastically barcoded targets with unique molecular label
sequences and identical complementary sequence can be substantially
the same as the occurrences of targets with sequences complementary
of the identical complementary sequence in the single cell or the
small number of cells. The plurality of cells can include a tissue,
a cell monolayer, fixed cells, a tissue section, or any combination
thereof. Amplifying the labeled target molecules can include bridge
amplification, amplification with a gene specific primer, a
universal primer, an oligo(dT) primer, or any combination
thereof.
Disclosed herein are methods for identifying distinct cells in two
or more samples. In some embodiments, the methods can include:
stochastically barcoding a plurality of targets in the two or more
samples using a plurality of stochastic barcodes, wherein each of
the plurality of stochastic barcodes can include a spatial label
and a molecular label; estimating the number of the plurality of
targets in the two or more samples using the molecular label; and
distinguishing the two or more samples from each other using the
spatial label, wherein the plurality of targets associated with
stochastic barcodes with different spatial labels can be from
different samples.
In some embodiments, stochastically barcoding the plurality of
targets in the two or more samples can include hybridizing the
plurality of stochastic barcodes with the plurality of targets to
generate stochastically barcoded targets, and at least one of the
plurality of targets can be hybridized to one of the plurality of
stochastic barcodes. Stochastically barcoding the plurality of
targets in the two or more samples can include generating an
indexed library of the stochastically barcoded targets. The spatial
label can include 5-20 nucleotides. The molecular label can include
5-20 nucleotides. Each of the two or more samples can include a
plurality of cells and the plurality of targets can be associated
with the plurality of cells. The plurality of targets can include
ribonucleic acids (RNAs), messenger RNAs (mRNAs), microRNAs, small
interfering RNAs (siRNAs), RNA degradation products, RNAs each
including a poly(A) tail, and any combination thereof.
Stochastically barcoding the plurality of targets in the two or
more samples can be performed with a solid support including a
plurality of synthetic particles associated with the plurality of
stochastic barcodes. The synthetic particles can be beads. The
beads can be silica gel beads, controlled pore glass beads,
magnetic beads, Dynabeads, Sephadex/Sepharose beads, cellulose
beads, polystyrene beads, or any combination thereof.
Disclosed herein are kits for determining the number and spatial
locations of a plurality of targets in a sample. In some
embodiments, the kits can include: a plurality of stochastic
barcodes, wherein each of the plurality of stochastic barcodes can
include a spatial label, wherein the spatial labels of the
plurality of stochastic barcodes differ from one another by at
least one nucleotide; and instructions for using the plurality of
stochastic barcodes. The plurality of stochastic barcodes can be
associated with a solid support. The solid support can include a
plurality of synthetic particles associated with the plurality of
synthetic particles.
In some embodiments, each of the plurality of synthetic particles
can include a first group of optical labels and a second group of
optical labels, and each optical label in the first group of
optical labels can include a first optical moiety, each optical
label in the second group of optical labels can include a second
optical moiety, and the first optical moiety and the second optical
moiety can be selected from a group including two or more
spectrally-distinct optical moieties. Each of the plurality of
stochastic barcodes can include one or more of a molecular label, a
universal label, and a cellular label, wherein universal labels and
cellular labels of all stochastic barcodes on the solid support can
be the same.
In some embodiments, the solid support can include the plurality of
stochastic barcodes in two dimensions or three dimensions. The
plurality of synthetic particles can be beads. The beads can be
silica gel beads, controlled pore glass beads, magnetic beads,
Dynabeads, Sephadex/Sepharose beads, cellulose beads, polystyrene
beads, or any combination thereof. The synthetic particles can be
magnetic beads. The solid support can include a polymer, a matrix,
a hydrogel, a needle array device, an antibody, or any combination
thereof. In some embodiments, the kits can include a buffer. The
kits can include a cartridge. The solid support can be pre-loaded
on a substrate. The kits can include one or more reagents for a
reverse transcription reaction. The kits can include one or more
reagents for an amplification reaction.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 shows a non-limiting exemplary embodiment for determining
spatial locations of distinct targets in a sample.
FIG. 2 illustrates a non-limiting exemplary stochastic barcode.
FIG. 3 shows a non-limiting exemplary workflow of stochastic
barcoding and digital counting.
FIG. 4 is a schematic illustration showing a non-limiting exemplary
process for generating an indexed library of the stochastically
barcoded targets from a plurality of targets.
FIG. 5 illustrates a non-limiting exemplary embodiment for
determining spatial locations of targets in a sample by maintaining
physiological orientation of sections of the sample.
FIG. 6 illustrates a non-limiting exemplary embodiment for
determining spatial locations of targets in a sample by time
points.
FIG. 7 illustrates a non-limiting exemplary embodiment for
determining spatial locations of targets in a sample by randomizing
the orientation of sections of the sample.
FIG. 8 shows a non-limiting exemplary schematic of label
lithography.
FIG. 9 shows a non-limiting exemplary embodiment for determining
spatial locations of targets in a sample using label
lithography.
FIG. 10 shows a non-limiting exemplary embodiment for
distinguishing targets of a sample for a plurality of samples.
FIG. 11 shows a non-limiting exemplary embodiment for
distinguishing subcellular localization of targets in a cell.
FIG. 12 illustrates a non-limiting exemplary embodiment for
homopolymer tailing.
FIG. 13 shows a non-limiting exemplary instrument used in the
methods of the disclosure.
FIG. 14 illustrates a non-limiting exemplary architecture of a
computer system that can be used in connection with embodiments of
the present disclosure.
FIG. 15 illustrates a non-limiting exemplary architecture showing a
network with a plurality of computer systems for use in the methods
of the disclosure.
FIG. 16 illustrates a non-limiting exemplary architecture of a
multiprocessor computer system using a shared virtual address
memory space in accordance with the methods of the disclosure.
FIGS. 17A-C depicts a non-limiting exemplary cartridge for use in
the methods of the disclosure.
FIGS. 18A-B shows different arrangements of optical labels on the
surface of a synthetic particle.
FIG. 19 shows the hybridization of oligonucleotides in the first
encoding step of Example 4.
FIG. 20 is a lookup table showing the oligonucleotide content in
each of the 96 wells in the first plate.
FIG. 21 shows the single stranded oligonucleotides in the various
regions on the synthetic particles after polymerization, ligation,
and denaturation of duplex DNA in the first encoding step.
FIG. 22 shows the hybridization of oligonucleotides in the second
encoding step of Example 4.
FIG. 23 is a lookup table showing the oligonucleotide content in
each of the 96 wells in the second plate.
FIG. 24 shows the single stranded oligonucleotides in the various
regions on the synthetic particles after polymerization, ligation,
and denaturation of duplex DNA in the second encoding step.
FIG. 25 shows the hybridization of oligonucleotides in the third
encoding step of example 4.
FIG. 26 is a lookup table showing the oligonucleotide content in
each of the 96 wells in the third plate.
FIG. 27 shows the single stranded oligonucleotides in the various
regions on the synthetic particles after polymerization, ligation,
and denaturation of duplex DNA in the third encoding step.
FIG. 28 is a schematic illustration of a non-limiting exemplary
synthetic particle being coated with DNA barcodes and the
spectrally resolvable barcode.
FIG. 29 shows an exemplary combination of the spectrally resolvable
barcode, PS1-9, of a synthetic particle.
DETAILED DESCRIPTION
In the following detailed description, reference is made to the
accompanying drawings, which form a part hereof. In the drawings,
similar symbols typically identify similar components, unless
context dictates otherwise. The illustrative embodiments described
in the detailed description, drawings, and claims are not meant to
be limiting. Other embodiments may be utilized, and other changes
may be made, without departing from the spirit or scope of the
subject matter presented herein. It will be readily understood that
the aspects of the present disclosure, as generally described
herein, and illustrated in the Figures, can be arranged,
substituted, combined, separated, and designed in a wide variety of
different configurations, all of which are explicitly contemplated
herein and made part of the disclosure herein.
In one aspect the disclosure provides for a method for determining
the number and spatial location of one or more targets in a sample
comprising: contacting the spatial location in the sample with one
or more stochastic barcodes, wherein each stochastic barcode
comprises a spatial label and a molecular label; estimating the
number of the one or more targets in the spatial location using the
molecular label; and identifying the spatial location of the one or
more targets using the spatial label. In some embodiments, the
contacting comprises hybridizing the stochastic barcode with the
one or more targets. In some embodiments, the hybridizing comprises
hybridizing the one or more targets such that each of the one or
more targets is hybridized to a unique stochastic barcode. In some
embodiments, molecular labels of the stochastic barcodes are
different. In some embodiments, the sample is physically divided
during the contacting. In some embodiments, the sample is intact
during the contacting. In some embodiments, the contacting is
performed on the surface of the sample. In some embodiments, the
contacting is performed inside the sample. In some embodiments, the
contacting is performed subcellularly in the sample. In some
embodiments, the spatial location is subcellular. In some
embodiments, the contacting is performed on a substrate. In some
embodiments, the substrate comprises the one or more stochastic
barcodes in a known order. In some embodiments, the substrate
comprises the one or more stochastic barcodes in an unknown order.
In some embodiments, the method further comprises decoding the
substrate. In some embodiments, the spatial label comprises from
5-20 nucleotides. In some embodiments, the estimating comprises
generating a target-barcode molecule. In some embodiments, the
target-barcode molecule comprises the sequence of a stochastic
barcode to which it is associated. In some embodiments, the
estimating further comprises determining the sequence of the
spatial label and the molecular label. In some embodiments, the
method further comprises counting occurrences of distinct sequences
of the molecular label. In some embodiments, the counting is used
to estimate the number of one or more targets. In some embodiments,
the determining comprises sequencing the stochastic barcodes. In
some embodiments, the sequencing comprises sequencing with read
lengths of at least 100 bases. In some embodiments, the sequencing
comprises sequencing with read lengths of at least 500 bases. In
some embodiments, the identifying comprises correlating the spatial
label with the spatial location in the sample. In some embodiments,
the method further comprises visualizing the number of the one or
more targets at the spatial location. In some embodiments, the
visualizing comprises mapping the number of the one or more targets
onto a map of the sample. In some embodiments, the visualizing
comprises imaging the sample at a time point selected from the
group consisting of: imaging the sample prior to the contacting,
imaging the sample after the contacting, imaging the sample before
lysing the sample, imaging the sample after lysing the sample. In
some embodiments, the imaging produces an image that is used to
construct a map of a physical representation of the sample. In some
embodiments, the map is two dimensional. In some embodiments, the
map is three dimensional. In some embodiments, the sample comprises
a single cell. In some embodiments, the sample comprises a
plurality of cells. In some embodiments, the plurality of cells
comprises a one or more different cell types. In some embodiments,
the one or more cell types are selected from the group consisting
of: brain cells, heart cells, cancer cells, circulating tumor
cells, organ cells, epithelial cells, metastatic cells, benign
cells, primary cells, and circulatory cells, or any combination
thereof. In some embodiments, the sample comprises a solid tissue.
In some embodiments, the sample is obtained from a subject. In some
embodiments, the subject is a subject selected from the group
consisting of: a human, a mammal, a dog, a rat, a mouse, a fish, a
fly, a worm, a plant, a fungus, a bacterium, a virus, a vertebrate,
and an invertebrate. In some embodiments, the one or more targets
are ribonucleic acid molecules. In some embodiments, the
ribonucleic acid molecules are selected from the group consisting
of: mRNA, microRNA, mRNA degradation products, and ribonucleic
acids comprising a poly(A) tail, or any combination thereof. In
some embodiments, the targets are deoxyribonucleic acid molecules.
In some embodiments, the contacting is performed with a solid
support. In some embodiments, the solid support can comprise a
plurality of stochastic barcodes. In some embodiments, each
stochastic barcode of the plurality of stochastic barcodes
comprises a spatial label. In some embodiments, spatial labels on
different solid supports differ by at least one nucleotide. In some
embodiments, the stochastic barcode further comprises a universal
label, and a cellular label. In some embodiments, the universal
label and the cellular label are the same for all stochastic
barcodes on the solid support. In some embodiments, the solid
support comprises stochastic barcodes in two dimensions. In some
embodiments, the solid support comprises stochastic barcodes in
three dimensions. In some embodiments, the solid supports comprise
a bead. In some embodiments, the bead is selected from the group
consisting of: silica gel bead, controlled pore glass bead,
magnetic bead, Dynabeads, Sephadex/Sepharose beads, cellulose
beads, and polystyrene beads, or any combination thereof. In some
embodiments, the bead comprises a magnetic bead. In some
embodiments, the solid support is semi-solid. In some embodiments,
the solid support comprises a polymer, a matrix, or a hydrogel. In
some embodiments, the solid support comprises a needle array
device. In some embodiments, the solid support comprises an
antibody. In some embodiments the solid support comprises
polystyrene.
In one aspect the disclosure provides for a method for determining
spatial locations of one or more targets in a sample by timing
comprising: contacting the spatial location in the sample with one
or more stochastic barcodes, at one or more time points, wherein
each stochastic barcode comprises a spatial label; and identifying
the spatial location of the one or more targets in the sample,
wherein the one or more time point correlates to the spatial
location. In some embodiments, stochastic barcodes at different
time points comprise different dimension labels. In some
embodiments, the dimension labels correlate to the one or more
times points. In some embodiments, the contacting is performed by a
device. In some embodiments, the device is a device selected from
the group consisting of: a needle, a needle array, a tube, a
suction device, an injection device, an electroporation device, a
fluorescent activated cell sorter device, and a microfluidic
device, or any combination thereof. In some embodiments, the device
contacts the sections at a specified rate. In some embodiments, the
specified rate is used to correlate the time point with the spatial
location. In some embodiments, the contacting comprises hybridizing
the one or more stochastic barcodes with the one or more targets.
In some embodiments, the hybridizing comprises hybridizing the one
or more targets such that each of the one or more targets is
hybridized to a unique stochastic barcode. In some embodiments, the
one or more stochastic barcodes comprises a molecular label. In
some embodiments, the molecular label is different for each of the
one or more stochastic barcodes. In some embodiments, the sample is
physically divided during the contacting. In some embodiments, the
sample is intact during the contacting. In some embodiments, the
contacting is performed on the surface of the sample. In some
embodiments, the contacting is performed inside the sample. In some
embodiments, the contacting is performed subcellularly in the
sample. In some embodiments, the spatial location is subcellular.
In some embodiments, the contacting is performed on a substrate. In
some embodiments, the substrate comprises the one or more
stochastic barcodes in a known order. In some embodiments, the
substrate comprises the one or more stochastic barcodes in an
unknown order. In some embodiments, the method further comprises
decoding the substrate. In some embodiments, the spatial label
comprises from 5-20 nucleotides. In some embodiments, the method
further comprises estimating the number of the one or more targets
using the stochastic barcode. In some embodiments, the estimating
comprises generating a target-barcode molecule. In some
embodiments, the target-barcode molecule comprises the sequence of
a stochastic barcode to which it is associated. In some
embodiments, the estimating further comprises determining the
sequence of the spatial label and a molecular label. In some
embodiments, the method further comprises counting occurrences of
distinct sequences of the molecular label. In some embodiments, the
counting is used to estimate the number of one or more targets. In
some embodiments, the determining comprises sequencing the
stochastic barcodes. In some embodiments, the sequencing comprises
sequencing with read lengths of at least 100 bases. In some
embodiments, the sequencing comprises sequencing with read lengths
of at least 500 bases. In some embodiments, the identifying
comprises correlating the spatial label with the spatial location
in the sample. In some embodiments, the method further comprises
visualizing the number of the one or more targets at the spatial
location. In some embodiments, the visualizing comprises mapping
the number of the one or more targets onto a map of the sample. In
some embodiments, the visualizing comprises imaging the sample at a
time point selected from the group consisting of: imaging the
sample prior to the contacting, imaging the sample after the
contacting, imaging the sample before lysing the sample, imaging
the sample after lysing the sample. In some embodiments, the
imaging produces an image that is used to construct a map of a
physical representation of the sample. In some embodiments, the map
is two dimensional. In some embodiments, the map is three
dimensional. In some embodiments, the sample comprises a single
cell. In some embodiments, the sample comprises a plurality of
cells. In some embodiments, the plurality of cells comprises a one
or more different cell types. In some embodiments, the one or more
cell types are selected from the group consisting of: brain cells,
heart cells, cancer cells, circulating tumor cells, organ cells,
epithelial cells, metastatic cells, benign cells, primary cells,
and circulatory cells, or any combination thereof. In some
embodiments, the sample comprises a solid tissue. In some
embodiments, the sample is obtained from a subject. In some
embodiments, the subject is a subject selected from the group
consisting of: a human, a mammal, a dog, a rat, a mouse, a fish, a
fly, a worm, a plant, a fungus, a bacterium, a virus, a vertebrate,
and an invertebrate. In some embodiments, the one or more targets
are ribonucleic acid molecules. In some embodiments, the
ribonucleic acid molecules are selected from the group consisting
of: mRNA, microRNA, mRNA degradation products, and ribonucleic
acids comprising a poly(A) tail, or any combination thereof. In
some embodiments, the targets are deoxyribonucleic acid molecules.
In some embodiments, the contacting is performed with a solid
support. In some embodiments, the solid support comprises a
plurality of stochastic barcodes. In some embodiments, each
stochastic barcode of the plurality of stochastic barcodes
comprises a spatial label. In some embodiments, spatial labels on
different solid supports differ by at least one nucleotide. In some
embodiments, the stochastic barcode further comprises a universal
label, a cellular label, and a molecular label. In some
embodiments, the universal label and the cellular label are the
same for all stochastic barcodes on a solid support. In some
embodiments, the solid supports comprise stochastic barcodes in two
dimensions. In some embodiments, the solid supports comprise
stochastic barcodes in three dimensions. In some embodiments, the
solid supports comprise a bead. In some embodiments, the bead is
selected from the group consisting of: silica gel bead, controlled
pore glass bead, magnetic bead, Dynabeads, Sephadex/Sepharose
beads, cellulose beads, and polystyrene beads, or any combination
thereof. In some embodiments, the bead comprises a magnetic bead.
In some embodiments, the solid support is semi-solid. In some
embodiments, the solid support comprises a polymer, a matrix, or a
hydrogel. In some embodiments, the solid support comprises a needle
array device. In some embodiments, the solid support comprises an
antibody.
In one aspect the disclosure provides for a method for determining
the spatial location of one or more targets on a sample comprising:
contacting one or more spatial locations of the sample with one or
more stochastic barcodes, wherein each stochastic barcode comprises
a pre-spatial label; concatenating one or more spatial label blocks
onto the pre-spatial label, thereby generating a spatial label; and
identifying the one or more spatial locations of the one or more
targets in the sample by correlating a length of the spatial label
with a spatial location in the sample. In some embodiments, spatial
labels at distinct spatial locations have different lengths. In
some embodiments, the contacting comprises hybridizing the
stochastic barcode with the one or more targets. In some
embodiments, the hybridizing comprises hybridizing the one or more
targets such that each of the one or more targets is hybridized to
a unique stochastic barcode. In some embodiments, the pre-spatial
label comprises a molecular label. In some embodiments, the
molecular label is different for each of the one or more stochastic
barcodes. In some embodiments, the sample is physically divided
during the contacting. In some embodiments, the sample is intact
during the contacting. In some embodiments, the contacting is
performed on the surface of the sample. In some embodiments, the
contacting is performed inside the sample. In some embodiments, the
contacting is performed subcellularly in the sample. In some
embodiments, the spatial location is subcellular. In some
embodiments, the contacting is performed on a substrate. In some
embodiments, the substrate comprises the one or more stochastic
barcodes in a known order. In some embodiments, the substrate
comprises the one or more stochastic barcodes in an unknown order.
In some embodiments, the method further comprises decoding the
substrate. In some embodiments, the spatial label comprises from
5-20 nucleotides. In some embodiments, the method further comprises
estimating the number of the distinct targets using the stochastic
barcodes. In some embodiments, the estimating comprises generating
a target-barcode molecule. In some embodiments, the target-barcode
molecule comprises the sequence of a stochastic barcode to which it
is associated. In some embodiments, the estimating further
comprises determining the sequence of the spatial label and a
molecular label. In some embodiments, the method further comprises
counting occurrences of distinct sequences of the molecular label.
In some embodiments, the counting is used to estimate the number of
one or more targets. In some embodiments, the determining comprises
sequencing the stochastic barcodes. In some embodiments, the
sequencing comprises sequencing with read lengths of at least 100
bases. In some embodiments, the sequencing comprises sequencing
with read lengths of at least 500 bases. In some embodiments, the
identifying comprises correlating the spatial label with the
spatial location in the sample. In some embodiments, the method
further comprises visualizing the number of the one or more targets
at the spatial location. In some embodiments, the visualizing
comprises mapping the number of the one or more targets onto a map
of the sample. In some embodiments, the visualizing comprises
imaging the sample at a time point selected from the group
consisting of: imaging the sample prior to the contacting, imaging
the sample after the contacting, imaging the sample before lysing
the sample, imaging the sample after lysing the sample. In some
embodiments, the imaging produces an image that is used to
construct a map of a physical representation of the sample. In some
embodiments, the map is two dimensional. In some embodiments, the
map is three dimensional. In some embodiments, the sample comprises
a single cell. In some embodiments, the sample comprises a
plurality of cells. In some embodiments, the plurality of cells
comprises a one or more different cell types. In some embodiments,
the one or more cell types are selected from the group consisting
of: brain cells, heart cells, cancer cells, circulating tumor
cells, organ cells, epithelial cells, metastatic cells, benign
cells, primary cells, and circulatory cells, or any combination
thereof. In some embodiments, the sample comprises a solid tissue.
In some embodiments, the sample is obtained from a subject. In some
embodiments, the subject is a subject selected from the group
consisting of: a human, a mammal, a dog, a rat, a mouse, a fish, a
fly, a worm, a plant, a fungus, a bacterium, a virus, a vertebrate,
and an invertebrate. In some embodiments, the one or more targets
are ribonucleic acid molecules. In some embodiments, the
ribonucleic acid molecules are selected from the group consisting
of: mRNA, microRNA, mRNA degradation products, and ribonucleic
acids comprising a poly(A) tail, or any combination thereof. In
some embodiments, the targets are deoxyribonucleic acid molecules.
In some embodiments, the contacting is performed with a solid
support. In some embodiments, the solid support can comprise a
plurality of stochastic barcodes. In some embodiments, each
stochastic barcode of the plurality of stochastic barcodes
comprises a spatial label. In some embodiments, spatial labels on
different solid supports differ by at least one nucleotide. In some
embodiments, the stochastic barcode further comprises a universal
label, and a cellular label. In some embodiments, the universal
label and the cellular label are the same for all stochastic
barcodes on the solid support. In some embodiments, the solid
support comprises stochastic barcodes in two dimensions. In some
embodiments, the solid support comprises stochastic barcodes in
three dimensions. In some embodiments, the solid support comprises
a bead. In some embodiments, the bead is selected from the group
consisting of: silica gel bead, controlled pore glass bead,
magnetic bead, Dynabeads, Sephadex/Sepharose beads, cellulose
beads, and polystyrene beads, or any combination thereof. In some
embodiments, the bead comprises a magnetic bead. In some
embodiments, the solid support is semi-solid. In some embodiments,
the solid support comprises a polymer, a matrix, or a hydrogel. In
some embodiments, the solid support comprises a needle array
device. In some embodiments, the solid support comprises an
antibody.
In one aspect the disclosure provides for a method for identifying
distinct cells in a population of cells comprising: contacting two
or more samples to a substrate, wherein the substrate comprises one
or more types of stochastic barcodes, wherein each type of the
types of stochastic barcodes comprises a different spatial label,
and wherein each stochastic barcode comprises a molecular label;
estimating the number of one or more targets in the plurality of
samples using the molecular label; and distinguishing a sample from
the two or more of samples by the spatial labels, wherein targets
associated with different spatial labels originate from different
samples. In some embodiments, the contacting comprises hybridizing
the stochastic barcode with the one or more targets. In some
embodiments, the hybridizing comprises hybridizing the one or more
targets such that each of the one or more targets is hybridized to
a unique stochastic barcode. In some embodiments, molecular labels
of the stochastic barcodes are different. In some embodiments, the
two or more samples are physically divided from each other during
the contacting. In some embodiments, the two or more samples can be
intact during the contacting. In some embodiments, the contacting
is performed on the surface of the two or more samples. In some
embodiments, the contacting is performed inside the two or more
samples. In some embodiments, the contacting is performed
subcellularly in the two or more samples. In some embodiments, the
spatial location is subcellular. In some embodiments, the substrate
comprises the one or more stochastic barcodes in a known order. In
some embodiments, the substrate comprises the one or more
stochastic barcodes in an unknown order. In some embodiments, the
method further comprises decoding the substrate. In some
embodiments, the spatial label comprises from 5-20 nucleotides. In
some embodiments, the estimating comprises generating a
target-barcode molecule. In some embodiments, the target-barcode
molecule comprises the sequence of a stochastic barcode to which it
is associated. In some embodiments, the estimating further
comprises determining the sequence of the spatial label and the
molecular label. In some embodiments, the method further comprises
counting occurrences of distinct sequences of the molecular label.
In some embodiments, the counting is used to estimate the number of
one or more targets. In some embodiments, the determining comprises
sequencing the stochastic barcodes. In some embodiments, the
sequencing comprises sequencing with read lengths of at least 100
bases. In some embodiments, the sequencing comprises sequencing
with read lengths of at least 500 bases. In some embodiments, the
method further comprises visualizing the number of the one or more
targets at the spatial location. In some embodiments, the
visualizing comprises mapping the number of the one or more targets
onto a map of the sample. In some embodiments, the visualizing
comprises imaging the sample at a time point selected from the
group consisting of: imaging the sample prior to the contacting,
imaging the sample after the contacting, imaging the sample before
lysing the sample, imaging the sample after lysing the sample. In
some embodiments, the imaging produces an image that is used to
construct a map of a physical representation of the sample. In some
embodiments, the map is two dimensional. In some embodiments, the
map is three dimensional. In some embodiments, the sample comprises
a single cell. In some embodiments, the sample comprises a
plurality of cells. In some embodiments, the plurality of cells
comprises a one or more different cell types. In some embodiments,
the one or more cell types are selected from the group consisting
of: brain cells, heart cells, cancer cells, circulating tumor
cells, organ cells, epithelial cells, metastatic cells, benign
cells, primary cells, and circulatory cells, or any combination
thereof. In some embodiments, the sample comprises a solid tissue.
In some embodiments, the sample is obtained from a subject. In some
embodiments, the subject is a subject selected from the group
consisting of: a human, a mammal, a dog, a rat, a mouse, a fish, a
fly, a worm, a plant, a fungus, a bacterium, a virus, a vertebrate,
and an invertebrate. In some embodiments, the one or more targets
are ribonucleic acid molecules. In some embodiments, the
ribonucleic acid molecules are selected from the group consisting
of: mRNA, microRNA, mRNA degradation products, and ribonucleic
acids comprising a poly(A) tail, or any combination thereof. In
some embodiments, the targets are deoxyribonucleic acid molecules.
In some embodiments, the contacting is performed with a solid
support. In some embodiments, the solid support comprises a
plurality of stochastic barcodes. In some embodiments, each
stochastic barcode of the plurality of stochastic barcodes
comprises a spatial label. In some embodiments, spatial labels on
different solid supports differ by at least one nucleotide. In some
embodiments, the stochastic barcode further comprises a universal
label, and a cellular label. In some embodiments, the universal
label and the cellular label are the same for all stochastic
barcodes on the solid support. In some embodiments, the solid
support comprises stochastic barcodes in two dimensions. In some
embodiments, the solid support comprises stochastic barcodes in
three dimensions. In some embodiments, the solid support comprises
a bead. In some embodiments, the bead is selected from the group
consisting of: silica gel bead, controlled pore glass bead,
magnetic bead, Dynabeads, Sephadex/Sepharose beads, cellulose
beads, and polystyrene beads, or any combination thereof. In some
embodiments, the bead comprises a magnetic bead. In some
embodiments, the solid support is semi-solid. In some embodiments,
the solid support comprises a polymer, a matrix, or a hydrogel. In
some embodiments, the solid support comprises a needle array
device. In some embodiments, the solid support comprises an
antibody.
In one aspect the disclosure provides for a kit comprising: one or
more types of stochastic barcodes, wherein each stochastic barcode
of the one or more types of stochastic barcodes comprises a spatial
label, wherein spatial labels of the one or more types of
stochastic barcodes differ by at least one nucleotide; and
instructions for use. In some embodiments, the one or more types of
stochastic barcodes are attached to a solid support. In some
embodiments, the one or more types of stochastic barcodes are
attached to a substrate. In some embodiments, the kit further
comprises a buffer. In some embodiments, the kit further comprises
a cartridge. In some embodiments, the one or more supports are
pre-loaded on a substrate. In some embodiments, the kit further
comprises reagents for a reverse transcription reaction. In some
embodiments, the kit further comprises reagents for an
amplification reaction.
In one aspect, the disclosure provides for a method comprising:
imaging a sample contacted to a substrate comprising a plurality of
probes, thereby producing an image; lysing the sample thereby
releasing nucleic acids from the sample; analyzing the nucleic
acids from the sample at locations on the substrate; correlating
locations on the image with data from the analyzing to identify a
spatial location of a nucleic acid in a sample. In some
embodiments, the imaging comprises staining the sample. In some
embodiments, the staining comprises staining with a stain selected
from the group consisting of: a fluorescent stain, a negative
stain, and an antibody stain, or any combination thereof. In some
embodiments, the imaging use a technique selected from the group
consisting of: optical microscopy, electron microscopy, confocal
microscopy, and fluorescence microscopy. In some embodiments, the
performing immunohistological analysis produces an image. In some
embodiments, the sample comprises a cell monolayer. In some
embodiments, the sample comprises fixed cells. In some embodiments,
the sample comprises a tissue section. In some embodiments, the
lysing is performed by heating the sample, contacting the sample
with a detergent, or changing the pH of the sample, or any
combination thereof. In some embodiments, the analyzing comprises
hybridizing the nucleic acids to the oligo(dT)s. In some
embodiments, the nucleic acids comprise polyadenylated nucleic
acids. In some embodiments, the method further comprises
homopolymer tailing the nucleic acids. In some embodiments, the
method further comprises amplifying the nucleic acids. In some
embodiments, the amplifying comprises bridge amplification. In some
embodiments, the amplifying comprises amplifying with a
gene-specific primer. In some embodiments, the amplifying comprises
amplifying with a universal primer. In some embodiments, the
amplifying comprises amplifying with an oligo(dT) primer. In some
embodiments, the method further comprises detecting the nucleic
acids. In some embodiments, the detecting comprises hybridizing one
or more probes to the nucleic acids. In some embodiments, the one
or more probes comprise a fluorescent label. In some embodiments,
the one or more probes can be 4 probes. In some embodiments, the
analyzing comprises hybridizing the nucleic acids to a microarray.
In some embodiments, the correlating comprises overlaying the image
with the data. In some embodiments, the correlating comprises
mapping the x-y location of a feature on the substrate onto the
image. In some embodiments, the probes comprise oligo(dT). In some
embodiments, the probes comprise gene-specific probes. In some
embodiments, the probes comprise a combination of oligo(dT) probes
and gene-specific probes. In some embodiments, the gene-specific
probes are gene-specific for at least 2 genes.
In one aspect the disclosure provides for a method for diagnosing a
subject comprising: imaging a sample from the subject contacted to
a substrate comprising a plurality of probes, thereby producing an
image; lysing the sample thereby releasing nucleic acids from the
sample; analyzing the nucleic acids from the sample at locations on
the substrate; diagnosing the subject based on the image and data
from the analyzing. In some embodiments, the subject is a human. In
some embodiments, the subject is a mouse, a dog, a rat, or a
vertebrate. In some embodiments, the diagnosing comprises
identifying different cell types of the sample. In some
embodiments, the diagnosing comprises determining if different cell
types respond to a therapy. In some embodiments, the diagnosing
comprises determining a genotype of one or more cells in the
sample. In some embodiments, the method further comprises treating
the subject. In some embodiments, the treating comprises
administering a drug to the subject. In some embodiments, the drug
is chosen based on predicted responsiveness to the identified cell
types of the sample. In some embodiments, the imaging comprises
staining the sample. In some embodiments, the staining comprises
staining with a stain selected from the group consisting of: a
fluorescent stain, a negative stain, and an antibody stain, or any
combination thereof. In some embodiments, the imaging use a
technique selected from the group consisting of: optical
microscopy, electron microscopy, confocal microscopy, and
fluorescence microscopy. In some embodiments, the performing
immunohistological analysis produces an image. In some embodiments,
the sample comprises a cell monolayer. In some embodiments, the
sample comprises fixed cells. In some embodiments, the sample
comprises a tissue section. In some embodiments, the lysing is
performed by heating the sample, contacting the sample with a
detergent, or changing the pH of the sample, or any combination
thereof. In some embodiments, the analyzing comprises hybridizing
the nucleic acids to the oligo(dT)s. In some embodiments, the
nucleic acids comprise polyadenylated nucleic acids. In some
embodiments, the method further comprises homopolymer tailing the
nucleic acids. In some embodiments, the method further comprises
amplifying the nucleic acids. In some embodiments, the amplifying
comprises bridge amplification. In some embodiments, the amplifying
comprises amplifying with a gene-specific primer. In some
embodiments, the amplifying comprises amplifying with a universal
primer. In some embodiments, the amplifying comprises amplifying
with an oligo(dT) primer. In some embodiments, the method further
comprises detecting the nucleic acids. In some embodiments, the
detecting comprises hybridizing one or more probes to the nucleic
acids. In some embodiments, the one or more probes comprise a
fluorescent label. In some embodiments, the one or more probes can
be 4 probes. In some embodiments, the analyzing comprises
hybridizing the nucleic acids to a microarray. In some embodiments,
the probes comprise oligo(dT). In some embodiments, the probes
comprise gene-specific probes. In some embodiments, the probes
comprise a combination of oligo(dT) probes and gene-specific
probes. In some embodiments, the gene-specific probes are
gene-specific for at least 2 genes.
In one aspect, the disclosure provides for a method comprising:
imaging a sample contacted to a first substrate comprising a
plurality of probes, thereby producing an image; lysing the sample
thereby releasing nucleic acids from the sample to hybridize to the
plurality of probes; analyzing the nucleic acids from the sample at
locations on the substrate; and replicating the first substrate
thereby making a replicate substrate. In some embodiments, the
probes of the first substrate comprise oligo(dT). In some
embodiments, the probes of the first substrate comprise
gene-specific primers. In some embodiments, probes of the replicate
substrate comprise gene-specific primers for another location on
the same gene as the gene-specific primers on the first substrate.
In some embodiments, the replicating comprises contacting the first
substrate with a replicate substrate. In some embodiments, the
replicating comprises hybridizing nucleic acids from the first
substrate to the replicate substrate. In some embodiments, the
imaging comprises staining the sample. In some embodiments, the
staining comprises staining with a stain selected from the group
consisting of: a fluorescent stain, a negative stain, and an
antibody stain, or any combination thereof. In some embodiments,
the imaging use a technique selected from the group consisting of:
optical microscopy, electron microscopy, confocal microscopy, and
fluorescence microscopy. In some embodiments, the performing
immunohistological analysis produces an image. In some embodiments,
the sample comprises a cell monolayer. In some embodiments, the
sample comprises fixed cells. In some embodiments, the sample
comprises a tissue section. In some embodiments, the lysing is
performed by heating the sample, contacting the sample with a
detergent, or changing the pH of the sample, or any combination
thereof. In some embodiments, the analyzing comprises hybridizing
the nucleic acids to the oligo(dT)s. In some embodiments, the
method further comprises homopolymer tailing the nucleic acids. In
some embodiments, the method further comprises amplifying the
nucleic acids to generate amplicons. In some embodiments, the
amplifying comprises bridge amplification. In some embodiments, the
amplifying comprises amplifying with a gene-specific primer. In
some embodiments, the amplifying comprises amplifying with a
universal primer. In some embodiments, the amplifying comprises
amplifying with an oligo(dT) primer. In some embodiments, the
replicating comprises hybridizing the amplicons onto the replicate
substrate.
Definitions
Unless otherwise defined, all technical terms used herein have the
same meaning as commonly understood by one of ordinary skill in the
art in the field to which this disclosure belongs. As used in this
specification and the appended claims, the singular forms "a,"
"an," and "the" include plural references unless the context
clearly dictates otherwise. Any reference to "or" herein is
intended to encompass "and/or" unless otherwise stated.
As used herein, the term "adaptor" can mean a sequence to
facilitate amplification or sequencing of associated nucleic acids.
The associated nucleic acids can comprise target nucleic acids. The
associated nucleic acids can comprise one or more of spatial
labels, target labels, sample labels, indexing label, barcodes,
stochastic barcodes, or molecular labels. The adapters can be
linear. The adaptors can be pre-adenylated adapters. The adaptors
can be double- or single-stranded. One or more adaptor can be
located on the 5' or 3' end of a nucleic acid. When the adaptors
comprise known sequences on the 5' and 3' ends, the known sequences
can be the same or different sequences. An adaptor located on the
5' and/or 3' ends of a polynucleotide can be capable of hybridizing
to one or more oligonucleotides immobilized on a surface. An
adapter can, in some embodiments, comprise a universal sequence. A
universal sequence can be a region of nucleotide sequence that is
common to two or more nucleic acid molecules. The two or more
nucleic acid molecules can also have regions of different sequence.
Thus, for example, the 5' adapters can comprise identical and/or
universal nucleic acid sequences and the 3' adapters can comprise
identical and/or universal sequences. A universal sequence that may
be present in different members of a plurality of nucleic acid
molecules can allow the replication or amplification of multiple
different sequences using a single universal primer that is
complementary to the universal sequence. Similarly, at least one,
two (e.g., a pair) or more universal sequences that may be present
in different members of a collection of nucleic acid molecules can
allow the replication or amplification of multiple different
sequences using at least one, two (e.g., a pair) or more single
universal primers that are complementary to the universal
sequences. Thus, a universal primer includes a sequence that can
hybridize to such a universal sequence. The target nucleic acid
sequence-bearing molecules may be modified to attach universal
adapters (e.g., non-target nucleic acid sequences) to one or both
ends of the different target nucleic acid sequences. The one or
more universal primers attached to the target nucleic acid can
provide sites for hybridization of universal primers. The one or
more universal primers attached to the target nucleic acid can be
the same or different from each other.
As used herein, the term "associated" or "associated with" can mean
that two or more species are identifiable as being co-located at a
point in time. An association can mean that two or more species are
or were within a similar container. An association can be an
informatics association, where for example digital information
regarding two or more species is stored and can be used to
determine that one or more of the species were co-located at a
point in time. An association can also be a physical association.
