U.S. patent application number 17/460005 was filed with the patent office on 2021-12-16 for non-hydrogen-bonding universal reader for dna sequencing.
The applicant listed for this patent is ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY. Invention is credited to Sovan Biswas, Stuart Lindsay, Suman Sen, Peiming Zhang.
Application Number | 20210389296 17/460005 |
Document ID | / |
Family ID | 1000005807909 |
Filed Date | 2021-12-16 |
United States Patent
Application |
20210389296 |
Kind Code |
A1 |
Zhang; Peiming ; et
al. |
December 16, 2021 |
NON-HYDROGEN-BONDING UNIVERSAL READER FOR DNA SEQUENCING
Abstract
The present disclosure provides apparatus and methods for
determining the sequence of a nucleic acid. The apparatus comprises
electrodes that form a tunnel gap through which the nucleic acid
can pass. The electrodes comprise a reagent that is capable of
selectively interacting with a nucleobase of the nucleic acid
sequence. When the reagent interacts with a nucleobase, a
detectable signal is produced and used to identify the nucleobase
of the nucleic acid. Advantageously, the apparatus of this
disclosure is specific to identifying nucleic acids.
Inventors: |
Zhang; Peiming; (Gilbert,
AZ) ; Biswas; Sovan; (Tempe, AZ) ; Sen;
Suman; (Tempe, AZ) ; Lindsay; Stuart;
(Phoenix, AZ) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE
UNIVERSITY |
Scottsdale |
AZ |
US |
|
|
Family ID: |
1000005807909 |
Appl. No.: |
17/460005 |
Filed: |
August 27, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16327232 |
Feb 21, 2019 |
11119089 |
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PCT/US2017/047818 |
Aug 21, 2017 |
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17460005 |
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62378033 |
Aug 22, 2016 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
C12Q 1/6869 20130101;
C07C 321/10 20130101; G01N 33/48721 20130101; C07C 2603/50
20170501 |
International
Class: |
G01N 33/487 20060101
G01N033/487; C12Q 1/6869 20060101 C12Q001/6869; C07C 321/10
20060101 C07C321/10 |
Goverment Interests
FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
[0002] This invention was made with government support under R01
HG006323 awarded by the National Institutes for Health. The
government has certain rights in the invention.
Claims
1. A compound of formula (I): ##STR00007## wherein R.sub.1 is
(C.sub.1-C.sub.6) alkyl or (C.sub.1-C.sub.6) alkoxy; R.sub.2 is
selected from the group consisting of thiol, disulfide, and amine;
and R.sub.3 is H, an electron withdrawing group or an electron
donating group; ring A or ring B is substituted with
R.sub.1-R.sub.2; and ring C or ring D is substituted with R.sub.3;
provided that (i) when ring A is substituted with R.sub.1-R.sub.2,
ring C is substituted with R.sub.3; and (ii) when ring B is
substituted with R.sub.1-R.sub.2, ring D is substituted with
R.sub.3.
2. The compound of claim 1, wherein R.sub.1 is (C.sub.1-C.sub.6)
alkyl.
3. The compound of claim 1, wherein R.sub.1 is (C.sub.1-C.sub.3)
alkyl.
4. The compound of claim 1, wherein R.sub.1 is ethyl.
5. The compound of claim 1, wherein R.sub.2 is thiol.
6. The compound of claim 2, wherein R.sub.2 is thiol.
7. The compound of claim 1, wherein R.sub.3 is H, --NO.sub.2 or
--CH.sub.3.
8. The compound of claim 6, wherein R.sub.3 is H, --NO.sub.2 or
--CH.sub.3.
9. The compound of claim 1, wherein R.sub.3 is H.
10. The compound of claim 8, wherein R.sub.3 is H
11. The compound of claim 1, wherein said compound is formula (Ia):
##STR00008## wherein R.sub.1 is (C.sub.1-C.sub.6) alkyl or
(C.sub.1-C.sub.6) alkoxy; and R.sub.2 is selected from the group
consisting of thiol, disulfide, and amine.
12. The compound of claim 11, wherein R.sub.1 is (C.sub.1-C.sub.6)
alkyl.
13. The compound of claim 11, wherein R.sub.1 is (C.sub.1-C.sub.3)
alkyl.
14. The compound of claim 11, wherein R.sub.1 is ethyl.
15. The compound of claim 11, wherein R.sub.2 is thiol.
16. The compound of claim 12, wherein R.sub.2 is thiol.
17. The compound of claim 13, wherein R.sub.2 is thiol.
18. The compound of claim 14, wherein R.sub.2 is thiol.
19. A compound of formula (I): ##STR00009## wherein R.sub.1 is
(C.sub.1-C.sub.3) alkyl; R.sub.2 is thiol; and R.sub.3 is H; ring A
or ring B is substituted with R.sub.1-R.sub.2; and ring C or ring D
is substituted with R.sub.3; provided that (i) when ring A is
substituted with R.sub.1-R.sub.2, ring C is substituted with
R.sub.3; and (ii) when ring B is substituted with R.sub.1-R.sub.2,
ring D is substituted with R.sub.3.
20. The compound of claim 19, wherein said compound is formula
(Ia): ##STR00010##
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a Divisional of U.S. patent application
Ser. No. 16/327,232, filed on Feb. 21, 2019 (published as
US20190195856), which is the U.S. National Stage of International
Application No. PCT/US2017/047818, filed on Aug. 21, 2017, which
claims the benefit of and priority to U.S. Provisional Patent
Application No. 62/378,033, filed on Aug. 22, 2016, the contents of
each of which are incorporated herein by reference in their
entireties.
BACKGROUND
[0003] DNA sequencing, particularly Next Generation Sequencing
(NGS),.sup.1 is the most powerful technology in genomic analysis at
the present. NGS can sequence an individual human genome in a few
days at a cost of $1000. Compared to conventional Sanger
sequencing, however, NGS has lower read accuracy and shorter read
length..sup.2 A recent study has warned that the reproducibility of
single nucleotide variants (SNVs) calls was only around 80% even
using the highest stringency of QC metrics with SOLiD sequencing, a
NGS technology that has sequencing accuracy higher than
others..sup.3 NGS also faces another great challenge of determining
long repetitive regions in a genome. Although single molecule real
time (SMRT) sequencing provides a long-read solution for the issue
(see the world wide web (www) at pacb.com), it produces sequences
at a much higher error rate per base than NGS does. Currently, DNA
sequencing by synthesis is a dominated technology, and its accuracy
is limited by the fidelity of polymerases, the error rates of which
are on the order of 10.sup.-5 to 10.sup.-7 per base pair from
commercially available products..sup.4,5 Given that the somatic
mutation rate in human B and T lymphocytes and in fibroblasts are
on the order of 2 to 10 mutations per diploid genome per cell
division,.sup.6 an ideal DNA sequencer should have an error rate
lower than the mutation rate of 10.sup.-9 per base. Moreover, since
approximately 50% of the human genome is comprised of repeats with
their lengths in a range of 2 to 100,000 bp,.sup.7 the sequencer
should have a read length of >100 kbp, and ideally be able to
read a chromosome from one end to another. For use in clinics, it
should have a single molecule sensitivity for rare genetic
variants, be able to sequence a human genome for less than $100,
and simple to operate..sup.8
[0004] Sequencing by protein nanopores has proven that a DNA
sequence can directly be read out based on physical properties of
nucleobases. As an example, MinION the commercial version of a
protein nanopore sequencer can currently achieve a read-length 98
kb.sup.9 while the theoretical read length is unlimited. However,
the nanopore sequencing has a high error rate per base read 15%).
In addition to stochastic motions of the single DNA molecule in the
pore, the error rate is due to the overlapped ionic current levels,
as five nucleotides contribute to a current blockade in the
nanopore,.sup.10 which results in 4.sup.5 or 1054 possible 5-mers
needed to be assigned, let alone the existence of modified bases in
the genome. Although improved data analysis has increased the
accuracy of MinION significantly,.sup.11 a technology breakthrough
is essential to improve the spatial resolution of nanopores to a
single nucleotide so that the assignment will be reduced to
distinguishing among the four naturally occurring nucleobases plus
their various modified forms. Thinner nanopores have been studied
to improve the resolution of DNA sequencing. For example, it has
been demonstrated that a Mycobacterium smegmatis porin A (MspA)
pore reads DNA by a block of four nucleotides (quadromer) at a
time, better than the .alpha.-hemolysin pore of the MinION..sup.12
The MspA nanopore has a funnel shape with a constriction region of
1.2 nm in diameter and 0.6 nm in length,.sup.13 smaller than
.alpha.-hemolysin that has a constriction site of 1.4 nm in
diameter, followed by a .beta.-barrel of about 5 nm long and 2 nm
wide. Since an ionic blockade is sensitive to the DNA bases lying
in the outsides of a nanopore as well,.sup.14 it is unlikely for
the ionic measurement to achieve a single nucleotide resolution
ever in an atomically thin nanopore (such as a graphene
nanopore).
[0005] Electron tunneling in a nanogap offers an alternative
readout to improve the accuracy of nanopore sequencing. Zwolak and
DiVentra first proposed to sequence DNA using changes in tunnel
current flowing transverse to the DNA axis..sup.15 Taniguchi and
Kawai et al. have demonstrated that nucleoside and deoxynucleoside
monophosphates can generate characteristic tunneling currents
through bare gold gaps of 0.8 to 1.0 nanometer wide..sup.16,17 This
is too small for a gap size to pass an intact single stranded DNA.
A second problem with bare gold electrodes lies in strong
chemisorption of adenine.sup.18, 19, 20 and rapid contamination on
their surfaces. U.S. Pat. No. 8,628,649 discloses a Recognition
Tunneling (RT) technique to read nucleobases using recognition
molecules covalently attached to two electrodes that interspace a
nanogap (.about.2.5 nm wide). The recognition molecule is able to
effectively interact with each individual nucleobase to generate
distinguishable electrical signals, so-called a universal reader.
Since each nucleobase contains multiple hydrogen bonding sites,
Liang et al.'s universal reader,
4(5)-(2-mercaptoethyl)-1H-imidazole-2-carboxamide (Iz) was designed
to bear multiple hydrogen bond donors and acceptors..sup.21 Iz is
extremely versatile and its interaction goes beyond nucleobases,
such as with amino acids, peptides, and carbohydrates..sup.23,24
Thus, there remains a need for a highly selective universal reader
that only recognizes nucleobases.
[0006] Citation of any reference in this section is not to be
construed as an admission that such reference is prior art to the
present disclosure.
SUMMARY
[0007] The present disclosure provides an apparatus and a method
for determining the sequence of a nucleic acid. The apparatus
comprises electrodes that form a tunnel gap through which the
nucleic acid can pass. The electrodes comprise a reagent that is
capable of selectively interacting with a nucleobase of the nucleic
acid sequence. When the reagent interacts with a nucleobase, a
detectable signal is produced and used to identify the nucleobase
of the nucleic acid. Advantageously, the apparatus of this
disclosure is specific to identifying nucleic acids.
[0008] The present disclosure also provides compounds that can be
used as reagents for attaching to electrodes used in the apparatus
of the disclosure. The compound has formula (I):
##STR00001##
wherein R.sub.1 is (C.sub.1-C.sub.6) alkyl or (C.sub.1-C.sub.6)
alkoxy; R.sub.2 is selected from the group consisting of thiol,
disulfide, and amine; and R.sub.3 is H, an electron withdrawing
group or an electron donating group; ring A or ring B is
substituted with R.sub.1-R.sub.2; and ring C or ring D is
substituted with R.sub.3; provided that (i) when ring A is
substituted with R.sub.1-R.sub.2, ring C is substituted with
R.sub.3; and (ii) when ring B is substituted with R.sub.1-R.sub.2,
ring D is substituted with R.sub.3.
BRIEF DESCRIPTION OF THE FIGURES
[0009] FIG. 1A shows hydrogen bonding sites (D: hydrogen bonding
donor; A: hydrogen bonding acceptor) and dipole moments
(R.dbd.CH.sub.3) of DNA bases; FIG. 1B shows the chemical
structures of reader molecules Iz (imidazole-2-carboxamide), Py
(pyrene), and Bn (benzene); and FIG. 1C shows computer modeling on
reader molecules interacting with deoxyguanosine monophosphate
(dGMP) in tunneling gaps created by fixing the distance between two
sulfur atoms and then carrying out the energy minimization in
software Spartan'14.