In some embodiments two or more associated species are "tethered",
"attached", or "immobilized" to one another or to a common solid or
semisolid surface. An association may refer to covalent or
non-covalent means for attaching labels to solid or semi-solid
supports such as beads. An association may be a covalent bond
between a target and a label.
As used herein, the term "complementary" can refer to the capacity
for precise pairing between two nucleotides. For example, if a
nucleotide at a given position of a nucleic acid is capable of
hydrogen bonding with a nucleotide of another nucleic acid, then
the two nucleic acids are considered to be complementary to one
another at that position. Complementarity between two
single-stranded nucleic acid molecules may be "partial," in which
only some of the nucleotides bind, or it may be complete when total
complementarity exists between the single-stranded molecules. A
first nucleotide sequence can be said to be the "complement" of a
second sequence if the first nucleotide sequence is complementary
to the second nucleotide sequence. A first nucleotide sequence can
be said to be the "reverse complement" of a second sequence, if the
first nucleotide sequence is complementary to a sequence that is
the reverse (i.e., the order of the nucleotides is reversed) of the
second sequence. As used herein, the terms "complement",
"complementary", and "reverse complement" can be used
interchangeably. It is understood from the disclosure that if a
molecule can hybridize to another molecule it may be the complement
of the molecule that is hybridizing.
As used herein, the term "digital counting" can refer to a method
for estimating a number of target molecules in a sample. Digital
counting can include the step of determining a number of unique
labels that have been associated with targets in a sample. This
stochastic methodology transforms the problem of counting molecules
from one of locating and identifying identical molecules to a
series of yes/no digital questions regarding detection of a set of
predefined labels.
As used herein, the term "label" or "labels" can refer to nucleic
acid codes associated with a target within a sample. A label can
be, for example, a nucleic acid label. A label can be an entirely
or partially amplifiable label. A label can be entirely or
partially sequencable label. A label can be a portion of a native
nucleic acid that is identifiable as distinct. A label can be a
known sequence. A label can comprise a junction of nucleic acid
sequences, for example a junction of a native and non-native
sequence. As used herein, the term "label" can be used
interchangeably with the terms, "index", "tag," or "label-tag."
Labels can convey information. For example, in various embodiments,
labels can be used to determine an identity of a sample, a source
of a sample, an identity of a cell, and/or a target.
As used herein, the term "non-depleting reservoirs" can refer to a
pool of stochastic barcodes made up of many different labels. A
non-depleting reservoir can comprise large numbers of different
stochastic barcodes such that when the non-depleting reservoir is
associated with a pool of targets each target is likely to be
associated with a unique stochastic barcode. The uniqueness of each
labeled target molecule can be determined by the statistics of
random choice, and depends on the number of copies of identical
target molecules in the collection compared to the diversity of
labels. The size of the resulting set of labeled target molecules
can be determined by the stochastic nature of the barcoding
process, and analysis of the number of stochastic barcodes detected
then allows calculation of the number of target molecules present
in the original collection or sample. When the ratio of the number
of copies of a target molecule present to the number of unique
stochastic barcodes is low, the labeled target molecules are highly
unique (i.e. there is a very low probability that more than one
target molecule will have been labeled with a given label).
As used herein, a "nucleic acid" can generally refer to a
polynucleotide sequence, or fragment thereof. A nucleic acid can
comprise nucleotides. A nucleic acid can be exogenous or endogenous
to a cell. A nucleic acid can exist in a cell-free environment. A
nucleic acid can be a gene or fragment thereof. A nucleic acid can
be DNA. A nucleic acid can be RNA. A nucleic acid can comprise one
or more analogs (e.g. altered backbone, sugar, or nucleobase). Some
non-limiting examples of analogs include: 5-bromouracil, peptide
nucleic acid, xeno nucleic acid, morpholinos, locked nucleic acids,
glycol nucleic acids, threose nucleic acids, dideoxynucleotides,
cordycepin, 7-deaza-GTP, fluorophores (e.g. rhodamine or
fluorescein linked to the sugar), thiol containing nucleotides,
biotin linked nucleotides, fluorescent base analogs, CpG islands,
methyl-7-guanosine, methylated nucleotides, inosine, thiouridine,
pseudouridine, dihydrouridine, queuosine, and wyosine. "Nucleic
acid", "polynucleotide, "target polynucleotide", and "target
nucleic acid" can be used interchangeably.
A nucleic acid can comprise one or more modifications (e.g., a base
modification, a backbone modification), to provide the nucleic acid
with a new or enhanced feature (e.g., improved stability). A
nucleic acid can comprise a nucleic acid affinity tag. A nucleoside
can be a base-sugar combination. The base portion of the nucleoside
can be a heterocyclic base. The two most common classes of such
heterocyclic bases are the purines and the pyrimidines. Nucleotides
can be nucleosides that further include a phosphate group
covalently linked to the sugar portion of the nucleoside. For those
nucleosides that include a pentofuranosyl sugar, the phosphate
group can be linked to the 2', the 3', or the 5' hydroxyl moiety of
the sugar. In forming nucleic acids, the phosphate groups can
covalently link adjacent nucleosides to one another to form a
linear polymeric compound. In turn, the respective ends of this
linear polymeric compound can be further joined to form a circular
compound; however, linear compounds are generally suitable. In
addition, linear compounds may have internal nucleotide base
complementarity and may therefore fold in a manner as to produce a
fully or partially double-stranded compound. Within nucleic acids,
the phosphate groups can commonly be referred to as forming the
internucleoside backbone of the nucleic acid. The linkage or
backbone can be a 3' to 5' phosphodiester linkage.
A nucleic acid can comprise a modified backbone and/or modified
internucleoside linkages. Modified backbones can include those that
retain a phosphorus atom in the backbone and those that do not have
a phosphorus atom in the backbone. Suitable modified nucleic acid
backbones containing a phosphorus atom therein can include, for
example, phosphorothioates, chiral phosphorothioates,
phosphorodithioates, phosphotriesters, aminoalkyl phosphotriesters,
methyl and other alkyl phosphonate such as 3'-alkylene
phosphonates, 5'-alkylene phosphonates, chiral phosphonates,
phosphinates, phosphoramidates including 3'-amino phosphoramidate
and aminoalkyl phosphoramidates, phosphorodiamidates,
thionophosphoramidates, thionoalkylphosphonates,
thionoalkylphosphotriesters, selenophosphates, and boranophosphates
having normal 3'-5' linkages, 2'-5' linked analogs, and those
having inverted polarity wherein one or more internucleotide
linkages is a 3' to 3', a 5' to 5' or a 2' to 2' linkage.
A nucleic acid can comprise polynucleotide backbones that are
formed by short chain alkyl or cycloalkyl internucleoside linkages,
mixed heteroatom and alkyl or cycloalkyl internucleoside linkages,
or one or more short chain heteroatomic or heterocyclic
internucleoside linkages. These can include those having morpholino
linkages (formed in part from the sugar portion of a nucleoside);
siloxane backbones; sulfide, sulfoxide and sulfone backbones;
formacetyl and thioformacetyl backbones; methylene formacetyl and
thioformacetyl backbones; riboacetyl backbones; alkene containing
backbones; sulfamate backbones; methyleneimino and
methylenehydrazino backbones; sulfonate and sulfonamide backbones;
amide backbones; and others having mixed N, O, S and CH2 component
parts.
A nucleic acid can comprise a nucleic acid mimetic. The term
"mimetic" can be intended to include polynucleotides wherein only
the furanose ring or both the furanose ring and the internucleotide
linkage are replaced with non-furanose groups, replacement of only
the furanose ring can also be referred as being a sugar surrogate.
The heterocyclic base moiety or a modified heterocyclic base moiety
can be maintained for hybridization with an appropriate target
nucleic acid. One such nucleic acid can be a peptide nucleic acid
(PNA). In a PNA, the sugar-backbone of a polynucleotide can be
replaced with an amide containing backbone, in particular an
aminoethylglycine backbone. The nucleotides can be retained and are
bound directly or indirectly to aza nitrogen atoms of the amide
portion of the backbone. The backbone in PNA compounds can comprise
two or more linked aminoethylglycine units which gives PNA an amide
containing backbone. The heterocyclic base moieties can be bound
directly or indirectly to aza nitrogen atoms of the amide portion
of the backbone.
A nucleic acid can comprise a morpholino backbone structure. For
example, a nucleic acid can comprise a 6-membered morpholino ring
in place of a ribose ring. In some of these embodiments, a
phosphorodiamidate or other non-phosphodiester internucleoside
linkage can replace a phosphodiester linkage.
A nucleic acid can comprise linked morpholino units (i.e.
morpholino nucleic acid) having heterocyclic bases attached to the
morpholino ring. Linking groups can link the morpholino monomeric
units in a morpholino nucleic acid. Non-ionic morpholino-based
oligomeric compounds can have less undesired interactions with
cellular proteins. Morpholino-based polynucleotides can be nonionic
mimics of nucleic acids. A variety of compounds within the
morpholino class can be joined using different linking groups. A
further class of polynucleotide mimetic can be referred to as
cyclohexenyl nucleic acids (CeNA). The furanose ring normally
present in a nucleic acid molecule can be replaced with a
cyclohexenyl ring. CeNA DMT protected phosphoramidite monomers can
be prepared and used for oligomeric compound synthesis using
phosphoramidite chemistry. The incorporation of CeNA monomers into
a nucleic acid chain can increase the stability of a DNA/RNA
hybrid. CeNA oligoadenylates can form complexes with nucleic acid
complements with similar stability to the native complexes. A
further modification can include Locked Nucleic Acids (LNAs) in
which the 2'-hydroxyl group is linked to the 4' carbon atom of the
sugar ring thereby forming a 2'-C, 4'-C-oxymethylene linkage
thereby forming a bicyclic sugar moiety. The linkage can be a
methylene (--CH2-), group bridging the 2' oxygen atom and the 4'
carbon atom wherein n is 1 or 2. LNA and LNA analogs can display
very high duplex thermal stabilities with complementary nucleic
acid (Tm=+3 to +10.degree. C.), stability towards 3'-exonucleolytic
degradation and good solubility properties.
A nucleic acid may also include nucleobase (often referred to
simply as "base") modifications or substitutions. As used herein,
"unmodified" or "natural" nucleobases can include the purine bases,
(e.g. adenine (A) and guanine (G)), and the pyrimidine bases, (e.g.
thymine (T), cytosine (C) and uracil (U)). Modified nucleobases can
include other synthetic and natural nucleobases such as
5-methylcytosine (5-me-C), 5-hydroxymethyl cytosine, xanthine,
hypoxanthine, 2-aminoadenine, 6-methyl and other alkyl derivatives
of adenine and guanine, 2-propyl and other alkyl derivatives of
adenine and guanine, 2-thiouracil, 2-thiothymine and
2-thiocytosine, 5-halouracil and cytosine, 5-propynyl
(--C.dbd.C--CH3) uracil and cytosine and other alkynyl derivatives
of pyrimidine bases, 6-azo uracil, cytosine and thymine, 5-uracil
(pseudouracil), 4-thiouracil, 8-halo, 8-amino, 8-thiol,
8-thioalkyl, 8-hydroxyl and other 8-substituted adenines and
guanines, 5-halo particularly 5-bromo, 5-trifluoromethyl and other
5-substituted uracils and cytosines, 7-methylguanine and
7-methyladenine, 2-F-adenine, 2-aminoadenine, 8-azaguanine and
8-azaadenine, 7-deazaguanine and 7-deazaadenine and 3-deazaguanine
and 3-deazaadenine. Modified nucleobases can include tricyclic
pyrimidines such as phenoxazine cytidine
(1H-pyrimido(5,4-b)(1,4)benzoxazin-2(3H)-one), phenothiazine
cytidine (1H-pyrimido(5,4-b)(1,4)benzothiazin-2(3H)-one), G-clamps
such as a substituted phenoxazine cytidine (e.g.
9-(2-aminoethoxy)-H-pyrimido(5,4-(b) (1,4)benzoxazin-2(3H)-one),
phenothiazine cytidine (1H-pyrimido(5,4-b)(1,4)
benzothiazin-2(3H)-one), G-clamps such as a substituted phenoxazine
cytidine (e.g. 9-(2-aminoethoxy)-H-pyrimido (5,4-(b)
(1,4)benzoxazin-2(3H)-one), carbazole cytidine
(2H-pyrimido(4,5-b)indol-2-one), pyridoindole cytidine
(H-pyrido(3',':4,5)pyrrolo[2,3-d]pyrimidin-2-one).
As used herein, the term "sample" can refer to a composition
comprising targets. Suitable samples for analysis by the disclosed
methods, devices, and systems include cells, tissues, organs, or
organisms.
As used herein, the term "sampling device" or "device" can refer to
a device which may take a section of a sample and/or place the
section on a substrate. A sample device can refer to, for example,
fluorescence activated cell sorting (FACS) machine, a cell sorter
machine, a biopsy needle, a biopsy device, a tissue sectioning
device, a microfluidic device, a blade grid, and/or a
microtome.
As used herein, the term "solid support" can refer to discrete
solid or semi-solid surfaces to which a plurality of stochastic
barcodes may be attached. A solid support may encompass any type of
solid, porous, or hollow sphere, ball, bearing, cylinder, or other
similar configuration composed of plastic, ceramic, metal, or
polymeric material (e.g., hydrogel) onto which a nucleic acid may
be immobilized (e.g., covalently or non-covalently). A solid
support may comprise a discrete particle that may be spherical
(e.g., microspheres) or have a non-spherical or irregular shape,
such as cubic, cuboid, pyramidal, cylindrical, conical, oblong, or
disc-shaped, and the like. A solid support may be used
interchangeably with the term "bead." A solid support can refer to
a "substrate." A substrate can be a type of solid support. A
substrate can refer to a continuous solid or semi-solid surface on
which the methods of the disclosure may be performed. A substrate
can refer to an array, a cartridge, a chip, a device, and a slide,
for example. As used herein, "solid support" and "substrate" are
sometimes used interchangeably.
As used here, the term, "spatial label" can refer to a label which
can be associated with a position in space.
As used herein, the term "stochastic barcode" can refer to a
polynucleotide sequence comprising labels. A stochastic barcode can
be a polynucleotide sequence that can be used for stochastic
labeling. Stochastic barcodes can be used to quantify targets
within a sample. Stochastic barcodes can be used to control for
errors which may occur after a label is associated with a target.
For example, a stochastic barcode can be used to assess
amplification or sequencing errors. A stochastic barcode associated
with a target can be called a stochastic barcode-target or
stochastic barcode-tag-target.
As used herein, the term "stochastic barcoding" can refer to the
random labeling (e.g., barcoding) of nucleic acids. Stochastic
barcoding can utilize a recursive Poisson strategy to associate and
quantify labels associated with targets.
As used herein, the term "target" can refer to a composition which
can be associated with a stochastic barcode. Exemplary suitable
targets for analysis by the disclosed methods, devices, and systems
include oligonucleotides, DNA, RNA, mRNA, microRNA, tRNA, and the
like. Targets can be single or double stranded. In some embodiments
targets can be proteins. In some embodiments targets are
lipids.
As used herein, the term "reverse transcriptases" can refer to a
group of enzymes having reverse transcriptase activity (i.e., that
catalyze synthesis of DNA from an RNA template). In general, such
enzymes include, but are not limited to, retroviral reverse
transcriptase, retrotransposon reverse transcriptase, retroplasmid
reverse transcriptases, retron reverse transcriptases, bacterial
reverse transcriptases, group II intron-derived reverse
transcriptase, and mutants, variants or derivatives thereof.
Non-retroviral reverse transcriptases include non-LTR
retrotransposon reverse transcriptases, retroplasmid reverse
transcriptases, retron reverse transciptases, and group II intron
reverse transcriptases. Examples of group II intron reverse
transcriptases include the Lactococcus lactis LI.LtrB intron
reverse transcriptase, the Thermosynechococcus elongates TeI4c
intron reverse transcriptase, or the Geobacillus stearothermophilus
GsI-IIC intron reverse transcriptase. Other classes of reverse
transcriptases can include many classes of non-retroviral reverse
transcriptases (i.e., retrons, group II introns, and
diversity-generating retroelements among others).
As used herein, the term "template switching" can refer to the
ability of a reverse transcriptase to switch from an initial
nucleic acid sequence template to the 3' end of a new nucleic acid
sequence template having little or no complementarity to the 3' end
of the nucleic acid synthesized from the initial template. Nucleic
acid copies of a target polynucleotide can be made using template
switching. Template switching allows, e.g., a DNA copy to be
prepared using a reverse transcriptase that switches from an
initial nucleic acid sequence template to the 3' end of a new
nucleic acid sequence template having little or no complementarity
to the 3' end of the DNA synthesized from the initial template,
thereby allowing the synthesis of a continuous product DNA that
directly links an adaptor sequence to a target oligonucleotide
sequence without ligation. Template switching can comprise ligation
of adaptor, homopolymer tailing (e.g., polyadenylation), random
primer, or an oligonucleotide that the polymerase can associate
with.
Stochastic Barcodes with Spatial Labels and Dimension Labels
Disclosed herein are methods, compositions, devices, systems, and
kits for spatial stochastic barcoding. Some embodiments disclosed
herein provide methods determining the number and spatial locations
of a plurality of targets in a sample. The methods include, in some
embodiments, stochastically barcoding the plurality of targets in
the sample using a plurality of stochastic barcodes, wherein each
of the plurality of stochastic barcodes include a spatial label and
a molecular label; estimating the number of each of the plurality
of targets using the molecular label; and identifying the spatial
location of each of the plurality of targets using the spatial
label. In some embodiments, the method can be multiplexed. The
sample can comprise a plurality of cells and the plurality of
targets can be associated with the plurality of cells.
Disclosed here are methods for determining spatial locations of a
plurality of targets in a sample. In some embodiments, the methods
include: stochastically barcoding the plurality of targets in the
sample at one or more time points using a plurality of stochastic
barcodes, wherein each of the plurality of stochastic barcodes
comprises a spatial label; and identifying the spatial location of
each of the plurality of targets using the spatial label.
Stochastically barcoding the plurality of targets in the sample
using the plurality of stochastic barcodes can include
stochastically barcoding the plurality of targets in the sample at
different time points using the plurality of stochastic barcodes.
Each of the plurality of stochastic barcodes can include a
dimension label, and the dimension labels of the plurality of
stochastic barcodes used for stochastic barcoding the plurality of
targets at the different time points can be different. The
dimension labels can correlate with the different time points.
Spatial stochastic barcoding can refer to the stochastic barcoding
of a plurality of target molecules in single cells to determine
spatial orientation of the target molecules. As shown in FIG. 1,
the disclosure provides for a method for correlating information in
real physical space with information in chemical space. A sample
comprising a two dimensional or three-dimensional sample (e.g., a
cell) 105 can be divided into multiple sections, for example
110/111/112/113. In some embodiments, sections 110/111/112/113 can
be physically divided, then chemically divided based on the
physical division. In some embodiments, sections 110/111/112/113
can be chemically divided without physical division. In some
embodiments, the sections 110/111/112/113 can be physically
separated 115 from the sample 105. Each section 110/111/112/113 can
be placed in a separate .Iadd.container 120 .Iaddend.on a substrate
125. The sections 110/111/112/113 in the substrate 125 can be
subjected to stochastic barcoding. Stochastic barcoding can
comprise labeling distinct targets in each section 110/111/112/113
with a different barcode. In some embodiments, the different
barcode comprises a spatial label. The sections can be
stochastically labeled, amplified, and/or digitally counted,
wherein the number of distinct targets can be estimated from the
digital counting of different barcodes. The information in the
spatial label of the different barcode can correspond to a location
on the sample 105. In this way, the method can be used to determine
the number of distinct targets in a sample 105 at distinct physical
locations.
The methods, devices and systems disclosed herein may be used for a
variety of applications in basic research, biomedical research,
environmental testing, and clinical diagnostics. Examples of
applications for the disclosed methods devices and systems include,
but are not limited to, genotyping, gene expression profiling,
detection and identification of rare cells, diagnosis of a disease
or condition, determining prognosis for a disease or condition,
determining a course of treatment for a disease or condition, and
monitoring the response to treatment for a disease or condition,
and understanding biological development processes. For example,
the methods of the disclosure can be used for whole transcriptome
analysis, rare cell (e.g., circulating tumor cell) analysis,
chimeric antigen receptor T-cell (CAR-T) therapy analysis (e.g.,
determining specific cells that respond to CAR-T therapy versus
non-responders), and neuroscience (e.g., therapies and diagnostics
for, e.g., Autism, Schizophrenia, Bipolar disorder, Parkinson's
disease, and Alzheimer's disease). In some embodiments, the methods
can include treating the subject. Treating the subject can include
administering a drug to the subject.
A stochastic barcode can refer to a polynucleotide sequence that
may be used to stochastically label (e.g., barcode, tag) a target.
A stochastic barcode can comprise one or more labels. Exemplary
labels can include a universal label, a cellular label, a molecular
label, a sample label, a plate label, a spatial label, and/or a
pre-spatial label. FIG. 2 illustrates an exemplary stochastic
barcode with a spatial label of the disclosure. A stochastic
barcode 204 can comprise a 5'amine that may link the stochastic
barcode to a solid support 205. The stochastic barcode can comprise
a universal label, a dimension label, a spatial label, a cellular
label, and/or a molecular label. The universal label may be 5'-most
label. The molecular label may be the 3'-most label. The spatial
label, dimension label, and the cellular label may be in any order.
In some embodiments, the universal label, the spatial label, the
dimension label, the cellular label, and the molecular label are in
any order. The stochastic barcode can comprise a target-binding
region. The target-binding region can interact with a target in a
sample. The target can be, or comprise, ribonucleic acids (RNAs),
messenger RNAs (mRNAs), microRNAs, small interfering RNAs (siRNAs),
RNA degradation products, RNAs each comprising a poly(A) tail, and
any combination thereof. In some embodiments, the plurality of
targets can include deoxyribonucleic acids (DNAs).
For example, a target-binding region can comprise an oligo(dT)
sequence which can interact with poly(A) tails of mRNAs. In some
embodiments, the labels of the stochastic barcode (e.g., universal
label, dimension label, spatial label, cellular label, and
molecular label) may be separated by 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 or more nucleotides.
In some embodiments, stochastically barcoding the plurality of
targets in the sample includes hybridizing the plurality of
stochastic barcodes with the plurality of targets to generate
stochastically barcoded targets, and at least one of the plurality
of targets is hybridized to one of the plurality of stochastic
barcodes. A portion or all of the plurality of targets can be
hybridized to the plurality of stochastic barcodes. For example, in
some embodiments, each of the plurality of targets is hybridized to
one of the plurality of stochastic barcodes. In some embodiments,
each of at least two, three, four, five, ten, twenty, fifty, one
hundred, or one thousand of the plurality of targets is hybridized
to one of the plurality of stochastic barcodes. A stochastic
barcode can comprise one or more universal labels. The one or more
universal labels can be the same for all stochastic barcodes in the
set of stochastic barcodes attached to a given solid support. In
some embodiments, the one or more universal labels can be the same
for all stochastic barcodes attached to a plurality of beads. In
some embodiments, a universal label can comprise a nucleic acid
sequence that is capable of hybridizing to a sequencing primer.
Sequencing primers can be used for sequencing stochastic barcodes
comprising a universal label. Sequencing primers (e.g., universal
sequencing primers) can comprise sequencing primers associated with
high-throughput sequencing platforms. In some embodiments, a
universal label can comprise a nucleic acid sequence that is
capable of hybridizing to a PCR primer. In some embodiments, the
universal label can comprise a nucleic acid sequence that is
capable of hybridizing to a sequencing primer and a PCR primer. The
nucleic acid sequence of the universal label that is capable of
hybridizing to a sequencing or PCR primer can be referred to as a
primer binding site. A universal label can comprise a sequence that
can be used to initiate transcription of the stochastic barcode. A
universal label can comprise a sequence that can be used for
extension of the stochastic barcode or a region within the
stochastic barcode. A universal label can be at least about 1, 2,
3, 4, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50 or more nucleotides in
length. A universal label can comprise at least about 10
nucleotides. A universal label can be at most about 1, 2, 3, 4, 5,
10, 15, 20, 25, 30, 35, 40, 45, 50 or more nucleotides in length.
In some embodiments, a cleavable linker or modified nucleotide can
be part of the universal label sequence to enable the stochastic
barcode to be cleaved off from the support.
A stochastic barcode can comprise a dimension label. A dimension
label can comprise a nucleic acid sequence that provides
information about a dimension in which the stochastic labeling
occurred. For example, a dimension label can provide information
about the time at which a target was stochastically barcoded. A
dimension label can be associated with a time of stochastic
barcoding in a sample. A dimension label can be activated at the
time of stochastic labeling. Different dimension labels can be
activated at different times. The dimension label provides
information about the order in which targets, groups of targets,
and/or samples were stochastically barcoded. For example, a
population of cells can be stochastically barcoded at the G0 phase
of the cell cycle. The cells can be pulsed again with stochastic
barcodes at the G1 phase of the cell cycle. The cells can be pulsed
again with stochastic barcodes at the S phase of the cell cycle,
and so on. Stochastic barcodes at each pulse (e.g., each phase of
the cell cycle), can comprise different dimension labels. In this
way, the dimension label provides information about which targets
were labelled at which phase of the cell cycle. Dimension labels
can interrogate many different biological times. Exemplary
biological times can include, but are not limited to, the cell
cycle, transcription (e.g., transcription initiation), and
transcript degradation. In another example, a sample (e.g., a cell,
a population of cells) can be stochastically labeled before and/or
after treatment with a drug and/or therapy. The changes in the
number of copies of distinct targets can be indicative of the
sample's response to the drug and/or therapy.
A dimension label can be activatable. An activatable dimension
label can be activated at a specific time point. The activatable
label can be, for example, constitutively activated (e.g., not
turned off). The activatable dimension label can be, for example,
reversibly activated (e.g., the activatable dimension label can be
turned on and turned off). The dimension label can be, for example,
reversibly activatable at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or
more times. The dimension label can be reversibly activatable, for
example, at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more times.
In some embodiments, the dimension label can be activated with
fluorescence, light, a chemical event (e.g., cleavage, ligation of
another molecule, addition of modifications (e.g., pegylated,
sumoylated, acetylated, methylated, deacetylated, demethylated), a
photochemical event (e.g., photocaging), and introduction of a
non-natural nucleotide.
The dimension label can, in some embodiments, be identical for all
stochastic barcodes attached to a given solid support (e.g., bead),
but different for different solid supports (e.g., beads). In some
embodiments, at least 60%, 70%, 80%, 85%, 90%, 95%, 97%, 99% or
100% of stochastic barcodes on the same solid support can comprise
the same dimension label. In some embodiments, at least 60% of
stochastic barcodes on the same solid support can comprise the same
dimension label. In some embodiments, at least 95% of stochastic
barcodes on the same solid support can comprise the same dimension
label.
There can be as many as 10.sup.6 or more unique dimension label
sequences represented in a plurality of solid supports (e.g.,
beads). A dimension label can be at least about 1, 2, 3, 4, 5, 10,
15, 20, 25, 30, 35, 40, 45, 50 or more nucleotides in length. A
dimension label can be at most about 300, 200, 100, 90, 80, 70, 60,
50, 40, 30, 20, 15, 12, 10, 9, 8, 7, 6, 5, 4 or fewer or more
nucleotides in length. A dimension label can comprise between about
5 to about 200 nucleotides. A dimension label can comprise between
about 10 to about 150 nucleotides. A dimension label can comprise
between about 20 to about 125 nucleotides in length.
A stochastic barcode can comprise a spatial label. A spatial label
can comprise a nucleic acid sequence that provides information
about the spatial orientation of a target molecule which is
associated with the stochastic barcode. A spatial label can be
associated with a coordinate in a sample. The coordinate can be a
fixed coordinate. For example a coordinate can be fixed in
reference to a substrate. A spatial label can be in reference to a
two or three-dimensional grid. A coordinate can be fixed in
reference to a landmark. The landmark can be identifiable in space.
A landmark can be a structure which can be imaged. A landmark can
be a biological structure, for example an anatomical landmark. A
landmark can be a cellular landmark, for instance an organelle. A
landmark can be a non-natural landmark such as a structure with an
identifiable identifier such as a color code, bar code, magnetic
property, fluorescents, radioactivity, or a unique size or shape. A
spatial label can be associated with a physical partition (e.g. a
well, a container, or a droplet). In some embodiments, multiple
spatial labels are used together to encode one or more positions in
space.
The spatial label can be identical for all stochastic barcodes
attached to a given solid support (e.g., bead), but different for
different solid supports (e.g., beads). In some embodiments, at
least 60%, 70%, 80%, 85%, 90%, 95%, 97%, 99% or 100% of stochastic
barcodes on the same solid support can comprise the same spatial
label. In some embodiments, at least 60% of stochastic barcodes on
the same solid support can comprise the same spatial label. In some
embodiments, at least 95% of stochastic barcodes on the same solid
support can comprise the same spatial label.
There can be as many as 10.sup.6 or more unique spatial label
sequences represented in a plurality of solid supports (e.g.,
beads). A spatial label can be at least about 1, 2, 3, 4, 5, 10,
15, 20, 25, 30, 35, 40, 45, 50 or more nucleotides in length. A
spatial label can be at most about 300, 200, 100, 90, 80, 70, 60,
50, 40, 30, 20, 15, 12, 10, 9, 8, 7, 6, 5, 4 or fewer or more
nucleotides in length. A spatial label can comprise between about 5
to about 200 nucleotides. A spatial label can comprise between
about 10 to about 150 nucleotides. A spatial label can comprise
between about 20 to about 125 nucleotides in length.
Stochastic barcodes can comprise a cellular label. A cellular label
can comprise a nucleic acid sequence that provides information for
determining which target nucleic acid originated from which cell.
In some embodiments, the cellular label is identical for all
stochastic barcodes attached to a given solid support (e.g., bead),
but different for different solid supports (e.g., beads). In some
embodiments, at least 60%, 70%, 80%, 85%, 90%, 95%, 97%, 99% or
100% of stochastic barcodes on the same solid support can comprise
the same cellular label. In some embodiments, at least 60% of
stochastic barcodes on the same solid support can comprise the same
cellular label. In some embodiment, at least 95% of stochastic
barcodes on the same solid support can comprise the same cellular
label.
There can be as many as 10.sup.6 or more unique cellular label
sequences represented in a plurality of solid supports (e.g.,
beads). A cellular label can be at least about 1, 2, 3, 4, 5, 10,
15, 20, 25, 30, 35, 40, 45, 50 or more nucleotides in length. A
cellular label can be at most about 300, 200, 100, 90, 80, 70, 60,
50, 40, 30, 20, 15, 12, 10, 9, 8, 7, 6, 5, 4 or fewer or more
nucleotides in length. A cellular label can comprise between about
5 to about 200 nucleotides. A cellular label can comprise between
about 10 to about 150 nucleotides. A cellular label can comprise
between about 20 to about 125 nucleotides in length.
The cellular label can further comprise a unique set of nucleic
acid sub-sequences of defined length, e.g. 7 nucleotides each
(equivalent to the number of bits used in some Hamming error
correction codes), which can be designed to provide error
correction capability. The set of error correction sub-sequences
comprise 7 nucleotide sequences can be designed such that any
pairwise combination of sequences in the set exhibits a defined
"genetic distance" (or number of mismatched bases), for example, a
set of error correction sub-sequences can be designed to exhibit a
genetic distance of 3 nucleotides. In this case, review of the
error correction sequences in the set of sequence data for labeled
target nucleic acid molecules (described more fully below) can
allow one to detect or correct amplification or sequencing errors.
In some embodiments, the length of the nucleic acid sub-sequences
used for creating error correction codes can vary, for example,
they can be 3 nucleotides, 7 nucleotides, 15 nucleotides, or 31
nucleotides in length. In some embodiments, nucleic acid
sub-sequences of other lengths can be used for creating error
correction codes.
In some embodiments, stochastic barcodes can comprise a molecular
label. A molecular label can comprise a nucleic acid sequence that
provides identifying information for the specific type of target
nucleic acid species hybridized to the stochastic barcode. A
molecular label can comprise a nucleic acid sequence that provides
a counter for the specific occurrence of the target nucleic acid
species hybridized to the stochastic barcode (e.g., target-binding
region). In some embodiments, a diverse set of molecular labels are
attached to a given solid support (e.g., bead). In some
embodiments, there can be as many as 10.sup.5 or more unique
molecular label sequences attached to a given solid support (e.g.,
bead). In some embodiments, there can be as many as 10.sup.4 or
more unique molecular label sequences attached to a given solid
support (e.g., bead). In some embodiments, there can be as many as
10.sup.3 or more unique molecular label sequences attached to a
given solid support (e.g., bead). In some embodiments, there can be
as many as 10.sup.2 or more unique molecular label sequences
attached to a given solid support (e.g., bead). A molecular label
can be at least about 1, 2, 3, 4, 5, 10, 15, 20, 25, 30, 35, 40,
45, 50 or more nucleotides in length. A molecular label can be at
most about 300, 200, 100, 90, 80, 70, 60, 50, 40, 30, 20, 15, 12,
10, 9, 8, 7, 6, 5, 4 or fewer nucleotides in length.
Stochastic barcodes can comprise a target binding region. In some
embodiments, the target binding regions can comprise a nucleic acid
sequence that hybridizes specifically to a target (e.g. target
nucleic acid, target molecule, e.g., a cellular nucleic acid to be
analyzed), for example to a specific gene sequence. In some
embodiments, a target binding region can comprise a nucleic acid
sequence that can attach (e.g., hybridize) to a specific location
of a specific target nucleic acid. In some embodiments, the target
binding region can comprise a nucleic acid sequence that is capable
of specific hybridization to a restriction enzyme site overhang
(e.g. an EcoRI sticky-end overhang). The stochastic barcode can
then ligate to any nucleic acid molecule comprising a sequence
complementary to the restriction site overhang.
In some embodiments, a target binding region can comprise a
non-specific target nucleic acid sequence. A non-specific target
nucleic acid sequence can refer to a sequence that can bind to
multiple target nucleic acids, independent of the specific sequence
of the target nucleic acid. For example, target binding region can
comprise a random multimer sequence, or an oligo-dT sequence that
hybridizes to the poly(A) tail on mRNA molecules. A random multimer
sequence can be, for example, a random dimer, trimer, quatramer,
pentamer, hexamer, septamer, octamer, nonamer, decamer, or higher
multimer sequence of any length. In some embodiments, the target
binding region is the same for all stochastic barcodes attached to
a given bead. In some embodiments, the target binding regions for
the plurality of stochastic barcodes attached to a given bead can
comprise two or more different target binding sequences. A target
binding region can be at least about 5, 10, 15, 20, 25, 30, 35, 40,
45, 50 or more nucleotides in length. A target binding region can
be at most about 5, 10, 15, 20, 25, 30, 35, 40, 45, 50 or more
nucleotides in length.
A stochastic barcode can comprise an orientation property which can
be used to orient (e.g., align) the stochastic barcodes. A
stochastic barcode can comprise a moiety for isoelectric focusing.
Different stochastic barcodes can comprise different isoelectric
focusing points. When these stochastic barcodes are introduced to a
sample, the sample can undergo isoelectric focusing in order to
orient the stochastic barcodes into a known way. In this way, the
orientation property can be used to develop a known map of
stochastic barcodes in a sample. Exemplary orientation properties
can include, electrophoretic mobility (e.g., based on size of the
stochastic barcode), isoelectric point, spin, conductivity, and/or
self-assembly. For example, stochastic barcodes with an orientation
property of self-assembly, can self-assemble into a specific
orientation (e.g., nucleic acid nanostructure) upon activation.
A stochastic barcode can comprise an affinity property. A spatial
label can comprise an affinity property. An affinity property can
include a chemical and/or biological moiety that can facilitate
binding of the stochastic barcode to another entity (e.g., cell
receptor). For example, an affinity property can comprise an
antibody. An antibody can be specific for a specific moiety (e.g.,
receptor) on a sample. An antibody can guide the stochastic barcode
to a specific cell type or molecule. Targets at and/or near the
specific cell type or molecule can be stochastically labeled. An
affinity property can also provide spatial information in addition
to the nucleotide sequence of the spatial label because the
antibody can guide the stochastic barcode to a specific location.
An antibody can be a therapeutic antibody. An antibody can be a
monoclonal antibody. An antibody can be a polyclonal antibody. An
antibody can be humanized. An antibody can be chimeric. An antibody
can be a naked antibody. An antibody can be a fusion antibody.
An antibody, can refer to a full-length (i.e., naturally occurring
or formed by normal immunoglobulin gene fragment recombinatorial
processes) immunoglobulin molecule (e.g., an IgG antibody) or an
immunologically active (i.e., specifically binding) portion of an
immunoglobulin molecule, like an antibody fragment.
An antibody can be an antibody fragment. An antibody fragment can
be a portion of an antibody such as F(ab')2, Fab', Fab, Fv, sFv and
the like. An antibody fragment can bind with the same antigen that
is recognized by the full-length antibody. An antibody fragment can
include isolated fragments consisting of the variable regions of
antibodies, such as the "Fv" fragments consisting of the variable
regions of the heavy and light chains and recombinant single chain
polypeptide molecules in which light and heavy variable regions are
connected by a peptide linker ("scFv proteins"). Exemplary
antibodies can include, but are not limited to, antibodies for
antibodies for cancer cells, antibodies for viruses, antibodies
that bind to cell surface receptors (CD8, CD34, CD45), and
therapeutic antibodies.
Solid Supports
The stochastic barcodes disclosed herein can be associated to
(e.g., attached to) a solid support (e.g., a bead). In some
embodiments, stochastically barcoding the plurality of targets in
the sample can be performed with a solid support including a
plurality of synthetic particles associated with the plurality of
stochastic barcodes. In some embodiments, the solid support can
include a plurality of synthetic particles associated with the
plurality of stochastic barcodes. The spatial labels of the
plurality of stochastic barcodes on different solid supports can
differ by at least one nucleotide. The solid support can, for
example, include the plurality of stochastic barcodes in two
dimensions or three dimensions. The synthetic particles can be
beads. The beads can be silica gel beads, controlled pore glass
beads, magnetic beads, Dynabeads, Sephadex/Sepharose beads,
cellulose beads, polystyrene beads, or any combination thereof. The
solid support can include a polymer, a matrix, a hydrogel, a needle
array device, an antibody, or any combination thereof. In some
embodiments, the solid supports can be free floating. In some
embodiments, the solid supports can be embedded in a semi-solid or
solid array. The stochastic barcodes may not be associated with
solid supports. The stochastic barcodes can be individual
nucleotides. The stochastic barcodes can be associated with a
substrate.
As used herein, the terms "tethered", "attached", and "immobilized"
are used interchangeably, and can refer to covalent or non-covalent
means for attaching stochastic barcodes to a solid support. Any of
a variety of different solid supports can be used as solid supports
for attaching pre-synthesized stochastic barcodes or for in situ
solid-phase synthesis of stochastic barcode.
In some embodiments, a solid support is a bead. A bead can
encompass one or more types of solid, porous, or hollow sphere,
ball, bearing, cylinder, or other similar configuration which a
nucleic acid can be immobilized (e.g., covalently or
non-covalently). The bead can be, for example, composed of plastic,
ceramic, metal, polymeric material, or any combination thereof. A
bead can be, or comprise, a discrete particle that is spherical
(e.g., microspheres) or have a non-spherical or irregular shape,
such as cubic, cuboid, pyramidal, cylindrical, conical, oblong, or
disc-shaped, and the like. In some embodiments, a bead can be
non-spherical in shape.
Beads can comprise a variety of materials including, but not
limited to, paramagnetic materials (e.g. magnesium, molybdenum,
lithium, and tantalum), superparamagnetic materials (e.g. ferrite
(Fe.sub.3O.sub.4; magnetite) nanoparticles), ferromagnetic
materials (e.g. iron, nickel, cobalt, some alloys thereof, and some
rare earth metal compounds), ceramic, plastic, glass, polystyrene,
silica, methylstyrene, acrylic polymers, titanium, latex,
sepharose, agarose, hydrogel, polymer, cellulose, nylon, and any
combination thereof.
The diameter of the beads can vary, for example, be at least about
100 nm, 500 nm, 1 .mu.m, 5 .mu.m, 10 .mu.m, 20 .mu.m, 25 .mu.m, 30
.mu.m, 35 .mu.m, 40 .mu.m, 45 .mu.m or 50 .mu.m. In some
embodiments, the diameter of the beads can be at most about 100 nm,
500 nm, 1 .mu.m, 5 .mu.m, 10 .mu.m, 20 .mu.m, 25 .mu.m, 30 .mu.m,
35 .mu.m, 40 .mu.m, 45 .mu.m or 50 .mu.m. In some embodiments, the
diameter of the bead can be related to the diameter of the wells of
the substrate. For example, the diameter of the bead can be at
least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% or 100% longer or
shorter than the diameter of the well. In some embodiments, the
diameter of the bead can be at most 10%, 20%, 30%, 40%, 50%, 60%,
70%, 80%, 90% or 100% longer or shorter than the diameter of the
well. The diameter of the bead can be related to the diameter of a
cell (e.g., a single cell entrapped by a well of the substrate).
The diameter of the bead can be at least 10%, 20%, 30%, 40%, 50%,
60%, 70%, 80%, 90%, 100%, 150%, 200%, 250%, or 300% or more longer
or shorter than the diameter of the cell. The diameter of the bead
can be at most 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%,
150%, 200%, 250%, or 300% or more longer or shorter than the
diameter of the cell.
A bead can be attached to and/or embedded in a substrate. A bead
can be attached to and/or embedded in a gel, hydrogel, polymer
and/or matrix. The spatial position of a bead within a substrate
(e.g., gel, matrix, scaffold, or polymer) can be identified using
the spatial label present on the stochastic barcode on the bead
which can serve as a location address.
Examples of beads can include, but are not limited to, streptavidin
beads, agarose beads, magnetic beads, Dynabeads.RTM., MACS.RTM.
microbeads, antibody conjugated beads (e.g., anti-immunoglobulin
microbeads), protein A conjugated beads, protein G conjugated
beads, protein A/G conjugated beads, protein L conjugated beads,
oligo(dT) conjugated beads, silica beads, silica-like beads,
anti-biotin microbeads, anti-fluorochrome microbeads, and BcMag.TM.
Carboxyl-Terminated Magnetic Beads.
A bead can be associated with (e.g. impregnated with) quantum dots
or fluorescent dyes to make it fluorescent in one fluorescence
optical channel or multiple optical channels. A bead can be
associated with iron oxide or chromium oxide to make it
paramagnetic or ferromagnetic. Beads can be identifiable. For
example, a bead can be imaged using a camera. A bead can have a
detectable code associated with the bead. For example, a bead can
comprise a stochastic barcode. A bead can change size, for example
due to swelling in an organic or inorganic solution. A bead can be
hydrophobic. A bead can be hydrophilic. A bead can be
biocompatible.
A solid support (e.g., bead) can be visualized. The solid support
can comprise a visualizing tag (e.g., fluorescent dye). A solid
support (e.g., bead) can be etched with an identifier (e.g., a
number). The identifier can be visualized through imaging the
beads.
A solid support can refer to an insoluble, semi-soluble, or
insoluble material. A solid support can be referred to as
"functionalized" when it includes a linker, a scaffold, a building
block, or other reactive moiety attached thereto, whereas a solid
support can be "nonfunctionalized" when it lack such a reactive
moiety attached thereto. The solid support can be employed free in
solution, such as in a microtiter well format; in a flow-through
format, such as in a column; or in a dipstick.
The solid support can comprise a membrane, paper, plastic, coated
surface, flat surface, glass, slide, chip, or any combination
thereof. A solid support can take the form of resins, gels,
microspheres, or other geometric configurations. A solid support
can comprise silica chips, synthetic particles, nanoparticles,
plates, and arrays. Solid supports can include beads (e.g., silica
gel, controlled pore glass, magnetic beads, Dynabeads, Wang resin;
Merrifield resin, Sephadex/Sepharose beads, cellulose beads,
polystyrene beads etc.), capillaries, flat supports such as glass
fiber filters, glass surfaces, metal surfaces (steel, gold silver,
aluminum, silicon and copper), glass supports, plastic supports,
silicon supports, chips, filters, membranes, microwell plates,
slides, or the like. plastic materials including multi-well plates
or membranes (e.g., formed of polyethylene, polypropylene,
polyamide, polyvinylidene difluoride), wafers, combs, pins or
needles (e.g., arrays of pins suitable for combinatorial synthesis
or analysis) or beads in an array of pits or nanoliter wells of
flat surfaces such as wafers (e.g., silicon wafers), wafers with
pits with or without filter bottoms.
In some embodiments stochastic barcodes of the disclosure can be
attached to a polymer matrix (e.g., gel, hydrogel). The polymer
matrix can be able to permeate intracellular space (e.g., around
organelles). The polymer matrix can able to be pumped throughout
the circulatory system.
A solid support can be a biological molecule. For example a solid
support can be a nucleic acid, a protein, an antibody, a histone, a
cellular compartment, a lipid, a carbohydrate, and the like. Solid
supports that are biological molecules can be amplified,
translated, transcribed, degraded, and/or modified (e.g.,
pegylated, sumoylated). A solid support that is a biological
molecule can provide spatial and time information in addition to
the spatial label that is attached to the biological molecule. For
example, a biological molecule can comprise a first confirmation
when unmodified, but can change to a second confirmation when
modified. The different conformations can expose stochastic
barcodes of the disclosure to targets. For example, a biological
molecule can comprise stochastic barcodes that are inaccessible due
to folding of the biological molecule. Upon modification of the
biological molecule (e.g., acetylation), the biological molecule
can change conformation to expose the stochastic labels. The timing
of the modification can provide another time dimension to the
method of stochastic barcoding of the disclosure.
In another example, the biological molecule comprising stochastic
barcodes of the disclosure can be located in the cytoplasm of a
cell. Upon activation, the biological molecule can move to the
nucleus, whereupon stochastic barcoding can take place. In this
way, modification of the biological molecule can encode additional
space-time information for the targets identified by the stochastic
barcodes.
A dimension label can provide information about space-time of a
biological event (e.g., cell division). For example, a dimension
label can be added to a first cell, the first cell can divide
generating a second daughter cell, the second daughter cell can
comprise all, some or none of the dimension labels. The dimension
labels can be activated in the original cell and the daughter cell.
In this way, the dimension label can provide information about time
of stochastic barcoded in distinct spaces.
Microarrays
In some embodiments, a solid support/substrate can refer to a
microarray. A microarray can comprise a plurality of polymers,
e.g., oligomers, synthesized in situ or pre-synthesized and
deposited on a substrate in an array pattern. Microarrays of
oligomers manufactured by solid-phase DNA synthesis can have
oligomer densities approaching 106/micron2. As used herein, the
support-bound oligomers can be referred to as called "probes",
which function to bind or hybridize with a sample of DNA or RNA
material under test. However, the terms can be used interchangeably
wherein the surface-bound oligonucleotides as targets and the
solution sample of nucleic acids as probes. Further, some
investigators bind the target sample under test to the microarray
substrate and put the oligomer probes in solution for
hybridization. Either of the "target" or "probes" can be the one
that is to be evaluated by the other (thus, either one could be an
unknown mixture of polynucleotides to be evaluated by binding with
the other). All of these iterations are within the scope of this
discussion herein. For the purpose of simplicity only, herein the
probe is the surface-bound oligonucleotide of known sequence and
the target is the moiety in a mobile phase (typically fluid), to be
detected by the surface-bound probes. The plurality of probes
and/or targets in each location in the array can be referred to as
a "nucleic acid feature" or "feature." A feature is defined as a
locus onto which a large number of probes and/or targets all having
the same nucleotide sequence are immobilized.
Depending on the make-up of the target sample, hybridization of
probe features may or may not occur at all probe feature locations
and can occur to varying degrees at the different probe feature
locations.
An "array" can refer to an intentionally created collection of
molecules which can be prepared either synthetically or
biosynthetically. The molecules in the array can be identical or
different from each other. The array can assume a variety of
formats, e.g., libraries of soluble molecules; libraries of
compounds tethered to resin beads, silica chips, or other solid
supports. Array Plate or a Plate a body having a plurality of
arrays in which each array can be separated from the other arrays
by a physical barrier resistant to the passage of liquids and
forming an area or space, referred to as a well.
The density of the microarrays can be higher than 500, 5000, 50000,
or 500,000 different probes per cm.sup.2. The feature size of the
probes can be smaller than 500, 150, 25, 9, or 1 .mu.m.sup.2. The
locations of the probes can be determined or decipherable. For
example, in some arrays, the specific locations of the probes are
known before binding assays. In some other arrays, the specific
locations of the probes are unknown until after the assays. The
probes can be immobilized on a substrate, optionally, via a linker,
beads, etc.
The array can comprise features made up of oligo(dT) probes. The
array can comprise features made up of gene-specific probes. In
some embodiments, the array is a microarray. In some embodiments,
the array is an array of solid supports (e.g., beads). In some
embodiments, the array is planar. In some embodiments, the array
has topographical features.
Substrates
A substrate can refer to a type of solid support. A substrate can
refer to a solid support that can comprise stochastic barcodes of
the disclosure. A substrate can comprise a plurality of microwells.
A microwell can comprise a small reaction chamber of defined
volume. A microwell can entrap one or more cells. A microwell can
entrap only one cell. A microwell can entrap one or more solid
supports. A microwell can entrap only one solid support. In some
embodiments, a microwell entraps a single cell and a single solid
support (e.g., bead).
The microwells of the array can be fabricated in a variety of
shapes and sizes. Appropriate well geometries can include, but are
not limited to, cylindrical, conical, hemispherical, rectangular,
or polyhedral (e.g., three dimensional geometries comprised of
several planar faces, for example, hexagonal columns, octagonal
columns, inverted triangular pyramids, inverted square pyramids,
inverted pentagonal pyramids, inverted hexagonal pyramids, or
inverted truncated pyramids). The microwells can comprise a shape
that combines two or more of these geometries. For example, a
microwell can be partly cylindrical, with the remainder having the
shape of an inverted cone. A microwell can include two side-by-side
cylinders, one of larger diameter (e.g. that corresponds roughly to
the diameter of the beads) than the other (e.g. that corresponds
roughly to the diameter of the cells), that are connected by a
vertical channel (that is, parallel to the cylinder axes) that
extends the full length (depth) of the cylinders. The opening of
the microwell can be at the upper surface of the substrate. The
opening of the microwell can be at the lower surface of the
substrate. The closed end (or bottom) of the microwell can be flat.
The closed end (or bottom) of the microwell can have a curved
surface (e.g., convex or concave). The shape and/or size of the
microwell can be determined based on the types of cells or solid
supports to be trapped within the microwells.
Microwell dimensions can be characterized in terms of the diameter
and depth of the well. As used herein, the diameter of the
microwell refers to the largest circle that can be inscribed within
the planar cross-section of the microwell geometry. The diameter of
the microwells can range from about 1-fold to about 10-folds the
diameter of the cells or solid supports to be trapped within the
microwells. The microwell diameter can be at least 1-fold, at least
1.5-fold, at least 2-folds, at least 3-folds, at least 4-folds, at
least 5-folds, or at least 10-folds the diameter of the cells or
solid supports to be trapped within the microwells. The microwell
diameter can be at most 10-folds, at most 5-folds, at most 4-folds,
at most 3-folds, at most 2-folds, at most 1.5-fold, or at most
1-fold the diameter of the cells or solid supports to be trapped
within the microwells. The microwell diameter can be about
2.5-folds the diameter of the cells or solid supports to be trapped
within the microwells.
The diameter of the microwells can be specified in terms of
absolute dimensions. The diameter of the microwells can range from
about 5 to about 50 micrometers. The microwell diameter can be at
least 5 micrometers, at least 10 micrometers, at least 15
micrometers, at least 20 micrometers, at least 25 micrometers, at
least 30 micrometers, at least 35 micrometers, at least 40
micrometers, at least 45 micrometers, or at least 50 micrometers.
The microwell diameter can be at most 50 micrometers, at most 45
micrometers, at most 40 micrometers, at most 35 micrometers, at
most 30 micrometers, at most 25 micrometers, at most 20
micrometers, at most 15 micrometers, at most 10 micrometers, or at
most 5 micrometers. The microwell diameter can be about 30
micrometers.
In some embodiments, the diameter of each microwell can be, or can
be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70,
80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, or a
number between any two of these values, nanometer. In some
embodiments, the diameter of each microwell can be, or can be
about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80,
90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, or a number
between any two of these values, micrometer. In some embodiments,
the diameter of each microwell can be, or can be about, 1, 2, 3, 4,
5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300,
400, 500, 600, 700, 800, 900, 1000, or a number between any two of
these values, minimeter.
The microwell depth can be chosen to provide efficient trapping of
cells and solid supports. The microwell depth can be chosen to
provide efficient exchange of assay buffers and other reagents
contained within the wells. The ratio of diameter to height (i.e.
aspect ratio) can be chosen such that once a cell and solid support
settle inside a microwell, they will not be displaced by fluid
motion above the microwell. In some embodiments, the height of the
microwell can be smaller than the diameter of the bead. For
example, the height of the microwell can be at least 5, 10, 15, 20,
25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100%
of the diameter of the bead. The bead can protrude outside of the
microwell.
The dimensions of the microwell can be chosen such that the
microwell has sufficient space to accommodate a solid support and a
cell of various sizes without being dislodged by fluid motion above
the microwell. The depth of the microwells can range from about
1-fold to about 10-fold the diameter of the cells or solid supports
to be trapped within the microwells. The microwell depth can be at
least 1-fold, at least 1.5-fold, at least 2-folds, at least
3-folds, at least 4-folds, at least 5-folds, or at least 10-folds
the diameter of the cells or solid supports to be trapped within
the microwells. The microwell depth can be at most 10-folds, at
most 5-folds, at most 4-folds, at most 3-folds, at most 2-folds, at
most 1.5-fold, or at most 1-fold the diameter of the cells or solid
supports to be trapped within the microwells. The microwell depth
can be about 2.5-folds the diameter of the cells or solid supports
to be trapped within the microwells.
The depth of the microwells can be specified in terms of absolute
dimensions. The depth of the microwells can range from about 10 to
about 60 micrometers. The microwell depth can be at least 10
micrometers, at least 20 micrometers, at least 25 micrometers, at
least 30 micrometers, at least 35 micrometers, at least 40
micrometers, at least 50 micrometers, or at least 60 micrometers.
The microwell depth can be at most 60 micrometers, at most 50
micrometers, at most 40 micrometers, at most 35 micrometers, at
most 30 micrometers, at most 25 micrometers, at most 20
micrometers, or at most 10 micrometers. The microwell depth can be
about 30 micrometers.
In some embodiments, the depth of each microwell can be, or can be
about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80,
90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, or a number
between any two of these values, nanometers. In some embodiments,
the depth of each microwell can be, or can be about, 1, 2, 3, 4, 5,
6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400,
500, 600, 700, 800, 900, 1000, or a number between any two of these
values, micrometers. In some embodiments, the depth of each
microwell can be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700,
800, 900, 1000, or a number between any two of these values,
minimeters.
The volume of the microwells used in the methods, devices, and
systems of the present disclosure can vary, for example range from
about 200 micrometers.sup.3 to about 120,000 micrometers.sup.3. The
microwell volume can be at least 200 micrometers.sup.3, at least
500 micrometers.sup.3, at least 1,000 micrometers.sup.3, at least
10,000 micrometers.sup.3, at least 25,000 micrometers.sup.3, at
least 50,000 micrometers.sup.3, at least 100,000 micrometers.sup.3,
or at least 120,000 micrometers.sup.3. The microwell volume can be
at most 120,000 micrometers.sup.3, at most 100,000
micrometers.sup.3, at most 50,000 micrometers.sup.3, at most 25,000
micrometers.sup.3, at most 10,000 micrometers.sup.3, at most 1,000
micrometers.sup.3, at most 500 micrometers.sup.3, or at most 200
micrometers.sup.3. The microwell volume can be about 25,000
micrometers.sup.3. The microwell volume can fall within any range
bounded by any of these values (e.g. from about 18,000
micrometers.sup.3 to about 30,000 micrometers.sup.3).
In some embodiments, each of the microwells can have a volume of
10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600,
700, 800, 900, 1000, or a number between any two of these values,
nanoliters. In some embodiments, each of the microwells can have a
volume of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70,
80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, or a
number between any two of these values, microliters. In some
embodiments, each of the microwells can have a volume of 1, 2, 3,
4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200,
300, 400, 500, 600, 700, 800, 900, 1000, or a number between any
two of these values, miniliters.
The volumes of the microwells used in the methods, devices, and
systems of the present disclosure can be further characterized in
terms of the variation in volume from one microwell to another. The
coefficient of variation (expressed as a percentage) for microwell
volume can range from about 1% to about 10%. The coefficient of
variation for microwell volume can be at least 1%, at least 2%, at
least 3%, at least 4%, at least 5%, at least 6%, at least 7%, at
least 8%, at least 9%, or at least 10%. The coefficient of
variation for microwell volume can be at most 10%, at most 9%, at
most 8%, at most 7%, at most 6%, at most 5%, at most 4%, at most
3%, at most 2%, or at most 1%. The coefficient of variation for
microwell volume can have any value within a range encompassed by
these values, for example between about 1.5% and about 6.5%. In
some embodiments, the coefficient of variation of microwell volume
can be about 2.5%.
The ratio of the volume of the microwells to the surface area of
the beads (or to the surface area of a solid support to which
stochastic barcode oligonucleotides can be attached) used in the
methods, devices, and systems of the present disclosure can vary,
for example range from about 2.5 to about 1,520 micrometers. The
ratio can be at least 2.5, at least 5, at least 10, at least 100,
at least 500, at least 750, at least 1,000, or at least 1,520. The
ratio can be at most 1,520, at most 1,000, at most 750, at most
500, at most 100, at most 10, at most 5, or at most 2.5. In some
embodiments, the ratio can be, or be about 67.5. The ratio of
microwell volume to the surface area of the bead (or solid support
used for immobilization) can fall within any range bounded by any
of these values (e.g. from about 30 to about 120).
The wells of the microwell array can be arranged in a one
dimensional, two dimensional, or three-dimensional array. A three
dimensional array can be achieved, for example, by stacking a
series of two or more two dimensional arrays (that is, by stacking
two or more substrates comprising microwell arrays).
The pattern and spacing between microwells can be chosen to
optimize the efficiency of trapping a single cell and single solid
support (e.g., bead) in each well, as well as to maximize the
number of wells per unit area of the array. The microwells can be
distributed according to a variety of random or non-random
patterns. For example, they can be distributed entirely randomly
across the surface of the array substrate, or they can be arranged
in a square grid, rectangular grid, hexagonal grid, or the like.
The center-to-center distance (or spacing) between wells can vary
from about 15 micrometers to about 75 micrometers. In other
embodiments, the spacing between wells is at least 15 micrometers,
at least 20 micrometers, at least 25 micrometers, at least 30
micrometers, at least 35 micrometers, at least 40 micrometers, at
least 45 micrometers, at least 50 micrometers, at least 55
micrometers, at least 60 micrometers, at least 65 micrometers, at
least 70 micrometers, or at least 75 micrometers. The microwell
spacing can be at most 75 micrometers, at most 70 micrometers, at
most 65 micrometers, at most 60 micrometers, at most 55
micrometers, at most 50 micrometers, at most 45 micrometers, at
most 40 micrometers, at most 35 micrometers, at most 30
micrometers, at most 25 micrometers, at most 20 micrometers, or at
most 15 micrometers. The microwell spacing can be about 55
micrometers. The microwell spacing can fall within any range
bounded by any of these values (e.g. from about 18 micrometers to
about 72 micrometers).
In some embodiments, microwells can be separated from each other by
no more than 0.01, 0.1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40,
50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900,
1000, or a number between any two of these values, micrometers. In
some embodiments, the microwells can be separated from one another
by no more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60,
70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, or a
number between any two of these values, minimeters.
In some embodiments, the microwell array can comprise 100, 200,
300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000,
6000, 7000, 8000, 9000, 10000, or a number between any two of these
values, wells per inch. In some embodiments, the microwell array
can comprise 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300,
400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000,
7000, 8000, 9000, 10000, or a number between any two of these
values, wells per cm.sup.2.
The microwell array can comprise surface features between the
microwells that are designed to help guide cells and solid supports
into the wells and/or prevent them from settling on the surfaces
between wells. Examples of suitable surface features can include,
but are not limited to, domed, ridged, or peaked surface features
that encircle the wells or straddle the surface between wells.
The total number of wells in the microwell array can be determined
by the pattern and spacing of the wells and the overall dimensions
of the array. The number of microwells in the array can vary, for
example, range from about 96 to about 5,000,000 or more. The number
of microwells in the array can be at least 96, at least 384, at
least 1,536, at least 5,000, at least 10,000, at least 25,000, at
least 50,000, at least 75,000, at least 100,000, at least 500,000,
at least 1,000,000, or at least 5,000,000. The number of microwells
in the array can be at most 5,000,000, at most 1,000,000, at most
75,000, at most 50,000, at most 25,000, at most 10,000, at most
5,000, at most 1,536, at most 384, or at most 96 wells. The number
of microwells in the array can be about 96. The number of
microwells can be about 150,000. The number of microwells in the
array can fall within any range bounded by any of these values
(e.g. from about 100 to 325,000).
Microwell arrays can be fabricated using any of a number of
fabrication techniques. Examples of fabrication methods that can be
used include, but are not limited to, bulk micromachining
techniques such as photolithography and wet chemical etching,
plasma etching, or deep reactive ion etching; micro-molding and
micro-embossing; laser micro-machining; 3D printing or other direct
write fabrication processes using curable materials; and similar
techniques.
Microwell arrays can be fabricated from any of a number of
substrate materials. The choice of material can depend on the
choice of fabrication technique, and vice versa. Examples of
suitable materials can include, but are not limited to, silicon,
fused-silica, glass, polymers (e.g. agarose, gelatin, hydrogels,
polydimethylsiloxane (PDMS; elastomer), polymethylmethacrylate
(PMMA), polycarbonate (PC), polypropylene (PP), polyethylene (PE),
high density polyethylene (HDPE), polyimide, cyclic olefin polymers
(COP), cyclic olefin copolymers (COL), polyethylene terephthalate
(PET), epoxy resins, thiol-ene based resins, metals or metal films
(e.g. aluminum, stainless steel, copper, nickel, chromium, and
titanium), and the like. A hydrophilic material can be desirable
for fabrication of the microwell arrays (e.g. to enhance
wettability and minimize non-specific binding of cells and other
biological material). Hydrophobic materials that can be treated or
coated (e.g. by oxygen plasma treatment, or grafting of a
polyethylene oxide surface layer) can also be used. The use of
porous, hydrophilic materials for the fabrication of the microwell
array can be desirable in order to facilitate capillary
wicking/venting of entrapped air bubbles in the device. The
microwell array can be fabricated from a single material. The
microwell array can comprise two or more different materials that
have been bonded together or mechanically joined.
Microwell arrays can be fabricated using substrates of any of a
variety of sizes and shapes. For example, the shape (or footprint)
of the substrate within which microwells are fabricated can be
square, rectangular, circular, or irregular in shape. The footprint
of the microwell array substrate can be similar to that of a
microtiter plate. The footprint of the microwell array substrate
can be similar to that of standard microscope slides, e.g. about 75
mm long.times.25 mm wide (about 3'' long.times.1'' wide), or about
75 mm long.times.50 mm wide (about 3'' long.times.2'' wide). The
thickness of the substrate within which the microwells are
fabricated can range from about 0.1 mm thick to about 10 mm thick,
or more. The thickness of the microwell array substrate can be at
least 0.1 mm thick, at least 0.5 mm thick, at least 1 mm thick, at
least 2 mm thick, at least 3 mm thick, at least 4 mm thick, at
least 5 mm thick, at least 6 mm thick, at least 7 mm thick, at
least 8 mm thick, at least 9 mm thick, or at least 10 mm thick. The
thickness of the microwell array substrate can be at most 10 mm
thick, at most 9 mm thick, at most 8 mm thick, at most 7 mm thick,
at most 6 mm thick, at most 5 mm thick, at most 4 mm thick, at most
3 mm thick, at most 2 mm thick, at most 1 mm thick, at most 0.5 mm
thick, or at most 0.1 mm thick. The thickness of the microwell
array substrate can be about 1 mm thick. The thickness of the
microwell array substrate can be any value within these ranges, for
example, the thickness of the microwell array substrate can be
between about 0.2 mm and about 9.5 mm.
A variety of surface treatments and surface modification techniques
can be used to alter the properties of microwell array surfaces.
Examples can include, but are not limited to, oxygen plasma
treatments to render hydrophobic material surfaces more
hydrophilic, the use of wet or dry etching techniques to smooth (or
roughen) glass and silicon surfaces, adsorption or grafting of
polyethylene oxide or other polymer layers (such as pluronic), or
bovine serum albumin to substrate surfaces to render them more
hydrophilic and less prone to non-specific adsorption of
biomolecules and cells, the use of silane reactions to graft
chemically-reactive functional groups to otherwise inert silicon
and glass surfaces, etc. Photodeprotection techniques can be used
to selectively activate chemically-reactive functional groups at
specific locations in the array structure, for example, the
selective addition or activation of chemically-reactive functional
groups such as primary amines or carboxyl groups on the inner walls
of the microwells can be used to covalently couple oligonucleotide
probes, peptides, proteins, or other biomolecules to the walls of
the microwells. The choice of surface treatment or surface
modification utilized can depend both or either on the type of
surface property that is desired and on the type of material from
which the microwell array is made.
The openings of microwells can be sealed, for example, during cell
lysis steps to prevent cross hybridization of target nucleic acid
between adjacent microwells. A microwell (or array of microwells)
can be sealed or capped using, for example, a flexible membrane or
sheet of solid material (i.e. a plate or platten) that clamps
against the surface of the microwell array substrate, or a suitable
bead, where the diameter of the bead is larger than the diameter of
the microwell.
A seal formed using a flexible membrane or sheet of solid material
can comprise, for example, inorganic nanopore membranes (e.g.,
aluminum oxides), dialysis membranes, glass slides, coverslips,
elastomeric films (e.g. PDMS), or hydrophilic polymer films (e.g.,
a polymer film coated with a thin film of agarose that has been
hydrated with lysis buffer).
Solid supports (e.g., beads) used for capping the microwells can
comprise any of the solid supports (e.g., beads) of the disclosure.
In some embodiments, the solid supports are cross-linked dextran
beads (e.g., Sephadex). Cross-linked dextran can range from about
10 micrometers to about 80 micrometers. The cross-linked dextran
beads used for capping can be from 20 micrometers to about 50
micrometers. In some embodiments, the beads can be at least about
10, 20, 30, 40, 50, 60, 70, 80 or 90% larger than the diameter of
the microwells. The beads used for capping can be at most about 10,
20, 30, 40, 50, 60, 70, 80 or 90% larger than the diameter of the
microwells.
The seal or cap can allow buffer to pass into and out of the
microwell, while preventing macromolecules (e.g., nucleic acids)
from migrating out of the well. A macromolecule of at least about
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 19, or
20 or more nucleotides can be blocked from migrating into or out of
the microwell by the seal or cap. A macromolecule of at most about
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 19, or
20 or more nucleotides can be blocked from migrating into or out of
the microwell by the seal or cap.
Solid supports (e.g., beads) can be distributed among a substrate.
Solid supports (e.g., beads) can be distributed among wells of the
substrate, removed from the wells of the substrate, or otherwise
transported through a device comprising one or more microwell
arrays by means of centrifugation or other non-magnetic means. A
microwell of a substrate can be pre-loaded with a solid support. A
microwell of a substrate can hold at least 1, 2, 3, 4, or 5, or
more solid supports. A microwell of a substrate can hold at most 1,
2, 3, 4, or 5 or more solid supports. In some embodiments, a
microwell of a substrate can hold one solid support.
Individual cells and beads can be compartmentalized using
alternatives to microwells, for example, a single solid support and
single cell could be confined within a single droplet in an
emulsion (e.g. in a droplet digital microfluidic system).
Cells could potentially be confined within porous beads that
themselves comprise the plurality of tethered stochastic barcodes.
Individual cells and solid supports can be compartmentalized in any
type of container, microcontainer, reaction chamber, reaction
vessel, or the like.
Single cell, stochastic barcoding or can be performed without the
use of microwells. Single cell, stochastic barcoding assays can be
performed without the use of any physical container. For example,
stochastic barcoding without a physical container can be performed
by embedding cells and beads in close proximity to each other
within a polymer layer or gel layer to create a diffusional barrier
between different cell/bead pairs. In another example, stochastic
barcoding without a physical container can be performed in situ, in
vivo, on an intact solid tissue, on an intact cell, and/or
subcellularly.
Microwell arrays can be a consumable component of the assay system.
Microwell arrays can be reusable. Microwell arrays can be
configured for use as a stand-alone device for performing assays
manually, or they can be configured to comprise a fixed or
removable component of an instrument system that provides for full
or partial automation of the assay procedure. In some embodiments
of the disclosed methods, the bead-based libraries of stochastic
barcodes can be deposited in the wells of the microwell array as
part of the assay procedure. In some embodiments, the beads can be
pre-loaded into the wells of the microwell array and provided to
the user as part of, for example, a kit for performing stochastic
barcoding and digital counting of nucleic acid targets.
In some embodiments, two mated microwell arrays can be provided,
one pre-loaded with beads which are held in place by a first
magnet, and the other for use by the user in loading individual
cells. Following distribution of cells into the second microwell
array, the two arrays can be placed face-to-face and the first
magnet removed while a second magnet is used to draw the beads from
the first array down into the corresponding microwells of the
second array, thereby ensuring that the beads rest above the cells
in the second microwell array and thus minimizing diffusional loss
of target molecules following cell lysis, while maximizing
efficient attachment of target molecules to the stochastic barcodes
on the bead.
In some embodiments, a substrate does not include microwells. For
example, beads can be assembled (e.g., self-assembled). The beads
can self-assemble into a mono-layer. The monolayer can be on a flat
surface of the substrate. The monolayer can be on a curved surface
of the substrate. The bead monolayer can be formed by any method,
such as alcohol evaporation.
Three-Dimensional Substrates
A three-dimensional array can be any shape. A three-dimensional
substrate can be made of any material used in a substrate of the
disclosure. In some embodiments, a three-dimensional substrate
comprises a DNA origami. DNA origami structures incorporate DNA as
a building material to make nanoscale shapes. The DNA origami
process can involve the folding of one or more long, "scaffold" DNA
strands into a particular shape using a plurality of rationally
designed "staple DNA strands. The sequences of the staple strands
can be designed such that they hybridize to particular portions of
the scaffold strands and, in doing so, force the scaffold strands
into a particular shape. The DNA origami can include a scaffold
strand and a plurality of rationally designed staple strands. The
scaffold strand can have any sufficiently non-repetitive
sequence.
The sequences of the staple strands can be selected such that the
DNA origami has at least one shape to which stochastic labels can
be attached. In some embodiments, the DNA origami can be of any
shape that has at least one inner surface and at least one outer
surface. An inner surface can be any surface area of the DNA
origami that is sterically precluded from interacting with the
surface of a sample, while an outer surface is any surface area of
the DNA origami that is not sterically precluded from interacting
with the surface of a sample. In some embodiments, the DNA origami
has one or more openings (e.g., two openings), such that an inner
surface of the DNA origami can be accessed by particles (e.g.,
solid supports). For example, in certain embodiments the DNA
origami has one or more openings that allow particles smaller than
10 micrometers, 5 micrometers, 1 micrometer, 500 nm, 400 nm, 300
nm, 250 nm, 200 nm, 150 nm, 100 nm, 75 nm, 50 nm, 45 nm or 40 nm to
contact an inner surface of the DNA origami.
The DNA origami can change shape (conformation) in response to one
or more certain environmental stimuli. Thus an area of the DNA
origami can be an inner surface when the DNA origami takes on some
conformations, but can be an outer surface when the device takes on
other conformations. In some embodiments, the DNA origami can
respond to certain environmental stimuli by taking on a new
conformation.
In some embodiments, the staple strands of the DNA origami can be
selected such that the DNA origami is substantially barrel- or
tube-shaped. The staples of the DNA origami can be selected such
that the barrel shape is closed at both ends or is open at one or
both ends, thereby permitting particles to enter the interior of
the barrel and access its inner surface. In certain embodiments,
the barrel shape of the DNA origami can be a hexagonal tube.
In some embodiments, the staple strands of the DNA origami can be
selected such that the DNA origami has a first domain and a second
domain, wherein the first end of the first domain is attached to
the first end of the second domain by one or more single-stranded
DNA hinges, and the second end of the first domain is attached to
the second domain of the second domain by the one or more molecular
latches. The plurality of staples can be selected such that the
second end of the first domain becomes unattached to the second end
of the second domain if all of the molecular latches are contacted
by their respective external stimuli. Latches can be formed from
two or more staple stands, including at least one staple strand
having at least one stimulus-binding domain that is able to bind to
an external stimulus, such as a nucleic acid, a lipid or a protein,
and at least one other staple strand having at least one latch
domain that binds to the stimulus binding domain. The binding of
the stimulus-binding domain to the latch domain supports the
stability of a first conformation of the DNA origami.
Spatial labels can be delivered to a sample in three dimensions.
For example a sample can be associated with an array, wherein the
array has spatial labels distributed or distributable in three
dimensions. A three dimensional array can be a scaffolding, a
porous substrate, a gel, a series of channels, or the like.
A three dimensional pattern of spatial labels can be associated
with a sample by injecting the samples into known locations with
the sample, for example using a robot. A single needle can be used
to serially inject spatial labels at different depths into a
sample. An array of needles can inject spatial labels at different
depths to generate a three dimensional distribution of labels.
In some embodiments, a three dimensional solid support can be a
device. For example, a needle array device (e.g., a biopsy needle
array device) can be a substrate. Stochastic barcodes of the
disclosure can be attached to the device. Placing the device in
and/or on a sample can bring the stochastic barcodes of the
disclosure into proximity with targets in and/or on the sample.
Different parts of the device can have stochastic barcodes with
different spatial labels. For example, on a needle array device,
each needle of the device can be coated with stochastic barcodes
with different spatial labels on each needle. In this way, spatial
labels can provide information about the location of the targets
(e.g., location in orientation to the needle array).
Probes
The solid support/substrate of the disclosure can comprise a
plurality of probes. The probes can be at least 1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 or more
nucleotides in length. The probes can be at most 1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 or more
nucleotides in length.
The probes can be oligo(dT) probes. The probes can be any
homopolymer sequence (e.g., poly(A), poly(C), poly (G),
poly(U)).
The probes can be gene-specific. The probes can target any location
of a gene (e.g., 3' UTR, 5' UTR, coding region, promoter). The
probes on the substrate can be gene-specific for a plurality of
genes. For example, a substrate can comprise probes that are
gene-specific for at least 10, 20, 30, 40, 50, 60, 70, 80, 90, or
100 or more genes. A substrate can comprise probes that are
gene-specific for at least 10, 20, 30, 40, 50, 60, 70, 80, 90, or
100 or more genes. The plurality of gene-specific probes can be
dispersed throughout the substrate evenly. The plurality of
gene-specific probes can be dispersed throughout the substrate in
discrete locations. There can be an equivalent number of
gene-specific probes for each gene. There can be an inequivalent
number of gene-specific probes for each gene. For examples, one or
more gene-specific probes can be represented on the substrate at
least 10, 20, 30, 40, 50, 60, 70, or 80% or more compared to one or
more other gene-specific probes. One or more gene-specific probes
can be represented on the substrate at most 10, 20, 30, 40, 50, 60,
70, or 80% or more compared to one or more other gene-specific
probes.
The substrate can comprise a plurality of gene-specific probes for
a plurality of genes and a plurality of oligo(dT) probes. The
combination of gene-specific probes and oligo (dT) probes can be
useful for bridge amplification methods of the disclosure. The
ratio of a gene-specific probe to an oligo(dT) probe can be at
least 1:1, 1:2, 1:3, 1:4, or 1:5 or more. The ratio of a
gene-specific probe to an oligo(dT) probe can be at most 1:1, 1:2,
1:3, 1:4, or 1:5 or more. The ratio of an oligo(dT) probe to a
gene-specific probe can be at least 1:1, 1:2, 1:3, 1:4, or 1:5 or
more. The ratio of an oligo(dT) probe to a gene-specific probe can
be at most 1:1, 1:2, 1:3, 1:4, or 1:5 or more.
The probes on the replicate substrate can comprise any of the
probes, or combination of probes of the disclosure. The probes on
the replicate substrate can be the same as the initial substrate.
The probes on the replicate substrate can be different from the
initial substrate. For example, the probes on the initial substrate
can be gene-specific for a first location of a gene. The probes on
the replicate slide can be gene-specific for a second location on
the same gene. In this way, the probes can be used to identify
(e.g., generate and/or detect) multiple amplicons from the same
gene. The multiple amplicons can comprise different genetic
features such as SNPs. Identification of multiple amplicons on the
same gene can be useful for identification of SNPs and/or genetic
mobility events (e.g., truncations, translocations,
transpositions).
In some embodiments, the probes on the initial substrate can be
oligo(dT) and the probes on the replicate substrate can be
gene-specific or a combination of gene-specific and oligo(dT).