[0010] FIG. 2 shows an energy-minimized structure of a .pi.-.pi.
stacked complex between two pyrene rings (attached to gold
electrodes) and a guanine.
[0011] FIG. 3 shows an energy optimized structure of the .pi.-.pi.
stacked complex between two pyrene rings (attached to gold
electrodes/metal slabs) and a uracil.
[0012] FIG. 4 shows a graph of calculated current vs bias. The top
line with round dots is for the complex from FIG. 2 and the bottom
line with square dots is the complex from FIG. 3.
[0013] FIG. 5 show an XPS spectrum of Py SAM on Palladium.
[0014] FIG. 6A and FIG. 6B show the FT-IR spectra of Py powder
(FIG. 6A) and Py SAM on palladium (FIG. 6B).
[0015] FIG. 7A and FIG. 7B show the FT-IR spectra of Bn neat (FIG.
7A) and Bn SAM on palladium (FIG. 7B).
[0016] FIG. 8 shows a surface plasmon resonance sensorgram
illustrating the response of a gold chip derivatized according to
the present disclosure to dGMP.
[0017] FIG. 9A-FIG. 9C show analysis of RT raw data. FIG. 9A shows
primary parameters in the time domain. FIG. 9B shows secondary
features in frequency domain. FIG. 9C shows secondary features in
cepstrum domain.
[0018] FIG. 10A-FIG. 10X show plots to display distributions of the
same feature from two different DNA nucleotides using a single
feature data that can only be assigned to one analyte with a
probability only marginally above random, or equal to P=0.5 in the
most cases.
[0019] FIG. 11A-FIG. 11T show RT spectra generated with: Iz
functionalized tip and substrate at a set point of 4 pA and 0.5 V
(FIG. 11A-FIG. 11F); Py functionalized tip and substrate at a set
point of 2 pA and 0.5 V (FIG. 11G-FIG. 11L); Bn functionalized tip
and substrate at a set point of 2 pA and 0.5 V (FIG. 11M-FIG. 11P);
Bn functionalized tip and Py substrate at a set point of 2 pA and
0.5 V (FIG. 11Q-FIG. 11T).
[0020] FIG. 12A-FIG. 12F show histograms of peak height (FIG. 12A
and FIG. 12D), averaged amplitude (FIG. 12B and FIG. 12E), peak
width (FIG. 12C and FIG. 12F), and their fitting curves of current
spikes from recognition of DNA nucleotides by Py at the set point
of 0.5 V and 2 pA; and by Iz at the set point of 0.5 V and 4
pA.
[0021] FIG. 13A and FIG. 13B show a plot for nucleotide calling
accuracy vs number of used signal features with Py (FIG. 13A) and
with Iz (FIG. 13B).
[0022] FIG. 14 shows a plot of accuracy determined by SVM analysis
of AP (read with Iz) and four DNA nucleotides (read with Py).
DETAILED DESCRIPTION
[0023] The invention includes the following:
(1.) An apparatus for analyzing a nucleic acid sequence in a
sample, the apparatus comprising a chamber, wherein the chamber
comprises: [0024] (a) a first and a second electrode that form a
tunnel gap through which the nucleic acid sequence can pass; [0025]
(b) a first reagent attached to the first electrode and a second
reagent attached to the second electrode, wherein the first and the
second reagent are capable of selectively interacting with a
nucleobase of the nucleic acid sequence, wherein a detectable
signal is produced when the nucleobase interacts with the first and
second reagent. (2.) An apparatus for selectively analyzing a
nucleic acid sequence in a sample, the apparatus comprising a
chamber, wherein the chamber comprises [0026] (a) a first and a
second electrode that form a tunnel gap through which the nucleic
sequence can pass; [0027] (b) a first reagent attached to the first
electrode and a second reagent attached to the second electrode,
wherein the first and the second reagent comprise an aromatic
compound, wherein a detectable signal is produced when the
nucleobase of the nucleic acid sequence interacts with the first
and second reagent. (3.) The apparatus according to the above (1.)
or (2.), wherein the first and/or second electrode comprise a metal
selected from the group consisting of palladium, gold, grapheme,
carbon nanotube, and molybdenum disulphide. (4.) The apparatus
according to the above (1.) or (2.), wherein the first and/or
second electrode comprise palladium. (5.) The apparatus according
to any one of the above (1.) to (4.), wherein the first and second
reagent are the same. (6.) The apparatus according to any one of
the above (1.), (3.) or (4.), wherein the first and/or second
reagent is an aromatic compound. (7.) The apparatus according to
the above (2.) or (6.), wherein the aromatic compound is selected
from the group consisting of pyrene, benzene, anthracene,
benzo[e]pyrene, 2-(phenylethynyl)pyrene, 2-phenyl pyrene,
3-nitro-1H-pyrrole and 5-nitro-1H-indole, wherein the polycyclic
aromatic compound is unsubstituted or substituted with a
substituent selected from nitro, phenyl, (C.sub.1-C.sub.6)alkyl
substituted with phenyl, (C2-C6)alkenyl substituted with phenyl and
(C.sub.2-C.sub.6)alkynyl substituted with phenyl. (8.) The
apparatus according to the above (7.), wherein the aromatic
compound is selected from the group consisting of pyrene,
1-(2-mercaptoethyl)pyrene, nitrobenzene, 2-nitroanthracene,
benzo[e]pyrene, 2-(phenylethynyl)pyrene, 2-phenyl pyrene,
3-nitro-1H-pyrrole and 5-nitro-1H-indole. (9.) The apparatus
according to the above (7.), wherein the aromatic compound is a
pyrene. (10.) The apparatus according to the above (9.), wherein
the aromatic compound is a pyrene substituted with
(C.sub.1-C.sub.6)mercaptoalkyl. (11.) The apparatus according to
any one of the above (1.) to (10.), wherein the aromatic compound
is 1-(2-mercaptoethyl)pyrene. (12.) The apparatus according to any
one of the above (1.) to (4.), wherein the aromatic compound
comprises a thiol, disulfide or amine. (13.) The apparatus
according to the above (12.), wherein the aromatic compound
comprises a thiol. (14.) The apparatus according to any one of the
above (1.) to (13.), wherein the tunnel gap has a width of about
1.0 nm to about 5.0 nm. (15.) The apparatus according to any one of
the above (1.) to (14.), further comprising a detector for
measuring the detectable signal. (16.) The apparatus according to
any one of the above (1.) to (15.), further comprising a system for
introducing and removing buffer and the sample into the chamber.
(17.) The apparatus according to any one of the above (1.) to
(16.), further comprising a system for analyzing the detectable
signal. (18.) The apparatus according to any one of the above (1.)
to (17.), wherein the sample is a biological sample. (19.) The
apparatus according to any one of the above (1.) to (18.), wherein
the nucleic acid is DNA. (20.) The apparatus according to any one
of the above (1.) to (18.), wherein the nucleic acid is RNA. (21.)
The apparatus according to any one of the above (1.) to (18.),
wherein the nucleic acid is PNA (22.) The apparatus according to
any one of the above (1.) to (18.), wherein the nucleic acid is XNA
(23.) The apparatus according to any one of the above (1.) to
(18.), wherein the nucleic acid comprises unnatural bases. (24.) A
compound of formula (I):
##STR00002##
[0027] wherein R.sub.1 is (C.sub.1-C.sub.6) alkyl or
(C.sub.1-C.sub.6) alkoxy; R.sub.2 is selected from the group
consisting of thiol, disulfide, and amine; and R.sub.3 is H, an
electron withdrawing group or an electron donating group; ring A or
ring B is substituted with R.sub.1-R.sub.2; and ring C or ring D is
substituted with R.sub.3; provided that (i) when ring A is
substituted with R.sub.1-R.sub.2, ring C is substituted with
R.sub.3; and (ii) when ring B is substituted with R.sub.1-R.sub.2,
ring D is substituted with R.sub.3. (25.) The compound of the above
(24.), wherein R.sub.1 is (C.sub.1-C.sub.6) alkyl. (26.) The
compound of the above (24.), wherein R.sub.1 is (C.sub.1-C.sub.3)
alkyl. (27.) The compound of the above (24.), wherein R.sub.1 is
ethyl. (28.) The compound of any one of the above (24.) through
(27.), wherein R.sub.2 is thiol. (29.) The compound of any one of
the above (24.) through (28.), wherein R.sub.3 is H, --NO.sub.2 or
CH.sub.3. (30.) The compound of any one of the above (24.) through
25, wherein R.sub.3 is H. (31.) The compound of the above (24.),
wherein said compound is formula (Ia):
##STR00003##
wherein R.sub.1 is (C.sub.1-C.sub.6) alkyl or (C.sub.1-C.sub.6)
alkoxy; and R.sub.2 is selected from the group consisting of thiol,
disulfide, and amine. (32.) The compound of the above (31.),
wherein R.sub.1 is (C.sub.1-C.sub.6) alkyl. (33.) The compound of
the above (31.), wherein R.sub.1 is (C.sub.1-C.sub.3) alkyl. (34.)
The compound of the above (31.), wherein R.sub.1 is ethyl. (35.)
The compound of any one of the above (31.) through (34.), wherein
R.sub.2 is thiol. (36.) A method of determining the sequence of a
nucleic acid, the method comprising [0028] (a) providing an
apparatus according to any one of the above (1.) to (23.); [0029]
(b) passing a nucleic acid through the tunnel gap; [0030] (c)
detecting the signal produced when a nucleobase of the nucleic acid
interacts with the first and second reagent; [0031] (d) from the
signal detected in (c), identifying the nucleobase of the nucleic
acid; and [0032] (e) repeating steps (b) through (d); [0033] (f)
from the nucleobases identified in (d), determining the sequence of
the nucleic acid. (37.) The method of the above (36.), wherein step
(c) comprises detecting an electrical current.
Definitions
[0034] Unless defined otherwise, all technical and scientific terms
used herein have the same meaning as those commonly understood by
one of ordinary skill in the art to which this invention belongs.
Although methods and materials similar or equivalent to those
described herein can be used in the practice or testing of the
present disclosure, suitable methods and materials are described
below. The materials, methods and examples are illustrative only,
and are not intended to be limiting. All publications, patents and
other documents mentioned herein are incorporated by reference in
their entirety.
[0035] Throughout this specification, the word "comprise" or
variations such as "comprises" or "comprising" will be understood
to imply the inclusion of a stated integer or groups of integers
but not the exclusion of any other integer or group of
integers.
[0036] The term "a" or "an" may mean more than one of an item.
[0037] The terms "and" and "or" may refer to either the conjunctive
or disjunctive and mean "and/or".
[0038] The term "about" means within plus or minus 10% of a stated
value. For example, "about 100" would refer to any number between
90 and 110.
[0039] The term "(C.sub.1-C.sub.6) alkyl" refers to saturated
linear or branched hydrocarbon structures having 1, 2, 3, 4, 5, or
6 carbon atoms. When an alkyl residue having a specific number of
carbons is named, all geometric isomers having that number of
carbons are intended to be encompassed; thus, for example, "propyl"
includes n-propyl and iso-propyl, and "butyl" includes n-butyl,
sec-butyl, iso-butyl and tert-butyl. Examples of "(C.sub.1-C.sub.6)
alkyl" include methyl, ethyl, n-propyl, iso-propyl, n-butyl,
tert-butyl, n-pentyl, n-hexyl, and the like.
[0040] The term "(C.sub.1-C.sub.3) alkyl" refers to saturated
linear or branched hydrocarbon structures having 1, 2 or 3 carbon
atoms. When an alkyl residue having a specific number of carbons is
named, all geometric isomers having that number of carbons are
intended to be encompassed; thus, for example, "propyl" includes
n-propyl and iso-propyl. Examples of "(C.sub.1-C.sub.3) alkyl"
include methyl, ethyl, n-propyl and iso-propyl.