Synthesis of Stochastic Barcodes on Solid Supports and
Substrates
A stochastic barcode can be synthesized on a solid support (e.g.,
bead). Pre-synthesized stochastic barcodes (e.g., comprising the
5'amine that can link to the solid support) can be attached to
solid supports (e.g., beads) through any of a variety of
immobilization techniques involving functional group pairs on the
solid support and the stochastic barcode. The stochastic barcode
can comprise a functional group. The solid support (e.g., bead) can
comprise a functional group. The stochastic barcode functional
group and the solid support functional group can comprise, for
example, biotin, streptavidin, primary amine(s), carboxyl(s),
hydroxyl(s), aldehyde(s), ketone(s), and any combination thereof. A
stochastic barcode can be tethered to a solid support, for example,
by coupling (e.g. using 1-Ethyl-3-(3-dimethylaminopropyl)
carbodiimide) a 5' amino group on the stochastic barcode to the
carboxyl group of the functionalized solid support. Residual
non-coupled stochastic barcodes can be removed from the reaction
mixture by performing multiple rinse steps. In some embodiments,
the stochastic barcode and solid support are attached indirectly
via linker molecules (e.g. short, functionalized hydrocarbon
molecules or polyethylene oxide molecules) using similar attachment
chemistries. The linkers can be cleavable linkers, e.g. acid-labile
linkers or photo-cleavable linkers.
The stochastic barcodes can be synthesized on solid supports (e.g.,
beads) using any of a number of solid-phase oligonucleotide
synthesis techniques, such as phosphodiester synthesis,
phosphotriester synthesis, phosphite triester synthesis, and
phosphoramidite synthesis. Single nucleotides can be coupled in
step-wise fashion to the growing, tethered stochastic barcode. A
short, pre-synthesized sequence (or block) of several
oligonucleotides can be coupled to the growing, tethered stochastic
barcode.
Stochastic barcodes can be synthesized by interspersing step-wise
or block coupling reactions with one or more rounds of split-pool
synthesis, in which the total pool of synthesis beads is divided
into a number of individual smaller pools which are then each
subjected to a different coupling reaction, followed by
recombination and mixing of the individual pools to randomize the
growing stochastic barcode sequence across the total pool of beads.
Split-pool synthesis is an example of a combinatorial synthesis
process in which a maximum number of chemical compounds are
synthesized using a minimum number of chemical coupling steps. The
potential diversity of the compound library thus created is
determined by the number of unique building blocks (e.g.
nucleotides) available for each coupling step, and the number of
coupling steps used to create the library. For example, a
split-pool synthesis comprising 10 rounds of coupling using 4
different nucleotides at each step will yield 4.sup.10=1,048,576
unique nucleotide sequences. In some embodiments, split-pool
synthesis can be performed using enzymatic methods such as
polymerase extension or ligation reactions rather than chemical
coupling. For example, in each round of a split-pool polymerase
extension reaction, the 3' ends of the stochastic barcodes tethered
to beads in a given pool can be hybridized with the 5'ends of a set
of semi-random primers, e.g. primers having a structure of
5'-(M).sub.k-(X).sub.i--(N).sub.j-3', where (X).sub.i is a random
sequence of nucleotides that is i nucleotides long (the set of
primers comprising all possible combinations of (X).sub.i),
(N).sub.j is a specific nucleotide (or series of j nucleotides),
and (M).sub.k is a specific nucleotide (or series of k
nucleotides), wherein a different deoxyribonucleotide triphosphate
(dNTP) is added to each pool and incorporated into the tethered
oligonucleotides by the polymerase.
The number of stochastic barcodes conjugated to or synthesized on a
solid support can comprise at least 100, 1000, 10000, or 1000000 or
more stochastic barcodes. The number of stochastic barcodes
conjugated to or synthesized on a solid support can comprise at
most 100, 1000, 10000, or 1000000 or more stochastic barcodes. The
number of oligonucleotides conjugated to or synthesized on a solid
support such as a bead can be at least 1, 2, 3, 4, 5, 6, 7, 8, 9,
or 10-folds more than the number of target nucleic acids in a cell.
The number of oligonucleotides conjugated to or synthesized on a
solid support such as a bead can be at most 1, 2, 3, 4, 5, 6, 7, 8,
9, or 10-folds more than the number of target nucleic acids in a
cell. At least 10, 20, 30, 40, 50, 60, 70, 80, 90 or 100% of the
stochastic barcode can be bound by a target nucleic acid. At most
10, 20, 30, 40, 50, 60, 70, 80, 90 or 100% of the stochastic
barcode can be bound by a target nucleic acid. At least 1, 2, 3, 4,
5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90 or 100 or more
different target nucleic acids can be captured by the stochastic
barcode on the solid support. At most 1, 2, 3, 4, 5, 6, 7, 8, 9,
10, 20, 30, 40, 50, 60, 70, 80, 90 or 100 or more different target
nucleic acids can be captured by the stochastic barcode on the
solid support.
In some embodiments, stochastic barcodes can be synthesized by
randomly distributing a single-stranded DNA mixture onto a
substrate pre-coated with primers. The single-stranded DNA can
hybridize to the primers. Bridge amplification can be performed to
convert the single-stranded DNAs into a cluster. Sequencing can be
performed to determine the sequence of the DNA at each cluster on
the substrate. A sample can be applied to the substrate, followed
by the stochastic barcoding methods of the disclosure.
In some embodiments, barcodes can be synthesized using size and/or
electrophoretic mobility. For example, a mixture of stochastic
barcodes can be prepared and separated into two-dimensions using
gel electrophoresis. The gel can be the substrate.
Methods of Stochastic Barcoding
The disclosure provides for methods for estimating the number of
distinct targets at distinct locations in a physical sample (e.g.,
tissue, organ, tumor, cell). The methods can comprise placing the
stochastic barcodes in close proximity with the sample, lysing the
sample, associating distinct targets with the stochastic barcodes,
amplifying the targets and/or digitally counting the targets. The
method can further comprise analyzing and/or visualizing the
information obtained from the spatial labels on the stochastic
barcodes. In some embodiments, the methods comprise visualizing the
plurality of targets in the sample. Mapping the plurality of
targets onto the map of the sample can include generating a two
dimensional map or a three dimensional map of the sample. The two
dimensional map and the three dimensional map can be generated
prior to or after stochastically barcoding the plurality of targets
in the sample. Visualizing the plurality of targets in the sample
can include mapping the plurality of targets onto a map of the
sample. Mapping the plurality of targets onto the map of the sample
can include generating a two dimensional map or a three dimensional
map of the sample. The two dimensional map and the three
dimensional map can be generated prior to or after stochastically
barcoding the plurality of targets in the sample. in some
embodiments, the two dimensional map and the three dimensional map
can be generated before or after lysing the sample. Lysing the
sample before or after generating the two dimensional map or the
three dimensional map can include heating the sample, contacting
the sample with a detergent, changing the pH of the sample, or any
combination thereof.
FIG. 3 illustrates an exemplary embodiment of the stochastic
barcoding method of the disclosure. A sample (e.g., section of a
sample, thin slice, and cell) can be contacted with a solid support
comprising a stochastic barcode. Targets in the sample can be
associated with the stochastic barcodes. The solid supports can be
collected. cDNA synthesis can be performed on the solid support.
cDNA synthesis can be performed off the solid support. cDNA
synthesis can incorporate the label information from the labels in
the stochastic barcode into the new cDNA target molecule being
synthesized, thereby generating a target-barcode molecule. The
target-barcode molecules can be amplified using PCT. The sequence
of the targets and the labels of the stochastic barcode on the
target-barcode molecule can be determined by sequencing
methods.
Contacting a Sample and a Stochastic Barcode
The disclosure provides for methods for contacting a sample (e.g.,
cells) to a substrate of the disclosure. A sample comprising, for
example, a cell, organ, or tissue thin section, can be contacted to
stochastic barcodes. The cells can be contacted, for example, by
gravity flow wherein the cells can settle and create a monolayer.
The sample can be a tissue thin section. The thin section can be
placed on the substrate. The sample can be one-dimensional (e.g.,
form a planar surface). The sample (e.g., cells) can be spread
across the substrate, for example, by growing/culturing the cells
on the substrate.
When stochastic barcodes are in close proximity to targets, the
targets can hybridize to the stochastic barcode. The stochastic
barcodes can be contacted at a non-depletable ratio such that each
distinct target can associate with a distinct stochastic barcode of
the disclosure. To ensure efficient association between the target
and the stochastic barcode, the targets can be crosslinked to the
stochastic barcode.
Cell Lysis Following the distribution of cells and stochastic
barcodes, the cells can be lysed to liberate the target molecules.
Cell lysis can be accomplished by any of a variety of means, for
example, by chemical or biochemical means, by osmotic shock, or by
means of thermal lysis, mechanical lysis, or optical lysis. Cells
can be lysed by addition of a cell lysis buffer comprising a
detergent (e.g. SDS, Li dodecyl sulfate, Triton X-100, Tween-20, or
NP-40), an organic solvent (e.g. methanol or acetone), or digestive
enzymes (e.g. proteinase K, pepsin, or trypsin), or any combination
thereof. To increase the association of a target and a stochastic
barcode, the rate of the diffusion of the target molecules can be
altered by for example, reducing the temperature and/or increasing
the viscosity of the lysate.
In some embodiments, the sample can be lysed using a filter paper.
The filter paper can be soaked with a lysis buffer on top of the
filter paper. The filter paper can be applied to the sample with
pressure which can facilitate lysis of the sample and hybridization
of the targets of the sample to the substrate.
In some embodiments, lysis can be performed by mechanical lysis,
heat lysis, optical lysis, and/or chemical lysis. Chemical lysis
can include the use of digestive enzymes such as proteinase K,
pepsin, and trypsin. Lysis can be performed by the addition of a
lysis buffer to the substrate. A lysis buffer can comprise Tris
HCl. A lysis buffer can comprise at least about 0.01, 0.05, 0.1,
0.5, or 1M or more Tris HCl. A lysis buffer can comprise at most
about 0.01, 0.05, 0.1, 0.5, or 1M or more Tris HCL. A lysis buffer
can comprise about 0.1 M Tris HCl. The pH of the lysis buffer can
be at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more. The pH
of the lysis buffer can be at most about 1, 2, 3, 4, 5, 6, 7, 8, 9,
or 10 or more. In some embodiments, the pH of the lysis buffer is
about 7.5. The lysis buffer can comprise a salt (e.g., LiCl). The
concentration of salt in the lysis buffer can be at least about
0.1, 0.5, or 1M or more. The concentration of salt in the lysis
buffer can be at most about 0.1, 0.5, or 1M or more. In some
embodiments, the concentration of salt in the lysis buffer is about
0.5M. The lysis buffer can comprise a detergent (e.g., SDS, Li
dodecyl sulfate, triton X, tween, NP-40). The concentration of the
detergent in the lysis buffer can be at least about 0.0001, 0.0005,
0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1, 2, 3, 4, 5, 6, or 7% or
more. The concentration of the detergent in the lysis buffer can be
at most about 0.0001, 0.0005, 0.001, 0.005, 0.01, 0.05, 0.1, 0.5,
1, 2, 3, 4, 5, 6, or 7% or more. In some embodiments, the
concentration of the detergent in the lysis buffer is about 1% Li
dodecyl sulfate. The time used in the method for lysis can be
dependent on the amount of detergent used. In some embodiments, the
more detergent used, the less time needed for lysis. The lysis
buffer can comprise a chelating agent (e.g., EDTA, EGTA). The
concentration of a chelating agent in the lysis buffer can be at
least about 1, 5, 10, 15, 20, 25, or 30 mM or more. The
concentration of a chelating agent in the lysis buffer can be at
most about 1, 5, 10, 15, 20, 25, or 30 mM or more. In some
embodiments, the concentration of chelating agent in the lysis
buffer is about 10 mM. The lysis buffer can comprise a reducing
reagent (e.g., beta-mercaptoethanol, DTT). The concentration of the
reducing reagent in the lysis buffer can be at least about 1, 5,
10, 15, or 20 mM or more. The concentration of the reducing reagent
in the lysis buffer can be at most about 1, 5, 10, 15, or 20 mM or
more. In some embodiments, the concentration of reducing reagent in
the lysis buffer is about 5 mM. In some embodiments, a lysis buffer
can comprise about 0.1M TrisHCl, about pH 7.5, about 0.5M LiCl,
about 1% lithium dodecyl sulfate, about 10 mM EDTA, and about 5 mM
DTT.Lysis can be performed at a temperature of about 4, 10, 15, 20,
25, or 30 C. Lysis can be performed for about 1, 5, 10, 15, or 20
or more minutes. A lysed cell can comprise at least about 100000,
200000, 300000, 400000, 500000, 600000, or 700000 or more target
nucleic acid molecules. A lysed cell can comprise at most about
100000, 200000, 300000, 400000, 500000, 600000, or 700000 or more
target nucleic acid molecules.
Attachment of Stochastic Barcodes to Target Nucleic Acid
Molecules
Following lysis of the cells and release of nucleic acid molecules
therefrom, the nucleic acid molecules can randomly associate with
the stochastic barcodes of the co-localized solid support.
Association can comprise hybridization of a stochastic barcode's
target recognition region to a complementary portion of the target
nucleic acid molecule (e.g., oligo(dT) of the stochastic barcode
can interact with a poly(A) tail of a target). The assay conditions
used for hybridization (e.g. buffer pH, ionic strength,
temperature, etc.) can be chosen to promote formation of specific,
stable hybrids. In some embodiments, the nucleic acid molecules
released from the lysed cells can associate with the plurality of
probes on the substrate (e.g., hybridize with the probes on the
substrate). When the probes comprise oligo(dT), mRNA molecules can
hybridize to the probes and be reverse transcribed. The oligo(dT)
portion of the oligonucleotide can act as a primer for first strand
synthesis of the cDNA molecule.
Attachment can further comprise ligation of a stochastic barcode's
target recognition region and a portion of the target nucleic acid
molecule. For example, the target binding region can comprise a
nucleic acid sequence that can be capable of specific hybridization
to a restriction site overhang (e.g. an EcoRI sticky-end overhang).
The assay procedure can further comprise treating the target
nucleic acids with a restriction enzyme (e.g. EcoRI) to create a
restriction site overhang. The stochastic barcode can then be
ligated to any nucleic acid molecule comprising a sequence
complementary to the restriction site overhang. A ligase (e.g., T4
DNA ligase) can be used to join the two fragments.
The labeled targets from a plurality of cells (or a plurality of
samples) (e.g., target-barcode molecules) can be subsequently
pooled, for example by retrieving the stochastic barcodes and/or
the beads to which the target-barcode molecules are attached. The
retrieval of solid support-based collections of attached
target-barcode molecules can be implemented by use of magnetic
beads and an externally-applied magnetic field. Once the
target-barcode molecules have been pooled, all further processing
can proceed in a single reaction vessel. Further processing can
include, for example, reverse transcription reactions,
amplification reactions, cleavage reactions, dissociation
reactions, and/or nucleic acid extension reactions. Further
processing reactions can be performed within the microwells, that
is, without first pooling the labeled target nucleic acid molecules
from a plurality of cells.
Reverse Transcription
The disclosure provides for a method to create a stochastic
target-barcode conjugate using reverse transcription. The
stochastic target-barcode conjugate can comprise the stochastic
barcode and a complementary sequence of all or a portion of the
target nucleic acid (i.e. a stochastically barcoded cDNA molecule).
Reverse transcription of the associated RNA molecule can occur by
the addition of a reverse transcription primer along with the
reverse transcriptase. The reverse transcription primer can be an
oligo-dT primer, a random hexanucleotide primer, or a
target-specific oligonucleotide primer. Oligo-dT primers can be, or
can be about, 12-18 nucleotides in length and bind to the
endogenous poly(A) tail at the 3' end of mammalian mRNA. Random
hexanucleotide primers can bind to mRNA at a variety of
complementary sites. Target-specific oligonucleotide primers
typically selectively prime the mRNA of interest.
In some embodiments, reverse transcription of the labeled-RNA
molecule can occur by the addition of a reverse transcription
primer. In some embodiments, the reverse transcription primer is an
oligo(dT) primer, random hexanucleotide primer, or a
target-specific oligonucleotide primer. Generally, oligo(dT)
primers are 12-18 nucleotides in length and bind to the endogenous
poly(A)+ tail at the 3' end of mammalian mRNA. Random
hexanucleotide primers can bind to mRNA at a variety of
complementary sites. Target-specific oligonucleotide primers
typically selectively prime the mRNA of interest.
Reverse transcription can occur repeatedly to produce multiple
labeled-cDNA molecules. The methods disclosed herein can comprise
conducting at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, or 20 reverse transcription reactions.
The method can comprise conducting at least about 25, 30, 35, 40,
45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100 reverse
transcription reactions.
Amplification
One or more nucleic acid amplification reactions can be performed
to create multiple copies of the labeled target nucleic acid
molecules. Amplification can be performed in a multiplexed manner,
wherein multiple target nucleic acid sequences are amplified
simultaneously. The amplification reaction can be used to add
sequencing adaptors to the nucleic acid molecules. The
amplification reactions can comprise amplifying at least a portion
of a sample label, if present. The amplification reactions can
comprise amplifying at least a portion of the cellular and/or
molecular label. The amplification reactions can comprise
amplifying at least a portion of a sample tag, a cellular label, a
spatial label, a molecular label, a target nucleic acid, or a
combination thereof. The amplification reactions can comprise
amplifying 0.5%, 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%,
25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%,
90%, 95%, 97%, 100%, or a range or a number between any two of
these values, of the plurality of nucleic acids. The method can
further comprise conducting one or more cDNA synthesis reactions to
produce one or more cDNA copies of target-barcode molecules
comprising a sample label, a cellular label, a spatial label,
and/or a molecular label.
In some embodiments, amplification can be performed using a
polymerase chain reaction (PCR). As used herein, PCR can refer to a
reaction for the in vitro amplification of specific DNA sequences
by the simultaneous primer extension of complementary strands of
DNA. As used herein, PCR can encompass derivative forms of the
reaction, including but not limited to, RT-PCR, real-time PCR,
nested PCR, quantitative PCR, multiplexed PCR, digital PCR, and
assembly PCR.
Amplification of the labeled nucleic acids can comprise non-PCR
based methods. Examples of non-PCR based methods include, but are
not limited to, multiple displacement amplification (MDA),
transcription-mediated amplification (TMA), nucleic acid
sequence-based amplification (NASBA), strand displacement
amplification (SDA), real-time SDA, rolling circle amplification,
or circle-to-circle amplification. Other non-PCR-based
amplification methods include multiple cycles of DNA-dependent RNA
polymerase-driven RNA transcription amplification or RNA-directed
DNA synthesis and transcription to amplify DNA or RNA targets, a
ligase chain reaction (LCR), and a Q.beta. replicase (Q.beta.)
method, use of palindromic probes, strand displacement
amplification, oligonucleotide-driven amplification using a
restriction endonuclease, an amplification method in which a primer
is hybridized to a nucleic acid sequence and the resulting duplex
is cleaved prior to the extension reaction and amplification,
strand displacement amplification using a nucleic acid polymerase
lacking 5' exonuclease activity, rolling circle amplification, and
ramification extension amplification (RAM). In some embodiments,
the amplification does not produce circularized transcripts.
In some embodiments, the methods disclosed herein further comprise
conducting a polymerase chain reaction on the labeled nucleic acid
(e.g., labeled-RNA, labeled-DNA, labeled-cDNA) to produce a
stochastically labeled-amplicon. The labeled-amplicon can be
double-stranded molecule. The double-stranded molecule can comprise
a double-stranded RNA molecule, a double-stranded DNA molecule, or
a RNA molecule hybridized to a DNA molecule. One or both of the
strands of the double-stranded molecule can comprise a sample
label, a spatial label, a cellular label, and/or a molecular label.
The stochastically labeled-amplicon can be a single-stranded
molecule. The single-stranded molecule can comprise DNA, RNA, or a
combination thereof. The nucleic acids of the disclosure can
comprise synthetic or altered nucleic acids.
Amplification can comprise use of one or more non-natural
nucleotides. Non-natural nucleotides can comprise photolabile or
triggerable nucleotides. Examples of non-natural nucleotides can
include, but are not limited to, peptide nucleic acid (PNA),
morpholino and locked nucleic acid (LNA), as well as glycol nucleic
acid (GNA) and threose nucleic acid (TNA). Non-natural nucleotides
can be added to one or more cycles of an amplification reaction.
The addition of the non-natural nucleotides can be used to identify
products as specific cycles or time points in the amplification
reaction.
Conducting the one or more amplification reactions can comprise the
use of one or more primers. The one or more primers can comprise,
for example, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15
or more nucleotides. The one or more primers can comprise at least
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 or more
nucleotides. The one or more primers can comprise less than 12-15
nucleotides. The one or more primers can anneal to at least a
portion of the plurality of stochastically labeled targets. The one
or more primers can anneal to the 3' end or 5' end of the plurality
of stochastically labeled targets. The one or more primers can
anneal to an internal region of the plurality of stochastically
labeled targets. The internal region can be at least about 50, 100,
150, 200, 220, 230, 240, 250, 260, 270, 280, 290, 300, 310, 320,
330, 340, 350, 360, 370, 380, 390, 400, 410, 420, 430, 440, 450,
460, 470, 480, 490, 500, 510, 520, 530, 540, 550, 560, 570, 580,
590, 600, 650, 700, 750, 800, 850, 900 or 1000 nucleotides from the
3' ends the plurality of stochastically labeled targets. The one or
more primers can comprise a fixed panel of primers. The one or more
primers can comprise at least one or more custom primers. The one
or more primers can comprise at least one or more control primers.
The one or more primers can comprise at least one or more
gene-specific primers.
The one or more primers can comprise a universal primer. The
universal primer can anneal to a universal primer binding site. The
one or more custom primers can anneal to a first sample label, a
second sample label, a spatial label, a cellular label, a molecular
label, a target, or any combination thereof. The one or more
primers can comprise a universal primer and a custom primer. The
custom primer can be designed to amplify one or more targets. The
targets can comprise a subset of the total nucleic acids in one or
more samples. The targets can comprise a subset of the total
stochastically labeled targets in one or more samples. The one or
more primers can comprise at least 96 or more custom primers. The
one or more primers can comprise at least 960 or more custom
primers. The one or more primers can comprise at least 9600 or more
custom primers. The one or more custom primers can anneal to two or
more different labeled nucleic acids. The two or more different
labeled nucleic acids can correspond to one or more genes.
Any amplification scheme can be used in the methods of the present
disclosure. For example, in one scheme, the first round PCR can
amplify molecules attached to the bead using a gene specific primer
and a primer against the universal Illumina sequencing primer 1
sequence. The second round of PCR can amplify the first PCR
products using a nested gene specific primer flanked by Illumina
sequencing primer 2 sequence, and a primer against the universal
Illumina sequencing primer 1 sequence. The third round of PCR adds
P5 and P7 and sample index to turn PCR products into an Illumina
sequencing library. Sequencing using 150 bp.times.2 sequencing can
reveal the cellular label and molecular index on read 1, the gene
on read 2, and the sample index on index 1 read.
In some embodiments, nucleic acids can be removed from the
substrate using chemical cleavage. For example, a chemical group or
a modified base present in a nucleic acid can be used to facilitate
its removal from a solid support. For example, an enzyme can be
used to remove a nucleic acid from a substrate. For example, a
nucleic acid can be removed from a substrate through a restriction
endonuclease digestion. For example, treatment of a nucleic acid
containing a dUTP or ddUTP with uracil-d-glycosylase (UDG) can be
used to remove a nucleic acid from a substrate. For example, a
nucleic acid can be removed from a substrate using an enzyme that
performs nucleotide excision, such as a base excision repair
enzyme, such as an apurinic/apyrimidinic (AP) endonuclease. In some
embodiments, a nucleic acid can be removed from a substrate using a
photocleavable group and light. In some embodiments, a cleavable
linker can be used to remove a nucleic acid from the substrate. For
example, the cleavable linker can comprise at least one of
biotin/avidin, biotin/streptavidin, biotin/neutravidin, Ig-protein
A, a photo-labile linker, acid or base labile linker group, or an
aptamer.
When the probes are gene-specific, the molecules can hybridize to
the probes and be reverse transcribed and/or amplified. In some
embodiments, after the nucleic acid has been synthesized (e.g.,
reverse transcribed), it can be amplified. Amplification can be
performed in a multiplex manner, wherein multiple target nucleic
acid sequences are amplified simultaneously. Amplification can add
sequencing adaptors to the nucleic acid.
In some embodiments, amplification can be performed on the
substrate, for example, with bridge amplification. cDNAs can be
homopolymer tailed in order to generate a compatible end for bridge
amplification using oligo(dT) probes on the substrate. In bridge
amplification, the primer that is complementary to the 3' end of
the template nucleic acid can be the first primer of each pair that
is covalently attached to the solid particle. When a sample
containing the template nucleic acid is contacted with the particle
and a single thermal cycle is performed, the template molecule can
be annealed to the first primer and the first primer is elongated
in the forward direction by addition of nucleotides to form a
duplex molecule consisting of the template molecule and a newly
formed DNA strand that is complementary to the template. In the
heating step of the next cycle, the duplex molecule can be
denatured, releasing the template molecule from the particle and
leaving the complementary DNA strand attached to the particle
through the first primer. In the annealing stage of the annealing
and elongation step that follows, the complementary strand can
hybridize to the second primer, which is complementary to a segment
of the complementary strand at a location removed from the first
primer. This hybridization can cause the complementary strand to
form a bridge between the first and second primers secured to the
first primer by a covalent bond and to the second primer by
hybridization. In the elongation stage, the second primer can be
elongated in the reverse direction by the addition of nucleotides
in the same reaction mixture, thereby converting the bridge to a
double-stranded bridge. The next cycle then begins, and the
double-stranded bridge can be denatured to yield two
single-stranded nucleic acid molecules, each having one end
attached to the particle surface via the first and second primers,
respectively, with the other end of each unattached. In the
annealing and elongation step of this second cycle, each strand can
hybridize to a further complementary primer, previously unused, on
the same particle, to form new single-strand bridges. The two
previously unused primers that are now hybridized elongate to
convert the two new bridges to double-strand bridges.
The amplification reactions can comprise amplifying at least 1%,
2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%,
45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 97%, or 100%
of the plurality of nucleic acids.
Amplification of the labeled nucleic acids can comprise PCR-based
methods or non-PCR based methods. Amplification of the labeled
nucleic acids can comprise exponential amplification of the labeled
nucleic acids. Amplification of the labeled nucleic acids can
comprise linear amplification of the labeled nucleic acids.
Amplification can be performed by polymerase chain reaction (PCR).
PCR can refer to a reaction for the in vitro amplification of
specific DNA sequences by the simultaneous primer extension of
complementary strands of DNA. PCR can encompass derivative forms of
the reaction, including but not limited to, RT-PCR, real-time PCR,
nested PCR, quantitative PCR, multiplexed PCR, digital PCR,
suppression PCR, semi-suppressive PCR and assembly PCR.
In some embodiments, amplification of the labeled nucleic acids
comprises non-PCR based methods. Examples of non-PCR based methods
include, but are not limited to, multiple displacement
amplification (MDA), transcription-mediated amplification (TMA),
nucleic acid sequence-based amplification (NASBA), strand
displacement amplification (SDA), real-time SDA, rolling circle
amplification, or circle-to-circle amplification. Other
non-PCR-based amplification methods include multiple cycles of
DNA-dependent RNA polymerase-driven RNA transcription amplification
or RNA-directed DNA synthesis and transcription to amplify DNA or
RNA targets, a ligase chain reaction (LCR), a Q.beta. replicase
(Q.beta.), use of palindromic probes, strand displacement
amplification, oligonucleotide-driven amplification using a
restriction endonuclease, an amplification method in which a primer
is hybridized to a nucleic acid sequence and the resulting duplex
is cleaved prior to the extension reaction and amplification,
strand displacement amplification using a nucleic acid polymerase
lacking 5' exonuclease activity, rolling circle amplification,
and/or ramification extension amplification (RAM).
In some embodiments, the methods disclosed herein further comprise
conducting a nested polymerase chain reaction on the amplified
amplicon (e.g., target). The amplicon can be double-stranded
molecule. The double-stranded molecule can comprise a
double-stranded RNA molecule, a double-stranded DNA molecule, or a
RNA molecule hybridized to a DNA molecule. One or both of the
strands of the double-stranded molecule can comprise a sample tag
or molecular identifier label. Alternatively, the amplicon can be a
single-stranded molecule. The single-stranded molecule can comprise
DNA, RNA, or a combination thereof. The nucleic acids of the
present invention can comprise synthetic or altered nucleic
acids.
In some embodiments, the method comprises repeatedly amplifying the
labeled nucleic acid to produce multiple amplicons. The methods
disclosed herein can comprise conducting at least about 1, 2, 3, 4,
5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20
amplification reactions. Alternatively, the method comprises
conducting at least about 25, 30, 35, 40, 45, 50, 55, 60, 65, 70,
75, 80, 85, 90, 95, or 100 amplification reactions.
Amplification can further comprise adding one or more control
nucleic acids to one or more samples comprising a plurality of
nucleic acids. Amplification can further comprise adding one or
more control nucleic acids to a plurality of nucleic acids. The
control nucleic acids can comprise a control label.
Amplification can comprise use of one or more non-natural
nucleotides. Non-natural nucleotides can comprise photolabile
and/or triggerable nucleotides. Examples of non-natural nucleotides
include, but are not limited to, peptide nucleic acid (PNA),
morpholino and locked nucleic acid (LNA), as well as glycol nucleic
acid (GNA) and threose nucleic acid (TNA). Non-natural nucleotides
can be added to one or more cycles of an amplification reaction.
The addition of the non-natural nucleotides can be used to identify
products as specific cycles or time points in the amplification
reaction.
Conducting the one or more amplification reactions can comprise the
use of one or more primers. The one or more primers can comprise
one or more oligonucleotides. The one or more oligonucleotides can
comprise at least about 7-9 nucleotides. The one or more
oligonucleotides can comprise less than 12-15 nucleotides. The one
or more primers can anneal to at least a portion of the plurality
of labeled nucleic acids. The one or more primers can anneal to the
3' end and/or 5' end of the plurality of labeled nucleic acids. The
one or more primers can anneal to an internal region of the
plurality of labeled nucleic acids. The internal region can be at
least about 50, 100, 150, 200, 220, 230, 240, 250, 260, 270, 280,
290, 300, 310, 320, 330, 340, 350, 360, 370, 380, 390, 400, 410,
420, 430, 440, 450, 460, 470, 480, 490, 500, 510, 520, 530, 540,
550, 560, 570, 580, 590, 600, 650, 700, 750, 800, 850, 900 or 1000
nucleotides from the 3' ends the plurality of labeled nucleic
acids. The one or more primers can comprise a fixed panel of
primers. The one or more primers can comprise at least one or more
custom primers. The one or more primers can comprise at least one
or more control primers. The one or more primers can comprise at
least one or more housekeeping gene primers. The one or more
oligonucleotides can comprise a sequence selected from a group
consisting of sequences in Table 23. The one or more primers can
comprise a universal primer. The universal primer can anneal to a
universal primer binding site. The one or more custom primers can
anneal to the first sample tag, the second sample tag, the
molecular identifier label, the nucleic acid or a product thereof.
The one or more primers can comprise a universal primer and a
custom primer. The custom primer can be designed to amplify one or
more target nucleic acids. The target nucleic acids can comprise a
subset of the total nucleic acids in one or more samples. In some
embodiments, the primers are the probes attached to the array of
the disclosure.
In some embodiments, stochastically barcoding the plurality of
targets in the sample further comprises generating an indexed
library of the stochastically barcoded targets. The molecular
labels of different stochastic barcodes can be different from one
another. Generating an indexed library of the stochastically
barcoded targets includes generating a plurality of indexed
polynucleotides from the plurality of targets in the sample. For
example, for an indexed library of the stochastically barcoded
targets comprising a first indexed target and a second indexed
target, the label region of the first indexed polynucleotide can
differ from the label region of the second indexed polynucleotide
by at least one, two, three, four, or five nucleotides. In some
embodiments, generating an indexed library of the stochastically
barcoded targets includes contacting a plurality of targets, for
example mRNA molecules, with a plurality of oligonucleotides
including a poly(T) region and a label region; and conducting a
first strand synthesis using a reverse transcriptase to produce
single-strand labeled cDNA molecules each comprising a cDNA region
and a label region, wherein the plurality of targets includes at
least two mRNA molecules of different sequences and the plurality
of oligonucleotides includes at least two oligonucleotides of
different sequences. Generating an indexed library of the
stochastically barcoded targets can further comprise amplifying the
single-strand labeled cDNA molecules to produce double-strand
labeled cDNA molecules; and conducting nested PCR on the
double-strand labeled cDNA molecules to produce labeled amplicons.
In some embodiments, the method can include generating an
adaptor-labeled amplicon.
Stochastic barcoding can use nucleic acid barcodes or tags to label
individual nucleic acid (e.g., DNA or RNA) molecules. In some
embodiments, it involves adding DNA barcodes or tags to cDNA
molecules as they are generated from mRNA. Nested PCR can be
performed to minimize PCR amplification bias. Adaptors can be added
for sequencing using, for example, next generation sequencing
(NGS).
FIG. 4 is a schematic illustration showing a non-limiting exemplary
process of generating an indexed library of the stochastically
barcoded targets, for example mRNAs. As shown in step 1, the
reverse transcription process can encode each mRNA molecule with a
unique molecular label, a spatial label, and a universal PCR site.
In particular, RNA molecules 402 can be reverse transcribed to
produce labeled cDNA molecules 404, including a cDNA region 406, by
the stochastic hybridization of a set of molecular identifier
labels 410 to the poly(A) tail region 408 of the RNA molecules 402.
Each of the molecular identifier labels 410 can comprise a
target-binding region, for example a poly (dT) region 412, a label
region 414, and a universal PCR region 416.
In some embodiments, the spatial label can include 3 to 20
nucleotides. In some embodiments, the molecular label can include 3
to 20 nucleotides. In some embodiments, each of the plurality of
stochastic barcodes further comprises one or more of a universal
label and a cellular label, wherein universal labels are the same
for the plurality of stochastic barcodes on the solid support and
cellular labels are the same for the plurality of stochastic
barcodes on the solid support. In some embodiments, the universal
label can include 3 to 20 nucleotides. In some embodiments, the
cellular label comprises 3 to 20 nucleotides.
In some embodiments, the label region 414 can include a molecular
label 418 and a spatial label 420. In some embodiments, the label
region 414 can include one or more of a universal label, a
dimension label, and a cellular label. The molecular label 418 can
be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50,
60, 70, 80, 90, 100, or a number or a range between any of these
values, of nucleotides in length. The spatial label 420 can be, or
can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60,
70, 80, 90, 100, or a number or a range between any of these
values, of nucleotides in length. The universal label can be, or
can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60,
70, 80, 90, 100, or a number or a range between any of these
values, of nucleotides in length. Universal labels can be the same
for the plurality of stochastic barcodes on the solid support and
cellular labels are the same for the plurality of stochastic
barcodes on the solid support. The dimension label can be, or can
be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70,
80, 90, 100, or a number or a range between any of these values, of
nucleotides in length.
In some embodiments, the label region 414 can comprise 1, 2, 3, 4,
5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300,
400, 500, 600, 700, 800, 900, 1000, or a number or a range between
any of these values, different labels, such as a molecular label
418 and a spatial label 420. Each label can be, or can be about, 1,
2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or
a number or a range between any of these values, of nucleotides in
length. A set of molecular identifier labels 410 can contain 10,
20, 40, 50, 70, 80, 90, 10.sup.2, 10.sup.3, 10.sup.4, 10.sup.5,
10.sup.6, 10.sup.7, 10.sup.8, 10.sup.9, 10.sup.10, 10.sup.11,
10.sup.12, 10.sup.13, 10.sup.14, 10.sup.15, 10.sup.20, or a number
or a range between any of these values, molecular identifier labels
410. And the set of molecular identifier labels 410 can, for
example, each contain a unique label region 414. The labeled cDNA
molecules 404 can be purified to remove excess molecular identifier
labels 410. Purification can comprise Ampure bead purification.
As shown in step 2, products from the reverse transcription process
in step 1 can be pooled into 1 tube and PCR amplified with a
1.sup.st PCR primer pool and a 1.sup.st universal PCR primer.
Pooling is possible because of the unique label region 414. In
particular, the labeled cDNA molecules 404 can be amplified to
produce nested PCR labeled amplicons 422. Amplification can
comprise multiplex PCR amplification. Amplification can comprise a
multiplex PCR amplification with 96 multiplex primers in a single
reaction volume. In some embodiments, multiplex PCR amplification
can utilize 10, 20, 40, 50, 70, 80, 90, 10.sup.2, 10.sup.3,
10.sup.4, 10.sup.5, 10.sup.6, 10.sup.7, 10.sup.8, 10.sup.9,
10.sup.10, 10.sup.11, 10.sup.12, 10.sup.13, 10.sup.14, 10.sup.15,
10.sup.20, or a number or a range between any of these values,
multiplex primers in a single reaction volume. Amplification can
comprise 1.sup.st PCR primer pool 424 of custom primers 426A-C
targeting specific genes and a universal primer 428. The custom
primers 426 can hybridize to a region within the cDNA portion 406'
of the labeled cDNA molecule 404. The universal primer 428 can
hybridize to the universal PCR region 416 of the labeled cDNA
molecule 404.
As shown in step 3 of FIG. 4, products from PCR amplification in
step 2 can be amplified with a nested PCR primers pool and a
2.sup.nd universal PCR primer. Nested PCR can minimize PCR
amplification bias. In particular, the nested PCR labeled amplicons
422 can be further amplified by nested PCR. The nested PCR can
comprise multiplex PCR with nested PCR primers pool 430 of nested
PCR primers 432A-C and a 2.sup.nd universal PCR primer 428' in a
single reaction volume. The nested PCR primer pool 428 can contain,
or contain about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50,
60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000,
or a number or a range between any of these values, different
nested PCR primers 430. The nested PCR primers 432 can contain an
adaptor 434 and hybridize to a region within the cDNA portion 406''
of the labeled amplicon 422. The universal primer 428' can contain
an adaptor 436 and hybridize to the universal PCR region 416 of the
labeled amplicon 422. Thus, step 3 produces adaptor-labeled
amplicon 438. In some embodiments, nested PCR primers 432 and the
2.sup.nd universal PCR primer 428' may not contain the adaptors 434
and 436. The adaptors 434 and 436 can instead be ligated to the
products of nested PCR to produce adaptor-labeled amplicon 438.
As shown in step 4, PCR products from step 3 can be PCR amplified
for sequencing using library amplification primers. In particular,
the adaptors 434 and 436 can be used to conduct one or more
additional assays on the adaptor-labeled amplicon 438. The adaptors
434 and 436 can be hybridized to primers 440 and 442. The one or
more primers 440 and 442 can be PCR amplification primers. The one
or more primers 440 and 442 can be sequencing primers. The one or
more adaptors 434 and 436 can be used for further amplification of
the adaptor-labeled amplicons 438. The one or more adaptors 434 and
436 can be used for sequencing the adaptor-labeled amplicon 438.