[0041] The term "(C.sub.2-C.sub.6) alkenyl" refers to a
straight-chain or branched unsaturated hydrocarbon radical having
2, 3, 4, 5 or 6 carbon atoms and a double bond in any position,
e.g., ethenyl, 1-propenyl, 2-propenyl (allyl), 1-butenyl,
2-butenyl, 3-butenyl, 1-methylethenyl, 1-methyl-1 propenyl,
2-methyl-2-propenyl, 2-methyl-1-propenyl, 1-methyl-2-propenyl,
1-hexenyl, 2-hexenyl, 3-hexenyl, 2-methyl-2-pentenyl,
4-methyl-2-pentenyl, 4-methyl-1-pentenyl, 3-methyl-1-pentenyl, and
the like.
[0042] The term "(C2-C6)alkynyl" refers to a straight chain or
branched hydrocarbon having 2, 3, 4, 5 or 6 carbon atoms and
including at least one carbon-carbon triple bond. Examples of
"(C2-C.sub.6)alkynyl" include ethynyl, propynyl, 1-butynyl,
2-butynyl, 1-pentynyl, 2-pentynyl, 1-hexynyl, 2-hexynyl, 3-hexynyl,
4-methyl-2-pentynyl and the like.
[0043] The term "(C.sub.1-C.sub.6)alkoxy" refers to
--O--(C.sub.1-C.sub.6)alkyl. Examples of "(C.sub.1-C.sub.6)alkoxy"
include methoxy, ethoxy, propoxy, n-propoxy, iso-propoxy, butoxy,
n-butoxy, sec-butoxy, tert-butoxy, pentoxy, hexyloxy, and the
like.
[0044] The term "(C.sub.1-C.sub.3)alkoxy" refers to
--O--(C.sub.1-C.sub.3)alkyl. Examples of "(C.sub.1-C.sub.6)alkoxy"
include methoxy, ethoxy, propoxy, n-propoxy and iso-propoxy.
[0045] The term "electron withdrawing group" refers to an atom or
group that draws electron density from neighboring atoms towards
itself. Examples of "electron withdrawing groups" include halo,
--CN, --CF.sub.3, --NO.sub.2, --SH, --C(O)H,
--C(O)--(C.sub.1-C.sub.6)alkyl, --C(O)O--(C.sub.1-C.sub.6)alkyl,
--C(O)OH, --C(O)--Cl, --SO.sub.2OH, --S(O).sub.2NHOH, --NH.sub.3,
--N((C.sub.1-C.sub.6)alkyl).sub.3 and the like.
[0046] The term "electron donating group" refers to an atom or a
group that donates some of its electron density to neighboring
atoms. Examples of "electron donating groups" include --OH,
--NH.sub.2, --N((C.sub.1-C.sub.6)alkyl).sub.2,
NHC(O)(C.sub.1-C.sub.6)alkyl), --OC(O)(C.sub.1-C.sub.6)alkyl),
(C.sub.1-C.sub.6)alkyl), phenyl,
--CH.dbd.C((C.sub.1-C.sub.6)alkyl)).sub.2 and the like.
[0047] The term "Peptide Nucleic Acid" or "PNA" is a non-naturally
occurring polymer comprising a polyamide backbone, and purine and
pyrimidine bases linked thereto.
[0048] The term "Xeno Nucleic Acid" or "XNA" is a non-naturally
occurring polymer in which the deoxyribose or ribose groups of DNA
and RNA have been replaced. Examples of XNA include, but are not
limited to, 1,5-anhydrohexitol nucleic acid (HNA), cyclohexene
nucleic acid (CeNA), threose nucleic acid (TNA), glycol nucleic
acid (GNA), locked nucleic acid (LNA), and peptide nucleic acid
(PNA).
[0049] The term "unnatural base" refers to a non-naturally
occurring molecule that is incorporated into a nucleic acid and can
form a base pair with a natural base or another unnatural base.
Unnatural bases are known in the art and examples include, but are
not limited to, substituted or unsubstituted 2-aminopurine,
substituted or unsubstituted imidazo[4,5-b]pyridine, substituted or
unsubstituted pyrrolo[2,3-b]pyridine, substituted or unsubstituted
pyridin-2-one, substituted or unsubstituted pyrrole-2-carbaldehyde,
and substituted or unsubstituted 2-nitropyrrole, isoguanine,
isocytosine, xanthosine, 2,4-diaminopyrimidine,
4-methylbenzimidazole, difluorotoluene, propynyl isocarbostyril,
7-azaindole, and 3-fluorobenzene.
[0050] The abbreviation "Py" refers to
1-(2-mercaptoethyl)pyrene.
[0051] The abbreviation "Iz" refers to
4(5)-(2-mercaptoethyl)-1H-imidazole-2-carboxamide.
[0052] The abbreviation "Bn" refers to
(2-mercaptoethyl)benzene.
[0053] The abbreviation "RT" refers to Recognition Tunneling.
[0054] The abbreviation "AP" refers to abasic 5'-monophosphate.
Apparatus
[0055] The present disclosure provides an apparatus for selectively
analyzing a nucleic acid sequence in a sample. The sample may be a
biological sample and comprises DNA in one embodiment and RNA in a
second embodiment. In one embodiment, the sample comprises DNA
derived from a patient. The apparatus comprises a chamber, which,
in turn comprises two electrodes. The two electrodes form a tunnel
gap through which the sample of nucleic acid sequence can pass.
[0056] The electrodes may be made of any suitable material that can
be functionalized with a reagent capable of interacting with a
nucleobase. In one embodiment, the electrode is made from a metal.
Suitable metals include palladium, gold, graphene, carbon nanotube,
and molybdenum disulphide.
[0057] In one embodiment, the electrodes comprise a reagent that is
capable of selectively interacting with a nucleobase of the nucleic
acid sequence. In another embodiment, the electrodes comprise an
aromatic compound that is capable of selectively interacting with a
nucleobase of the nucleic acid sequence. The electrodes may be
functionalized with the same reagent in one embodiment, a
combination of reagents in a second embodiment, or individually
functionalized with different reagents in a third embodiment.
[0058] In one embodiment, the reagent comprises a functional group
that selectively attaches to the electrode surface. Suitable
functional groups include a thiol, disulfide or amine. The
selection of a functional group will depend on the electrode used.
For example, when the electrode is made from gold or palladium, a
reagent comprising a thiol may be used. When the electrode is made
from graphene or carbon nanotubes, a reagent comprising an amine
may be used.
[0059] In embodiments in which the electrode comprises an aromatic
compound, the aromatic compound is selected from the group
consisting of pyrene, benzene, anthracene, benzo[e]pyrene,
2-(phenylethynyl)pyrene, 2-phenyl pyrene, 3-nitro-1H-pyrrole and
5-nitro-1H-indole, wherein the aromatic compound is unsubstituted
or substituted with a substituent selected from the group
consisting of nitro, phenyl, (C.sub.1-C.sub.6)alkyl substituted
with phenyl, (C.sub.2-C.sub.6)alkenyl substituted with phenyl and
(C.sub.2-C.sub.6)alkynyl substituted with phenyl. In one
embodiment, the aromatic compound is selected from the group
consisting of pyrene, 1-(2-mercaptoethyl)pyrene, nitrobenzene,
2-nitroanthracene, benzo[e]pyrene, 2-(phenyl ethynyl)pyrene,
2-phenyl pyrene, 3-nitro-1H-pyrrole and 5-nitro-1H-indole. In
another embodiment, the aromatic compound is a pyrene. In another
embodiment, the aromatic compound is a pyrene substituted with
(C.sub.1-C.sub.6)mercaptoalkyl. In another embodiment, the aromatic
compound is 1-(2-mercaptoethyl)pyrene. In another embodiment, the
aromatic compound is a compound of formula (I), as disclosed
herein.
[0060] The tunnel gap comprises the space between the two
electrodes and can be adjusted to a width such that the nucleic
acid fits into the gap. The gap width will vary depending on the
reagent used and the nucleic acid to be analyzed. The gap may have
a width from about 1 nm to about 5 nm, from about 1.5 nm to about
4.5 nm, from about 2 nm to about 4 nm, from about 2 nm to about 3.5
nm, from about 2 nm to about 3 nm, or from about 2 nm to about 2.5
nm.
[0061] Methods for determining suitable gap widths are known in the
art. For example, U.S. Pat. No. 9,140,682 provides that suitable
gap widths may be determined by using a device capable of a
dynamically adjusting the gap. In some embodiments, a dynamically
adjustable device may be used to analyze target units. In either
case, the gap width may be determined or set as follows: The
electrodes are approached together until a chosen tunnel current is
achieved at a particular bias. For example, a current of 6 pA at
0.5V bias corresponds to a gap of 2.5 nm when tunneling in
1,2,4-trichlorobenzene. The gap is maintained by applying active
servo control as is well known in the art for scanning tunneling
microscopy.
[0062] When the nucleobase is passed through the tunnel gap, it
interacts with the first and second reagent via .pi.-.pi.
interactions. The interaction between the nucleobase and the
reagent produce a detectable signal. The apparatus of this
disclosure is highly specific to nucleobases.
[0063] In one embodiment, the apparatus further comprises one or
more of the following: a detector for measuring the detectable
signal, a system for introducing and removing buffer and the sample
into the chamber, and a system for analyzing the detectable
signal.
Compounds of Formula (I)
[0064] The present disclosure provides a compound of formula
(I):
##STR00004##
wherein R.sub.1 is (C.sub.1-C.sub.6) alkyl or (C.sub.1-C.sub.6)
alkoxy; R.sub.2 is selected from the group consisting of thiol,
disulfide, and amine; and R.sub.3 is H, an electron withdrawing
group or an electron donating group; ring A or ring B is
substituted with R.sub.1-R.sub.2; and ring C or ring D is
substituted with R.sub.3; provided that (i) when ring A is
substituted with R.sub.1-R.sub.2, ring C is substituted with
R.sub.3; and (ii) when ring B is substituted with R.sub.1-R.sub.2,
ring D is substituted with R.sub.3.
[0065] In one embodiment, R.sub.1 is (C.sub.1-C.sub.3) alkyl or
(C.sub.1-C.sub.3) alkoxy. In another embodiment, R.sub.1 is
(C.sub.1-C.sub.6) alkyl. In another embodiment, R.sub.1 is
(C.sub.1-C.sub.6) alkoxy. In another embodiment, R.sub.1 is
(C.sub.1-C.sub.3) alkyl.
[0066] In another embodiment, R.sub.1 is (C.sub.1-C.sub.3) alkoxy.
In another embodiment, R.sub.1 is methyl or ethyl. In another
embodiment, R.sub.1 is methyl. In another embodiment, R.sub.1 is
ethyl. In another embodiment, R.sub.1 is methoxy or ethoxy. In
another embodiment, R.sub.1 is methoxy. In another embodiment,
R.sub.1 is ethoxy.
[0067] In one embodiment, R.sub.2 is thiol or disulfide. In another
embodiment, R.sub.2 is thiol or amine. In another embodiment,
R.sub.2 is disulfide or amine. In another embodiment, R.sub.2 is
thiol. In another embodiment, R.sub.2 is disulfide. In another
embodiment, R.sub.2 is amine.
[0068] In one embodiment, R.sub.3 is H or an electron withdrawing
group. In another embodiment, R.sub.3 is H or an electron donating
group. In another embodiment, R.sub.3 is an electron withdrawing
group or an electron donating group. In another embodiment, R.sub.3
is H. In another embodiment, R.sub.3 is an electron withdrawing
group. In another embodiment, R.sub.3 is an electron donating
group. In another embodiment, R.sub.3 is H, --NO.sub.2, or
--CH.sub.3. In another embodiment, R.sub.3 is H or --NO.sub.2. In
another embodiment, R.sub.3 is H or --CH.sub.3. In another
embodiment, R.sub.3 is --NO.sub.2 or --CH.sub.3. In another
embodiment, R.sub.3 is --NO.sub.2. In another embodiment, R.sub.3
is --CH.sub.3.