The primer 442 can contain a plate index 444 so that amplicons
generated using the same set of molecular identifier labels 408 can
be sequenced in one sequencing reaction using NGS.
Sequencing
In some embodiments, estimating the number of the plurality of
targets using the molecular label includes determining sequences of
the spatial labels and molecular labels of the plurality of the
stochastic labels and counting the number of the molecular labels
with distinct sequences. Determining the sequences of the spatial
labels and the molecular labels of the plurality of the stochastic
barcodes can include sequencing some or all of the plurality of
stochastic barcodes. Sequencing some or all of the plurality of
stochastic barcodes can include generating sequences each with a
read length of 100 or more bases.
Determining the number of different stochastically labeled nucleic
acids can comprise determining the sequence of the labeled target,
the spatial label, the molecular label, the sample label, and the
cellular label or any product thereof (e.g. labeled-amplicons,
labeled-cDNA molecules). An amplified target can be subjected to
sequencing. Determining the sequence of the stochastically labeled
nucleic acid or any product thereof can comprise conducting a
sequencing reaction to determine the sequence of at least a portion
of a sample label, a spatial label, a cellular label, a molecular
label, at least a portion of the stochastically labeled target, a
complement thereof, a reverse complement thereof, or any
combination thereof.
Determination of the sequence of a nucleic acid (e.g. amplified
nucleic acid, labeled nucleic acid, cDNA copy of a labeled nucleic
acid, etc.) can be performed using variety of sequencing methods
including, but not limited to, sequencing by hybridization (SBH),
sequencing by ligation (SBL), quantitative incremental fluorescent
nucleotide addition sequencing (QIFNAS), stepwise ligation and
cleavage, fluorescence resonance energy transfer (FRET), molecular
beacons, TaqMan reporter probe digestion, pyrosequencing,
fluorescent in situ sequencing (FISSEQ), FISSEQ beads, wobble
sequencing, multiplex sequencing, polymerized colony (POLONY)
sequencing; nanogrid rolling circle sequencing (ROLONY),
allele-specific oligo ligation assays (e.g., oligo ligation assay
(OLA), single template molecule OLA using a ligated linear probe
and a rolling circle amplification (RCA) readout, ligated padlock
probes, or single template molecule OLA using a ligated circular
padlock probe and a rolling circle amplification (RCA) readout),
and the like.
In some embodiments, determining the sequence of the labeled
nucleic acid or any product thereof comprises paired-end
sequencing, nanopore sequencing, high-throughput sequencing,
shotgun sequencing, dye-terminator sequencing, multiple-primer DNA
sequencing, primer walking, Sanger dideoxy sequencing,
Maxim-Gilbert sequencing, pyrosequencing, true single molecule
sequencing, or any combination thereof. Alternatively, the sequence
of the labeled nucleic acid or any product thereof can be
determined by electron microscopy or a chemical-sensitive field
effect transistor (chemFET) array.
High-throughput sequencing methods, such as cyclic array sequencing
using platforms such as Roche 454, Illumina Solexa, ABI-SOLiD, ION
Torrent, Complete Genomics, Pacific Bioscience, Helicos, or the
Polonator platform, can also be utilized. In some embodiment,
sequencing can comprise MiSeq sequencing. In some embodiment,
sequencing can comprise HiSeq sequencing.
The stochastically labeled targets can comprise nucleic acids
representing from about 0.01% of the genes of an organism's genome
to about 100% of the genes of an organism's genome. For example,
about 0.01% of the genes of an organism's genome to about 100% of
the genes of an organism's genome can be sequenced using a target
complimentary region comprising a plurality of multimers by
capturing the genes containing a complimentary sequence from the
sample. In some embodiments, the labeled nucleic acids comprise
nucleic acids representing from about 0.01% of the transcripts of
an organism's transcriptome to about 100% of the transcripts of an
organism's transcriptome. For example, about 0.501% of the
transcripts of an organism's transcriptome to about 100% of the
transcripts of an organism's transcriptome can be sequenced using a
target complimentary region comprising a poly-T tail by capturing
the mRNAs from the sample.
Determining the sequences of the spatial labels and the molecular
labels of the plurality of the stochastic barcodes can include
sequencing 0.00001%, 0.0001%, 0.001%, 0.01%, 0.1%, 1%, 2%, 3%, 4%,
5%, 6%, 7%, 8%, 9%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%,
99%, 100%, or any number or range between two of these values, of
the plurality of stochastic barcodes. Determining the sequences of
the spatial labels and the molecular labels of the plurality of the
stochastic barcodes can include sequencing 1, 10, 20, 30, 40, 50,
60, 70, 80, 90, 100, 10.sup.3, 10.sup.4, 10.sup.5, 10.sup.6,
10.sup.7, 10.sup.8, 10.sup.9, 10.sup.10, 10.sup.11, 10.sup.12,
10.sup.13, 10.sup.14, 10.sup.15, 10.sup.16, 10.sup.17, 10.sup.18,
10.sup.19, 10.sup.20, or any number or range between two of these
values, of the plurality of stochastic barcodes. Sequencing some or
all of the plurality of stochastic barcodes can include generating
sequences each with a read length of 10, 20, 30, 40, 50, 60, 70,
80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000,
3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, or any number or
range between two of these values, of nucleotides or bases.
Sequencing can comprise sequencing at least about 10, 20, 30, 40,
50, 60, 70, 80, 90, 100 or more nucleotides or base pairs of the
labeled nucleic acid. Sequencing can comprise sequencing at least
about 200, 300, 400, 500, 600, 700, 800, 900, 1,000 or more
nucleotides or base pairs of the labeled nucleic acid. Sequencing
can comprise sequencing at least about 1,500; 2,000; 3,000; 4,000;
5,000; 6,000; 7,000; 8,000; 9,000; or 10,000 or more nucleotides or
base pairs of the labeled nucleic acid.
Sequencing can comprise at least about 200, 300, 400, 500, 600,
700, 800, 900, 1,000 or more sequencing reads per run. In some
embodiments, sequencing comprises sequencing at least about 1,500;
2,000; 3,000; 4,000; 5,000; 6,000; 7,000; 8,000; 9,000; or 10,000
or more sequencing reads per run. Sequencing can comprise less than
or equal to about 1,600,000,000 sequencing reads per run.
Sequencing can comprise less than or equal to about 200,000,000
reads per run.
Samples
A sample for use in the method of the disclosure can comprise one
or more cells. A sample can refer to one or more cells. In some
embodiments, the plurality of cells can include one or more cell
types. At least one of the one or more cell types can be brain
cell, heart cell, cancer cell, circulating tumor cell, organ cell,
epithelial cell, metastatic cell, benign cell, primary cell,
circulatory cell, or any combination thereof. In some embodiments,
the cells are cancer cells excised from a cancerous tissue, for
example, breast cancer, lung cancer, colon cancer, prostate cancer,
ovarian cancer, pancreatic cancer, brain cancer, melanoma and
non-melanoma skin cancers, and the like. In some embodiments, the
cells are derived from a cancer but collected from a bodily fluid
(e.g. circulating tumor cells). Non-limiting examples of cancers
can include, adenoma, adenocarcinoma, squamous cell carcinoma,
basal cell carcinoma, small cell carcinoma, large cell
undifferentiated carcinoma, chondrosarcoma, and fibrosarcoma. The
sample can include a tissue, a cell monolayer, fixed cells, a
tissue section, or any combination thereof. The sample can include
a biological sample, a clinical sample, an environmental sample, a
biological fluid, a tissue, or a cell from a subject. The sample
can be obtained from a human, a mammal, a dog, a rat, a mouse, a
fish, a fly, a worm, a plant, a fungus, a bacterium, a virus, a
vertebrate, or an invertebrate.
In some embodiments, the cells are cells that have been infected
with virus and contain viral oligonucleotides. In some embodiments,
the viral infection can be caused by a virus selected from the
group consisting of double-stranded DNA viruses (e.g. adenoviruses,
herpes viruses, pox viruses), single-stranded (+ strand or "sense")
DNA viruses (e.g. parvoviruses), double-stranded RNA viruses (e.g.
reoviruses), single-stranded (+ strand or sense) RNA viruses (e.g.
picornaviruses, togaviruses), single-stranded (- strand or
antisense) RNA viruses (e.g. orthomyxoviruses, rhabdoviruses),
single-stranded ((+ strand or sense) RNA viruses with a DNA
intermediate in their life-cycle) RNA-RT viruses (e.g.
retroviruses), and double-stranded DNA-RT viruses (e.g.
hepadnaviruses). Exemplary viruses can include, but are not limited
to, SARS, HIV, coronaviruses, Ebola, Malaria, Dengue, Hepatitis C,
Hepatitis B, and Influenza.
In some embodiments, the cells are bacteria. These can include
either gram-positive or gram-negative bacteria. Examples of
bacteria that can be analyzed using the disclosed methods, devices,
and systems include, but are not limited to, Actinomedurae,
Actinomyces israelii, Bacillus anthracis, Bacillus cereus,
Clostridium botulinum, Clostridium difficile, Clostridium
perfringens, Clostridium tetani, Corynebacterium, Enterococcus
faecalis, Listeria monocytogenes, Nocardia, Propionibacterium
acnes, Staphylococcus aureus, Staphylococcus epiderm, Streptococcus
mutans, Streptococcus pneumoniae and the like. Gram negative
bacteria include, but are not limited to, Afipia felis,
Bacteroides, Bartonella bacilliformis, Bortadella pertussis,
Borrelia burgdorferi, Borrelia recurrentis, Brucella,
Calymmatobacterium granulomatis, Campylobacter, Escherichia coli,
Francisella tularensis, Gardnerella vaginalis, Haemophilius
aegyptius, Haemophilius ducreyi, Haemophilius influenziae,
Heliobacter pylori, Legionella pneumophila, Leptospira interrogans,
Neisseria meningitidia, Porphyromonas gingivalis, Providencia
sturti, Pseudomonas aeruginosa, Salmonella enteridis, Salmonella
typhi, Serratia marcescens, Shigella boydii, Streptobacillus
moniliformis, Streptococcus pyogenes, Treponema pallidum, Vibrio
cholerae, Yersinia enterocolitica, Yersinia pestis and the like.
Other bacteria can include Myobacterium avium, Myobacterium leprae,
Myobacterium tuberculosis, Bartonella henseiae, Chlamydia psittaci,
Chlamydia trachomatis, Coxiella burnetii, Mycoplasma pneumoniae,
Rickettsia akari, Rickettsia prowazekii, Rickettsia rickettsii,
Rickettsia tsutsugamushi, Rickettsia typhi, Ureaplasma urealyticum,
Diplococcus pneumoniae, Ehrlichia chafensis, Enterococcus faecium,
Meningococci and the like.
In some embodiments, the cells are fungi. Non-limiting examples of
fungi that can be analyzed using the disclosed methods, devices,
and systems include, but are not limited to, Aspergilli, Candidae,
Candida albicans, Coccidioides immitis, Cryptococci, and
combinations thereof.
In some embodiments, the cells are protozoans or other parasites.
Examples of parasites to be analyzed using the methods, devices,
and systems of the present disclosure include, but are not limited
to, Balantidium coli, Cryptosporidium parvum, Cyclospora
cayatanensis, Encephalitozoa, Entamoeba histolytica, Enterocytozoon
bieneusi, Giardia lamblia, Leishmaniae, Plasmodii, Toxoplasma
gondii, Trypanosomae, trapezoidal amoeba, worms (e.g., helminthes),
particularly parasitic worms including, but not limited to,
Nematoda (roundworms, e.g., whipworms, hookworms, pinworms,
ascarids, filarids and the like), Cestoda (e.g., tapeworms).
As used herein, the term "cell" can refer to one or more cells. In
some embodiments, the cells are normal cells, for example, human
cells in different stages of development, or human cells from
different organs or tissue types (e.g. white blood cells, red blood
cells, platelets, epithelial cells, endothelial cells, neurons,
glial cells, fibroblasts, skeletal muscle cells, smooth muscle
cells, gametes, or cells from the heart, lungs, brain, liver,
kidney, spleen, pancreas, thymus, bladder, stomach, colon, small
intestine). In some embodiments, the cells can be undifferentiated
human stem cells, or human stem cells that have been induced to
differentiate. In some embodiments, the cells can be fetal human
cells. The fetal human cells can be obtained from a mother pregnant
with the fetus. In some embodiments, the cells are rare cells. A
rare cell can be, for example, a circulating tumor cell (CTC),
circulating epithelial cell, circulating endothelial cell,
circulating endometrial cell, circulating stem cell, stem cell,
undifferentiated stem cell, cancer stem cell, bone marrow cell,
progenitor cell, foam cell, mesenchymal cell, trophoblast, immune
system cell (host or graft), cellular fragment, cellular organelle
(e.g. mitochondria or nuclei), pathogen infected cell, and the
like.
In some embodiments, the cells are non-human cells, for example,
other types of mammalian cells (e.g. mouse, rat, pig, dog, cow, or
horse). In some embodiments, the cells are other types of animal or
plant cells. In other embodiments, the cells can be any prokaryotic
or eukaryotic cells.
In some embodiments, a first cell sample is obtained from a person
not having a disease or condition, and a second cell sample is
obtained from a person having the disease or condition. In some
embodiments, the persons are different. In some embodiments, the
persons are the same but cell samples are taken at different time
points. In some embodiments, the persons are patients, and the cell
samples are patient samples. The disease or condition can be a
cancer, a bacterial infection, a viral infection, an inflammatory
disease, a neurodegenerative disease, a fungal disease, a parasitic
disease, a genetic disorder, or any combination thereof.
In some embodiments, cells suitable for use in the presently
disclosed methods can range in size from about 2 micrometers to
about 100 micrometers in diameter. In some embodiments, the cells
can have diameters of at least 2 micrometers, at least 5
micrometers, at least 10 micrometers, at least 15 micrometers, at
least 20 micrometers, at least 30 micrometers, at least 40
micrometers, at least 50 micrometers, at least 60 micrometers, at
least 70 micrometers, at least 80 micrometers, at least 90
micrometers, or at least 100 micrometers. In some embodiments, the
cells can have diameters of at most 100 micrometers, at most 90
micrometers, at most 80 micrometers, at most 70 micrometers, at
most 60 micrometers, at most 50 micrometers, at most 40
micrometers, at most 30 micrometers, at most 20 micrometers, at
most 15 micrometers, at most 10 micrometers, at most 5 micrometers,
or at most 2 micrometers. The cells can have a diameter of any
value within a range, for example from about 5 micrometers to about
85 micrometers. In some embodiments, the cells have diameters of
about 10 micrometers.
In some embodiments the cells are sorted prior to associating a
cell with a bead. For example the cells can be sorted by
fluorescence-activated cell sorting or magnetic-activated cell
sorting, or more generally by flow cytometry. The cells can be
filtered by size. In some embodiments a retentate contains the
cells to be associated with the bead. In some embodiments the flow
through contains the cells to be associated with the bead.
A sample can refer to a plurality of cells. The sample can refer to
a monolayer of cells. The sample can refer to a thin section (e.g.,
tissue thin section). The sample can refer to a solid or semi-solid
collection of cells that can be place in one dimension on an
array.
Resolution of Spatial Labels
The methods of the disclosure relate to the relationship between
the resolution of spatial labels and the size and/or spacing of the
stochastic barcodes (e.g., cells). When samples are larger the
spacing of spatial labels, the resolution of targets in the sample
can be higher. When samples are smaller than the spacing of spatial
labels the resolution of the location of targets in the sample can
be lower.
The stochastic barcodes can be spaced at a distance at least 5, 10,
15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95,
or 100% of the longest dimension of the sample. The stochastic
barcodes can be spaced at a distance at most 5, 10, 15, 20, 25, 30,
35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100% of the
longest dimension of the sample. The stochastic barcodes can be
spaced at a distance at least 5, 10, 15, 20, 25, 30, 35, 40, 45,
50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100% of the shortest
dimension of the sample. The stochastic barcodes can be spaced at a
distance at most 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65,
70, 75, 80, 85, 90, 95, or 100% of the shortest dimension of the
sample.
A sample can associate with one or more types of stochastic
barcodes, wherein each type of stochastic barcode comprises a
different spatial label. A sample can associate with at least 1, 2,
3, 4, 5, 6, 7, 8, 9, or 10 or more types of stochastic barcodes
(e.g., different spatial labels). A sample can associate with at
most 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more types of stochastic
barcodes (e.g., different spatial labels). The number of types of
stochastic barcodes to which a sample can associate with can be
related to the spacing of the barcodes relative to the size of the
sample.
In some embodiments, the methods of the disclosure relate to the
relationship between the resolution of spatial labels and the
spacing of the samples. When samples are spaced far apart (e.g., on
a substrate), the spatial resolution of the targets in the sample
can be higher because diffusion between samples may not contaminate
the samples. When samples are spaced close together (e.g., on a
substrate), the spatial resolution of the targets in the sample can
be lower because diffusion of targets between the samples can
contaminate a neighboring sample.
The samples can be spaced at least 1, 100, 200, 300, 400, 500, 600,
700, 800, 900 or more micrometers apart. The samples can be spaced
at most 1, 100, 200, 300, 400, 500, 600, 700, 800, 900 or more
micrometers apart. The samples can be spaced at least 1, 100, 200,
300, 400, 500, 600, 700, 800, 900 or more millimeters apart. The
samples can be spaced at most 1, 100, 200, 300, 400, 500, 600, 700,
800, 900 or more millimeters apart. The samples can be spaced at
least 1, 100, 200, 300, 400, 500, 600, 700, 800, 900 or more meters
apart. The samples can be spaced at most 1, 100, 200, 300, 400,
500, 600, 700, 800, 900 or more meters apart.
Targets from a sample can diffuse at least 1, 2, 3, 4, 5, 6, 7, 8,
9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85,
90, 95, or 100 or more nanometers. Targets from a sample can
diffuse at most 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35,
40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100 or more
nanometers. Targets from a sample can diffuse at least 0.1, 0.2,
0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, or 1 or more millimeters.
Targets from a sample can diffuse at most 0.1, 0.2, 0.3, 0.4, 0.5,
0.6, 0.7, 0.8, 0.9, or 1 or more millimeters.
Methods for Spatial Identification of a Nucleic Acid in a
Sample
Disclosed herein are methods for determining spatial locations of a
plurality of targets in a sample. In some embodiments, the methods
include: imaging the sample to generate a sample image;
stochastically barcoding the plurality of targets in the sample
using a plurality of stochastic barcodes to generate stochastically
barcoded targets, wherein each of the plurality of stochastic
barcodes comprises a spatial label; and identifying the spatial
location of each of the plurality of targets using the spatial
label. Identifying the spatial location of each of the plurality of
targets using the spatial label can include correlating the sample
image with the spatial labels of the plurality of targets in the
sample. Imaging the sample can include staining the sample with a
stain, wherein the stain is a fluorescent stain, a negative stain,
an antibody stain, or any combination thereof. Imaging the sample
can include imaging the sample using optical microscopy, electron
microscopy, confocal microscopy, fluorescence microscopy, or any
combination thereof. Correlating the sample image with the spatial
labels of the plurality of targets in the sample can include
overlaying the sample image with the spatial labels of the
plurality of targets in the sample. The sample can include a
biological sample, a clinical sample, an environmental sample, a
biological fluid, a tissue, or a cell from a subject. In some
embodiments, the methods can include determining genotype,
phenotype, or one or more genetic mutations of the subject based on
the spatial labels of the plurality of targets in the sample. In
some embodiments, the methods can include predicting susceptibility
of the subject to one or more diseases. At least one of the one or
more diseases can be cancer or a hereditary disease. The sample can
include a plurality of cells and the plurality of targets can be
associated with the plurality of cells. The plurality of cells can
include one or more cell types. In some embodiments, the methods
can include determining cell types of the plurality of cells in the
sample. The drug can be chosen based on predicted responsiveness of
the cell types of the plurality of cells in the sample.
Imaging
The sample contacted to the substrate can be analyzed (e.g., with
immunohistochemistry, staining and/or imaging). Exemplary methods
of immunohistochemistry can comprise a step of reacting a labeled
probe biological substance obtained by introducing a label into a
substance capable of recognizing a biological substance to be
detected to a tissue section, to visualize the biological substance
to be detected present on the tissue section via a specific binding
reaction between the biological substances.
For histology specimens, the tissue pieces can be fixed in a
suitable fixative, typically formalin, and embedded in melted
paraffin wax. The wax block can be cut on a microtome to yield a
thin slice of paraffin containing the tissue. The specimen slice
can be applied to a substrate, air dried, and heated to cause the
specimen to adhere to the glass slide. Residual paraffin can be
dissolved with a suitable solvent, typically xylene, toluene, or
others. These so-called deparaffinizing solvents can be removed
with a washing-dehydrating type reagent prior to staining. Slices
can be prepared from frozen specimens, fixed briefly in 10%
formalin, then infused with dehydrating reagent. The dehydrating
reagent can be removed prior to staining with an aqueous stain.
In some embodiments, the Papanicolaou staining technique can be
used (e.g., a progressive stain and/or hematoxylineosin [H&E],
i.e., a regressive stain). HE (hematoxylin-eosin) stain uses
hematoxylin and eosin as a dye. Hematoxylin is a blue-violet dye,
and has a property of staining basophilic tissues such as cell
nuclei, bone tissues, part of cartilage tissues, and serous
components. Eosin is a red to pink dye, and has a property of
staining eosinophilic tissues such as cytoplasm, connective tissues
of the softtissue, red blood cells, fibrin, and endocrine
granules.
Immunohistochemistry (IHC) can be referred to as "immunological
staining" due to the process of color development for visualizing
an antigen-antibody reaction which is otherwise invisible
(hereinafter, the term "immunohistochemical staining" can be used
for immunohistochemistry). Lectin staining is a technique that can
use a property of lectin of binding to a specific sugar chain in a
non-immunological and specific manner in order to detect a sugar
chain in a tissue specimen using lectin.
HE staining, immunohistochemistry and lectin staining can be used
for detecting a location of, for example, cancer cells in a cell
specimen. For example, when it is desired to confirm a location of
cancer cells in a cell specimen, a pathologist, in order to
determine the presence or absence of cancer cells in the cell
specimen, can prepare tissue sections and place them on a substrate
of the disclosure. The section on the array can be subjected to HE
staining, imaging, or any immunohistochemical analysis in order to
obtain its morphological information and/or any other identifying
features (such as presence or absence of rare cells). The sample
can be lysed and the presence or absence of nucleic acid molecules
can be determined using the methods of the disclosure. The nucleic
acid information can be compared (e.g., spatially compared) to the
image, thereby indicating the spatial location of nucleic acids in
a sample.
In some embodiments, the tissue is stained with a staining enhancer
(e.g., a chemical penetrant enhancer). Examples of tissue chemical
penetrant enhancers that facilitate penetration of the stain into
the tissue include, but are not limited to, polyethylene glycol
(PEG), surfactants such as polyoxyethylenesorbitans,
polyoxyethylene ethers (polyoxyethylenesorbitan monolaurate (Tween
20) and other Tween derivatives, polyoxyethylene 23 lauryl ether
(Brij 35), Triton X-100, Brij 35, Nonidet P-40, detergent-like
substances such as lysolecithins, saponins, non-ionic detergents
such as TRITON.RTM. X-100, etc., aprotic solvents such as dimethyl
sulfoxide (DMSO), ethers such as tetrahydrofuran, dioxane, etc.;
esters such as ethyl acetate, butyl acetate, isopropyl acetate;
hydrocarbons such as toluene, chlorinated solvents such as
dichloromethane, dichloroethane, chlorobenzene, etc.; ketones such
as acetone, nitriles such as acetonitrile, and/or other agents that
increase cell membrane permeability.
In some embodiments, a composition is provided that facilitates
staining of a mammalian tissue sample. The composition can comprise
a stain, such as hematoxylin, or hematoxylin and eosin-Y, at least
one tissue chemical penetrant enhancer, such as a surfactant, an
aprotic solvent, and/or PEG, or any combination thereof.
In some embodiments, the sample is imaged (e.g., either before or
after IHC or without IHC). Imaging can comprise microscopy such as
bright field imaging, oblique illumination, dark field imaging,
dispersion staining, phase contrast, differential interference
contrast, interference reflection microscopy, fluorescence,
confocal, electron microscopy, transmission electron microscopy,
scanning electron microscopy, and single plane illumination, or any
combination thereof. Imaging can comprise the use of a negative
stain (e.g., nigrosin, ammonium molybdate, uranyl acetate, uranyl
formate, phosphotungstic acid, osmium tetroxide). Imaging can
comprise the use of heavy metals (e.g., gold, osmium) that can
scatter electrons.
Imaging can comprise imaging a portion of the sample (e.g.,
slide/array). Imaging can comprise imaging at least 10, 20, 30, 40,
50, 60, 70, 80, 90, or 100% of the sample. Imaging can comprise
imaging at most 10, 20, 30, 40, 50, 60, 70, 80, 90, or 100% of the
sample. Imaging can be done in discrete steps (e.g., the image may
not need to be contiguous). Imaging can comprise taking at least 1,
2, 3, 4, 5, 6, 7, 8, 9, or 10 or more different images. Imaging can
comprise taking at most 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more
different images.
Detection
The substrate surface can be contacted with one or more targets
under conditions that promote specific, high-affinity binding
(i.e., hybridization) of the target to one or more of the probes.
The target nucleic acids can hybridize with complementary nucleic
acids of the known oligonucleotide optical labels and thus,
information about the target samples can be obtained. The targets
can be labeled with an optically detectable label, such as a
fluorescent tag or fluorophore, so that the targets are detectable
with scanning equipment after a hybridization assay. The targets
can be labeled either prior to, during, or even after the
hybridization protocol, depending on the labeling system chosen,
such that the fluorophore will associate only with probe-bound
hybridized targets.
The targets (e.g., molecules, amplified molecules) can be detected,
for example, using detection probes (e.g., fluorescent probes). The
array can be hybridized with at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or
10 or more detection probes. The array can be hybridized with at
most 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more detection probes. In
some embodiments, the array is hybridized with 4 detection
probes.
The detection probes can comprise a sequence complementary to a
sequence of a gene of interest. The length of the detection probe
can be at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or
15 or more nucleotides. The length of the detection probe can be at
most 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 or more
nucleotides. The detection probes can comprise a sequence that is
perfectly complementary to a sequence in a gene of interest (e.g.,
target). The detection probes can comprise a sequence that is
imperfectly complementary to a sequence in a gene of interest
(e.g., target). The detection probes can comprise a sequence with
at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more mismatches to the
sequence of the gene of interest. The detection probes can comprise
a sequence with at most 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more
mismatches to the sequence of the gene of interest.
The detection probes can comprise a detectable label. Exemplary
detectable labels can comprise a fluorophore, chromophore, small
molecule, nanoparticle, hapten, enzyme, antibody, and magnetic
property, or any combination thereof.
Hybridized probes can be imaged. The image can be used to determine
the relative expression level of the genes of interest based on the
intensity of the detectable signal (e.g., fluorescent signal).
Scanning laser fluorescence microscopes or readers can be used to
acquire digital images of the emitted light from substrate (e.g.,
microarray). A focused light source (usually a laser) can be
scanned across the hybridized substrate causing the hybridized
areas to emit an optical signal, such as fluorescence. The
fluorophore-specific fluorescence data can be collected and
measured during the scanning operation, and then an image of the
substrate can be reconstructed via appropriate algorithms, software
and computer hardware. The expected or intended locations of probe
nucleic acid features can then be combined with the fluorescence
intensities measured at those locations, to yield the data that is
then used to determine gene expression levels or nucleic acid
sequence of the target samples. The process of collecting data from
expected probe locations can be referred to as "feature
extraction". The digital images can be comprised of several
thousand to hundreds of millions of pixels that typically range in
size from 5 to 50 microns. Each pixel in the digital image can be
represented by a 16 bit integer, allowing for 65,535 different
grayscale values. The reader can sequentially acquire the pixels
from the scanned substrate and writes them into an image file which
can be stored on a computer hard drive. The substrates can contain
several different fluorescently tagged probe DNA samples at each
spot location. The scanner repeatedly scans the entire substrate
with a laser of the appropriate wavelength to excite each of the
probe DNA samples and store them in their separate image files. The
image files are analyzed and subsequently viewed with the aid of a
programmed computer.
The substrate can be imaged with a confocal laser scanner. The
scanner can scan the substrate slide to produce one image for each
dye used by sequentially scanning the with a laser of a proper
wavelength for the particular dye. Each dye can have a known
excitation spectra and a known emission spectra. The scanner can
include a beam splitter which reflects a laser beam towards an
objective lens which, in turn, focuses the beam at the surface of
slide to cause fluorescence spherical emission. A portion of the
emission can travel back through the lens and the beam splitter.
After traveling through the beam splitter, the fluorescence beam
can be reflected by a mirror, travels through an emission filter, a
focusing detector lens and a central pinhole.
Correlation Between Probing and Imaging Data
The data from the substrate scan can be correlated to the image of
the unlysed sample on the substrate. The data can be overlayed
thereby generating a map. A map of the location of targets from a
sample can be constructed using information generated using the
methods described herein. The map can be used to locate a physical
location of a target. The map can be used to identify the location
of multiple targets. The multiple targets can be the same species
of target, or the multiple targets can be multiple different
targets. For example a map of a brain can be constructed to show
the amount and location of multiple targets.
The map can be generated from data from a single sample. The map
can be constructed using data from multiple samples, thereby
generating a combined map. The map can be constructed with data
from tens, hundreds, and/or thousands of samples. A map constructed
from multiple samples can show a distribution of targets associated
with regions common to the multiple samples. For example,
replicated assays can be displayed on the same map. At least 1, 2,
3, 4, 5, 6, 7, 8, 9, or 10 or more replicates can be displayed
(e.g., overlaid) on the same map. At most 1, 2, 3, 4, 5, 6, 7, 8,
9, or 10 or more replicates can be displayed (e.g., overlaid) on
the same map. The spatial distribution and number of targets can be
represented by a variety of statistics.
Combining data from multiple samples can increase the locational
resolution of the combined map. The orientation of multiple samples
can be registered by common landmarks and/or x-y positions on the
array, wherein the individual locational measurements across
samples are at least in part non-contiguous. Multiplexing the above
approach will allow for high resolution maps of target nucleic
acids in a sample.
The data analysis and correlation can be useful for determining the
presence and/or absence of a specific cell type (e.g., rare cell,
cancer cell). The data correlation can be useful for determining
the relative ratios of target nucleic acids in distinct locations
either within a cell, or within a sample.
The methods and compositions disclosed herein can be companion
diagnostics for a medical professional (e.g., a pathologist)
wherein a subject can be diagnosed by visually looking at a
pathology image and correlating the image to genetic expression
(e.g., identification of expression of oncogenes). The methods and
compositions can be useful for identifying a cell from a population
of cells, and determining the genetic heterogeneity of the cells
within a sample. The methods and compositions can be useful for
determining the genotype of a sample.
The disclosure provides for methods for making replicates of
substrates. The substrates can be reprobed with different probes
for different genes of interest, or to selectively choose specific
genes. For example, a sample can be placed on a substrate
comprising a plurality of oligo(dT) probes. mRNAs can hybridize to
the probes. Replicate substrates comprising oligo(dT) probes can be
contacted to the initial slide and make replicates of the mRNAs.
Replicate substrates comprising RNA gene-specific probes can be
contacted to the initial slide to make a replicate.
The mRNA can be reverse transcribed into cDNA. The cDNA can be
homopolymer tailed and/or amplified (e.g., via bridge
amplification). The array can be contacted with a replicate array.
The replicate array can comprise gene-specific probes that can bind
to the cDNAs of interest. The replicate array can comprise polyA
probes that can bind to cDNAs with a polyadenylation sequence.
The number of replicates that can be made can be at least 1, 2, 3,
4, 5, 6, 7, 8, 9, or 10 or more. The number of replicates that can
be made can be at most 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or
more.
In some embodiments, the initial substrate comprises a plurality of
gene-specific probes and the replicate substrate comprises the same
gene-specific probes, or different probes that correspond to the
same genes as the gene-specific probes.
Stochastic Barcoding with Physical Separation of Samples
In some embodiments, the sample can be physically divided or can be
intact during stochastically barcoding the plurality of targets in
the sample. The spatial locations of the plurality of targets in
the sample can be on a surface of the sample, inside the sample,
subcellularly in the sample, or any combination thereof. In some
embodiments, stochastic barcoding the plurality of targets in the
sample can be performed on the surface of the sample, subcellularly
in the sample, inside the sample, or any combination thereof.
A sample can be physically separated into different containers.
Physical separation can be accomplished by dissection, for example
by physically cutting a sample. Physical separation can be
accomplished by sectioning, for example sectioning with a
microtome. Physical separation can be accomplished by using a blade
grid (e.g., a substrate wherein the edges of containers in the
substrate are sharp such that they can cut a sample, and wherein
the pieces of the cut sample can fall into the containers on the
substrate). A blade grid can simultaneously separate and physically
isolate the parts of the samples.
The process of physical separation can preserve information about
the physically separated sample. Information preservation can occur
by associating a known part of the sample with a particular spatial
label and/or container. The containers can comprise spatial labels
which can be used to represent the original physical relationships
present before the sample was separated. The spatial labels can
then be associated with targets within the parts of the physically
separated samples. In this way targets from an identifiable
location within the sample can be stochastically labeled and
digitally counted.
In a basic example, a sample, for example a solid tissue, can be
bisected along a midsagittal plane. The right half of the organ can
be placed in one container. The left half of the organ can be
placed in a second container. A pool of non-depletable labels can
be associated with targets in each container. The labels can be
used to stochastically label targets within the sample. The labels
can comprise a spatial label which can be used to identify which
targets were in each container. The labeled targets from each
container can be recombined for analysis. The analysis can include
an amplification step. The amplified labeled-targets can be
sequenced or hybridized to an array for analysis. The data
generated from the analysis can include a stochastic count of the
number of starting targets and, for each target, spatial
information regarding whether the target was to the left or right
of the midsagittal bisection.
A sample can be physically separated into more than two sections. A
sample can be divided into at least 2, 3, 4, 5, 6, 7, 8, 9, 10 or
more sections. A sample can be divided into at most 2, 3, 4, 5, 6,
7, 8, 9, 10 or more sections. A sample can be divided into hundreds
of sections. A sample can be divided into at least 100, 200, 300,
400, 500, 600, 700, 800, or 900 or more sections. A sample can be
divided into at most 100, 200, 300, 400, 500, 600, 700, 800, or 900
or more sections. A sample can be divided into thousands of
sections. A sample can be divided into at least 1000, 10000, 20000,
30000, 40000, 50000, 60000, 70000, 80000 or 90000 or more sections.
A sample can be divided into at most 1000, 10000, 20000, 30000,
40000, 50000, 60000, 70000, 80000 or 90000 or more sections. A
sample can be divided into 16, 32, 48, 96, or 384 sections. The
higher the number of sections the sample is divided into the
greater the spatial resolution imparted by the spatial labels.
The sections (e.g., of the solid tissue and/or comprising the
targets) can be arranged such that a physical relationship of
sections is similar to the physical relationship between containers
on a substrate (e.g., a grid). For example a target that is in a
"top right" section of a sample can be located in a "top right"
container. This can allow for a sample to be directly applied to a
substrate to preserve the physical relationship between the
sections of the sample (e.g., solid tissue). FIG. 5 illustrates how
a solid tissue 505 can be divided into sections 510 (e.g., sections
1-10). The sections can be placed on a substrate 515 (e.g., grid).
The sections 510 of the solid tissue 505 can be placed onto a
specific location within the substrate 515, wherein the specific
location is a replicated map of the solid tissue 505. The placement
of sections of a solid tissue onto the substrate can be performed
in two or three dimensions. FIG. 5 illustrates an exemplary
embodiment of a two dimensional substrate. In some embodiments, the
substrate can be three-dimensional. Tens, hundreds, thousands, or
millions of sections from a sample can be reflected by physical
locations of containers on the substrate.
If the location of the first section in the sample is known, then
that information can be associated with targets within the
container containing the section. For example, as shown in FIG. 5,
after the sections 510 of the solid tissue 505 have been placed in
containers on the substrate 515, the targets of the sections can be
stochastically labeled, amplified, and/or counted. The information
(e.g., number of types of molecules) arising from container aa on
the grid 515 can correspond 520 to physical section (e.g.,
location) 1 of the solid tissue 505. Similarly, the information
arising from container ab of the substrate 515 can correspond 520
to physical section 4 of the solid tissue 505.
In some embodiments, the methods of the disclosure can be used for
identifying the surface of a sample. For example, spatial labels
can be added to the surface of sample (e.g., solid tissue). The
sample can be lysed, stochastically labeled with the spatial
labels, amplified, and/or digitally counted. Targets which were on
the surface of the sample can be distinguished from targets on the
interior of the sample, based on the spatial label. Identifying the
surface of a sample, and/or distinguishing between the interior and
exterior of a sample can be useful for determining boundaries of a
solid tissue (e.g., tumor), determining if resection of a solid
tissue was performed completely, and/or identifying boundaries of
different physiological structure or cell types.
Spatial labels can be associated with a spatially intact sample.
For example, a needle, or array of needles, can insert spatial
labels into an intact sample. Spatial labels can be inserted into
an intact sample in a variety of ways, including but not limited
to, needle insertion, pin insertion, insertion through blood
capillaries, injection, electroporation, transduction, and
transformation. The intact sample can then be lysed for stochastic
barcoding, amplification, and digital counting.
Stochastic Barcoding with Physical Separation of Samples Combined
with Time Separation
In some embodiments, stochastically barcoding the plurality of
targets in the sample can include contacting the sample with a
device. The device can be a needle, a needle array, a tube, a
suction device, an injection device, an electroporation device, a
fluorescent activated cell sorter device, a microfluidic device, or
any combination thereof. The device can contact sections of the
sample at a specified rate. The specified rate can correlate the
spatial locations of the plurality of targets with the one or more
time points.
Containers on a substrate can be filled in an order that reflects a
physical location. Spatial labels can be combined with a section as
a part of the sample collection. For example a sampling device
comprising a suction device could be used to remove a sample in a
predefined pattern. As the section of the sample travels through
the suction device spatial labels can be associated with the
section. The serial addition of the spatial labels can identify
where the suction device was in space at the time of
sectioning.