[0069] In one embodiment, R.sub.1 is (C.sub.1-C.sub.3) alkyl and
R.sub.2 is thiol. In another embodiment, R.sub.1 is
(C.sub.1-C.sub.3) alkyl and R.sub.2 is disulfide. In another
embodiment, R.sub.1 is (C.sub.1-C.sub.3) alkyl and R.sub.2 is
amine. In another embodiment, R.sub.1 is methyl and R.sub.2 is
thiol. In another embodiment, R.sub.1 is methyl and R.sub.2 is
disulfide. In another embodiment, R.sub.1 is methyl and R.sub.2 is
amine. In another embodiment, R.sub.1 is ethyl and R.sub.2 is
thiol. In another embodiment, R.sub.1 is ethyl and R.sub.2 is
disulfide. In another embodiment, R.sub.1 is ethyl and R.sub.2 is
amine.
[0070] In one embodiment, R.sub.1 is (C.sub.1-C.sub.3) alkoxy and
R.sub.2 is thiol. In another embodiment, R.sub.1 is
(C.sub.1-C.sub.3) alkoxy and R.sub.2 is disulfide. In another
embodiment, R.sub.1 is (C.sub.1-C.sub.3) alkoxy and R.sub.2 is
amine. In another embodiment, R.sub.1 is methoxy and R.sub.2 is
thiol. In another embodiment, R.sub.1 is methoxy and R.sub.2 is
disulfide. In another embodiment, R.sub.1 is methoxy and R.sub.2 is
amine. In another embodiment, R.sub.1 is ethoxy and R.sub.2 is
thiol. In another embodiment, R.sub.1 is ethoxy and R.sub.2 is
disulfide. In another embodiment, R.sub.1 is ethoxy and R.sub.2 is
amine.
[0071] The present disclosure also provides a compound of formula
(Ia):
##STR00005##
wherein R.sub.1 is (C.sub.1-C.sub.6) alkyl or (C.sub.1-C.sub.6)
alkoxy; and R.sub.2 is selected from the group consisting of thiol,
disulfide, and amine.
[0072] In one embodiment, R.sub.1 is (C.sub.1-C.sub.3) alkyl or
(C.sub.1-C.sub.3) alkoxy. In another embodiment, R.sub.1 is
(C.sub.1-C.sub.6) alkyl. In another embodiment, R.sub.1 is
(C.sub.1-C.sub.6) alkoxy. In another embodiment, R.sub.1 is
(C.sub.1-C.sub.3) alkyl. In another embodiment, R.sub.1 is
(C.sub.1-C.sub.3) alkoxy. In another embodiment, R.sub.1 is methyl
or ethyl. In another embodiment, R.sub.1 is methyl. In another
embodiment, R.sub.1 is ethyl. In another embodiment, R.sub.1 is
methoxy or ethoxy. In another embodiment, R.sub.1 is methoxy. In
another embodiment, R.sub.1 is ethoxy.
[0073] In one embodiment, R.sub.2 is thiol or disulfide. In another
embodiment, R.sub.2 is thiol or amine. In another embodiment,
R.sub.2 is disulfide or amine. In another embodiment, R.sub.2 is
thiol. In another embodiment, R.sub.2 is disulfide. In another
embodiment, R.sub.2 is amine.
[0074] In one embodiment, R.sub.1 is (C.sub.1-C.sub.3) alkyl and
R.sub.2 is thiol. In another embodiment, R.sub.1 is
(C.sub.1-C.sub.3) alkyl and R.sub.2 is disulfide. In another
embodiment, R.sub.1 is (C.sub.1-C.sub.3) alkyl and R.sub.2 is
amine. In another embodiment, R.sub.1 is methyl and R.sub.2 is
thiol. In another embodiment, R.sub.1 is methyl and R.sub.2 is
disulfide. In another embodiment, R.sub.1 is methyl and R.sub.2 is
amine. In another embodiment, R.sub.1 is ethyl and R.sub.2 is
thiol. In another embodiment, R.sub.1 is ethyl and R.sub.2 is
disulfide. In another embodiment, R.sub.1 is ethyl and R.sub.2 is
amine.
[0075] In one embodiment, R.sub.1 is (C.sub.1-C.sub.3) alkoxy and
R.sub.2 is thiol. In another embodiment, R.sub.1 is
(C.sub.1-C.sub.3) alkoxy and R.sub.2 is disulfide. In another
embodiment, R.sub.1 is (C.sub.1-C.sub.3) alkoxy and R.sub.2 is
amine. In another embodiment, R.sub.1 is methoxy and R.sub.2 is
thiol. In another embodiment, R.sub.1 is methoxy and R.sub.2 is
disulfide. In another embodiment, R.sub.1 is methoxy and R.sub.2 is
amine. In another embodiment, R.sub.1 is ethoxy and R.sub.2 is
thiol. In another embodiment, R.sub.1 is ethoxy and R.sub.2 is
disulfide. In another embodiment, R.sub.1 is ethoxy and R.sub.2 is
amine.
[0076] In one embodiment, the compound of formula (Ia) is a
1-pyrene, 2-pyrene or 4-pyrene. In another embodiment, the compound
of formula (Ia) is 1-pyrene or 2-pyrene. In another embodiment, the
compound of formula (Ia) is 1-pyrene or 4-pyrene. In another
embodiment, the compound of formula (Ia) is 2-pyrene or 4-pyrene.
In another embodiment, the compound of formula (Ia) is 1-pyrene. In
another embodiment, the compound of formula (Ia) is 2-pyrene. In
another embodiment, the compound of formula (Ia) is 4-pyrene.
Methods of Use
[0077] The present disclosure also provides a method of determining
the sequence of a nucleic acid. The method comprises providing an
apparatus as disclosed herein. A sample comprising a nucleic acid
is passed through the tunnel gap either by diffusion or through
electrophoresis. When a nucleobase of the nucleic acid passes
through the tunnel gap it interacts with the first and second
reagent. This interaction is due to .pi.-.pi. stacking between the
first and second reagent (e.g., the aromatic compound) and the
nucleobase. The .pi.-.pi. stacking interaction causes a detectable
signal. The signal so produced can be detected, e.g., by detecting
an electrical current. From the detectable signal, the nucleobase
is identified. These steps are repeated until the sequence of the
nucleic acid is determined. The nucleic acid is DNA in one
embodiment and RNA in a second embodiment.
[0078] In one embodiment, the method of determining the sequence of
a nucleic acid further comprises providing a second apparatus
comprising a third and a fourth electrode that form a tunnel gap
through which the nucleic acid sequence can pass, wherein the third
and the fourth reagents are each capable of forming a transient
bond to a nucleobase of the nucleic acid, the third and fourth
reagents being independently selected from the group consisting of
mercaptobenzoic acid, 4-mercaptobenzcarbamide,
imidazole-2-carboxide, and 4-carbamonylphenyldithiocarbamate. A
sample comprising a nucleic acid is passed through the tunnel gap
either by diffusion or through electrophoresis. When the transient
bond between the third and fourth reagent and the nucleobase forms,
a detectable signal is produced. From this detected signal, the
nucleobase is identified.
[0079] These steps are repeated until the sequence of the nucleic
acid is determined. The nucleic acid is DNA in one embodiment and
RNA in a second embodiment.
[0080] In embodiments in which the nucleic acid is sequenced using
two apparatus, the first and second reagent are as defined in
herein and the third and fourth reagent is
4(5)-(2-mercaptoethyl)-1H-imidazole-2-carboxamide (Iz). In one
embodiment, the first and second reagent is
1-(2-mercaptoethyl)pyrene (Py) and the third and fourth reagent is
4(5)-(2-mercaptoethyl)-1H-imidazole-2-carboxamide (Iz).
[0081] The two apparatus sequencing method provides comprehensive
information on genome sequences, for example, damages of DNA bases,
which is lost in NGS due to the use of polymerases that can
incorporate dAMP into the opposite of an abasic site ("A
rule".sup.38) or cause a frameshift..sup.39
[0082] In order that this invention be more fully understood, the
following examples are set forth. These examples are for the
purpose of illustration only and are not to be construed as
limiting the scope of the invention in any way.
EXAMPLES
Example 1--Computer Modeling
[0083] To demonstrate the feasibility to distinguish between two
DNA bases via the .pi.-.pi., a computer model comprising two gold
electrodes each carrying a Py molecule through a S--Au bond, which
sandwiches a uracil base (FIG. 2) or a guanine base (FIG. 3) was
built. With the gold atoms fixed, the system geometry is optimized
to the minimum energy using Self-Consistent Charge-Tight-Binding
DFT (SCC-DFTB) (Aradi B et al., J. Phys. Chem. A 2007, 111:
5678-5684; Elstner M, et al. Physical Review B 1998, 58(11):
7260-7268; and Porezag D, et al. Physical Review B 1995, 51(19):
12947-12957). Using first-principles quantum transport simulations,
based on the nonequilibrium Green function formalism (Datta S.
Nanotechnology 2004, 15(7): S433-S451) combined with tight-binding
density functional theory (NEGF+DFTB) (Pecchia A, Carlo A D.
Reports on Progress in Physics 2004, 67(8): 1497-1561; Pecchia A,
et al., New Journal of Physics 2008, 10(6): 065022; and Carlo A D
et al., In: Cuniberti G, Fagas G, Richter K (eds). Introducing
Molecular Electronics: Lecture Notes in Physics vol. 680. Springer:
Berlin, 2005, pp 153-184), changes in the total electronic currents
through the system were examined with the voltage bias U applied
between the gold electrodes in a range of 0.01 V to 1 V.
[0084] As shown in FIG. 4, at lower bias the current response is a
weak power dependence on the voltage (up to .about.0.2 V for
guanine, and to .about.0.4 V for uracil), which can be fit to an
analytic form I=G(U/U.sub.0).sup.b, where for uracil G=307 pA,
b=1.03 and for guanine G=1.228.6, b=1.24. In both cases U.sub.0=1
V. This example shows that a sandwiched complex of pyrene with a
purine (guanine) ring is more conductive than with the pyrimidine
(uracil) in a nanogap when they are optimally stacked without
steric hindrance.
Example 2--Synthesis
General Information.
[0085] Reagents and solvents were purchased from commercial
suppliers (Sigma-Aldrich, Alfa Aesar, Fluka, TCI America) and used
as received unless otherwise noted. All experiments requiring
anhydrous conditions were performed in flame-dried glassware under
nitrogen atmosphere. Reactions were monitored by thin layer
chromatography (TLC) using glass plates pre-coated with silica gel
(EMD Chemicals Inc.). Flash chromatography was performed in an
automated flash chromatography system (CombiFlash R.sub.f, Teledyne
Isco, Inc.) with silica gel columns (60-120 mesh). Purchased
1-bromopyrene (95% purity) was further purified by silica gel flash
chromatography eluting with hexane, dried at 40.degree. C.
overnight, and stored over drierite under vacuum. THF was freshly
distilled over sodium prior to use. Nitrogen was flowed through
drierite before it went into the reaction vessel. Ethylene oxide
(1.2 M solution in dichloromethane) was stored over molecular
sieves for two days before use. .sup.1H NMR and .sup.13C NMR
spectra were recorded on Varian INOVA 400 (400 MHz) and Varian
INOVA 500 (500 MHz) spectrometers at 25.degree. C. at the Magnetic
Resonance Research Center at Arizona State University. Chemical
shifts (6) are given in parts per million (ppm) and are referenced
to the residual solvent peak (CDCl.sub.3: .delta..sub.H=7.26 ppm,
CD.sub.3OD: .delta..sub.H=3.31 ppm, DMSO-d.sub.6:
.delta..sub.H=2.50 ppm). Coupling constants (1) are expressed in
hertz (Hz) and the values are rounded to the nearest 0.1 Hz.
Splitting patterns are reported as follows: br, broad; s, singlet;
d, doublet; dd, doublet of doublets; t, triplet; dt, doublet of
triplets; q, quartet and m, multiplet. High resolution mass spectra
(HRMS) are acquired at the Arizona State University CLAS High
Resolution Mass Spectrometry Facility.
2.1--1-(2-mercaptoethyl)pyrene (Py)
[0086] 1-(2-mercaptoethyl)pyrene (Py) can be synthesized according
to Scheme 1.