For example, as shown in FIG. 6, a solid tissue 605 can be divided
into sections 610 with a sampling device. The sections 610 can be
transported to a substrate 615 based on the order in which they
were obtained from the sample. For example, section 1 can be placed
in a container in the substrate 615 which corresponds to time 1
(T1). The container which corresponds to T1 can comprise a time
label (see below). The targets in the sections can be
stochastically labeled, amplified, and/or counted. The information
(e.g., number of types of molecules) arising from container T1 on
the substrate 615 can correspond 620 to physical section (e.g.,
location) 1 of the solid tissue 605. Similarly, the information
arising from container T4 of the substrate 615 can correspond 620
to physical section 4 of the solid tissue 605. The time label can
indicate the physical location of the section in the sample by
comparing the rate at which the sampling device processes each
section from the sample to the substrate. Obtainment of the
sections by the sampling device can be performed serially. The time
labels can be added to sections and/or containers in serial before
sections are added, simultaneously with addition of the section to
the container, or after the section is added to the container.
For example, a needle array device can inject solid supports
comprising stochastic barcodes with spatial labels into a solid
tissue. As the needle retracts the solid support is left in the
tissue. As the needle retracts further up a column of a solid
tissue, a series of solid supports can be placed in the tissue
(e.g., along a column). The rate of movement of the device can be
correlated to a time that the device was in a specific position. In
this way, the time a spatial label was associated with a target can
be indicative of its position in the sample.
In another example, the sampling device can comprise a microfluidic
chip. The sampling device can be capable of taking a section of a
sample, and placing it in a microfluidic chip. Inside the
microfluidic chip the section can be encapsulated in an emulsion
(e.g., droplet). The emulsion can comprise a stochastic barcode
with a spatial label. The emulsion can be placed in a container of
a substrate. The location in the substrate in which the emulsion is
placed can be indicative of the physical location of the section in
the sample because of the information carried in the time
label.
Non-Physical Representation of Containers
The disclosure provides for a method for estimating the number of
molecules in a specific location of a sample. The method can
comprise dividing the sample into sections and stochastically
labeling the sections with a barcode such that they contain
information about the physical location of the sections. The
stochastic barcoding does not have to occur in containers that have
a similar physical relationship to the sample, as described in
FIGS. 5 and 6. The containers do not have a similar physical
relationship to the sample. The method do not need to make use of
containers. For example, as shown in FIG. 7, the sample 605 can be
divided into sections 710. The sections 710 can be placed into one
or more randomly located containers on a substrate 715, wherein the
location of the section has no physical relationship to the
physical structure, shape and/or morphology of the sample 705. The
placement of sections of a solid tissue onto the substrate can be
performed in two or three dimensions. FIG. 7 illustrates an
exemplary embodiment of a two dimensional substrate. In some
embodiments, the substrate can be three-dimensional. Tens,
hundreds, thousands, or millions of sections from a sample can be
reflected by physical locations of containers on the substrate.
If the location of the first section in the sample is known, then
that information can be associated with targets within the
container containing the section. For example, as shown in FIG. 7,
after the sections 710 of the solid tissue 705 have been placed in
containers on the substrate 715 the targets of the sections can be
stochastically labeled, amplified, and/or counted. The information
(e.g., number of types of molecules) arising from container aa on
the grid 715 can correspond 720 to a physical section (e.g.,
location) of the solid tissue 605 (container aa corresponds to
section 5, though it is located where section 1 of the sample
is).
Addition of Stochastic Barcodes to Samples
Samples and/or sections of samples can be added to containers on a
substrate in parallel. A sampling device can obtain spatially known
samples in parallel and then be used associate the samples with a
spatial label. For example an array of biopsies can be obtained.
The biopsies can be associated with labels on the device which
obtains the biopsies. The biopsies can be associated with labels
after the biopsies are put into containers. In some embodiments a
needle array is used to obtain samples.
The spatial labels can be combined with a sample as a part of the
sample collection. For example a suction device could be used to
remove a sample in a predefined pattern. As the sample travels
through the suction device spatial labels can be associated with
the sample. The serial addition of the label can identify where the
suction device was in space at the time of collection.
For example a solid tumor can be resected. The resected tumor has
its exterior labeled with spatial labels, for example by spraying
the sample, immersing the sample, or contact the sample with a
composition comprising a spatial label.
Spatial Barcoding of Specific Cells
In some embodiments, spatial labels are delivered to a specific
target location. The target location can refer to a location in the
body, a specific type of cell, and/or a subcellular compartment. A
spatial label can be associated with a molecule known to target a
specific organ in the body. For example, a spatial label can be
associated with a molecule that is processed in the liver, a
spatial label can be associated with a molecule that can cross the
blood brain barrier, a spatial label can be associated with a
molecule that can be taken up by blood capillaries. The molecule to
which a spatial label is associated with can bring the spatial
label in close proximity to a location in the body of interest. The
location of the body of interest can be isolated, stochastically
labeled with the spatial labeled, amplified, and/or digitally
counted to obtain information about the number of targets in the
location of interest.
A spatial label can be associated with a molecule known to target a
specific cell. For example, a spatial label can be associated with
a molecule that targets an immune cell (e.g., a targeting
molecule). A spatial label can be associated with a molecule that
targets a virus. A spatial label can be associated with a molecule
that targets the blood brain barrier. The molecule can be a
targeting molecule that can bring the spatial label to a location
in a sample (e.g., subject).
A spatial label can be associated with a molecule known to target a
specific subcellular compartment. For example, a spatial label can
be associated with a vesicle which can comprise a location tag,
such as for the endoplasmic reticulum. The vesicle can deliver the
spatial label within close proximity of the endoplasmic reticulum.
The endoplasmic reticulum can be isolated, stochastically labeled
with the spatial label, amplified, and/or digitally counted.
Exemplary subcellular compartments can include, but are not limited
to mitochondria, Golgi complex, cell wall, endoplasmic reticulum,
nucleus, nucleolus, lysosomes, protein complexes (e.g., APC,
lincRNAs), and the like. Exemplary targeting molecules can include
but are not limited to nuclear localization sequences, nuclear
export sequences, chloroplast localization signals, mitochondrial
localization signals, and the like. In some embodiments, the
targeting molecule can comprise a vesicle. Exemplary vesicles can
include liposomes, microsomes, nanodots, quantum dots,
nanoparticles, and viral capsids, or any combination thereof.
Method of Label Lithography
The methods of the disclosure can provide for building a spatial
label after the label has been constricted within and/or contacted
to a sample. In some embodiments, the methods include:
stochastically barcoding the plurality of targets in the sample
using a plurality of stochastic barcodes, wherein each of the
plurality of stochastic barcodes comprises a pre-spatial label;
concatenating one or more spatial label blocks onto the pre-spatial
label to generate a spatial label; and identifying the spatial
location of each of the plurality of targets using the spatial
label.
FIG. 8 shows an exemplary embodiment of the label lithography
method of the disclosure. A target 804 can associate with a
pre-spatial label 805. A pre-spatial label 805 can comprise a
nucleotide sequence that can hybridize with targets of interest
(e.g., gene specific nucleotide sequence or oligo(dT)) 810. The
pre-spatial label 805 can comprise an activatable consensus
sequence 815. The activatable consensus sequence 815 can be a
nucleotide sequence that can be linked to another nucleotide
sequence or base. For example, an activatable sequence 815 can be a
restriction site, a site for TA-ligation, and/or a
photo-activatable nucleotide. The activatable consensus sequence
815 can be linked to a spatial label block 820/821. A spatial label
block 820/821 can comprise a nucleotide sequence that is indicative
of a spatial location 825. A spatial label block can comprise
linking sequences 830. Linking sequences 830 can interact with the
activatable consensus sequence 815 and/or other linking sequences
in spatial label blocks 820. For example, a first group (Group I)
of spatial label blocks 820/821 can comprise a first (A') and
second (B) linking sequence. The first linking sequence (A') can
interact with the activatable consensus sequence 815 in the
pre-spatial label 705. A second group (Group II) of spatial label
blocks 821 can comprise a first (B') and second (A) linking
sequence. The first linking sequence (B') can interact with the
second linking sequence (B) of the first group of spatial label
blocks 821. In this way spatial label blocks 820/821 can be linked
together.
Pre-Spatial Labels, Spatial Label Blocks, and Spatial Labels
A pre-spatial label can comprise a sequence that can associate with
a target of interest. A pre-spatial label can associate with
nucleic acid, including but not limited to, DNA, mRNA, RNA
fragments, gene-specific regions, and regulatory elements (e.g.,
promoter, enhancer). A sequence that can bind to a target of
interest can comprise a gene-specific region (e.g., a nucleotide
sequence that is adapted to bind to a specific region of a gene),
or a non-specific binding region (e.g., oligo(dT), random hexamer,
random oligomer). A sequence that can associate with a target of
interest can be at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more
nucleotides in length. A sequence that can associate with a target
of interest can be at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or
more nucleotides in length.
A pre-spatial label can comprise a molecular label, a cellular
label, and/or a sample label. A pre-spatial label can comprise a
sequence that can associate (e.g., hybridize) with a target. A
pre-spatial label can be associated with a solid support. A
pre-spatial label can be associated with a substrate.
A pre-spatial label can comprise an activatable consensus sequence.
An activatable consensus sequence can comprise a sequence that can
be activated to bind to a spatial label block. An activatable
consensus sequence can be a cleavable sequence (e.g., restriction
endonuclease cleavage site), a sequence that can be tagged, and/or
a sequenced that can be ligated. An activatable consensus sequence
can comprise a chemical moiety that can be activated. For example,
the chemical moiety can comprise a fluorophore that can be excited,
a photo-cleavable moiety, a moiety that responds to magnets, and a
binding moiety (e.g., biotin/streptavidin).
An activatable consensus sequence can comprise at least 1, 2, 3, 4,
5, 6, 7, 8, 9, or 10 or more nucleotides. An activatable consensus
sequence can comprise at most 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or
more nucleotides.
A pre-spatial label can comprise a sequence that can associate with
a target of interest, a molecular label, a sample label and/or an
activatable consensus sequence. In some embodiments, a pre-spatial
label comprises a sequence that can associate with a target of
interest, a molecular label, a sample label and/or an activatable
consensus sequence.
A pre-spatial label can be at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12, 13, 14, 15 16, 17, 18, 19, 20, 21, 222, 23, 24, 25, 26, 27,
28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
45, 46, 47, 48, 49, or 50 or more nucleotides in length. A
pre-spatial label can be at most 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15 16, 17, 18, 19, 20, 21, 222, 23, 24, 25, 26, 27, 28,
29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45,
46, 47, 48, 49, or 50 or more nucleotides in length.
A spatial label block can comprise a sequence of nucleotides. The
sequence can comprise at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or
more nucleotides. The sequence can comprise at most 1, 2, 3, 4, 5,
6, 7, 8, 9, or 10 or more nucleotides. A spatial label block can be
linked to another (e.g., previous) spatial label block. Spatial
label blocks can be linked together, for example, by chemistry
(e.g., click chemistry), ligation, split-pool synthesis,
combinatorial chemistry, and/or photoactivatable chemistry.
For example, a first group of spatial label blocks can comprise two
sticky end sequences, wherein the sense strand has a first sticky
end sequence, and the antisense strand has a second sticky end
sequence on the 5' ends of each strand. A second group of spatial
label blocks can comprise two sticky end sequences, wherein the
sense strand has the second complementary sticky end sequence and
the antisense strand has the first complementary sticky end
sequence. The first group can be ligated to the second group. Only
one ligation can occur. Subsequently, the first group can be
contacted to the growing spatial label. The first group can ligate
to the sticky end of the second group. Only one ligation can occur.
In this way, a spatial label can be able to be lithographically
produced on sample.
Linking of spatial label blocks can be performed before, during,
and/or after contacting the pre-spatial label with a target of
interest. Pre-spatial labels can be associated with targets before,
during and/or after linking with spatial label blocks using
chemical means such as cross-linking, hybridization to aid the
association between the pre-spatial label and the target. This can
reduce dissociation and/or diffusion of the pre-spatial labels away
from the targets.
Linking of spatial label blocks can be performed in a geometric
manner such that the resulting length of the spatial label
corresponds to the geometric manner in which the spatial label
blocks were linked. FIG. 9 shows an exemplary embodiment of a
geometric manner of linking spatial label blocks. For example, as
one moves left to right on a sample, spatial label blocks can be
increasingly added to the pre-spatial label, thereby generating
spatial labels with different lengths. The length of the spatial
label can correspond to a physical location in the sample. A sample
905 can be divided into sections 910. The sections can be contacted
with a pre-spatial label. The pre-spatial label can be contacted
with an integer number of spatial label blocks. For example, the
sections in row a are contacted with one spatial label block. The
sections in row b are contacted with two spatial label blocks. The
sections in row c are contacted with three spatial label blocks.
The sections in row d are contacted with four spatial label blocks.
Moving right to left, sections in column A can be contacted with
one spatial label block, sections in column B can be contacted with
two spatial label blocks. Sections in column C can be contacted
with three spatial label blocks. The number of spatial label blocks
in each section can be a representation of its location in a first
dimension (y, vertical) and a second dimension (x horizontal) space
within the sample.
The sections can be contacted with the spatial label blocks in any
order. The sections can be contacted by rows only. The sections can
be contacted by columns only. The sections can be contacted first
by rows and then by columns. The sections can be contacted first by
columns and then by rows.
The sections can be stochastically labeled, amplified, and/or
digitally counted. The length of the spatial label can provide
information about the x and y location of the section in the
sample. In the embodiment shown in FIG. 7, the shortest spatial
label corresponds to the top left-most corner and the longest
spatial label corresponds to the bottom right-most corner.
Methods for Determining Spatial Location of Targets
Disclosed herein are methods for identifying distinct cells in two
or more samples. In some embodiments, the methods include:
stochastically barcoding a plurality of targets in the two or more
samples using a plurality of stochastic barcodes, wherein each of
the plurality of stochastic barcodes comprises a spatial label and
a molecular label; estimating the number of the plurality of
targets in the two or more samples using the molecular label; and
distinguishing the two or more samples from each other using the
spatial label, wherein the plurality of targets associated with
stochastic barcodes with different spatial labels are from
different samples.
Stochastically barcoding the plurality of targets in the two or
more samples can include hybridizing the plurality of stochastic
barcodes with the plurality of targets to generate stochastically
barcoded targets, and at least one of the plurality of targets can
be hybridized to one of the plurality of stochastic barcodes.
Stochastically barcoding the plurality of targets in the two or
more samples can include generating an indexed library of the
stochastically barcoded targets.
Each of the two or more samples can include a plurality of cells
and the plurality of targets are associated with the plurality of
cells. Stochastically barcoding the plurality of targets in the two
or more samples can be performed with a solid support comprising a
plurality of synthetic particles associated with the plurality of
stochastic barcodes.
Identification of Specific Cells in a Population of Cells
Spatial labels can be used to identify and label distinct samples
(e.g., cells) in a mixed population of samples (e.g., cells). The
samples can be, for example, cells in a mixed population of
cells.
FIG. 10 illustrates an exemplary embodiment of the method of
identifying distinct cells with a spatial label. A sample, for
example, comprising a mixed population of cells 1015/1020 can be
contacted to a substrate 10905, wherein the substrate 1005
comprises a distribution of different groups of spatial labels
1010/1011/1012. Targets from an individual cell 1015 can be
physically close to a first group of same spatial labels 1010.
Targets from a different individual cell 1020 can be physically
more distant from the first group of spatial labels 1010, but can
be close in physical space to other spatial labels 1012 (e.g., a
second group of spatial labels). The cells can be lysed,
stochastically labeled, amplified, and/or digitally counted. The
spatial label can then be used as a code to distinguish between
targets from different individual cells.
The targets can be associated with the closest spatial labels.
Spatial labels can be any spatial labels of the disclosure (e.g.,
pre-spatial labels, spatial labels). The targets can be associated
with spatial labels that are at least 1, 2, 3, 4, 5, 6, 7, 8, 9,
10, 15, 20, 25, 30, 35, 40, 45, or 50 more micrometers from the
outer edge of the sample (e.g., cell). The targets can be
associated with spatial labels that are at most 1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, or 50 more micrometers
from the outer edge of the sample (e.g., cell).
Identification of Spatial Location of Targets in a Sample
The disclosure provides for methods for determining the subcellular
location of targets in a cell. FIG. 11 illustrates how subcellular
information can be obtained using spatial labels. A sample (e.g., a
cell) 1105 can be contacted to a substrate 1009 comprising one or
more groups of spatial labels 1110/1111/1112/1113. The groups of
spatial labels 1110/1111/1112/1113 can be distributed over the
surface of a substrate. The groups of spatial labels
1110/1111/1112/1113 can be distributed over containers (e.g.,
microwells) of the substrate. The groups of spatial labels
1110/1111/1112/1113 can be distributed into the sample 1105. The
groups of spatial labels 1110/1111/1112/1113 can be arranged such
that the sample (e.g., a cell) 1105 contacts multiple distinct
groups of spatial labels 1110/1111/1112/1113. The sample 1005 can
be crosslinked, physically separated, lysed, stochastically labeled
with the distinct groups of spatial labels 1110/1111/1112/1113,
amplified, and/or digitally counted. Because the location of the
distinct groups of spatial labels 1110/1111/1112/1113 can be known,
the location of the targets in the cell can be correlated to the
identification of the spatial labels 1110/1111/1112/1113. In this
way, spatial labels can be used to identify the spatial location of
targets in a sample.
Methods for Optical Barcoding and Optical Barcoding
Disclosed herein are methods for determining spatial locations of a
plurality of singles cells. In some embodiments, the methods
include: stochastically barcoding the plurality of singe cells
using a plurality of synthetic particles, wherein each of the
plurality of synthetic particles comprises a plurality of
stochastic barcodes, a first group of optical labels, and a second
group of optical labels, wherein each of the plurality of
stochastic barcodes comprises a cellular label and a molecular
label, wherein each optical label in the first group of optical
labels comprises a first optical moiety and each optical label in
the second group of optical labels comprises a second optical
moiety, and wherein each of the plurality of synthetic particles is
associated with an optical barcode comprising the first optical
moiety and the second optical moiety; detecting the optical barcode
of each of the plurality of synthetic particles to determine the
location of each of the plurality of synthetic particles; and
determining the spatial locations of the plurality of single cells
based on the locations of the plurality of synthetic particles.
Synthetic Particles with Stochastic Barcodes and Optical
Barcodes
Disclosed herein are synthetic particles (for examples beads and
magnetic beads) associated with (e.g., attached with) stochastic
barcodes and optical labels. For example, a synthetic particle can
have one or more optical label regions in which the optical labels
are associated with the synthetic particle. In some embodiments,
each synthetic particle can have, or have about, 1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50,
60, 70, 80, 90, 100, 1000, 2000, 3000, 4000, 5000, 6000, 7000,
8000, 9000, 10000, or a number or a range between any two of these
values, optical label regions. The size of the optical label region
can vary, for example, an optical label region can be, or be about,
a few microns to tens of microns in width, length, or diameter. In
some embodiments, the width, length, or diameter of the optical
label region can be, or be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50, 60, 70, 80, 90,
100, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000
microns, or a number or a range between any two of these values. In
some embodiments, the length of the optical label region can be, or
be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000, 2000, 3000,
4000, 5000, 6000, 7000, 8000, 9000, 10000 microns, or a number or a
range between any two of these values. For a synthetic particle
with more than one optical label regions, each of the optical label
regions can have the same size or different sizes. For example, at
least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80,
90, 100, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000,
10000, or a number or a range between any two of these values, of
the optical label regions can have different sizes. For example, at
least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80,
90, 100, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000,
10000, or a number or a range between any two of these values, of
the optical label regions can have the same size.
The arrangement of the optical label regions can vary. Non-limiting
examples of the arrangement of the optical label regions include a
longitudinal format, a vertical format, a grid manner, a circular
format, or any combination thereof. The shape of the optical label
regions can also vary. For example, the optical label regions can
be oval-, rectangle-, triangle-, diamond-shaped, or any combination
thereof. The optical label regions can be grouped together or be
separated from one another. For example, two optical label regions
can be separated from one another by, or by about, 1, 2, 3, 4, 5,
6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50,
60, 70, 80, 90, 100, 1000, 2000, 3000, 4000, 5000, 6000, 7000,
8000, 9000, 10000 microns, or a number or a range between any two
of these values.
The optical label regions can occupy substantially the entire
synthetic particle surface, or part of the synthetic particle
surface. In some embodiments, the optical label regions can occupy,
or occupy about, 0.00001%, 0.0001%, 0.01%, 0.1%, 1%, 2%, 3%, 4%,
5%, 6%, 7%, 8%, 9%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%,
99.9%, or a number or a range between any two of these values, of
the synthetic particle surface. Optical label regions can include
optical labels. In some embodiments, an optical label region can
have an optical label (OL) attached to the surface of the synthetic
particle. The number of optical labels in each of the optical label
region can vary, for example, be or be about, 1, 2, 3, 4, 5, 6, 7,
8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50, 60,
70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000. In
some embodiments, an optical label comprises a probe sequence.
In some embodiments, each synthetic particle can include 9 types of
optical labels, OL1-9, attached to the surface of the synthetic
particle. In some embodiments, each synthetic particle can include
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
20, 30, 40, 50, 60, 70, 80, 90, 100, 1000, 2000, 3000, 4000, 5000,
6000, 7000, 8000, 9000, 10000, or a number or a range between any
two of these numbers, types of optical labels. For each synthetic
particle, OL1-9 can be the same or different. In some embodiments,
each type of optical labels is attached to the synthetic particle
in one optical label region. In some embodiments, at least one of
the optical label regions on the synthetic particle comprises more
than one type of optical labels. In some embodiments, two, three,
four, five, or more types of optical labels are present in one
optical label region.
An optical label can comprise an oligonucleotide sequence. The
optical label can comprise an oligonucleotide. In some embodiments,
the optical label can comprise two or more oligonucleotides with
the same sequence. The optical label can be, or be about, 1, 2, 3,
4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000,
2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, or a number
or a range between any two of these values, nucleotides in length.
The oligonucleotides of optical labels can be, or be about, 1, 2,
3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000,
2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, or a number
or a range between any two of these values, nucleotides in
length.
In some embodiments, OL1-3 can be used to encode cellular label
part 1 corresponding to a first 96 unique cellular labels in the
first encoding step; OS4-6 can be used to encode cellular label
part 2 corresponding to a second 96 unique cellular labels in the
second split step; and OL7-9 can be used to encode cellular label
part 3 corresponding to a third 96 unique cellular labels in the
third split step. In some embodiments, OLs encode 1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or a number
between any two of these values cellular label parts. In some
embodiments, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70,
80, 90, 100, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000,
10000, or a number between any two of these values, optical labels
can be used to encode a part of a cellular label. In some
embodiments, each part of a cellular label can represent 1, 2, 3,
4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000,
10000, 100000, 1000000, 10000000, 10000000, 100000000, 1000000000,
or a number or a range between any two of these values, unique
cellular labels. An optical barcode of a synthetic particle can
include the optical labels on the synthetic particle. The optical
barcode of a synthetic particle can include 1, 2, 3, 4, 5, 6, 7, 8,
9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000, 2000, 3000, 4000,
5000, 6000, 7000, 8000, 9000, 10000, or a number between any two of
these values, optical labels.
In some embodiments, an optical label can comprise an optical
moiety, for example a fluorophore or a chromophore. In some
embodiments, each nucleotide of an optical label can be associated
with an optical moiety, for example a fluorophore or a chromophore,
on the 3' end. The optical moiety can be selected from a group of
spectrally-distinct optical moieties. Spectrally-distinct optical
moieties include optical moieties with distinguishable emission
spectra even if their emission spectral may overlap.
Non-limiting examples of optical moieties include Xanthene
derivatives: fluorescein, rhodamine, Oregon green, eosin, and Texas
red; Cyanine derivatives: cyanine, indocarbocyanine,
oxacarbocyanine, thiacarbocyanine, and merocyanine; Squaraine
derivatives and ring-substituted squaraines, including Seta, SeTau,
and Square dyes; Naphthalene derivatives (dansyl and prodan
derivatives); Coumarin derivatives; oxadiazole derivatives:
pyridyloxazole, nitrobenzoxadiazole and benzoxadiazole; Anthracene
derivatives: anthraquinones, including DRAQ5, DRAQ7 and CyTRAK
Orange; Pyrene derivatives: cascade blue; Oxazine derivatives: Nile
red, Nile blue, cresyl violet, oxazine 170; Acridine derivatives:
proflavin, acridine orange, acridine yellow; Arylmethine
derivatives: auramine, crystal violet, malachite green; and
Tetrapyrrole derivatives: porphin, phthalocyanine, bilirubin. Other
non-limiting examples of optical moieties include Hydroxycoumarin,
Aminocoumarin, Methoxycoumarin, Cascade Blue, Pacific Blue, Pacific
Orange, Lucifer yellow, NBD, R-Phycoerythrin (PE), PE-Cy5
conjugates, PE-Cy7 conjugates, Red 613, PerCP, TruRed, FluorX,
Fluorescein, BODIPY-FL, Cy2, Cy3, Cy3B, Cy3.5, Cy5, Cy5.5, Cy7,
TRITC, X-Rhodamine, Lissamine Rhodamine B, Texas Red,
Allophycocyanin (APC), APC-Cy7 conjugates, Hoechst 33342, DAPI,
Hoechst 33258, SYTOX Blue, Chromomycin A3, Mithramycin, YOYO-1,
Ethidium Bromide, Acridine Orange, SYTOX Green, TOTO-1, TO-PRO-1,
TO-PRO: Cyanine Monomer, Thiazole Orange, CyTRAK Orange, Propidium
Iodide (PI), LDS 751, 7-AAD, SYTOX Orange, TOTO-3, TO-PRO-3, DRAQ5,
DRAQ7, Indo-1, Fluo-3, Fluo-4, DCFH, DHR, and SNARF.
The excitation wavelength of the optical moieties can vary, for
example be, or be about, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100,
110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230,
240, 250, 260, 270, 280, 290, 300, 310, 320, 330, 340, 350, 360,
370, 380, 390, 400, 410, 420, 430, 440, 450, 460, 470, 480, 490,
500, 510, 520, 530, 540, 550, 560, 570, 580, 590, 600, 610, 620,
630, 640, 650, 660, 670, 680, 690, 700, 710, 720, 730, 740, 750,
760, 770, 780, 790, 800, 810, 820, 830, 840, 850, 860, 870, 880,
890, 900, 910, 920, 930, 940, 950, 960, 970, 980, 990, 1000
nanometers, or a number or a range between any two of these values.
The emission wavelength of the optical moieties can also vary, for
example be, or be about, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100,
110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230,
240, 250, 260, 270, 280, 290, 300, 310, 320, 330, 340, 350, 360,
370, 380, 390, 400, 410, 420, 430, 440, 450, 460, 470, 480, 490,
500, 510, 520, 530, 540, 550, 560, 570, 580, 590, 600, 610, 620,
630, 640, 650, 660, 670, 680, 690, 700, 710, 720, 730, 740, 750,
760, 770, 780, 790, 800, 810, 820, 830, 840, 850, 860, 870, 880,
890, 900, 910, 920, 930, 940, 950, 960, 970, 980, 990, 1000
nanometers, or a number or a range between any two of these
values.
The molecular weights of the optical moieties can vary, for example
be, or be about, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120,
130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250,
260, 270, 280, 290, 300, 310, 320, 330, 340, 350, 360, 370, 380,
390, 400, 410, 420, 430, 440, 450, 460, 470, 480, 490, 500, 510,
520, 530, 540, 550, 560, 570, 580, 590, 600, 610, 620, 630, 640,
650, 660, 670, 680, 690, 700, 710, 720, 730, 740, 750, 760, 770,
780, 790, 800, 810, 820, 830, 840, 850, 860, 870, 880, 890, 900,
910, 920, 930, 940, 950, 960, 970, 980, 990, 1000 Daltons (Da), or
a number or a range between any two of these values. The molecular
weights of the optical moieties can also vary, for example be, or
be about, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130,
140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260,
270, 280, 290, 300, 310, 320, 330, 340, 350, 360, 370, 380, 390,
400, 410, 420, 430, 440, 450, 460, 470, 480, 490, 500, 510, 520,
530, 540, 550, 560, 570, 580, 590, 600, 610, 620, 630, 640, 650,
660, 670, 680, 690, 700, 710, 720, 730, 740, 750, 760, 770, 780,
790, 800, 810, 820, 830, 840, 850, 860, 870, 880, 890, 900, 910,
920, 930, 940, 950, 960, 970, 980, 990, 1000 kilo Daltons (kDa), or
a number or a range between any two of these values.
The group of spectrally distinct optical moieties can, for example,
include five different fluorophores, five different chromophores, a
combination of five fluorophores and chromophores, a combination of
four different fluorophores and a non-fluorophore, a combination of
four chromophores and a non-chromophore, or a combination of four
fluorophores and chromophores and a non-fluorophore
non-chromophore. In some embodiments, the optical moieties can be
one of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80,
90, 100, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000,
10000, or a number or a range between any two of these values, of
spectrally-distinct moieties.
In some embodiments, each of a plurality of synthetic particles has
a unique optical barcode. For example, the plurality of synthetic
particles can include, include about, or include more than 1, 2, 3,
4, 5, 6, 7, 8, 9, 10, 100, 200, 300, 400, 500, 600, 700, 800, 900,
10.sup.3, 10.sup.4, 10.sup.5, 10.sup.6, 10.sup.7, 10.sup.8,
10.sup.9, 10.sup.10, 10.sup.11, 10.sup.12, or a number or a range
between any two of these values, synthetic particles each with a
unique optical barcode. Some of a plurality of synthetic particles
can have the same optical barcode. The plurality of synthetic
particles can include, include about, or include more than 1, 2, 3,
4, 5, 6, 7, 8, 9, 10, 100, 200, 300, 400, 500, 600, 700, 800, 900,
10.sup.3, 10.sup.4, 10.sup.5, 10.sup.6, 10.sup.7, 10.sup.8,
10.sup.9, 10.sup.10, 10.sup.11, 10.sup.12, or a number or a range
between any two of these values, synthetic particles some of which
with the same optical barcodes.
In addition to the "optical labels," substantially entire synthetic
particle surface or some part of the synthetic particle surface can
be attached with stochastic barcodes. For example, the stochastic
barcodes can occupy 0.00001%, 0.0001%, 0.01%, 0.1%, 1%, 2%, 3%, 4%,
5%, 6%, 7%, 8%, 9%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%,
99.9%, or a number or a range between any two of these values, of
the synthetic particle surface. The stochastic barcodes can be, or
be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70,
80, 90, 100, 1000, or a number or a range between any two of these
values, nucleotides in length.
Methods for Loading Spatial Labels on a Substrate
Spatial labels can be pre-located on a substrate. A surface of
substrate can be pre-imprinted with stochastic barcodes. In other
words, the coordinates of each stochastic barcode on the surface of
the substrate can be known. Stochastic barcodes can be
pre-imprinted in any geometric manner. In some embodiments, a solid
support comprising stochastic barcodes can be pre-located on a
substrate. In some embodiments, the coordinates of the stochastic
barcodes on a substrate can be unknown. The location of the
stochastic barcodes can be user-generated. When the location of the
stochastic barcodes on a substrate is unknown, the location of the
stochastic barcodes can be decoded.
Methods for Encoding Solid Supports
Disclosed herein are methods for creating encoded solid supports,
such as encoded synthetic particles, for determining spatial
locations of a plurality of singles cells. Each synthetic particle
can contain 9 "anchor regions." In some embodiments, each synthetic
particle can contain, or contain about, 1, 2, 3, 4, 5, 6, 7, 8, 9,
10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50, 60, 70, 80,
90, 100, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000,
10000, or a number or a range between any two of these values,
anchor regions. Each anchor region can have a size of about a few
microns to tens of microns wide. In some embodiments, each anchor
region can have a size of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50, 60, 70, 80, 90, 100,
1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, or a
number or a range between any two of these values, microns in
size.
The arrangement of the anchor regions can vary. Non-limiting
examples of the arrangement of the anchor regions include a
longitudinal format, a vertical format, a grid manner, a circular
format, or any combination thereof. The shape of the anchor regions
can also vary. For example, the anchor regions can be oval-,
rectangle-, triangle-, diamond-shaped, or any combination thereof,
in shape. The anchor regions can be grouped together or be
separated from one another. For example, two anchor regions can be
separated from one another by, or by about, 1, 2, 3, 4, 5, 6, 7, 8,
9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50, 60, 70,
80, 90, 100, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000,
10000 microns, or a number or a range between any two of these
values.
The anchor regions can occupy substantially the entire synthetic
particle surface, or part of the synthetic particle surface In some
embodiments, the anchor regions can occupy, or occupy about,
0.00001%, 0.0001%, 0.01%, 0.1%, 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%,
10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 99.9%, or a number or
a range between any two of these values, of the synthetic particle
surface. Anchor regions can include optical labels. In some
embodiments, an anchor region can have an optical label (OL)
attached to the surface of the synthetic particle. The number of
optical labels in each of the anchor region can vary, for example,
be or be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
16, 17, 18, 19, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400,
500, 600, 700, 800, 900, 1000. In some embodiments, an optical
label comprises a probe sequence. Anchor regions with optical
labels attached can be referred to as optical label regions.
Each anchor region can have a unique optical label (OL) attached to
the surface of the synthetic particle. In some embodiments, each
synthetic particle can include 9 types of optical labels, OL1-9,
attached to the surface of the synthetic particle. In some
embodiments, each synthetic particle can include 1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50,
60, 70, 80, 90, 100, 1000, 2000, 3000, 4000, 5000, 6000, 7000,
8000, 9000, 10000, or a number or a range between any two of these
numbers, types of optical labels. For each synthetic particle,
OL1-9 can be the same or different. In some embodiments, each type
of optical labels is attached to the synthetic particle in one
anchor region. In some embodiments, at least one of the anchor
regions on the synthetic particle comprises more than one type of
optical labels. In some embodiments, two, three, four, five, or
more types of optical labels are present in one anchor region.
An optical label can comprise an oligonucleotide sequence. The
optical label can comprise an oligonucleotide. In some embodiments,
the optical label can comprise two or more oligonucleotides with
the same sequence. The optical label can be, or can be about, 1, 2,
3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000,
2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, or a number
or a range between any two of these values, nucleotides in length.
The oligonucleotides of optical labels can be, or can be about, 1,
2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100,
1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, or a
number or a range between any two of these values, nucleotides in
length.
In some embodiments, OL1-3 can be used to encode cellular label
part 1 corresponding to a first 96 unique cellular labels in the
first encoding step; OS4-6 can be used to encode cellular label
part 2 corresponding to a second 96 unique cellular labels in the
second split step; and OL7-9 can be used to encode cellular label
part 3 corresponding to a third 96 unique cellular labels in the
third split step. In some embodiments, 1, 2, 3, 4, 5, 6, 7, 8, 9,
10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or a number between any
two of these values, optical labels can be used to encode a part of
a cellular label. In some embodiments, each part of a cellular
label correspond to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50,
60, 70, 80, 90, 100, 1000, 10000, 100000, 1000000, 10000000,
10000000, 100000000, 1000000000, or a number or a range between any
two of these values, unique cellular labels. An optical barcode of
a synthetic particle can include the optical labels on the
synthetic particle. The optical barcode of a synthetic particle can
include 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80,
90, 100, 1000, or a number between any two of these values, optical
labels.
In addition to the "optical label" constituting the optical
barcode, the entire synthetic particle surface or part of the
synthetic particle surface can be attached with the universal
sequence (US) with 3' up, i.e. 3' end of the oligonucleotide is not
attached to the synthetic particle. In some embodiments, the OL
oligonucleotides can be 5' up and not 3' ends up. If the OL
oligonucleotides are 5' up, the optical moieties can be added by
ligation method. The universal sequence can occupy 0.00001%,
0.0001%, 0.01%, 0.1%, 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 20%,
30%, 40%, 50%, 60%, 70%, 80%, 90%, 99.9%, or a number or a range
between any two of these values, of the synthetic particle surface.
The universal sequence can be, or can be about, 1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000, or a number
or a range between any two of these values, nucleotides in
length.
For cellular labels each comprising three parts, encoding the
synthetic particles can include three encoding steps. The cellular
label can include part 1 of the cellular label, part 2 of the
cellular label, and part 3 of the cellular label. In some
embodiments, the cellular label can include 1, 2, 3, 4, 5, 6, 7, 8,
9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000, or a number or a
range between any two of these values, parts. Encoding the
synthetic particles can include 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20,
30, 40, 50, 60, 70, 80, 90, 100, 1000, or a number or a range
between any two of these values, encoding steps.
At the first encoding step/the first split step, synthetic
particles can be distributed across 96 wells of a first plate and
hybridize to oligonucleotides in each well. In some embodiments,
the first plate can include 96, 394, 1000, 2000, 3000, 4000, 5000,
6000, 7000, 8000, 9000, 10000, or a number between any two of these
values, wells. Each well can contain 4 types of oligonucleotides,
possibly including the universal sequence (US) and three additional
types of oligonucleotides. Each additional type of oligonucleotides
can include an optical label with an optical moiety, for example a
fluorophore or a chromophore, on the 3' end. The three additional
types of oligonucleotides encode a cellular label part. In some
embodiments, each well can contain, or contain about, 1, 2, 3, 4,
5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30, 40,
50, 60 70, 80, 90, 100, 1000, or a number of range between any two
of these values, additional types of oligonucleotides. Each type of
oligonucleotides can be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8,
9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000, 10000, or a
number or a range between any two of these values, nucleotides in
length. Each cellular part can be, or can be about, 1, 2, 3, 4, 5,
6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000, or a
number or a range between any two of these values, nucleotides in
length.
The first type of oligonucleotides each can contain a region
complementary to the universal sequence (US), followed by part 1 of
the cellular label (1 of 96), followed by a linker sequence (linker
1). The region complementary to the universal sequence can be, or
can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60,
70, 80, 90, 100, 1000, or a number or a range between any two of
these values, nucleotides in length. Linker 1 can be, or can be
about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80,
90, 100, 1000, 10000, or a number or a range between any two of
these values, nucleotides in length.
The second type of oligonucleotides each can include a duplex
structure that contains a strand complementary to OL1 with a small
5' extension, and a shorter strand complementary to the extension
on the longer strand. The shorter strand can include an optical
label with an optical moiety, for example a fluorophore or a
chromophore, on the 3' end. In some embodiments, the optical label
is on the 5's end, or neither 5's end nor 3's end. The optical
label can be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20,
30, 40, 50, 60, 70, 80, 90, 100, 1000, 2000, 3000, 4000, 5000,
6000, 7000, 8000, 9000, 10000, or a number or a range between any
two of these values, nucleotides in length. The optical moiety can
be selected from a group of spectrally-distinct optical moieties.
Spectrally-distinct optical moieties include optical moieties with
distinguishable emission spectra even if their emission spectral
may overlap.
The third type of oligonucleotides each can include a duplex
structure that contains a strand complementary to OL2 with a small
5' extension, and a shorter strand complementary to the extension
on the longer strand. The shorter strand can include an optical
label with an optical moiety, for example a fluorophore or a
chromophore, on the 3' end. In some embodiments, the optical label
is on the 5's end, or neither 5's end nor 3's end. The optical
moiety can be selected from a group of spectrally-distinct optical
moieties.
The fourth type of oligonucleotides each can include a duplex
structure that contains a strand complementary to OL3 with a small
5' extension, and a shorter strand complementary to the extension
on the longer strand. The shorter strand can include an optical
label with an optical moiety, for example a fluorophore or a
chromophore, on the 3' end. In some embodiments, the optical label
is on the 5's end, or neither 5's end nor 3's end. The optical
moiety can be selected from a group of spectrally-distinct optical
moieties.
After the synthetic particles are distributed across 96 wells of
the first plate and hybridize to oligonucleotides in each well, a
polymerase such as a DNA polymerase and a ligase such as a DNA
ligase can be introduced into each well. DNA polymerase can extend
the universal sequence with cellular label part 1 and linker 1
sequences. DNA ligase can covalently attach the optical moieties
onto the OL oligonucleotides.
At the second encoding step including pool and second split,
synthetic particles from all the wells of the first plate can be
pooled, and split into each of the 96 wells of a second plate. In
some embodiments, the second plate can include 96, 394, 1000, 2000,
3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, or a number
between any two of these values, wells. Each well can contain 4
types of oligonucleotides, possibly including the universal
sequence (US) and three additional types of oligonucleotides. Each
additional type of oligonucleotides can include an optical label
with an optical moiety, for example a fluorophore or a chromophore,
on the 3' end. The three additional types of oligonucleotides
encode a cellular label part. In some embodiments, each well can
contain, or contain about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50, 60 70, 80, 90, 100,
1000, or a number of range between any two of these values,
additional types of oligonucleotides. Each type of oligonucleotides
can be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40,
50, 60, 70, 80, 90, 100, 1000, 10000, or a number or a range
between any two of these values, nucleotides in length. Each
cellular part can be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9,
10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000, or a number or a
range between any two of these values, nucleotides in length.
The first type of oligonucleotide each can include linker 1,
followed by part 2 of the cellular label (1 of 96, for example),
followed by another linker sequence (linker 2). Linker 2 can be, or
can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60,
70, 80, 90, 100, 1000, 10000, or a number or a range between any
two of these values, nucleotides in length.
The second type of oligonucleotides each can include a duplex
structure that contains a strand complementary to OL4 with a small
5' extension, and a shorter strand complementary to the extension
on the longer strand. The shorter strand can include an optical
label with an optical moiety, for example a fluorophore or a
chromophore, on the 3' end. In some embodiments, the optical label
is on the 5's end, or neither 5's end nor 3's end. The optical
label can be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20,
30, 40, 50, 60, 70, 80, 90, 100, 1000, 2000, 3000, 4000, 5000,
6000, 7000, 8000, 9000, 10000, or a number or a range between any
two of these values, nucleotides in length. The optical moiety can
be selected from a group of spectrally-distinct optical moieties.
Spectrally-distinct optical moieties include optical moieties with
distinguishable emission spectra even if the emission spectral may
overlap.
The third type of oligonucleotides each can include a duplex
structure that contains a strand complementary to OL5 with a small
5' extension, and a shorter strand complementary to the extension
on the longer strand. The shorter strand can include an optical
label with an optical moiety, for example a fluorophore or a
chromophore, on the 3' end. In some embodiments, the optical label
is on the 5's end, or neither 5's end nor 3's end. The optical
moiety can be selected from a group of spectrally-distinct optical
moieties.
The fourth type of oligonucleotides each can include a duplex
structure that contains a strand complementary to OL6 with a small
5' extension, and a shorter strand complementary to the extension
on the longer strand. The shorter strand can include an optical
label with an optical moiety, for example a fluorophore or a
chromophore, on the 3' end. In some embodiments, the optical label
is on the 5's end, or neither 5's end nor 3's end. The optical
moiety can be selected from a group of spectrally-distinct optical
moieties.
After the synthetic particles are distributed across 96 wells of
the second plate and hybridize to oligonucleotides in each well, a
polymerase such as a DNA polymerase and a ligase such as a DNA
ligase can be introduced into each well. DNA polymerase can extend
the universal sequence with cellular label part 2 and linker 2
sequences. DNA ligase can covalently attach the optical moieties
onto the OL oligonucleotides.
At the third encoding step including pool and third split,
synthetic particles from all the wells of the second plate can be
pooled, and split into each of the 96 wells of a third plate. In
some embodiments, the third plate can include 96, 394, 1000, 2000,
3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, or a number
between any two of these values, wells. Each well can contain 4
types of oligonucleotides, possibly including the universal
sequence (US) and three additional types of oligonucleotides. Each
additional type of oligonucleotides can include an optical label
with an optical moiety, for example a fluorophore or a chromophore,
on the 3' end. The three additional types of oligonucleotides
encode a cellular label part. In some embodiments, each well can
contain, or contain about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50, 60 70, 80, 90, 100,
1000, or a number of range between any two of these values,
additional types of oligonucleotides. Each type of oligonucleotides
can be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40,
50, 60, 70, 80, 90, 100, 1000, 10000, or a number or a range
between any two of these values, nucleotides in length. Each
cellular part can be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9,
10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000, or a number or a
range between any two of these values, nucleotides in length.
The first type of oligonucleotide each can include linker 2,
followed by part 3 of the cellular label (1 of 96), followed by
molecular index (randomers) and oligo(dA). The molecular index can
be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50,
60, 70, 80, 90, 100, 1000, 10000, or a number or a range between
any two of these values, nucleotides in length. The oligo(dA) can
be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50,
60, 70, 80, 90, 100, 1000, 10000, or a number or a range between
any two of these values, nucleotides in length.
The second type of oligonucleotides each can include a duplex
structure that contains a strand complementary to OL7 with a small
5' extension, and a shorter strand complementary to the extension
on the longer strand. The shorter strand can include an optical
label with an optical moiety, for example a fluorophore or a
chromophore, on the 3' end. In some embodiments, the optical label
is on the 5's end, or neither 5's end nor 3's end. The optical
label can be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20,
30, 40, 50, 60, 70, 80, 90, 100, 1000, 2000, 3000, 4000, 5000,
6000, 7000, 8000, 9000, 10000, or a number or a range between any
two of these values, nucleotides in length. The optical moiety can
be selected from a group of spectrally-distinct optical moieties.
Spectrally-distinct optical moieties include optical moieties with
distinguishable emission spectra even if the emission spectral may
overlap.
The third type of oligonucleotides each can include a duplex
structure that contains a strand complementary to OL8 with a small
7' extension, and a shorter strand complementary to the extension
on the longer strand. The shorter strand can include an optical
label with an optical moiety, for example a fluorophore or a
chromophore, on the 3' end. In some embodiments, the optical label
is on the 5's end, or neither 5's end nor 3's end. The optical
moiety can be selected from a group of spectrally-distinct optical
moieties.
The fourth type of oligonucleotides each can include a duplex
structure that contains a strand complementary to OL9 with a small
5' extension, and a shorter strand complementary to the extension
on the longer strand. The shorter strand can include an optical
label with an optical moiety, for example a fluorophore or a
chromophore, on the 3' end. In some embodiments, the optical label
is on the 5's end, or neither 5's end nor 3's end. The optical
moiety can be selected from a group of spectrally-distinct optical
moieties.
After the synthetic particles are distributed across 96 wells of
the third plate and hybridize to oligonucleotides in each well, a
polymerase such as a DNA polymerase and a ligase such as a DNA
ligase can be introduced into each well. DNA polymerase can extend
the universal sequence with cellular label part 3 sequence. DNA
ligase can covalently attach the optical moiety onto the OL
oligonucleotides.
At the i.sup.th encoding step including pool and second split,
synthetic particles from all the wells of the (i-1).sup.th plate
can be pooled, and split into each of the 96 wells of a i.sup.th
plate. In some embodiments, the i.sup.th plate can include 96, 394,
1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, or a
number between any two of these values, wells. Each well can
contain m types of oligonucleotides, possibly including the
universal sequence (US) and j additional types of oligonucleotides.
Each additional type of oligonucleotides can include an optical
label with an optical moiety, for example a fluorophore or a
chromophore, on the 3' end. The optical moiety can be part of an
oligonucleotide. The j additional types of oligonucleotides encode
a cellular label part. In some embodiments, each well can contain,
or contain about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 30, 40, 50, 60 70, 80, 90, 100, 1000, or a
number of range between any two of these values, additional types
of oligonucleotides. Each type of oligonucleotides can be, or can
be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70,
80, 90, 100, 1000, 10000, or a number or a range between any two of
these values, nucleotides in length. Each cellular part can be, or
can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60,
70, 80, 90, 100, 1000, or a number or a range between any two of
these values, nucleotides in length.
The first type of oligonucleotide each can include linker (i-1),
followed by part i of the cellular label (1 of 96, for example),
followed by another linker sequence (linker i). Linker i and linker
(i-1) can be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20,
30, 40, 50, 60, 70, 80, 90, 100, 1000, 10000, or a number or a
range between any two of these values, nucleotides in length.
Each of the j additional types of oligonucleotides can include a
duplex structure that contains a strand complementary to OLm with a
small 5' extension, and a shorter strand complementary to the
extension on the longer strand. The shorter strand can include an
optical label with an optical moiety, for example a fluorophore or
a chromophore, on the 3' end. In some embodiments, the optical
label is on the 5's end, or neither 5's end nor 3's end. The
optical label can be, or can be about, 1, 2, 3, 4, 5, 6, 7, 8, 9,
10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000, 2000, 3000, 4000,
5000, 6000, 7000, 8000, 9000, 10000, or a number or a range between
any two of these values, nucleotides in length. The optical moiety
can be selected from a group of k spectrally-distinct optical
moieties. Spectrally-distinct optical moieties include optical
moieties with distinguishable emission spectra even if the emission
spectral may overlap.
After the synthetic particles are distributed across 96 wells of
the i.sup.th plate and hybridize to oligonucleotides in each well,
a polymerase such as a DNA polymerase and a ligase such as a DNA
ligase can be introduced into each well. DNA polymerase can extend
the universal sequence with cellular label part i and linker i
sequences. DNA ligase can covalently attach the optical moieties
onto the OL oligonucleotides. In some embodiments, optical moieties
can be added to each of the OL oligonucleotides by polymerase
extension with optical moieties labeled nucleotides. For an optical
barcode comprising n optical labels, possibly encoded by i encoding
steps each with j additional types of oligonucleotides, each
selected from a group of k spectrally-distinct optical moieties,
the optical barcode can represent k.sup.n=k.sup.i*.sup.j unique
cellular labels.
In some embodiments, the first encoding reaction with coupling of
OS1-3 and 1 of the 96 cell label part 1 can be achieved by an
enzymatic process. In some embodiments, the first encoding reaction
can be incorporated in the lithography process. Instead of
generating 1 type of core synthetic particle with lithography, 96
types of synthetic particles can be generated by lithography. The
universal sequence can be replaced by one of the 96 `cell label
part 1` oligonucleotides. The corresponding combination of OS1,
OS2, and OS3 optical moieties can be attached to the synthetic
particles during the lithography process.
Synthetic Particle Synthesis
In some embodiments, the synthetic particles are generated using
photolithography. In some embodiments, the synthetic particles are
generated using stop flow lithography. To generate synthetic
particles with n OL oligonucleotides, for example 9 OL
oligonucleotides, fabricate a microfluidic device (e.g. PDMS or
NOA) with n input ports converging to a single channel, leading to
1 output port. In each of the input port, feed in a mixture of, for
example, Poly(ethylene glycol) diacrylate PEGDA, photoinitiator, 5'
acrydite modified universal sequence (US) oligonucleotide, and 5'
acrydite modified OL oligonucleotide (OL1 oligonucleotide for input
port 1, OL2 oligonucleotide for input port 2, . . . , OLn
oligonucleotide for input port n). Subsequently, apply pressure at
each of the input ports. The n inputs will form n parallel streams
under laminar flow regime. Expose a region of the converged channel
with, for example, UV through a photomask with the outline of the
shape of the synthetic particle. Upon UV exposure, PEGDA and
acrydite oligonucleotides can crosslink to form a solid hydrogel
synthetic particle, with n regions each with a different OL
oligonucleotide arranged side by side. The synthetic particles can
be collected at the output port and used for the encoding solid
supports such for synthetic particles.
Methods for Decoding Substrates
In some embodiments, the methods can include decoding the solid
support. In some embodiments, the method can include decoding the
plurality of synthetic particles. Decoding the plurality of
synthetic particles can include detecting the optical barcode of
the plurality of synthetic particles. The methods can include
determining the locations of the plurality of synthetic particles.
Detecting the optical barcode of each of the plurality of synthetic
particles to determine the location of each of the plurality of
synthetic particles can include generating an optical image showing
the optical barcodes and the locations of the plurality of
synthetic particles.
The disclosure provides for methods for decoding substrates (e.g.,
arrays) comprising stochastic barcodes. In some embodiments, the
methods comprise decoding the solid support. In some embodiments,
decoding does not rely solely on the use of optical signatures, for
example optical barcodes (although as described herein, the use of
beads with optical signatures can allow the "reuse" of the decoding
probes), but rather on the use of combinatorial decoding nucleic
acids that are added during a decoding step. Decoding can be
performed with sequential hybridizations. The decoding nucleic
acids can hybridize either to a distinct identifier coding nucleic
acid (identifier probe) that is placed on the beads, or to the
bioactive agent itself, for example when the bioactive agent is a
nucleic acid, at least some portion of which is single stranded to
allow hybridization to a decoding probe. The decoding nucleic acids
can be either directly or indirectly labeled. Decoding occurs by
detecting the presence of the label.
The coding nucleic acids (also termed identifier probes (IP) or
identifier nucleic acids) can comprise a primer sequence and an
adjacent decoding sequence. Each decoder (or decoding) probe can
comprise a priming sequence (sometimes referred to herein as an
"invariant sequence"), that can hybridize to the primer sequence,
and at least one decoding nucleotide, generally contained within a
variable sequence. The decoder probes can be made as sets, with
each set comprising at least four subsets that each have a
different decoding nucleotide at the same position i.e. the
detection position, (i.e. adenine, thymidine (or uracil, as
desired), cytosine and guanine), with each nucleotide at the
detection position (detection nucleotide) comprising a unique
label, preferably a fluorophore. The decoder probes can be added
under conditions that allow discrimination of perfect
complementarity and imperfect complementarity. Thus, the decoding
probe that comprises the correct base for basepairing with the
coding nucleotide being interrogated can hybridize the best. The
other decoding probes can be washed away. The detection of the
unique fluorophore associated with the detection nucleotide can
allow for the identification of the coding nucleotide at that
position. By repeating these steps with a new set of decoding
probes that extends the position of the detection nucleotide by one
base, the identity of next coding nucleotide can be elucidated.
Decoding can use a large number of probes. Split and mix
combinatorial synthesis can be used to prepare the decoding
probes.
Parity analysis can be used during decoding to increase the
robustness and accuracy of the system. Parity analysis can refer to
a decoding step wherein the signal of a particular element can be
analyzed across a plurality of decoding stages. That is, following
at least one decoding step, the signal of an array element across
the decoding stages can be analyzed. The signal from a particular
bead can be evaluated across multiple stages. Although the analysis
can include any parameter that can be obtained from the signals,
such as evaluating the total signal obtained across the stages, the
parity of the signals across the stages can be analyzed.
Parity can refer to the digital or modular readout of signals, i.e.
odd or even, when binary signals are used. The digit sum of the
signals across a plurality of stages can be translated into a
parity determination. The parity determination can be useful in
evaluating the decoding process. For example, codes can be designed
to have an odd number of a particular signal, for example a red
signal, when viewed across all stages or decoding steps, or a
pre-determined plurality of stages or decoding steps. The detection
of an even number of red stages can provide an indication that an
error has occurred at some point in decoding. When this result is
obtained, the faulty code can either be discarded, or the analysis
repeated.
The disclosure provides for introducing a "redundant stage" into
the decoding system. A redundant stage can refer to a stage that
serves as a parity check. That is, following the decoding stages,
an additional stage can be included to analyze the parity. This
analysis can provide an indication of the competence or validity of
the decoding. When codes are designed with a pre-determined parity,
the redundant stage can be used to detect the parity of the signals
obtained from the decoding step. The redundant stage can detect
errors in parity because if there has been an error in decoding,
the parity detected following the redundant stage will be different
from the parity designed into the codes.
In some embodiments, decoding can occur through the use of 8-mer
oligonucleotides strung together to create a decoding
oligonucleotide with a few 8-mers on it. The decoding
oligonucleotide can comprise at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or
10 or more 8-mers on it. The decoding oligonucleotide can comprise
at most 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more 8-mers on it. The
decoding oligonucleotide can hybridize to a few different
stochastic barcodes (e.g., by hybridizing its different 8-mer
regions to different 8-mer regions on stochastic barcodes). The
decoding oligonucleotide can be fluorescently labeled, melted off,
and sequenced. The decoding oligonucleotides can be fluorescently
labeled in different colors. The decoding oligonucleotides can be
fluorescently labeled with the same color but with various levels
of fluorescent intensity, thereby generating a "gray-scale" map of
a probe. Repeating this can provide a solvable map of where each
8-mer of a stochastic barcode is in relation to each other. The
method can be repeated at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or
more times. The method can be repeated at most 1, 2, 3, 4, 5, 6, 7,
8, 9, or 10 or more times.
In some embodiments, decoding can be performed by sequencing by
synthesis (e.g., using 454 and/or ion torrent sequencing). Decoding
can be performed by imaging of optically encoded beads. For
example, beads can be encoded with quantum dots or fluorophores
which can be embedded in the beads. The quantum dots or
fluorophores can be used in the decoding process. In some
embodiments, the optically encoded beads can comprise a dye. The
dye can be used to distinguish beads with different stochastic
barcodes. Decoding can occur with the use of physically encoded
solid supports (e.g., beads). For example, a bead can be patterned
or engraved with an identifier. The identifier can be etched into
the bead with a laser or with lithography methods. In some
embodiments, the beads can be physically encoded based on size
and/or shape. Decoding can occur with electronically encoded beads.
Decoding can use an electronic readout to read the electronic
identifier in the beads. An electronic identifier can include, for
example, an RFID tag, an electrical resistance, and/or an
electrical capacitance.
Diffusion Across a Substrate
When a sample (e.g., cell) is stochastically barcoded according to
the methods of the disclosure, the cell can be lysed. In some
embodiments, lysis of a cell can result in the diffusion of the
contents of the lysis (e.g., cell contents) away from the initial
location of lysis. In other words, the lysis contents can move into
a larger surface area than the surface area taken up by the
cell.
Diffusion of sample lysis mixture (e.g., comprising targets) can be
modulated by various parameters including, but not limited to,
viscosity of the lysis mixture, temperature of the lysis mixture,
the size of the targets, the size of physical barriers in a
substrate, the concentration of the lysis mixture, and the like.
For example, the temperature of the lysis reaction can be performed
at a temperature of at least 1, 2, 3, 4, 5, 10, 15, 20, 25, 30, 35,
or 40 C or more. The temperature of the lysis reaction can be
performed at a temperature of at most 1, 2, 3, 4, 5, 10, 15, 20,
25, 30, 35, or 40 C or more. The viscosity of the lysis mixture can
be altered by, for example, adding thickening reagents (e.g.,
glycerol, beads) to slow the rate of diffusion. The viscosity of
the lysis mixture can be altered by, for example, adding thinning
reagents (e.g., water) to increase the rate of diffusion. A
substrate can comprise physical barriers (e.g., wells, microwells,
microhills) that can alter the rate of diffusion of targets from a
sample. The concentration of the lysis mixture can be altered to
increase or decrease the rate of diffusion of targets from a
sample. The concentration of a lysis mixture can be increased or
decreased by at least 1, 2, 3, 4, 5, 6, 7, 8, or 9 or more fold.
The concentration of a lysis mixture can be increased or decreased
by at most 1, 2, 3, 4, 5, 6, 7, 8, or 9 or more fold.
The rate of diffusion can be increased. The rate of diffusion can
be decreased. The rate of diffusion of a lysis mixture can be
increased or decreased by at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10
or more fold compared to an un-altered lysis mixture. The rate of
diffusion of a lysis mixture can be increased or decreased by at
most 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more fold compared to an
un-altered lysis mixture. The rate of diffusion of a lysis mixture
can be increased or decreased by at least 10, 20, 30, 40, 50, 60,
70, 80, 90 or 100% compared to an un-altered lysis mixture. The
rate of diffusion of a lysis mixture can be increased or decreased
by at least 10, 20, 30, 40, 50, 60, 70, 80, 90 or 100% compared to
an un-altered lysis mixture.
Sample Imaging
The disclosure provides for compositions, methods, kits, and
systems for identifying the spatial location of nucleic acids in a
target from a sample. FIG. 12 illustrates an exemplary embodiment
of the homopolymer tailing method of the disclosure The disclosure
provides for a substrate 1210 comprising a plurality of probes 1205
attached to the surface of the substrate. The substrate 1210 can be
a microarray. The plurality of probes 1205 can comprise an
oligo(dT). The plurality of probes 1205 can comprise a
gene-specific sequence. The plurality of probes 105 can comprise a
stochastic barcode. A sample (e.g., cells) 1215 can be placed
and/or grown on the substrate 1210. The substrate comprising the
sample can be analyzed 1220, for example by imaging and/or
immunohistochemistry. The sample 1215 can be lysed 1225 on the
substrate 1210. The nucleic acids 1230 from the sample 1215 can
associate (e.g., hybridize) with the plurality of probes 1205 on
the substrate 1210. In some embodiments, the nucleic acids 1230 can
be reverse transcribed, homopolymer tailed, and/or amplified (e.g.,
with bridge amplification). The amplified nucleic acids can be
interrogated 1235 with detection probes 1240 (e.g., fluorescent
probes). The detection probes 1240 can be gene-specific probes. The
location of binding of the detection probes 1240 on the substrate
1210 can be correlated with the image of the substrate, thereby
producing a map that indicates the spatial location of nucleic
acids in the sample.
In some embodiments, the methods of the disclosure can comprise
making 1245 a replicate 1246 of the original substrate 1210. The
replicate substrate 1246 can comprise a plurality of probes 1231.
The plurality of probes 1231 can be the same as the plurality of
probes 1205 on the original substrate 1210. The plurality of probes
1231 can be different than the plurality of probes 1205 on the
original substrate 1210. For example, the plurality of probes 1205
can be oligo(dT) probes and the plurality of probes 1231 on the
replicate substrate 1246 can be gene-specific probes. The replicate
substrate can be processed like the original substrate, such as
with interrogation by detection (e.g., fluorescent) probes.
Data Analysis and Display Software
Data Analysis and Visualization of Spatial Resolution of
Targets
The disclosure provides for methods for estimating the number and
position of targets with stochastic barcoding and digital counting
using spatial labels. The data obtained from the methods of the
disclosure can be visualized on a map. A map of the number and
location of targets from a sample can be constructed using
information generated using the methods described herein. The map
can be used to locate a physical location of a target. The map can
be used to identify the location of multiple targets. The multiple
targets can be the same species of target, or the multiple targets
can be multiple different targets. For example a map of a brain can
be constructed to show the digital count and location of multiple
targets.
The map can be generated from data from a single sample. The map
can be constructed using data from multiple samples, thereby
generating a combined map. The map can be constructed with data
from tens, hundreds, and/or thousands of samples. A map constructed
from multiple samples can show a distribution of digital counts of
targets associated with regions common to the multiple samples. For
example, replicated assays can be displayed on the same map. At
least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more replicates can be
displayed (e.g., overlaid) on the same map. At most 1, 2, 3, 4, 5,
6, 7, 8, 9, or 10 or more replicates can be displayed (e.g.,
overlaid) on the same map. The spatial distribution and number of
targets can be represented by a variety of statistics.
Combining data from multiple samples can increase the locational
resolution of the combined map. The orientation of multiple samples
can be registered by common landmarks, wherein the individual
locational measurements across samples are at least in part
non-contiguous. A particular example is sectioning a sample using a
microtome on one axis and then sectioning a second sample along a
different access. The combined dataset will give three dimensional
spatial locations associated with digital counts of targets.
Multiplexing the above approach will allow for high resolution
three dimensional maps of digital counting statistics.
In some embodiments of the instrument system, the system will
comprise computer-readable media that includes code for providing
data analysis for the sequence datasets generated by performing
single cell, stochastic barcoding assays. Examples of data analysis
functionality that can be provided by the data analysis software
include, but are not limited to, (i) algorithms for
decoding/demultiplexing of the sample label, cellular label,
spatial label, and molecular label, and target sequence data
provided by sequencing the stochastic barcode library created in
running the assay, (ii) algorithms for determining the number of
reads per gene per cell, and the number of unique transcript
molecules per gene per cell, based on the data, and creating
summary tables, (iii) statistical analysis of the sequence data,
e.g. for clustering of cells by gene expression data, or for
predicting confidence intervals for determinations of the number of
transcript molecules per gene per cell, etc., (iv) algorithms for
identifying sub-populations of rare cells, for example, using
principal component analysis, hierarchical clustering, k-mean
clustering, self-organizing maps, neural networks etc., (v)
sequence alignment capabilities for alignment of gene sequence data
with known reference sequences and detection of mutation,
polymorphic markers and splice variants, and (vi) automated
clustering of molecular labels to compensate for amplification or
sequencing errors. In some embodiments, commercially-available
software can be used to perform all or a portion of the data
analysis, for example, the Seven Bridges
(https://www.sbgenomics.com/) software can be used to compile
tables of the number of copies of one or more genes occurring in
each cell for the entire collection of cells. In some embodiments,
the data analysis software can include options for outputting the
sequencing results in useful graphical formats, e.g. heatmaps that
indicate the number of copies of one or more genes occurring in
each cell of a collection of cells. In some embodiments, the data
analysis software can further comprise algorithms for extracting
biological meaning from the sequencing results, for example, by
correlating the number of copies of one or more genes occurring in
each cell of a collection of cells with a type of cell, a type of
rare cell, or a cell derived from a subject having a specific
disease or condition. In some embodiment, the data analysis
software can further comprise algorithms for comparing populations
of cells across different biological samples.
In some embodiments all of the data analysis functionality can be
packaged within a single software package. In some embodiments, the
complete set of data analysis capabilities can comprise a suite of
software packages. In some embodiments, the data analysis software
can be a standalone package that is made available to users
independently of the assay instrument system. In some embodiments,
the software can be web-based, and can allow users to share
data.
In some embodiments all of the data analysis functionality can be
packaged within a single software package. In some embodiments, the
complete set of data analysis capabilities can comprise a suite of
software packages. In some embodiments, the data analysis software
can be a standalone package that is made available to users
independently of the assay instrument system. In some embodiments,
the software can be web-based, and can allow users to share
data.
System Processors and Networks
In general, the computer or processor included in the presently
disclosed instrument systems, as illustrated in FIG. 13, can be
further understood as a logical apparatus that can read
instructions from media 1311 or a network port 1305, which can
optionally be connected to server 1309 having fixed media 1312. The
system 1300, such as shown in FIG. 13 can include a CPU 1301, disk
drives 1303, optional input devices such as keyboard 1315 or mouse
1316 and optional monitor 1307. Data communication can be achieved
through the indicated communication medium to a server at a local
or a remote location. The communication medium can include any
means of transmitting or receiving data. For example, the
communication medium can be a network connection, a wireless
connection or an internet connection. Such a connection can provide
for communication over the World Wide Web. It is envisioned that
data relating to the present disclosure can be transmitted over
such networks or connections for reception or review by a party
1322 as illustrated in FIG. 13.
FIG. 14 illustrates an exemplary embodiment of a first example
architecture of a computer system 1400 that can be used in
connection with example embodiments of the present disclosure. As
depicted in FIG. 14, the example computer system can include a
processor 1402 for processing instructions. Non-limiting examples
of processors include: Intel Xeon.TM. processor, AMD Opteron.TM.
processor, Samsung 32-bit RISC ARM 1176JZ(F)-S v1.0.TM. processor,
ARM Cortex-A8 Samsung S5PC100.TM. processor, ARM Cortex-A8 Apple
A4.TM. processor, Marvell PXA 930.TM. processor, or a
functionally-equivalent processor. Multiple threads of execution
can be used for parallel processing. In some embodiments, multiple
processors or processors with multiple cores can also be used,
whether in a single computer system, in a cluster, or distributed
across systems over a network comprising a plurality of computers,
cell phones, or personal data assistant devices.
As illustrated in FIG. 14, a high speed cache 1404 can be connected
to, or incorporated in, the processor 1402 to provide a high speed
memory for instructions or data that have been recently, or are
frequently, used by processor 1402. The processor 1402 is connected
to a north bridge 1406 by a processor bus 1408. The north bridge
1406 is connected to random access memory (RAM) 1410 by a memory
bus 1412 and manages access to the RAM 1410 by the processor 1402.
The north bridge 1406 is also connected to a south bridge 1414 by a
chipset bus 1416. The south bridge 1414 is, in turn, connected to a
peripheral bus 1418. The peripheral bus can be, for example, PCI,
PCI-X, PCI Express, or other peripheral bus. The north bridge and
south bridge are often referred to as a processor chip set and
manage data transfer between the processor, RAM, and peripheral
components on the peripheral bus 118. In some alternative
architectures, the functionality of the north bridge can be
incorporated into the processor instead of using a separate north
bridge chip.
In some embodiments, system 1400 can include an accelerator card
1422 attached to the peripheral bus 1418. The accelerator can
include field programmable gate arrays (FPGAs) or other hardware
for accelerating certain processing. For example, an accelerator
can be used for adaptive data restructuring or to evaluate
algebraic expressions used in extended set processing.
Software and data are stored in external storage 1424 and can be
loaded into RAM 1410 or cache 1404 for use by the processor. The
system 1400 includes an operating system for managing system
resources; non-limiting examples of operating systems include:
Linux, Windows.TM., MACOS.TM., BlackBerry OS.TM., iOS.TM., and
other functionally-equivalent operating systems, as well as
application software running on top of the operating system for
managing data storage and optimization in accordance with example
embodiments of the present invention.
In this example, system 1400 also includes network interface cards
(NICs) 1420 and 1421 connected to the peripheral bus for providing
network interfaces to external storage, such as Network Attached
Storage (NAS) and other computer systems that can be used for
distributed parallel processing.
FIG. 15 illustrates an exemplary diagram showing a network 1500
with a plurality of computer systems 1502a, and 1502b, a plurality
of cell phones and personal data assistants 1502c, and Network
Attached Storage (NAS) 1504a, and 1504b. In example embodiments,
systems 1512a, 1512b, and 1512c can manage data storage and
optimize data access for data stored in Network Attached Storage
(NAS) 1514a and 1514b. A mathematical model can be used for the
data and be evaluated using distributed parallel processing across
computer systems 1512a, and 1512b, and cell phone and personal data
assistant systems 1512c. Computer systems 1512a, and 1512b, and
cell phone and personal data assistant systems 1512c can also
provide parallel processing for adaptive data restructuring of the
data stored in Network Attached Storage (NAS) 1514a and 1514b. FIG.
15 illustrates an example only, and a wide variety of other
computer architectures and systems can be used in conjunction with
the various embodiments of the present invention. For example, a
blade server can be used to provide parallel processing. Processor
blades can be connected through a back plane to provide parallel
processing. Storage can also be connected to the back plane or as
Network Attached Storage (NAS) through a separate network
interface.
In some example embodiments, processors can maintain separate
memory spaces and transmit data through network interfaces, back
plane or other connectors for parallel processing by other
processors. In other embodiments, some or all of the processors can
use a shared virtual address memory space.
FIG. 16 illustrates an exemplary a block diagram of a
multiprocessor computer system 1600 using a shared virtual address
memory space in accordance with an example embodiment. The system
includes a plurality of processors 1602a-f that can access a shared
memory subsystem 1604. The system incorporates a plurality of
programmable hardware memory algorithm processors (MAPs) 1606a-f in
the memory subsystem 1604. Each MAP 1606a-f can comprise a memory
1608a-f and one or more field programmable gate arrays (FPGAs)
1610a-f. The MAP provides a configurable functional unit and
particular algorithms or portions of algorithms can be provided to
the FPGAs 1610a-f for processing in close coordination with a
respective processor. For example, the MAPs can be used to evaluate
algebraic expressions regarding the data model and to perform
adaptive data restructuring in example embodiments. In this
example, each MAP is globally accessible by all of the processors
for these purposes. In one configuration, each MAP can use Direct
Memory Access (DMA) to access an associated memory 308a-f, allowing
it to execute tasks independently of, and asynchronously from, the
respective microprocessor 302a-f. In this configuration, a MAP can
feed results directly to another MAP for pipelining and parallel
execution of algorithms.
The above computer architectures and systems are examples only, and
a wide variety of other computer, cell phone, and personal data
assistant architectures and systems can be used in connection with
example embodiments, including systems using any combination of
general processors, co-processors, FPGAs and other programmable
logic devices, system on chips (SOLs), application specific
integrated circuits (ASICs), and other processing and logic
elements. In some embodiments, all or part of the computer system
can be implemented in software or hardware. Any variety of data
storage media can be used in connection with example embodiments,
including random access memory, hard drives, flash memory, tape
drives, disk arrays, Network Attached Storage (NAS) and other local
or distributed data storage devices and systems.
In example embodiments, the computer subsystem of the present
disclosure can be implemented using software modules executing on
any of the above or other computer architectures and systems. In
other embodiments, the functions of the system can be implemented
partially or completely in firmware, programmable logic devices
such as field programmable gate arrays (FPGAs), system on chips
(SOLs), application specific integrated circuits (ASICs), or other
processing and logic elements. For example, the Set Processor and
Optimizer can be implemented with hardware acceleration through the
use of a hardware accelerator card, such as accelerator card.
Kits
Disclosed herein are kits for performing single cell, stochastic
barcoding assays. The kit can comprise one or more substrates
(e.g., microwell array), either as a free-standing substrate (or
chip) comprising one or more microwell arrays, or packaged within
one or more flow-cells or cartridges, and one or more solid support
suspensions, wherein the individual solid supports within a
suspension comprise a plurality of attached stochastic barcodes of
the disclosure. In some embodiments, the kit can further comprise a
mechanical fixture for mounting a free-standing substrate in order
to create reaction wells that facilitate the pipetting of samples
and reagents into the substrate. The kit can further comprise
reagents, e.g. lysis buffers, rinse buffers, or hybridization
buffers, for performing the stochastic barcoding assay. The kit can
further comprise reagents (e.g. enzymes, primers, or buffers) for
performing nucleic acid extension reactions, for example, reverse
transcription reactions. The kit can further comprise reagents
(e.g. enzymes, universal primers, sequencing primers,
target-specific primers, or buffers) for performing amplification
reactions to prepare sequencing libraries. The kit can comprise
reagents for performing the label lithography method of the
disclosure (e.g., pre-spatial labels and reagents for activating
the activatable consensus sequence).
The kit can comprise one or more molds, for example, molds
comprising an array of micropillars, for casting substrates (e.g.,
microwell arrays), and one or more solid supports (e.g., bead),
wherein the individual beads within a suspension comprise a
plurality of attached stochastic barcodes of the disclosure. The
kit can further comprise a material for use in casting substrates
(e.g. agarose, a hydrogel, PDMS, and the like).
The kit can comprise one or more substrates that are pre-loaded
with solid supports comprising a plurality of attached stochastic
barcodes of the disclosure. In some embodiments, there can be on
solid support per microwell of the substrate. In some embodiments,
the plurality of stochastic barcodes can be attached directly to a
surface of the substrate, rather than to a solid support. In any of
these embodiments, the one or more microwell arrays can be provided
in the form of free-standing substrates (or chips), or they can be
packed in flow-cells or cartridges.
In some embodiments of the disclosed kits, the kit can comprise one
or more cartridges that incorporate one or more substrates. In some
embodiments, the one or more cartridges can further comprise one or
more pre-loaded solid supports, wherein the individual solid
supports within a suspension comprise a plurality of attached
stochastic barcodes of the disclosure. In some embodiments, the
beads can be pre-distributed into the one or more microwell arrays
of the cartridge. In some embodiments, the beads, in the form of
suspensions, can be pre-loaded and stored within reagent wells of
the cartridge. In some embodiments, the one or more cartridges can
further comprise other assay reagents that are pre-loaded and
stored within reagent reservoirs of the cartridges.
Disclosed herein are kits for performing spatial analysis of
nucleic acids in a sample. The kit can comprise one or more
substrates (e.g., array) of the disclosure, either as a
free-standing substrate (or chip) comprising one or more arrays.
The array can comprise probes of the disclosure. The kit can
comprise one or more replicate arrays of the disclosure. The
replicate arrays can comprise either gene-specific or
oligo(dT)/poly(A) probes.
The kit can further comprise reagents, e.g. lysis buffers, rinse
buffers, or hybridization buffers, for performing the assay. The
kit can further comprise reagents (e.g. enzymes, primers, dNTPs,
NTPs, RNase inhibitors, or buffers) for performing nucleic acid
extension reactions, for example, reverse transcription reactions
and primer extension reactions. The kit can further comprise
reagents (e.g. enzymes, universal primers, sequencing primers,
target-specific primers, or buffers) for performing amplification
reactions to prepare sequencing libraries. The kit can comprise
reagents for homopolymer tailing of molecules (e.g., a terminal
transferase enzyme, and dNTPs). The kit can comprise reagents for,
for example, any enzymatic cleavage of the disclosure (e.g., Exol
nuclease, restriction enzyme).
Kits can generally include instructions for carrying out one or
more of the methods described herein. Instructions included in kits
can be affixed to packaging material or can be included as a
package insert. While the instructions are typically written or
printed materials they are not limited to such. Any medium capable
of storing such instructions and communicating them to an end user
is contemplated by the disclosure. Such media can include, but are
not limited to, electronic storage media (e.g., magnetic discs,
tapes, cartridges, chips), optical media (e.g., CD ROM), RF tags,
and the like. As used herein, the term "instructions" can include
the address of an internet site that provides the instructions.
Devices
Flow Cells
The microwell array substrate can be packaged within a flow cell
that provides for convenient interfacing with the rest of the fluid
handling system and facilitates the exchange of fluids, e.g. cell
and solid support suspensions, lysis buffers, rinse buffers, etc.,
that are delivered to the microwell array and/or emulsion droplet.
Design features can include: (i) one or more inlet ports for
introducing cell samples, solid support suspensions, or other assay
reagents, (ii) one or more microwell array chambers designed to
provide for uniform filling and efficient fluid-exchange while
minimizing back eddies or dead zones, and (iii) one or more outlet
ports for delivery of fluids to a sample collection point or a
waste reservoir. The design of the flow cell can include a
plurality of microarray chambers that interface with a plurality of
microwell arrays such that one or more different cell samples can
be processed in parallel. The design of the flow cell can further
include features for creating uniform flow velocity profiles, i.e.