##STR00006##
2-(pyren-1-yl)ethanol (1)
[0087] A solution of 1-bromopyrene (0.4 g, 1.42 mmol in 12 mL THF)
was added onto magnesium turnings (0.1 g, 4.27 mmol) in a
flame-dried Schlenk flask. It was refluxed at 70.degree. C. while
the solution turned into dark brown color and continued to reflux
for another 2 h. The resulting solution was cooled in an ice bath
followed by addition of ethylene oxide solution (3.6 mL, 4.27 mmol
in 6 mL THF). The mixture was allowed to warm to room temperature
and stirred for 12 h. It was cooled in an ice bath then hydrolyzed
by careful addition of HCl (5 mL 10%), and extracted with ethyl
acetate (20 mL.times.2). The combined organic layers were washed
with brine (40 mL), dried over MgSO.sub.4, filtered and evaporated
to dryness by rotary evaporator. The product was separated through
a silica gel column by flash chromatography using a gradient of
ethyl acetate (0-20% for 3 h) in hexane. Compound 1 was obtained as
yellow solid (0.14 g, 40%). .sup.1H NMR (500 MHz, CDCl.sub.3):
.delta. 8.29 (d, J=9.0 Hz, 1H, ArH), 8.18 (d, J=8.0 Hz, 2H, ArH),
8.10-8.13 (m, 2H, ArH), 7.99-8.04 (m, 3H, ArH), 7.90 (d, J=8.0 Hz,
1H, ArH), 5.29 (s, br, 1H, OH), 4.09 (t, J=6.5 Hz, 2H,
CH.sub.2CH.sub.2OH), 3.61 ppm (t, J=6.5 Hz, 2H,
CH.sub.2CH.sub.2OH); .sup.13C NMR (125 MHz, CDCl.sub.3): .delta.
132.53, 131.52, 130.98, 130.42, 129.36, 128.07, 127.68, 127.57,
127.09, 126.06, 125.24, 125.19, 125.00, 124.97, 123.30, 63.95,
36.78, 29.85 ppm; HRMS (FAB+): found m/z 247.1129; calculated for
C.sub.18H.sub.14O+H: 247.1123.
2-(Pyren-1-yl)ethyl 4-methylbenzenesulfonate (2)
[0088] Triethyl amine (0.08 mL, 0.55 mmol) was added into a
solution of compound 1 (45 mg, 0.18 mmol) and tosyl chloride (52
mg, 0.28 mmol) in dichloromethane (1.5 mL) at room temperature. The
resulting solution was stirred for 16 h, followed by addition of
saturated sodium bicarbonate solution (5 mL), extracted with
dichloromethane (3.times.10 mL). The combined organic phase was
washed with brine (30 mL), dried over MgSO.sub.4, filtered and
evaporated to dryness by rotary evaporator. The residue was
separated by flash chromatography through a silica gel column using
a gradient of ethyl acetate (0-20% over a period of 3 h) in hexane.
Compound 2 was obtained as a white solid (60 mg, 82%). .sup.1H NMR
(500 MHz, CDCl.sub.3): .delta. 8.17 (q, J=7.5 Hz, 2H, ArH),
7.95-8.05 (m, 6H, ArH), 7.76 (d, J=7.5 Hz, 1H, ArH), 7.33 (d, J=8.5
Hz, 2H, Tosyl-ArH), 6.68 (d, J=8.5 Hz, 2H, Tosyl-ArH), 4.44 (t,
J=7.0 Hz, 2H, CH.sub.2CH.sub.2OTs), 3.64 (t, J=7.0 Hz, 2H,
CH.sub.2CH.sub.2OTs), 1.85 ppm (s, 3H, CH.sub.3); .sup.13C NMR (125
MHz, CDCl.sub.3): .delta. 144.28, 132.23, 131.37, 130.73, 130.65,
129.96, 129.17, 128.87, 128.28, 127.80, 127.47, 127.40, 127.23,
126.08, 125.32, 125.13, 125.06, 124.80, 124.79, 122.52, 70.41,
33.06, 21.05 ppm; HRMS (FAB+): found m/z 401.1213; calculated for
C.sub.25H.sub.20O.sub.3S+H 401.1211.
S-(2-(pyren-1-yl)ethyl) ethanethioate (3)
[0089] Potassium thioacetate (24 mg, 0.206 mmol) was added to a
solution of 2 (55 mg, 0.138 mmol) in DMF (1.5 mL). The resulting
mixture was stirred for 16 h at room temperature. Brine (10 mL) was
added into the reaction mixture, extracted with dichloromethane
(2.times.10 mL). The combined organic phase was dried over
MgSO.sub.4, filtered and evaporated to dryness by rotary
evaporator. The residue was separated by flash chromatography
through a silica gel column using a gradient of ethyl acetate (0-5%
over 3 h) in hexane. Compound 3 was obtained as a white solid (32
mg, 78%). .sup.1H NMR (500 MHz, CDCl.sub.3): .delta. 8.42 (d, J=9.5
Hz, 1H, ArH), 8.15-8.20 (m, 3H, ArH), 8.12 (d, J=8.0 Hz, 1H, ArH),
7.99-8.04 (m, 3H, ArH), 7.89 (d, J=8.0 Hz, 1H, ArH), 3.60 (t, J=8.0
Hz, 2H, CH.sub.2CH.sub.2S), 3.32 (t, J=8.0 Hz, 2H,
CH.sub.2CH.sub.2S), 2.41 ppm (s, 3H, CH.sub.3); .sup.13C NMR (125
MHz, CDCl.sub.3): .delta. 196.17, 134.14, 131.49, 131.00, 130.47,
129.01, 127.86, 127.56, 127.10, 126.02, 125.18, 125.17, 125.06,
125.03, 124.96, 123.30, 33.95, 30.87 ppm (two carbons were not
identified); HRMS (FAB+): found m/z 305.1001; calculated for
C.sub.20H.sub.16OS+H: 305.1000.
1-(2-Mercaptoethyl)pyrene (Py)
[0090] Pyrrolidine (2 .mu.L, 24.6 .mu.mol) was added into a
solution of 3 (5 mg, 16.4 .mu.mol) in ethanol (1 mL) and stirred
for 30 min at room temperature. Solvent was evaporated to dryness
by rotary evaporator to obtain Py (4.3 mg, 100%). R.sub.f on TLC:
0.18 (9:1 hexane/ethyl acetate). HRMS (APCI+): found m/z 263.0886;
calculated for C.sub.18H.sub.14S+H: 263.0894.
Example 3--Monolayers on Palladium Substrates
3.1 Fabrication of Palladium Substrate
[0091] Palladium substrates were made in ASU CSSER cleanroom using
Lesker PVD75 Electron Beam Evaporator (Lesker#3). Pure (99.99%)
palladium and titanium metal targets were bought from Kurt J.
Lesker Company and circular silicon wafers (10 cm diameter) were
purchased from Silicon Quest International. Prior to use, silicon
wafers were cleaned with hydrofluoric acid, washed with isopropanol
and nanopure water, and then blow-dried with a nitrogen flow. Over
the silicon wafer a thin titanium adhesive layer (10 nm thick) was
deposited, and then a palladium layer (200 nm thick) was deposited
over titanium film. Small squares of 1.times.1 cm.sup.2 were cut
prior to use.
3.2 Monolayer Formation and Characterization
[0092] 3.2.1 Rp Monolayer.
[0093] A solution of compound 3 (100 .mu.M) and pyrrolidine (1 mM)
in degassed ethanol was prepared. After 30 min, a palladium
substrate was immersed into the solution for 8 h, washed thoroughly
with ethanol, dried with a nitrogen flow, used immediately for the
RT measurement. The Py monolayer was characterized with
elliposometry and contact angle (Table 1), XPS (FIG. 5), and FTIR
(FIG. 6A and FIG. 6B).
TABLE-US-00001 TABLE 1 Thickness* and contact angle** of Py SAM on
palladium Thickness by Ellipsometry (.ANG.) Contact Angle
(.degree.) 8.6 .+-. 0.6 67.8 .+-. 4.5 *Thickness of self-assembled
monolayers were measured using LSE STOKES Ellipsometer with HeNe
laser (632.8 nm wavelength) and 70.degree. incident angle of
measuring laser beam. Prior to functionalization, ellipsometric
parameters of bare clean palladium substrates were measured and
used for determination of the thickness of the functionalized
substrates. Refractive index value for organic film was set as
1.46. **Easydrop was used to measure water contact angle of SAM on
palladium substrate. The data reported is an average of five
measurements taken on each sample with a water droplet volume of 1
.mu.L.
[0094] For the XPS experiments, X-ray photoelectron spectra were
obtained using Al-K.alpha. radiation (15 keV) at 6.times.10-10 mbar
base pressure on VG ESCALAB 220i-XL photoelectron spectrometer.
Wide scan spectra were recorded at 150 eV pass energy and high
resolution spectra for C(1s), Pd(3d) and S(2p) were obtained at 20
eV pass energy. Elemental ratio of the SAM was calculated from area
under the peaks of corresponding elements using CasaXPS software
package. Table 2 shows the calculated elemental ratio and
experimental elemental ratio.
TABLE-US-00002 TABLE 2 Calculated Elemental Ratio Found Elemental
Ratio for S:C for S:C (from XPS) 1:18 1:13.5 .+-. 1.5
[0095] For the FTIR experiments, the spectrum of powder sample was
acquired with smart orbit (attenuated total reflection) and SAM
spectra with SAGA (Specular Aperture Grazing Angle) accessory on
Thermo Nicolet A Nicolet 6700 FT-IR (Thermo Electron CoPyoration)
instrument equipped with a MCT detector. A background spectrum was
recorded before recording the FT-IR of powder sample and a bare
palladium substrate in case of monolayer sample. All the FT-IR data
were subjected to baseline correction using the built-in spectrum
program. The vibration around 3040 cm.sup.-1 is assigned to
aromatic C--H stretching, 1600 cm.sup.-1 aromatic C--C stretching,
.about.2925 cm.sup.-1 aliphatic C--H stretching from methylene
group, and 2564 cm.sup.-1 s-h stretching, which is absent in SAM
spectrum.
[0096] 3.2.2 Bn Monolayer.
[0097] A palladium substrate was immersed in an ethanolic
(degassed) solution of Bn (50 .mu.M) for 2.5 h, washed thoroughly
with ethanol, dried with a nitrogen flow, and used immediately. The
Bn monolayer was characterized with elliposometry and contact angle
following the protocol of Example 3.2.1 (Table 3), and FTIR (FIG.
7A and FIG. 7B)
TABLE-US-00003 TABLE 3 Thickness and contact angle of Bn SAM on
palladium Thickness by Ellipsometry (.ANG.) Contact Angle
(.degree.) 5.6 .+-. 0.9 79.5 .+-. 4.1
[0098] For the FTIR experiments, the spectrum of neat sample was
acquired with SMART ORBIT (Attenuated Total Reflection) and SAM
spectra with SAGA (Specular Aperture Grazing Angle) accessory on
Thermo Nicolet A Nicolet 6700 FT-IR (Thermo Electron CoPyoration)
instrument equipped with a MCT detector. A background spectrum was
recorded before recording the FTIR of powder sample and a bare
Palladium substrate in case of monolayer sample. All the FTIR data
were subjected to baseline correction using the built-in SPECTRUM
program. The vibration around 3020 cm".sup.1 is assigned to
aromatic C--H stretching, 1600 cm".sup.1 aromatic C--C stretching,
2930 cm".sup.1 aliphatic C--H stretching from methylene group, and
2568 cm".sup.1 S--H stretching, which is absent in the SAM
spectrum.
[0099] 3.2.3 Iz monolayer. A palladium substrate was immersed in a
degassed ethanolic solution of Iz (500 .mu.M) for 16 h, washed
thoroughly with ethanol, dried with a nitrogen flow, and used
immediately (Chang S, et al. Nanotechnology 23, 425202 (2012).
[0100] This example confirms by contact angle measurements,
elliposometry, FTIR and XPS that both Py and Bn could form
monolayers on the Pd substrate.
Example 4--Surface Plasmon Resonance (SPR)
[0101] A gold chip was immersed into an absolute ethanol solution
of Py (100 .mu.M) for 24 h, followed by rinsing with absolute
ethanol and drying with a nitrogen flow, and used immediately. The
instrument Bi 2000 from Biosensing Instrument was used for SPR
measurements. The Py modified gold chip was mounted on the
instrument and calibrated with 1% ethanol in a phosphate buffer, pH
7.4. A solution of dGMP (500 .mu.M) was flowed onto the chip at a
rate of 50 ul/min over a period of 1.5 min, followed by flowing the
PBS buffer (FIG. 8). Association (k.sub.on) and dissociation rate
constants (k.sub.off) were determined using built-in Biosensing
Instrument SPR data analysis software version 2.4.6 (Table 4).
TABLE-US-00004 TABLE 4 Kinetic parameters of dGMP on the pyrene
monolayer.sup.1 k.sub.on k.sub.off K.sub.d.sup.2 dGMP (M.sup.-1
s.sup.-1) (s.sup.-1) (mM) Res. sd 500 uM 41.60 .+-. 2.50 0.09 .+-.
0.01 2.46 .+-. 0.12 10.2 .+-. 1.4 4 .sup.1Each datum listed is an
average of three measurements. .sup.2K.sub.d =
k.sub.off/k.sub.on
[0102] This example shows that DNA nucleotides, such as dGMP, can
be absorbed on the Py monolayer with an affinity of K.sub.d=2.46 mM
in aqueous solution.
Example 5--Recognition Tunneling Using Scanning Tunneling
Microscope
[0103] In this example, Scanning Tunneling Microscope (STM) was
used to create the tunnel nanogaps between a Pd probe and a Pd
substrate, which were functionalized with Py, Iz, or a
(2-mercaptoethyl)benzene control (Bn) prior to use.
5.1 DNA Monophosphate Solution
[0104] All of analytes were purchased from Sigma Aldrich with
purity of .gtoreq.98% except AP (.gtoreq.95%). Ultrapure water with
specific resistance .about.18 M.OMEGA. and organic carbon particle
.about.4 ppb from MilliQ system was used for solution preparation.
Each analyte solution was prepared with a concentration of 100
.mu.M in 1.0 mM phosphate buffer pH 7.4.
5.2 Functionalization of Palladium Probes
[0105] Probe preparation followed a known method..sup.10 A batch of
4 STM Probes were made by electrochemically etching palladium wires
with 0.25 mm diameter (from California Fine Wires) in a mixed
solution of con. hydrochloric acid (36% w) and ethanol (1:1),
followed by insulation with high density polyethylene, which left
the apexes open. Any probes with leakage current >1 pA were
discarded and the rest were functionalized with reader molecules in
the same procedure as described above for preparation of the
monolayer, and used immediately for RT measurements.
5.3 Data Collection
[0106] The measurements were carried out in PicoSPM instrument
(Agilent Technologies), interfaced with a customized Labview
program. The sampling rate for tunnel current was 50 kHz. Prior to
the experiment, the STM teflon cell was cleaned with piranha
followed by vigorous rinsing with Milli-Q water and ethanol. After
adding .about.150 .mu.L, of phosphate buffer (1.0 mM, pH 7.4 to the
STM cell, the functionalized palladium probe (with leakage current
<1 pA; prepare in Example 5.2) and Pd-substrate were installed
to the scanner. The probe was approached to the functionalized
surface with a set value of 1.0 for integral and proportional gain
at 2 pA current set-point and -500 mV bias (substrate negative).
Then a few images were scanned to ensure that the probe was
perfectly oriented over the substrate and the Pd crystal grains can
be seen clearly. After that, the probe was withdrawn for 10 .mu.m
for 2 hours to ensure that there was no drift and minimal
mechanical noise. Then the probe was engaged again and control data
was recorded with a reduced value of integral and proportional gain
(0.1). Once the tunnel junction was stabilized, the phosphate
buffer was discarded and an analyte solution was introduced
(typically 100 .mu.M in 1.0 mM phosphate buffer, pH 7.4) to the
liquid cell, and current recordings were collected under a
predefined tip-substrate bias. Four naturally occurring DNA
nucleoside monophosphates (dAMP, dCMP, dGMP and dTMP) and two sugar
molecules (abasic 5'-monophosphate, designated as AP, and
D-glucose) were used as analytes (prepared in Section 5.1). For
each analyte, four data sets were collected separately with freshly
made probes, substrates, and samples.
5.4 Data Analysis
[0107] 5.4.1 Analysis of RT Raw Data
[0108] Data recorded in the time domain was characterized by peak
height, averaged amplitude, peak width, and so on (FIG. 9A) using
Matlab. First, the baseline tunneling current was shifted to zero
and a threshold was set at 15 pA for the tunneling spikes. The peak
height, averaged amplitude, peak width data were exported to
OriginPro 2016 for the analysis and the curve fitting was performed
using the built-in Levenberg-Marquardt algorithm. The results are
listed in Table 5.
TABLE-US-00005 TABLE 5 Py Iz dAMP dCMP dGMP dTMP Average dAMP dCMP
dGMP dTMP Average Peak Median 9.74 .+-. 8.29 .+-. 8.92 .+-. 8.97
.+-. 8.98 .+-. 8.46 .+-. 8.88 .+-. 8.81 .+-. 8.75 .+-. 8.72 .+-.
height 0.06 0.03 0.04 0.03 0.02 0.03 0.03 0.03 0.03 0.02 (pA) Mean
10.34 .+-. 8.52 .+-. 9.28 .+-. 9.33 .+-. 9.36 .+-. 8.69 .+-. 9.16
.+-. 9.10 .+-. 9.02 .+-. 8.99 .+-. 0.07 0.03 0.05 0.04 0.02 0.03
0.04 0.03 0.03 0.02 Sigma 3.67 .+-. 2.03 .+-. 2.65 .+-. 2.67 .+-.
2.76 .+-. 2.03 .+-. 2.35 .+-. 2.35 .+-. 2.29 .+-. 2.26 .+-.
(.sigma.) 0.08 0.04 0.05 0.04 0.03 0.03 0.04 0.04 0.03 0.02
Averaged Median 4.64 .+-. 4.87 .+-. 4.41 .+-. 3.62 .+-. 4.39 .+-.
4.38 .+-. 4.45 .+-. 4.32 .+-. 4.33 .+-. 4.37 .+-. amplitude 0.02
0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 (pA) Mean 4.91 .+-.
5.02 .+-. 4.62 .+-. 3.89 .+-. 4.61 .+-. 4.57 .+-. 4.67 .+-. 4.54
.+-. 4.54 .+-. 4.58 .+-. 0.02 0.01 0.02 0.01 0.01 0.01 0.01 0.01
0.01 0.01 Sigma 1.68 .+-. 1.26 .+-. 1.45 .+-. 1.52 .+-. 1.48 .+-.
1.37 .+-. 1.48 .+-. 1.45 .+-. 1.43 .+-. 1.43 .+-. (.sigma.) 0.02
0.01 0.02 0.01 0.01 0.01 0.01 0.01 0.01 0.01 Peak Median 0.378 .+-.
0.413 .+-. 0.395 .+-. 0.349 .+-. 0.384 .+-. 0.404 .+-. 0.404 .+-.
0.398 .+-. 0.404 .+-. 0.403 .+-. width 0.002 0.001 0.002 0.001
0.001 0.002 0.002 0.003 0.002 0.001 (ms) Mean 0.397 .+-. 0.430 .+-.
0.412 .+-. 0.360 .+-. 0.400 .+-. 0.421 .+-. 0.421 .+-. 0.414 .+-.
0.420 .+-. 0.419 .+-. 0.002 0.001 0.003 0.001 0.001 0.003 0.003
0.003 0.003 0.002 Sigma 0.126 .+-. 0.125 .+-. 0.124 .+-. 0.090 .+-.
0.116 .+-. 0.123 .+-. 0.125 .+-. 0.119 .+-. 0.120 .+-. 0.122 .+-.
(.sigma.) 0.002 0.001 0.003 0.001 0.001 0.003 0.003 0.003 0.003
0.002 Spike 7.5 .+-. 8.1 .+-. 8.1 .+-. 12.4 .+-. 9.0 .+-. 6.9 .+-.
8.4 .+-. 8.9 .+-. 6.2 .+-. 7.6 .+-. Frequency 2.2 2.2 4.7 3.0 1.7
2.5 6.4 3.3 0.8 1.9
[0109] 5.4.2 Extraction of Features from RT Data
[0110] RT spectrum were analyzed by defining two types of event
signals, spikes and clusters. The spike is an individual single RT
spectrum and the cluster is a subset of close spikes. To define a
cluster, a Gaussian window (4096 data points and one-unit height)
was applied to the center of each spike.
[0111] Spike that lie within a region where the sum of the Gaussian
windows continuously exceeds 0.1 were identified as belonging to a
cluster. Although each independent tunneling spike was identified
by having amplitude above 15 pA, the cluster includes all the
spikes within the defined region. Table 6 lists features used to
describe an individual spike.
TABLE-US-00006 TABLE 6 Feature Name Feature Description Primary
P_max Amplitude Maximum amplitude of the peak Features P_average
Amplitude Average current of the peak P_top Average Average of the
peak above half maximum P_peakWidth Full width at half maximum
P_roughness Standard deviation of the peak above half maximum
height P_frequency Number of peaks per millisecond over a window of
4096 C_peaksInCluster Number of peaks in the cluster C_frequency
Number of peaks in cluster divided by millisecond length of cluster
C_average Amplitude Average amplitude of all cluster peaks C_top
Average Average amplitude of all peaks above half maximum C_cluster
Width Cluster time length in millisecond C_roughness Standard
deviation of whole cluster signal C_max Amplitude Average of the
max of all the peaks in cluster Secondary P_totalPower Square root
of the sum of power spectrum Features P_iFFTLow Average of the
first three frequency bands P_iFFTMedium Average of the middle
three frequency bands P_iFFTHigh Average of the highest three
frequency bands P_peakFFT1~10 Downsampled FFT spectrum
P_highLow_Ratio Ratio of P_iFFTLow to P_iFFTHigh P_Odd_FFT Sum of
all odd frequencies from the non- downsampled FFT P_Even FFT Sum of
all even frequencies from the non- downsampled FFT P_OddEvenRatio
Ratio of the odd to the even FFT sums P_peakFFT_Whole1~51
Downsampled FFT spectrum into various bandwidths. (Lower frequency
range, smaller bandwidth size) C_totalPower Square root of the sum
of the power spectrum C_iFFTLow Average of the first three
frequency bands C_iFFTMedium Average of the middle three frequency
bands C_iFFTHigh Average of the highest three frequency bands
C_clusterFFT1~61 Downsampled FFT spectrum of cluster C_highLow
Ratio of the odd to the even FFT sums of cluster
C_freq_Maximum_Peak1~4 Frequency of the four dominant peaks in the
spectrum, ordered by the height of the peaks C_clusterCepstrum1~61
Spectrum of the power spectrum of the cluster, downsampled to 61
points C_clusterFFT_Whole1~51 Downsampled FFT spectrum into various
bandwidths. (Lower frequency range, smaller bandwidth size)
[0112] Spikes and clusters in a RT spectrum were Fourier
transformed into a 25 kHz window that is the Nyquist frequency of
amplifier, and then the whole frequency range was downsampled to
small windows. As shown in FIG. 9B, peakFFT and clusterFFT denote
features that have the same sampling window size (marked in red),
and peakFFT Whole and clusterFFT Whole denote features with varied
window size (marked in green), of which those with lower
frequencies have smaller sampling window sizes (only six windows
are shown for the simplicity in the figure). Furthermore, logarithm
of the Fourier transformed spectrum was subjected to the inverse
Fourier transform, which generated a new spectrum, referred to as
cepstrum (FIG. 9C). The cepstrum was also down sampled into the
even size of windows for sampling. Once all the features were
determined, they were normalized and scaled to make standard
deviation to 1. In this way, features of large numeric values were
prevented from dominating those that have small numeric values.
[0113] 5.4.3 Feature Selection
[0114] Randomly selected 10% data were used to construct support
vectors (hyper plane to separate analyte data points) to train the
SVM, and then tested the rest 90% of data to determine the calling
accuracy for each DNA nucleotide. There are totally 264 features in
Table 6. Some of them are strongly correlated with one another so
they were removed through the normalized correlation calculation
between feature pairs with coefficient larger than 0.7. A feature
variation between the repeated experiments and different analytes
are calculated by comparing histograms of a feature in a single
measurement with the accumulated measurements. The difference
between the repeated runs histogram and the accumulated histogram
of an analyte is assigned as `in-group` fluctuation (variation of
the repeats). The difference of a feature between the normalized
histogram of a pairs of analytes is `out-group` fluctuation
(variation of the analytes). The features were ranked by the ratio
between the in-group fluctuation and the out-group fluctuation, and
the low ranked features were dropped. The survived features were
further optimized to get the maximum true positive accuracy.