"plug flow", across the width of the array chamber to provide for
more uniform delivery of cells and beads to the microwells, for
example, by using a porous barrier located near the chamber inlet
and upstream of the microwell array as a "flow diffuser", or by
dividing each array chamber into several subsections that
collectively cover the same total array area, but through which the
divided inlet fluid stream flows in parallel. In some embodiments,
the flow cell can enclose or incorporate more than one microwell
array substrate. In some embodiments, the integrated microwell
array/flow cell assembly can constitute a fixed component of the
system. In some embodiments, the microwell array/flow cell assembly
can be removable from the instrument.
In general, the dimensions of fluid channels and the array
chamber(s) in flow cell designs will be optimized to (i) provide
uniform delivery of cells and beads to the microwell array, and
(ii) to minimize sample and reagent consumption. In some
embodiments, the width of fluid channels will be between 50 um and
20 mm. In other embodiments, the width of fluid channels can be at
least 50 um, at least 100 um, at least 200 um, at least 300 um, at
least 400 um, at least 500 um, at least 750 um, at least 1 mm, at
least 2.5 mm, at least 5 mm, at least 10 mm, at least 20 mm, at
least 50 mm, at least 100 mm, or at least 150 mm. In yet other
embodiments, the width of fluid channels can be at most 150 mm, at
most 100 mm, at most 50 mm, at most 20 mm, at most 10 mm, at most 5
mm, at most 2.5 mm, at most 1 mm, at most 750 um, at most 500 um,
at most 400 um, at most 300 um, at most 200 um, at most 100 um, or
at most 50 um. In one embodiment, the width of fluid channels is
about 2 mm. The width of the fluid channels can fall within any
range bounded by any of these values (e.g. from about 250 um to
about 3 mm).
In some embodiments, the depth of the fluid channels will be
between 50 um and 2 mm. In other embodiments, the depth of fluid
channels can be at least 50 um, at least 100 um, at least 200 um,
at least 300 um, at least 400 um, at least 500 um, at least 750 um,
at least 1 mm, at least 1.25 mm, at least 1.5 mm, at least 1.75 mm,
or at least 2 mm. In yet other embodiments, the depth of fluid
channels can at most 2 mm, at most 1.75 mm, at most 1.5 mm, at most
1.25 mm, at most 1 mm, at most 750 um, at most 500 um, at most 400
um, at most 300 um, at most 200 um, at most 100 um, or at most 50
um. In one embodiment, the depth of the fluid channels is about 1
mm. The depth of the fluid channels can fall within any range
bounded by any of these values (e.g. from about 800 um to about 1
mm).
Flow cells can be fabricated using a variety of techniques and
materials known to those of skill in the art. In general, the flow
cell will be fabricated as a separate part and subsequently either
mechanically clamped or permanently bonded to the microwell array
substrate. Examples of suitable fabrication techniques include
conventional machining, CNC machining, injection molding, 3D
printing, alignment and lamination of one or more layers of laser
or die-cut polymer films, or any of a number of microfabrication
techniques such as photolithography and wet chemical etching, dry
etching, deep reactive ion etching, or laser micromachining. Once
the flow cell part has been fabricated it can be attached to the
microwell array substrate mechanically, e.g. by clamping it against
the microwell array substrate (with or without the use of a
gasket), or it can be bonded directly to the microwell array
substrate using any of a variety of techniques (depending on the
choice of materials used) known to those of skill in the art, for
example, through the use of anodic bonding, thermal bonding, or any
of a variety of adhesives or adhesive films, including epoxy-based,
acrylic-based, silicone-based, UV curable, polyurethane-based, or
cyanoacrylate-based adhesives.
Flow cells can be fabricated using a variety of materials known to
those of skill in the art. In general, the choice of material used
will depend on the choice of fabrication technique used, and vice
versa. Examples of suitable materials include, but are not limited
to, silicon, fused-silica, glass, any of a variety of polymers,
e.g. polydimethylsiloxane (PDMS; elastomer), polymethylmethacrylate
(PMMA), polycarbonate (PC), polypropylene (PP), polyethylene (PE),
high density polyethylene (HDPE), polyimide, cyclic olefin polymers
(COP), cyclic olefin copolymers (COL), polyethylene terephthalate
(PET), epoxy resins, metals (e.g. aluminum, stainless steel,
copper, nickel, chromium, and titanium), a non-stick material such
as teflon (PTFE), or a combination of these materials.
Cartridges
In some embodiments of the system, the microwell array, with or
without an attached flow cell, can be packaged within a consumable
cartridge that interfaces with the instrument system. Design
features of cartridges can include (i) one or more inlet ports for
creating fluid connections with the instrument or manually
introducing cell samples, bead suspensions, or other assay reagents
into the cartridge, (ii) one or more bypass channels, i.e. for
self-metering of cell samples and bead suspensions, to avoid
overfilling or back flow, (iii) one or more integrated microwell
array/flow cell assemblies, or one or more chambers within which
the microarray substrate(s) are positioned, (iv) integrated
miniature pumps or other fluid actuation mechanisms for controlling
fluid flow through the device, (v) integrated miniature valves (or
other containment mechanisms) for compartmentalizing pre-loaded
reagents (for example, bead suspensions) or controlling fluid flow
through the device, (vi) one or more vents for providing an escape
path for trapped air, (vii) one or more sample and reagent waste
reservoirs, (viii) one or more outlet ports for creating fluid
connections with the instrument or providing a processed sample
collection point, (ix) mechanical interface features for
reproducibly positioning the removable, consumable cartridge with
respect to the instrument system, and for providing access so that
external magnets can be brought into close proximity with the
microwell array, (x) integrated temperature control components or a
thermal interface for providing good thermal contact with the
instrument system, and (xi) optical interface features, e.g. a
transparent window, for use in optical interrogation of the
microwell array.
The cartridge can be designed to process more than one sample in
parallel. The cartridge can further comprise one or more removable
sample collection chamber(s) that are suitable for interfacing with
stand-alone PCR thermal cyclers or sequencing instruments. The
cartridge itself can be suitable for interfacing with stand-alone
PCR thermal cyclers or sequencing instruments. The term "cartridge"
as used in this disclosure can be meant to include any assembly of
parts which contains the sample and beads during performance of the
assay.
The cartridge can further comprise components that are designed to
create physical or chemical barriers that prevent diffusion of (or
increase path lengths and diffusion times for) large molecules in
order to minimize cross-contamination between microwells. Examples
of such barriers can include, but are not limited to, a pattern of
serpentine channels used for delivery of cells and solid supports
(e.g., beads) to the microwell array, a retractable platen or
deformable membrane that is pressed into contact with the surface
of the microwell array substrate during lysis or incubation steps,
the use of larger beads, e.g. Sephadex beads as described
previously, to block the openings of the microwells, or the release
of an immiscible, hydrophobic fluid from a reservoir within the
cartridge during lysis or incubation steps, to effectively separate
and compartmentalize each microwell in the array.
The dimensions of fluid channels and the array chamber(s) in
cartridge designs can be optimized to (i) provide uniform delivery
of cells and beads to the microwell array, and (ii) to minimize
sample and reagent consumption. The width of fluid channels can be
between 50 micrometers and 20 mm. In other embodiments, the width
of fluid channels can be at least 50 micrometers, at least 100
micrometers, at least 200 micrometers, at least 300 micrometers, at
least 400 micrometers, at least 500 micrometers, at least 750
micrometers, at least 1 mm, at least 2.5 mm, at least 5 mm, at
least 10 mm, or at least 20 mm. In yet other embodiments, the width
of fluid channels can at most 20 mm, at most 10 mm, at most 5 mm,
at most 2.5 mm, at most 1 mm, at most 750 micrometers, at most 500
micrometers, at most 400 micrometers, at most 300 micrometers, at
most 200 micrometers, at most 100 micrometers, or at most 50
micrometers. The width of fluid channels can be about 2 mm. The
width of the fluid channels can fall within any range bounded by
any of these values (e.g. from about 250 um to about 3 mm).
The fluid channels in the cartridge can have a depth. The depth of
the fluid channels in cartridge designs can be between 50
micrometers and 2 mm. The depth of fluid channels can be at least
50 micrometers, at least 100 micrometers, at least 200 micrometers,
at least 300 micrometers, at least 400 micrometers, at least 500
micrometers, at least 750 micrometers, at least 1 mm, at least 1.25
mm, at least 1.5 mm, at least 1.75 mm, or at least 2 mm. The depth
of fluid channels can at most 2 mm, at most 1.75 mm, at most 1.5
mm, at most 1.25 mm, at most 1 mm, at most 750 micrometers, at most
500 micrometers, at most 400 micrometers, at most 300 micrometers,
at most 200 micrometers, at most 100 micrometers, or at most 50
micrometers. The depth of the fluid channels can be about 1 mm. The
depth of the fluid channels can fall within any range bounded by
any of these values (e.g. from about 800 micrometers to about 1
mm).
Cartridges can be fabricated using a variety of techniques and
materials known to those of skill in the art. In general, the
cartridges will be fabricated as a series of separate component
parts (FIGS. 17A-C) and subsequently assembled using any of a
number of mechanical assemblies or bonding techniques. Examples of
suitable fabrication techniques include, but are not limited to,
conventional machining, CNC machining, injection molding,
thermoforming, and 3D printing. Once the cartridge components have
been fabricated they can be mechanically assembled using screws,
clips, and the like, or permanently bonded using any of a variety
of techniques (depending on the choice of materials used), for
example, through the use of thermal bonding/welding or any of a
variety of adhesives or adhesive films, including epoxy-based,
acrylic-based, silicone-based, UV curable, polyurethane-based, or
cyanoacrylate-based adhesives.
Cartridge components can be fabricated using any of a number of
suitable materials, including but not limited to silicon,
fused-silica, glass, any of a variety of polymers, e.g.
polydimethylsiloxane (PDMS; elastomer), polymethylmethacrylate
(PMMA), polycarbonate (PC), polypropylene (PP), polyethylene (PE),
high density polyethylene (HDPE), polyimide, cyclic olefin polymers
(COP), cyclic olefin copolymers (COL), polyethylene terephthalate
(PET), epoxy resins, non-stick materials such as teflon (PTFE),
metals (e.g. aluminum, stainless steel, copper, nickel, chromium,
and titanium), or any combination thereof.
The inlet and outlet features of the cartridge can be designed to
provide convenient and leak-proof fluid connections with the
instrument, or can serve as open reservoirs for manual pipetting of
samples and reagents into or out of the cartridge. Examples of
convenient mechanical designs for the inlet and outlet port
connectors can include, but are not limited to, threaded
connectors, Luer lock connectors, Luer slip or "slip tip"
connectors, press fit connectors, and the like. The inlet and
outlet ports of the cartridge can further comprise caps,
spring-loaded covers or closures, or polymer membranes that can be
opened or punctured when the cartridge is positioned in the
instrument, and which serve to prevent contamination of internal
cartridge surfaces during storage or which prevent fluids from
spilling when the cartridge is removed from the instrument. The one
or more outlet ports of the cartridge can further comprise a
removable sample collection chamber that is suitable for
interfacing with stand-alone PCR thermal cyclers or sequencing
instruments.
The cartridge can include integrated miniature pumps or other fluid
actuation mechanisms for control of fluid flow through the device.
Examples of suitable miniature pumps or fluid actuation mechanisms
can include, but are not limited to, electromechanically- or
pneumatically-actuated miniature syringe or plunger mechanisms,
membrane diaphragm pumps actuated pneumatically or by an external
piston, pneumatically-actuated reagent pouches or bladders, or
electro-osmotic pumps.
The cartridge can include miniature valves for compartmentalizing
pre-loaded reagents or controlling fluid flow through the device.
Examples of suitable miniature valves can include, but are not
limited to, one-shot "valves" fabricated using wax or polymer plugs
that can be melted or dissolved, or polymer membranes that can be
punctured; pinch valves constructed using a deformable membrane and
pneumatic, magnetic, electromagnetic, or electromechanical
(solenoid) actuation, one-way valves constructed using deformable
membrane flaps, and miniature gate valves.
The cartridge can include vents for providing an escape path for
trapped air. Vents can be constructed according to a variety of
techniques, for example, using a porous plug of
polydimethylsiloxane (PDMS) or other hydrophobic material that
allows for capillary wicking of air but blocks penetration by
water.
The mechanical interface features of the cartridge can provide for
easily removable but highly precise and repeatable positioning of
the cartridge relative to the instrument system. Suitable
mechanical interface features can include, but are not limited to,
alignment pins, alignment guides, mechanical stops, and the like.
The mechanical design features can include relief features for
bringing external apparatus, e.g. magnets or optical components,
into close proximity with the microwell array chamber (FIG.
17B).
The cartridge can also include temperature control components or
thermal interface features for mating to external temperature
control modules. Examples of suitable temperature control elements
can include, but are not limited to, resistive heating elements,
miniature infrared-emitting light sources, Peltier heating or
cooling devices, heat sinks, thermistors, thermocouples, and the
like. Thermal interface features can be fabricated from materials
that are good thermal conductors (e.g. copper, gold, silver, etc.)
and can comprise one or more flat surfaces capable of making good
thermal contact with external heating blocks or cooling blocks.
The cartridge can include optical interface features for use in
optical imaging or spectroscopic interrogation of the microwell
array. The cartridge can include an optically transparent window,
e.g. the microwell substrate itself or the side of the flow cell or
microarray chamber that is opposite the microwell array, fabricated
from a material that meets the spectral requirements for the
imaging or spectroscopic technique used to probe the microwell
array. Examples of suitable optical window materials can include,
but are not limited to, glass, fused-silica, polymethylmethacrylate
(PMMA), polycarbonate (PC), cyclic olefin polymers (COP), or cyclic
olefin copolymers (COL).
While preferred embodiments of the present invention have been
shown and described herein, it will be obvious to those skilled in
the art that such embodiments are provided by way of example only.
Numerous variations, changes, and substitutions will now occur to
those skilled in the art without departing from the invention. It
should be understood that various alternatives to the embodiments
of the invention described herein can be employed in practicing the
invention. It is intended that the following claims define the
scope of the invention and that methods and structures within the
scope of these claims and their equivalents be covered thereby.
EXAMPLES
Some aspects of the embodiments discussed above are disclosed in
further detail in the following examples, which are not in any way
intended to limit the scope of the present disclosure.
Example 1
Methods for Determining the Number of Distinct Targets at Spatial
Locations in a Sample Using a Spatial Label
The disclosure provides for methods for determining the number of
distinct targets and their distinct spatial locations in a sample
using a spatial label on a stochastic barcode of the disclosure. A
tissue thin-slice is separated into sections. The sections are
placed on a substrate in a known way. The sections are placed on a
substrate such that they preserve the physical order of the tissue
section. The sections are placed on a substrate such that they do
not preserve the physical order of the tissue section. The tissue
section is contacted with a plurality of solid supports. The tissue
section is contacted with a plurality of solid supports in a known
way such that a user knows which solid support with which spatial
label contacted which section. A single solid support can contact
each section of the tissue thin slice. The solid supports comprise
a plurality of stochastic barcodes. The stochastic barcodes
comprise a universal label, a spatial label, a cellular label, a
molecular label, and a target-association region. The tissue thin
section is imaged with the solid supports. The image captures the
physical structure of the tissue thin slice and identifies the
orientation of the solid supports associated with the tissue thin
slice. For example, solid supports can be etched with an identifier
that can be visible in the image. The sequence of the spatial label
on each of the etched solid supports is pre-known.
The targets in the section of the tissue thin slice associate with
the target-association region (e.g., through their poly(A) tail).
The targets are cross-linked to the target-association region. The
solid supports are removed from the tissue thin section. The
targets associated with the target-association region are reverse
transcribed using a reverse transcriptase, thereby generating a
target-barcode molecule which is a transcript incorporating the
labels of the stochastic barcode into its polynucleotide sequence.
The target-barcode molecule is amplified using polymerase chain
reaction. The sequence of the target-barcode molecule is
determined, for example, through sequencing. The sequence reaction
determines the spatial label, the cellular label, the molecular
label, and some or all of the sequence of the target. The number of
distinct targets are counted, wherein the unique occurrences of a
specific molecular label indicate a distinct target. The sequence
of the spatial label is used to correlate the number of the
distinct targets with a position in physical space of the tissue
thin slice. A map is generated that displays the location and
amount of a distinct target in the tissue thin section. The amount
of the distinct target is displayed as a colorimetric
intensity.
Example 2
Methods for Determining the Number of Distinct Target at a Spatial
Location in a Sample Using a Timing Correlation
The disclosure provides for methods for determining the number of
distinct targets and their distinct spatial locations in a sample
using a spatial label on a stochastic barcode of the disclosure and
a timing correlation. A tissue thin-slice is separated into
sections using a device. The device places the sections on a
substrate in a known way. The sections are placed on a substrate
such that they preserve the physical order of the tissue section.
The sections are placed on a substrate such that they do not
preserve the physical order of the tissue section.
In some embodiments, a device takes biopsies of a solid tissue at a
given rate. The device places the biopsy samples on a substrate at
a given location. The location of the biopsy sample is related to
the rate at which the device took the biopsy samples. This is
related to the time the device was in a specific location to take
the biopsy sample.
In either case, the sample/section is contacted with a plurality of
solid supports. The sample/section is contacted with a plurality of
solid supports in a known way such that a user knows which solid
support with which spatial label contacted which section. A single
solid support can contact each section of the sample/section. The
solid supports comprise a plurality of stochastic barcodes. The
stochastic barcodes comprise a universal label, a spatial label, a
cellular label, a molecular label, and a target-association region.
The sample/section is imaged with the solid supports. The image
captures the physical structure of the tissue thin slice and
identifies the orientation of the solid supports associated with
the tissue thin slice. For example, solid supports can be etched
with an identifier that can be visible in the image. The sequence
of the spatial label on each of the etched solid supports is
pre-known.
The targets in the section of the sample/section associate with the
target-association region (e.g., through their poly(A) tail). The
targets are cross-linked to the target-association region. The
solid supports are removed from the sample/section. The targets
associated with the target-association region are reverse
transcribed using a reverse transcriptase, thereby generating a
target-barcode molecule which is a transcript incorporating the
labels of the stochastic barcode into its polynucleotide sequence.
The target-barcode molecule is amplified using polymerase chain
reaction. The sequence of the target-barcode molecule is
determined, for example, through sequencing. The sequence reaction
determines the spatial label, the cellular label, the molecular
label, and some or all of the sequence of the target. The number of
distinct targets are counted, wherein the unique occurrences of a
specific molecular label indicate a distinct target. The sequence
of the spatial label is used to correlate the number of the
distinct targets with a specific solid support, which is correlated
with a specific time at which the solid support was contacted to
the sample/section. In this way, the position of the distinct
targets in physical space of the sample/section and be analyzed. A
map is generated that displays the location and amount of a
distinct target in the sample/section. The amount of the distinct
target is displayed as a colorimetric intensity.
Example 3
Method for Determining the Number of Distinct Targets at a Spatial
Location in a Sample Using Label Lithography
The disclosure provides for methods for determining the number of
distinct targets and their distinct spatial locations in a sample
using lengths of spatial labels on a stochastic barcode of the
disclosure. A tissue thin-slice is separated into sections. The
sections are placed on a substrate in a known way. The sections are
placed on a substrate such that they preserve the physical order of
the tissue section. The sections are placed on a substrate such
that they do not preserve the physical order of the tissue section.
In some embodiments, the tissue thin slice is not separated into
section. In some embodiments, the tissue thin-slice is left
intact.
In either instance, the tissue is contacted with a plurality of
solid supports. A single solid support can contact each section of
the tissue thin slice. The solid supports can comprise a
pre-spatial label. The pre-spatial label is attached to the solid
support. The pre-spatial label comprises a cellular label, a
molecular label, and a target-association region. The pre-spatial
label comprises an activatable consensus sequence. The activatable
consensus sequence is activated to link to a spatial label block
which comprises a corresponding activatable sequence. For example,
the pre-spatial label comprises biotin and the spatial label block
comprises avidin on one end and biotin on the other end. The
spatial label block is a sequence of nucleotides that when
concatenated together forms a spatial label.
Concatenation of the spatial label occurs in a geometric manner
such that discrete spatial label blocks are added to specific
pre-spatial labels at specific physical locations. Spatial label
blocks are added in an increasing manner while moving from top to
bottom across the tissue thin-slice. Spatial label blocks are then
added in an increasing manner while moving from left to right
across the tissue thin-slice. In this way, the length of the
spatial label (i.e., comprising concatenated spatial label blocks)
is indicative of a physical location in the tissue sample.
The tissue thin section is imaged with the solid supports before
they have been linked to spatial label blocks. The image captures
the physical structure of the tissue thin slice and identifies the
orientation of the solid supports associated with the tissue thin
slice. For example, solid supports can be etched with an identifier
that can be visible in the image. The sequence of the spatial label
on each of the etched solid supports is pre-known.
The targets in the section of the tissue thin slice associate with
the target-association region (e.g., through their poly(A) tail).
The targets are cross-linked to the target-association region. The
solid supports are removed from the tissue thin section. The
targets associated with the target-association region are reverse
transcribed using a reverse transcriptase, thereby generating a
target-barcode molecule which is a transcript incorporating the
labels of the stochastic barcode into its polynucleotide sequence.
The target-barcode molecule is amplified using polymerase chain
reaction. The sequence of the target-barcode molecule is
determined, for example, through sequencing. The sequence reaction
determines the spatial label, the cellular label, the molecular
label, and some or all of the sequence of the target. The number of
distinct targets are counted, wherein the unique occurrences of a
specific molecular label indicate a distinct target. The length of
the spatial label is used to correlate the number of the distinct
targets with a position in physical space of the tissue thin slice.
A map is generated that displays the location and amount of a
distinct target in the tissue thin section. The amount of the
distinct target is displayed as a colorimetric intensity.
Example 4
Combinatorial Methods for Generating Large Libraries of Unique
Synthetic Particles with Both DNA Barcodes and Spectrally
Resolvable Barcodes
This example demonstrates a combinatorial method to generate large
libraries of at least 96.sup.3 unique synthetic particles with both
DNA barcodes such as stochastic barcodes and spectrally resolvable
barcodes such as optical barcodes.
The method is used to encode synthetic particles. As shown in FIG.
18A, each synthetic particle can contain 9 "anchor regions." Each
anchor region can have a size 1802 of about a few microns to tens
of microns wide. The anchor regions can be arranged in a
longitudinal format as shown in FIG. 18A, or a grid format as shown
in FIG. 18B. The anchor regions can occupy the entire synthetic
particle surface as shown in FIG. 18A, or part of the synthetic
particle surface as shown in FIG. 18B. Each anchor region can have
a unique optical label (OL) attached to the surface of the
synthetic particle. FIGS. 18A-B show 9 optical labels, OL1-9,
attached to the surface of the synthetic particle. The unique
optical label can include an oligonucleotide sequence. The unique
optical label can include a unique optical moiety. The unique
optical moiety can be a fluorophore. OL1-3 can be used to encode
cellular label part 1 corresponding to a first 96 unique cellular
labels in the first encoding step. OL4-6 can be used to encode
cellular label part 2 corresponding to a second 96 unique cellular
labels in the second split step. OL7-9 can be used to encode
cellular label part 3 corresponding to a third 96 unique cellular
labels in the third split step. In addition to the `optical label,`
the entire synthetic particle surface or part of the synthetic
particle surface can be attached with universal sequence (US) with
3' up, i.e. 3' end of the oligonucleotide is not attached to the
synthetic particle.
At the first encoding step/the first split step, synthetic
particles are distributed across 96 wells of a first plate and
hybridize to oligonucleotides in each well. FIG. 19 shows the
hybridization of oligonucleotides in the first encoding step. Each
well can contain, for example, 4 types of oligonucleotides. The
first type of oligonucleotides each can contain a region
complementary to the universal sequence (US), followed by part 1 of
the cellular label (1 of 96), followed by a linker sequence (linker
1). The second type of oligonucleotides each can include a duplex
structure that contains a strand complementary to OL1 with a small
5' extension, and a shorter strand complementary to the extension
on the longer strand. The shorter strand can include an optical
label with an optical moiety, for example a fluorophore, on the 3'
end. The fluorophore can be one of five possibilities such as 5
different fluorophores, or 4 different fluorophores and the
possibility of having no fluorophore. The third type of
oligonucleotides each can include a duplex structure that contains
a strand complementary to OL2 with a small 5' extension, and a
shorter strand complementary to the extension on the longer strand.
The shorter strand can include an optical label with an optical
moiety, for example a fluorophore, on the 3' end. The fluorophore
can be one of five possibilities such as 5 different fluorophores,
or 4 different fluorophores and the possibility of having no
fluorophore. The fourth type of oligonucleotides each can include a
duplex structure that contains a strand complementary to OL3 with a
small 5' extension, and a shorter strand complementary to the
extension on the longer strand. The shorter strand can include an
optical label with an optical moiety, for example a fluorophore, on
the 3' end. The fluorophore can be one of five possibilities such
as 5 different fluorophores, or 4 different fluorophores and the
possibility of having fluorophore).
FIG. 20 is a lookup table showing the oligonucleotide content in
each of the 96 wells in the first plate. The oligonucleotide
content in each of the 96 wells in the first plate shows the
correspondence of cellular label part 1 and encoding by OL1-3. The
number of optical moieties in a group of spectrally-distinct
optical moieties, i.e. the number of possibilities of fluorophores,
has to be sufficient to allow encoding of at least the number of
the unique synthetic particles. To encode 96 unique synthetic
particles, k.sup.n has to be greater or equal to 96, where k is the
number of optical moieties in the group of spectrally-distinct
optical moieties, n is the number of regions. In this example, n of
OL1-3 is 3, n of OL4-6 is 3, and n of OL7-9 is 3. Thus k has to be
at least 5, with k.sup.n=5^3=125>96.
After the synthetic particles are distributed across 96 wells of
the first plate and hybridize to oligonucleotides in each well, DNA
polymerase and DNA ligase can be introduced into each well. DNA
polymerase can extend the US sequence with cellular label part 2
and linker 2 sequences. DNA ligase can covalently attach the
fluorescent probe onto the OL oligonucleotides. FIG. 21 shows the
single stranded oligonucleotides in the various regions on the
synthetic particles after polymerization, ligation, and
denaturation of duplex DNA in the first encoding step.
At the second encoding step including pool and second split,
synthetic particles from all the wells of the first plate can be
pooled, and split into each of the 96 wells of a second plate. FIG.
22 shows the hybridization of oligonucleotides in the second
encoding step. Each well of the second plate can contain 4 types of
oligonucleotides. Each well contains 4 types of oligonucleotides.
The first type of oligonucleotide each can include linker 1,
followed by part 2 of the cellular label (1 of 96), followed by
another linker sequence (linker 2). The second type of
oligonucleotide each can include a duplex structure that contains a
strand complementary to OL4 with a small 5' extension, and a
shorter strand complementary to the extension on the longer strand.
The shorter strand can include an optical label with an optical
moiety, for example a fluorophore, on the 3' end. The fluorophore
can be one of five possibilities such as 5 different fluorophores,
or 4 different fluorophores and the possibility of no fluorophore.
The third type of oligonucleotide each can include a duplex
structure that contains a strand complementary to OL5 with a small
5' extension, and a shorter strand complementary to the extension
on the longer strand. The shorter strand can include an optical
label with an optical moiety, for example a fluorophore, on the 3'
end. The fluorophore can be one of five possibilities such as 5
different fluorophores, or 4 different fluorophores and the
possibility of no fluorophore. The fourth type of oligonucleotide
each can include a duplex structure that contains a strand
complementary to OL6 with a small 5' extension, and a shorter
strand complementary to the extension on the longer strand. The
shorter strand can include an optical label with an optical moiety,
for example a fluorophore, on the 3' end. The fluorophore can be
one of five possibilities such as 5 different fluorophores, or 4
different fluorophores and the possibility of no fluorophore.
FIG. 23 is a lookup table showing the oligonucleotide content in
each of the 96 wells in the second plate. The oligonucleotide
content in each of the 96 wells in the second plate shows the
correspondence of cellular label part 2 and encoding by OL4-6.
After the synthetic particles are distributed across 96 wells of
the second plate and hybridize to oligonucleotides in each well,
DNA polymerase and DNA ligase can be introduced into each well. DNA
polymerase can extend the US sequence with cellular label part 1
and linker 1 sequences. DNA ligase can covalently attach the
fluorescent probe onto the OL oligonucleotides. FIG. 24 shows the
single stranded oligonucleotides in the various regions on the
synthetic particles after polymerization, ligation, and
denaturation of duplex DNA in the second encoding step.
At the third encoding step including pool and third split,
synthetic particles from all the wells of the second plate can be
pooled, and split into each of the 96 wells of a third plate. FIG.
25 shows the hybridization of oligonucleotides in the third
encoding step. Each well of the third plate can contain 4 types of
oligonucleotides. Each well contains 4 types of oligonucleotides.
The first type of oligonucleotide each can include linker 2,
followed by part 3 of the cellular label (1 of 96), followed by
molecular index (randomers) and oligo(dA). The second type of
oligonucleotides each can include a duplex structure that contains
a strand complementary to OL7 with a small 5' extension, and a
shorter strand complementary to the extension on the longer strand.
The shorter strand can include an optical label with an optical
moiety, for example a fluorophore, on the 3' end. The fluorophore
can be one of five possibilities such as 5 different fluorophores,
or 4 fluorophores and the possibility of no fluorophore. The third
type of oligonucleotide each can include a duplex structure that
contains a strand complementary to OL8 with a small 5' extension,
and a shorter strand complementary to the extension on the longer
strand. The shorter strand can include an optical label with an
optical moiety, for example a fluorophore, on the 3' end. The
fluorophore can be one of five possibilities such as 5 different
fluorophores, or 4 fluorophores and the possibility of no
fluorophore. The fourth type of oligonucleotides each can include a
duplex structure that contains a strand complementary to OL9 with a
small 5' extension, and a shorter strand complementary to the
extension on the longer strand. The shorter strand can include an
optical label with an optical moiety, for example a fluorophore, on
the 3' end. The fluorophore can be one of five possibilities such
as 5 different fluorophores, or 4 fluorophores and the possibility
of no fluorophore.
FIG. 26 is a lookup table showing the oligonucleotide content in
each of the 96 wells in the third plate. The oligonucleotide
content in each of the 96 wells in the third plate shows the
correspondence of cellular label part 2 and encoding by OL4-6.
After the synthetic particles are distributed across 96 wells of
the third plate and hybridize to oligonucleotides in each well, DNA
polymerase and DNA ligase can be introduced into each well. DNA
polymerase can extend the US sequence with cellular label part 1
and linker 1 sequences. DNA ligase can covalently attach the
fluorescent probe onto the OL oligonucleotides. FIG. 27 shows the
single stranded oligonucleotides in the various regions on the
synthetic particles after polymerization, ligation, and
denaturation of duplex DNA in the third encoding step.
FIG. 28 shows an entire synthetic particle coated with both DNA
barcodes and the spectrally resolvable barcode. Each DNA barcode,
such as a stochastic barcode, can include a universal sequence, a
cellular label, a molecular label, and an oligo(dT) region. The
cellular label can include cellular label part 1, cellular label
part 2, and cellular label part 3 separated by linker 1 and linker
2. Each resolvable barcode, such as an optical barcode, can include
OL1-9 and the accompanying optical moieties.
FIG. 29 shows an exemplary combination of the spectrally resolvable
barcode, OL1-9, of a synthetic particle. The synthetic particle can
be attached with a unique combination of 9 optical moieties, such
as 9 fluorescence regions. The unique combination of optical
moieties corresponds to a unique cellular label sequence. The
fluorescence in each fluorescence region within the synthetic
particle can be detected using fluorescent imaging and image
analysis. The cellular label attached with the synthetic particle
can then be determined based on the three tables in FIGS. 20, 23,
and 26. The combination of the 9 fluorescence regions correspond to
cellular label 12, 70, 22.
Altogether, these data demonstrate the use split-pool method to
encode synthetic particles with both DNA labels and spectral
barcodes to generate large libraries of synthetic particles.
Example 5
Generation of Spatial Gene Expression Map of Tissue Slices
This example demonstrates the use of encoded synthetic particles
from Example 4 to generate spatial gene expression map of tissue
slices.
First, the encoded synthetic particles are randomly sprinkled on a
slide. Second, suspend the encoded synthetic particles. Upon
drying, synthetic particles will be immobilized and form a
non-overlapping monolayer. Third, scan the slide under different
fluorescent channels. Fourth, analyze the image to deduce the
spectral signature of each encoded synthetic particle, and deduce
the cellular label identity using the lookup tables. Fifth, place a
thin tissue section on top of the slide with the encoded synthetic
particles. Sixth, place a piece of filter paper soaked with lysis
buffer on top of the tissue section and apply pressure, and hold to
allow cell lysis and mRNA hybridization. Seventh, layer cDNA
synthesis reagents on top of the slide to carry out cDNA synthesis
reaction. Eighth, layer PCR reagents on top of slide to generate
copies of the cDNA. Alternatively, encoded synthetic particles can
be retrieved at any step after mRNA hybridization, and the
subsequent reactions can be carried out with encoded synthetic
particles in tubes. Ninth, sequence PCR products to determine
cellular label, molecule label, and gene identity. Tenth, map the
molecules associated with each cell to the location on the slide.
For each gene, obtain a 2D picture of the number of target
molecules found at a specific location.
Altogether, these data demonstrate the use of encoded synthetic
particles to generate spatial gene expression map of tissue
slices.
Example 6
Synthetic Particle Synthesis
This example demonstrates synthetic particle synthesis by stop flow
lithography.
First, fabricate a microfluidic device (e.g. PDMS or NOA) with 9
input ports converging to a single channel, leading to 1 output
port. Second, in each of the input port, feed in a mixture of:
Poly(ethylene glycol) diacrylate PEGDA, photoinitiator, 5' acrydite
modified universal sequence (US) oligonucleotide, and 5' acrydite
modified OL oligonucleotide (OL1 oligonucleotide for input port 1,
OL2 oligonucleotide for input port 2, . . . , OL9 oligonucleotide
for input port 9). Third, apply pressure at each of the input
ports. The 9 inputs will form 9 parallel streams under laminar flow
regime. Fourth, expose a region of the converged channel with UV
through a photomask with the outline of the shape of the synthetic
particle. Upon UV exposure, PEGDA and acrydite oligonucleotides can
crosslink to form a solid hydrogel synthetic particle, with 9
regions each with a different OL oligonucleotide arranged side by
side. The synthetic particles can be collected at the output port
and used for the split-pool encoding process outlined in Example
4.
Altogether, these data demonstrate the use of synthetic particle
synthesis by stop flow lithography.
In at least some of the previously described embodiments, one or
more elements used in an embodiment can interchangeably be used in
another embodiment unless such a replacement is not technically
feasible. It will be appreciated by those skilled in the art that
various other omissions, additions and modifications may be made to
the methods and structures described above without departing from
the scope of the claimed subject matter. All such modifications and
changes are intended to fall within the scope of the subject
matter, as defined by the appended claims.
With respect to the use of substantially any plural and/or singular
terms herein, those having skill in the art can translate from the
plural to the singular and/or from the singular to the plural as is
appropriate to the context and/or application. The various
singular/plural permutations may be expressly set forth herein for
sake of clarity.
It will be understood by those within the art that, in general,
terms used herein, and especially in the appended claims (e.g.,
bodies of the appended claims) are generally intended as "open"
terms (e.g., the term "including" should be interpreted as
"including but not limited to," the term "having" should be
interpreted as "having at least," the term "includes" should be
interpreted as "includes but is not limited to," etc.). It will be
further understood by those within the art that if a specific
number of an introduced claim recitation is intended, such an
intent will be explicitly recited in the claim, and in the absence
of such recitation no such intent is present. For example, as an
aid to understanding, the following appended claims may contain
usage of the introductory phrases "at least one" and "one or more"
to introduce claim recitations. However, the use of such phrases
should not be construed to imply that the introduction of a claim
recitation by the indefinite articles "a" or "an" limits any
particular claim containing such introduced claim recitation to
embodiments containing only one such recitation, even when the same
claim includes the introductory phrases "one or more" or "at least
one" and indefinite articles such as "a" or "an" (e.g., "a" and/or
"an" should be interpreted to mean "at least one" or "one or
more"); the same holds true for the use of definite articles used
to introduce claim recitations. In addition, even if a specific
number of an introduced claim recitation is explicitly recited,
those skilled in the art will recognize that such recitation should
be interpreted to mean at least the recited number (e.g., the bare
recitation of "two recitations," without other modifiers, means at
least two recitations, or two or more recitations). Furthermore, in
those instances where a convention analogous to "at least one of A,
B, and C, etc." is used, in general such a construction is intended
in the sense one having skill in the art would understand the
convention (e.g., "a system having at least one of A, B, and C"
would include but not be limited to systems that have A alone, B
alone, C alone, A and B together, A and C together, B and C
together, and/or A, B, and C together, etc.). In those instances
where a convention analogous to "at least one of A, B, or C, etc."
is used, in general such a construction is intended in the sense
one having skill in the art would understand the convention (e.g.,
"a system having at least one of A, B, or C" would include but not
be limited to systems that have A alone, B alone, C alone, A and B
together, A and C together, B and C together, and/or A, B, and C
together, etc.). It will be further understood by those within the
art that virtually any disjunctive word and/or phrase presenting
two or more alternative terms, whether in the description, claims,
or drawings, should be understood to contemplate the possibilities
of including one of the terms, either of the terms, or both terms.
For example, the phrase "A or B" will be understood to include the
possibilities of "A" or "B" or "A and B."
In addition, where features or aspects of the disclosure are
described in terms of Markush groups, those skilled in the art will
recognize that the disclosure is also thereby described in terms of
any individual member or subgroup of members of the Markush
group.
As will be understood by one skilled in the art, for any and all
purposes, such as in terms of providing a written description, all
ranges disclosed herein also encompass any and all possible
sub-ranges and combinations of sub-ranges thereof. Any listed range
can be easily recognized as sufficiently describing and enabling
the same range being broken down into at least equal halves,
thirds, quarters, fifths, tenths, etc. As a non-limiting example,
each range discussed herein can be readily broken down into a lower
third, middle third and upper third, etc. As will also be
understood by one skilled in the art all language such as "up to,"
"at least," "greater than," "less than," and the like include the
number recited and refer to ranges which can be subsequently broken
down into sub-ranges as discussed above. Finally, as will be
understood by one skilled in the art, a range includes each
individual member. Thus, for example, a group having 1-3 articles
refers to groups having 1, 2, or 3 articles. Similarly, a group
having 1-5 articles refers to groups having 1, 2, 3, 4, or 5
articles, and so forth.
While various aspects and embodiments have been disclosed herein,
other aspects and embodiments will be apparent to those skilled in
the art. The various aspects and embodiments disclosed herein are
for purposes of illustration and are not intended to be limiting,
with the true scope and spirit being indicated by the following
claims.
* * * * *
References