[0115] 5.4.4 SVM Analysis
[0116] The kernel-mode SVM available from the world wide web (www)
at github.com/vjethava/svm-theta was used. The WM running
parameters C and gamma were optimized through cross-validation of
randomly selected sub data set. Full details of the SVM (written in
Matlab) can be found on the world wide web (www) at
github.com/ochensati/SVM_DNA_TunnelVision.
5.5 RT of AP
[0117] RT spectra of AP were collected in the same way as we
collected those of the DNA nucleotides. A solution (100 .mu.M) of
AP (purchased from Sigma Aldrich) was prepared in phosphate buffer,
pH 7.4. The RT measurements with Py were carried out at a set point
of 2 pA current and 500 mV probe bias, and those with Iz at a
set-point of 4 pA current and 500 mV probe bias, always following a
clean baseline achieved with pure phosphate buffer.
[0118] While RT signals were generated with Iz and four sets of
data were recorded for SVM analysis, no AP signal was obtained from
the RT experiments with Py as expected. The SVM could not separate
the AP signals from those of DNA nucleotides generated by Iz.
However, the AP signals appear to be much different from the DNA
nucleotide signals generated with Py. As a result, all five
analytes (dAMP, dCMP, dGMP, dTMP & AP) were classified with
high accuracy (Table 7).
TABLE-US-00007 TABLE 7 dAMP dCMP dGMP dTMP AP (Py) (Py) (Py) (Py)
(Iz) Average Accuracy 98.4 98.7 97.9 97.0 97.2 97.8
5.6 Results
[0119] It was first determined that at the set point of 4 pA and
0.5 V the tunneling gap functionalized with Iz presented a clean
baseline. Under these conditions, the gap distance was estimated to
be .about.2.4 nm..sup.35 As expected, Iz produced RT signals
(spikes) with all of the analytes we measured (FIG. 11A-FIG. 11F).
On changing the set-point to 2 pA and 0.5 V, corresponding to a
larger gap size, Iz still read the analytes, but less frequently
than at 4 pA (data not shown). In contrast, Py presented a cleaner
baseline at 2 pA, 0.5 V than at 4 pA, 0.5 V, and it generated RT
signals with all the four naturally occurring DNA nucleoside
monophosphates, but not with the AP and sugar molecules (FIG.
11G-FIG. 11L). The results may be best explained as a consequence
of the formation of sandwiched structures between pyrenes and DNA
bases..sup.36 Under the same set point of 2 pA and 0.5 V, the Bn
control didn't generate any tunneling signals from these
nucleotides (FIG. 11M-FIG. 11P). When the tip was functionalized
with Bn and the substrate with Py, interestingly, the purine
nucleotides dAMP and dGMP gave tunneling signals, but the
pyrimidine nucleotides did not (FIG. 11Q-FIG. 11T). This indicates
that the stacking interactions in the tunneling gap are driven by
the size of reader molecules, given that Bn is smaller than Py in
size, but more polar and hydrophobic. These data show that Py can
distinguish DNA nucleotides from other species more effectively
than Iz.
[0120] RT data were typically collected in the time domain. Each
spike in RT spectra was characterized by peak height (in picoamps,
pA), averaged amplitude (pA)--an average of all individual current
points constituting a spike, and peak width (in milliseconds, ms).
The distributions of these parameters for DNA nucleotides acquired
using both Py and Iz are plotted in histograms along with their
fitting curves respectively (FIG. 12A-FIG. 12F, see Example 5.4.1,
for details on analysis of RT raw data). These data were well fit
into a Log-Normal function (adjusted R.sup.2 >94%), from which
mean, median and sigma (.sigma.) of those parameters were derived
(Table 5). The results show that the tunnel gap functionalized with
Py has a marginally higher tunneling current (9.4 pA) with the DNA
nucleotides than the one with Iz (9.0 pA) on average for the four
nucleotides although the former had a smaller set-point current (2
pA) than the latter (4 pA), but their averaged heights for both Py
and Iz are about same (see FIG. 12A-FIG. 12F and Table 5 for the
averaged amplitude). The residence time of peaks for Iz with a mean
value of 0.42 ms is distributed among the nucleotides more
uniformly than those for Py with a mean value of 0.40 ms (FIG.
12A-FIG. 12F and Table 5), an indication that the hydrogen bonding
reader is less discriminatory to the nucleobases than the stacking
reader. The most important is that the Py reader resolves the four
DNA nucleotides with distinguishable modes (FIG. 12A-FIG. 12F)
although significant overlaps remain in the distributions. Also, Py
can generate tunneling spikes as frequently as Iz with dAMP, dMP
and dGMP, and much more frequently with dTMP than Iz (Table 5).
This suggests that the .pi.-.pi. stacking is as efficient as the
hydrogen bonding for reading DNA bases. However, none of these
parameters alone are sufficient to identify the DNA
nucleotides.
[0121] In order to call DNA nucleotides from the tunneling current
data, the RT spectra were subjected to Fourier transform and
cepstrum conversion (Example 5.4.2 and FIG. 9A-FIG. 9C), which
resulted in 264 features (listed in Table 6). As shown in FIG.
10A-FIG. 10X, no single feature has a capability to distinguish two
DNA nucleotides from each other. However, the probability that any
particular pair of signal feature values occur together is much
more effective in separating analytes. A two-dimensional plot of
"Peak FFT whole 41" and "Cluster roughness" for dAMP and dCMP can
be assigned with 77% accuracy using the pair-wise features (data
not shown). While possible combinations of other features have been
tested (data not shown), only the two just above mentioned gave the
best separation between dAMP and dCMP. It is significantly larger
than a random case of no separation with a value of P=0.5 (or 50%).
Overall, Py can distinguish well between two analytes in any of six
possible pairs consisted of four DNA nucleotides with accuracy of
.about.82% on average (data not shown). In comparison, Iz can only
distiguish between dAMP and dCMP with accuracy of 66% (data not
shown), .about.10% lower than Py. In the best case, Py can achieve
.about.89% separation with the two features alone for dCMP and
dTMP, whereas Iz can only achieve 70% for the two nucleotides of
dAMP and dGMP (data not shown).
[0122] As mentioned above, a 2-D plot was used to illustrate a more
general and harder to visualize multi-dimensional (.gtoreq.4D)
analysis of feature ensembles to attain much higher accuracy. To do
this, a Support Vector Machine (SVM), a machine-learning algorithm,
was used to analyze the tunneling data..sup.22 In brief, the SVM
was first trained using a combination of randomly selected 10%
subsets of the four data pools generated from the feature
extraction for each nucleotide. The process iteratively reduced the
264 available signal features (see Example 5.4.3) to a range of
smaller numbers that maintains a 100% separation for the training
data (see FIG. 13A and FIG. 13B for training accuracy curves). As a
result, the best 94 features were generated for Py and 55 for Iz
(listed in Tables 8 and 9) to identify DNA nucleotides in the
remaining 90% of the data.
TABLE-US-00008 TABLE 8 Independent features of Py for SVM to assign
DNA nucleotides 1. Peak Max Amplitude 2. Peak Average Amplitude 3.
Peak Top Average 4. Peak Width 5. Peak Total Power 6. Peak FFT 3 7.
Peak FFT 6 8. Peak FFT 7 9. Peak FFT 8 10. Peak High Low Ratio 11.
Peak FFT Whole 4 12. Peak FFT Whole 5 13. Peak FFT Whole 6 14. Peak
FFT Whole 7 15. Peak FFT Whole 8 16. Peak FFT Whole 9 17. Peak FFT
Whole 48 18. Peak FFT Whole 49 19. Cluster Average Amplitude 20.
Cluster Roughness 21. Cluster Total Power 22. Cluster FFT Low 23.
Cluster FFT High 24. Cluster FFT 1 25. Cluster FFT 2 26. Cluster
FFT 3 27. Cluster FFT 11 28. Cluster FFT 12 29. Cluster FFT 13 30.
Cluster FFT 14 31. Cluster FFT 15 32. Cluster FFT 16 33. Cluster
FFT 17 34. Cluster FFT 18 35. Cluster FFT 23 36. Cluster FFT 25 37.
Cluster FFT 26 38. Cluster FFT 27 39. Cluster FFT 28 40. Cluster
FFT 29 41. Cluster FFT 30 42. Cluster FFT 31 43. Cluster FFT 32 44.
Cluster FFT 38 45. Cluster FFT 39 46. Cluster FFT 40 47. Cluster
FFT 41 48. Cluster FFT 42 49. Cluster FFT 43 50. Cluster FFT 44 51.
Cluster FFT 47 52. Cluster FFT 48 53. Cluster FFT 49 54. Cluster
FFT 50 55. Cluster FFT 51 56. Cluster FFT 52 57. Cluster FFT 53 58.
Cluster FFT 54 59. Cluster FFT 55 60. Cluster FFT 56 61. Cluster
FFT 57 62. Cluster FFT 58 63. Cluster FFT 59 64. Cluster FFT 60 65.
Cluster FFT 61 66. Cluster High Low 67. Cluster Freq. Maximum Peaks
1 68. Cluster Freq. Maximum Peaks 2 69. Cluster FFT Whole 1 70.
Cluster FFT Whole 16 71. Cluster FFT Whole 17 72. Cluster FFT Whole
18 73. Cluster FFT Whole 19 74. Cluster FFT Whole 20 75. Cluster
FFT Whole 21 76. Cluster FFT Whole 22 77. Cluster FFT Whole 23 78.
Cluster FFT Whole 24 79. Cluster FFT Whole 30 80. Cluster FFT Whole
31 81. Cluster FFT Whole 32 82. Cluster FFT Whole 33 83. Cluster
FFT Whole 34 84. Cluster FFT Whole 35 85. Cluster FFT Whole 36 86.
Cluster FFT Whole 37 87. Cluster FFT Whole 38 88. Cluster FFT Whole
39 89. Cluster FFT Whole 40 90. Cluster FFT Whole 41 91. Cluster
FFT Whole 42 92. Cluster FFT Whole 47 93. Cluster FFT Whole 48 94.
Cluster FFT Whole 49
TABLE-US-00009 TABLE 9 Independent features of Iz for SVM to assign
DNA nucleotides 1. Peak Odd Even Ratio 2. Cluster Average Amplitude
3. Cluster Top Average 4. Cluster Cepstrum 3 5. Cluster Cepstrum 4
6. Cluster Cepstrum 5 7. Cluster Cepstrum 6 8. Cluster Cepstrum 7
9. Cluster Cepstrum 8 10. Cluster Cepstrum 9 11. Cluster Cepstrum
10 12. Cluster Cepstrum 11 13. Cluster Cepstrum 12 14. Cluster
Cepstrum 13 15. Cluster Cepstrum 14 16. Cluster Cepstrum 15 17.
Cluster Cepstrum 16 18. Cluster Cepstrum 17 19. Cluster Cepstrum 18
20. Cluster Cepstrum 19 21. Cluster Cepstrum 20 22. Cluster
Cepstrum 21 23. Cluster Cepstrum 22 24. Cluster Cepstrum 23 25.
Cluster Cepstrum 24 26. Cluster Cepstrum 25 27. Cluster Cepstrum 26
28. Cluster Cepstrum 27 29. Cluster Cepstrum 28 30. Cluster
Cepstrum 29 31. Cluster Cepstrum 30 32. Cluster Cepstrum 31 33.
Cluster Cepstrum 32 34. Cluster Cepstrum 33 35. Cluster Cepstrum 34
36. Cluster Cepstrum 35 37. Cluster Cepstrum 36 38. Cluster
Cepstrum 37 39. Cluster Cepstrum 38 40. Cluster Cepstrum 39 41.
Cluster Cepstrum 40 42. Cluster Cepstrum 41 43. Cluster Cepstrum 42
44. Cluster Cepstrum 43 45. Cluster Cepstrum 44 46. Cluster
Cepstrum 45 47. Cluster Cepstrum 46 48. Cluster Cepstrum 47 49.
Cluster Cepstrum 49 50. Cluster Cepstrum 52 51. Cluster Cepstrum 53
52. Cluster Cepstrum 54 53. Cluster Cepstrum 55 54. Cluster
Cepstrum 56 55. Cluster Cepstrum 58
[0123] The SVM first removed those signals common to all the data
obtained from different samples owing to contamination, capture
events that were insensitive to chemical variation and noise spikes
generated by the STM electronics and servo control, which amounted
to about 30% of signal spikes, and then assigned the remaining
signals to individual DNA nucleotides with the trained features
(see Example 5.4.4). Such a method of training on a subset of all
four data sets (collected with four microscopically-different
tunnel junctions) sets an upper limit on accuracy (called the
"optimistic" accuracy) of identifying an analyte. Practically, it
can be achieved by calibrating the RT device with a standard
solution prior to testing the real sample. As shown in FIG. 13A and
FIG. 13B, the final accuracies fluctuate, depending on different
combinations of those features. Table 10 lists the highest
optimistic accuracy achieved by the SVM for identifying each
individual DNA nucleotide in the plot.
TABLE-US-00010 TABLE 10 The accuracy (%) of both Py and Iz achieved
in determining individual DNA nucleotides by RT dAMP dCMP dGMP dTMP
Mean .+-. .sigma. Py Optimistic 98.8 99.4 97.1 96.7 98.0 .+-. 1.3
Predictive 76.3 89.0 93.4 83.6 85.6 .+-. 7.4 Iz Optimistic 96.5
97.4 96.4 98.1 97.1 .+-. 0.8 Predictive 94.6 75.3 40.3 44.1 63.6
.+-. 26.0
[0124] With the Py reader, the four DNA nucleotides can be
identified with accuracies ranging from 99.4% to 96.7, on average
98.0%, whereas Iz can read the DNA nucleotides with accuracy from
98.1% to 96.4, on average 97.1%. There is a .about.1% improvement
to the optimistic accuracy from Iz to Py. Importantly, even a 0.1%
improvement to accuracy is of great significance for sequencing of
large genomes such as the human genome especially when the focus is
on cancer mutations. This is because misidentification of 1 out of
1,000 nucleotides would result in about 3,000,000 false calls over
a human genome that is composed of .about.3 billion of base pairs.
It is challenging to confirm a single nucleotide variant (SNV)
generated by NGS either owing to a true biological variant or a
technical error..sup.3,37 The RT technology directly reads DNA
bases from their intrinsic properties, providing a method to reduce
the uncertainties in detection of SNVs.
[0125] More interesting is the "predictive" accuracy, which was
generated by training the SVM on data from three tunnel junctions
and then using it to analyze data from the fourth junction. Py can
read the four DNA nucleotides with its predictive accuracies
ranging from 76% to 93%, on average of .about.86%, whereas Iz from
40% to 95%, on average of .about.64% with a much larger standard
deviation (Table 10). These data manifest Py as a better reader
molecule than Iz. Although the predictive accuracy of Py is modest,
it can be improved by measuring the same sample with multiple times
since the RT process is a stochastic. With the predictive
capability, RT can be used to identify unknown samples that contain
analytes that are already built in a RT database.
[0126] In conclusion, .pi.-.pi. stacking interaction can be used to
identify DNA bases in the tunnel gap. Compared to Iz, the pyrene
reader is not only more specific, but also more accurate to reading
those canonical DNA bases. Interestingly, Iz recognizes the abasic
site, which may be used to identify the depurination and
depyrimidination in genomes when a comparison is run with data
generated by Py. Preliminary analysis shows that the RT data of AP
can be separated from those of DNA nucleotides generated by Py with
optimistic accuracy of .about.95% (see Example 5.5, FIG. 14, and
Table 7), but not from those generated by Iz. Thus, the RT
sequencing with both Py and
[0127] Iz should collect more comprehensive information on genomic
sequences, for example damages of DNA bases, which is lost in NGS
due to the use of polymerases that can incorporate dAMP into the
opposite of an abasic site ("A rule".sup.38) or cause a
frameshift..sup.39
REFERENCES
[0128] The following references are hereby incorporated by
reference in their entireties: [0129] 1. Goodwin S, McPherson J D,
McCombie W R. Coming of age: ten years of next-generation
sequencing technologies. Nat Rev Genet 17, 333-351 (2016). [0130]
2. Liu L, et al. Comparison of next-generation sequencing systems.
J Biomed Biotechnol 2012, 251364 (2012). [0131] 3. Qi Y, et al.
Reproducibility of Variant Calls in Replicate Next Generation
Sequencing Experiments. PLoS One 10, e0119230 (2015). [0132] 4.
Huang H, Keohavong P. Fidelity and predominant mutations produced
by deep vent wild-type and exonuclease-deficient DNA polymerases
during in vitro DNA amplification. DNA Cell Biol 15, 589-594
(1996). [0133] 5. Paez J G, et al. Genome coverage and sequence
fidelity of phi29 polymerase-based multiple strand displacement
whole genome amplification. Nucleic Acids Res 32, e71 (2004).
[0134] 6. Martincorena Ii, Campbell P J. Somatic mutation in cancer
and normal cells. Science 349, 1483-1489 (2015). [0135] 7. Treangen
T J, Salzberg S L. Repetitive DNA and next-generation sequencing:
computational challenges and solutions. Nat Rev Genet 13, 36-46
(2012). [0136] 8. Mukhopadhyay R. DNA sequencers: the next
generation. Anal Chem 81, 1736-1740 (2009). [0137] 9. Laver T, et
al. Assessing the performance of the Oxford Nanopore Technologies
MinION. Biomolecular Detection and Quantification 3, 1-8 (2015).
[0138] 10. Szalay T, Golovchenko J A. De novo sequencing and
variant calling with nanopores using PoreSeq. Nat Biotechnol 33,
1087-1091 (2015). [0139] 11. Jain M, Fiddes I T, Miga K H, Olsen H
E, Paten B, Akeson M. Improved data analysis for the MinION
nanopore sequencer. Nat Methods 12, 351-356 (2015). [0140] 12.
Laszlo A H, et al. Decoding long nanopore sequencing reads of
natural DNA. Nat Biotechnol 32, 829-833 (2014). [0141] 13. Manrao E
A, et al. Reading DNA at single-nucleotide resolution with a mutant
MspA nanopore and phi29 DNA polymerase. Nat Biotechnol 30, 349-353
(2012). [0142] 14. Lindsay S. The promises and challenges of
solid-state sequencing. Nat Nanotechnol 11, 109-111 (2016). [0143]
15. Zwolak M, Ventra M D. Electronic Signature of DNA Nucleotides
via Transverse
[0144] Transport. Nano Lett 5, 421-424 (2005). [0145] 16. Tsutsui
M, Taniguchi M, Yokota K, Kawai T. Identifying single nucleotides
by tunnelling current. Nat Nanotechnol 5, 286-290 (2010). [0146]
17. Ohshiro T, Matsubara K, Tsutsui M, Furuhashi M, Taniguchi M,
Kawai T. Single-molecule electrical random resequencing of DNA and
RNA. Sci Rep 2, 501 (2012). [0147] 18. Erdmann M, David R, Fornof A
R, Gaub H E. Electrically induced bonding of DNA to gold. Nat Chem
2, 745-749 (2010). [0148] 19. Bano F, Sluysmans D, Wislez A, Duwez
A S. Unraveling the complexity of the interactions of DNA
nucleotides with gold by single molecule force spectroscopy.
Nanoscale 7, 19528-19533 (2015). [0149] 20. Kimura-Suda H,
Petrovykh D Y, Tarlov M J, Whitman L J. Base-Dependent Competitive
Adsorption of Single-Stranded DNA on Gold. J Am Chem Soc 125,
9014-9015 (2003). [0150] 21. Liang F, Li S, Lindsay S, Zhang P.
Synthesis, Physicochemical Properties, and Hydrogen Bonding of
4(5)-Substituted-1H-imidazole-2-carboxamide, A Potential Universal
Reader for DNA Sequencing by Recognition Tunneling. Chemistry--a
European Journal 18, 5998 6007 (2012). [0151] 22. Chang S, et al.
Chemical recognition and binding kinetics in a functionalized
tunnel junction. Nanotechnology 23, 235101 (2012). [0152] 23. Zhao
Y, et al. Single-molecule spectroscopy of amino acids and peptides
by recognition tunnelling. Nature Nanotechnology 9, 466-473 (2014).
[0153] 24. Im J, et al. Electronic Single Molecule Identification
of Carbohydrate Isomers by Recognition Tunneling. arXiv, 1601.04221
(2016). [0154] 25. Petersheimf M, Turner D H. Base-Stacking and
Base-Pairing Contributions to Helix Stability: Thermodynamics of
Double-Helix Formation with CCGG, CCGGp, CCGGAp, ACCGGp, CCGGUp,
and ACCGGUp. Biochemistry 22, 256-263 (1983). [0155] 26. Yakovchuk
P, Protozanova E, Frank-Kamenetskii M D. Base-stacking and
base-pairing contributions into thermal stability of the DNA double
helix. Nucleic Acids Res 34, 564-574 (2006). [0156] 27. Riley K E,
Hobza P H. On the Importance and Origin of Aromatic Interactions in
Chemistry and Biodisciplines. ACCOUNTS OF CHEMICAL RESEARCH 46,
927-936 (2013). [0157] 28. Kelley S O, Barton J K. Electron
Transfer Between Bases in Double Helical DNA. Science 283, 375-381
(1999). [0158] 29. Xu B, Zhang P, Li X, Tao N. Direct Conductance
Measurement of Single DNA Molecules in Aqueous Solution. Nano
letters 4, 1105-1108 (2004). [0159] 30. Guckian K M, Schweitzer B
A, Ren R X-F, Sheils C J, Tahmassebi D C, Kool E T. Factors
Contributing to Aromatic Stacking in Water: Evaluation in the
Context of DNA. J Am Chem Soc 122, 2213-2222 (2000). [0160] 31.
Swart M, van der Wij st T, Fonseca Guerra C, Bickelhaupt F M. Pi-pi
stacking tackled with density functional theory. J Mol Model 13,
1245-1257 (2007). [0161] 32. Lai J S, Qu J, Kool E T. Fluorinated
DNA bases as probes of electrostatic effects in DNA base stacking.
Angew Chem Int Ed Engl 42, 5973-5977 (2003). [0162] 33. Liang F, Li
S, Lindsay S, Zhang P. Synthesis, physicochemical properties, and
hydrogen bonding of 4(5)-substituted 1-H-imidazole-2-carboxamide, a
potential universal reader for DNA sequencing by recognition
tunneling. Chemistry (Easton) 18, 5998-6007 (2012). [0163] 34.
Chang S, et al. Palladium electrodes for molecular tunnel
junctions. Nanotechnology 23, 425202 (2012). [0164] 35. Chang S, He
J, Zhang P, Gyarfas B, Lindsay S. Gap distance and interactions in
a molecular tunnel junction. J Am Chem Soc 133, 14267-14269 (2011).
[0165] 36. Grimme S. Do special noncovalent pi-pi stacking
interactions really exist? Angew Chem Int Ed Engl 47, 3430-3434
(2008). [0166] 37. Robasky K, Lewis N E, Church G M. The role of
replicates for error mitigation in next-generation sequencing. Nat
Rev Genet 15, 56-62 (2014). [0167] 38. Strauss B S. The "A" rule
revisited: polymerases as determinants of mutational specificity.
DNA Repair 1, 125-135 (2002). [0168] 39. Patra A, Zhang Q, Lei L,
Su Y, Egli M, Guengerich F P. Structural and kinetic analysis of
nucleoside triphosphate incorporation opposite an abasic site by
human translesion DNA polymerase eta. J Biol Chem 290, 8028-8038
(2015).
[0169] While particular materials, formulations, operational
sequences, process parameters, and end products have been set forth
to describe and exemplify this invention, they are not intended to
be limiting. Rather, it should be noted by those ordinarily skilled
in the art that the written disclosures are exemplary only and that
various other alternatives, adaptations, and modifications may be
made within the scope of the present invention. Accordingly, the
present invention is not limited to the specific embodiments
illustrated herein, but is limited only by the following
claims.
* * * * *