U.S. patent application number 10/632725 was filed with the patent office on 2004-04-29 for method of measuring molecular interactions.
Invention is credited to Bulseco, Dylan A., Wolf, David E..
Application Number | 20040082080 10/632725 |
Document ID | / |
Family ID | 31499331 |
Filed Date | 2004-04-29 |
United States Patent
Application |
20040082080 |
Kind Code |
A1 |
Wolf, David E. ; et
al. |
April 29, 2004 |
Method of measuring molecular interactions
Abstract
The invention features a method of assaying for the interaction
of a probe and an unknown target, said method including a) exciting
a sample with radiation, the sample including at least one unknown
target, at least one probe, and at least one fluorescent tag, b)
measuring the fluorescence from a subvolume of the sample, and c)
analyzing the fluctuations of the fluorescence.
Inventors: |
Wolf, David E.; (Sudbury,
MA) ; Bulseco, Dylan A.; (Princeton, MA) |
Correspondence
Address: |
Allison Johnson
Allison Johnson, P.A.
6016 Logan Ave. S.
Minneapolis
MN
55419
US
|
Family ID: |
31499331 |
Appl. No.: |
10/632725 |
Filed: |
August 1, 2003 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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60461394 |
Apr 8, 2003 |
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60430273 |
Dec 2, 2002 |
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60400503 |
Aug 1, 2002 |
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Current U.S.
Class: |
436/518 ;
435/6.1; 435/6.18; 435/7.1 |
Current CPC
Class: |
G01N 2021/6417 20130101;
G01N 2021/6482 20130101; G01N 2021/6484 20130101; G01N 21/6428
20130101; G01N 21/645 20130101; G01J 3/4406 20130101; G01J 3/457
20130101; G01N 33/582 20130101 |
Class at
Publication: |
436/518 ;
435/006; 435/007.1 |
International
Class: |
C12Q 001/68; G01N
033/53; G01N 033/543 |
Claims
What is claimed is:
1. A method of assaying for the equilibrium interaction of a probe
and an unknown target, said method comprising: exciting a sample at
with radiation, said sample comprising at least a portion of the
members of a library, at least one probe, and at least one
fluorescent tag; measuring the fluorescence from a subvolume of
said sample; and analyzing the fluctuations of said
fluorescence.
2. The method of claim 1 further comprising selecting additional
portions of said library, sequentially exciting an additional
portion of said library with radiation; measuring the fluorescence
of a subvolume of the additional portion; and analyzing the
fluctuations of said fluorescence.
3. The method of claim 1, said sample comprises a plurality of
fluorescent tags, said fluorescent tags being attached to said
members.
4. The method of claim 1 further comprising separating at least one
of the members of said portion of said library from at least one
other member of said portion of said library, and repeating the
method of claim 1 on said at least one separated member.
5. The method of claim 1, wherein said members comprise said
fluorescent tag.
6. The method of claim 1, wherein said fluorescent tag is attached
to said probe.
7. The method of claim 1, further comprising generating a
library.
8. The method of claim 1, further comprising generating a library
comprising fluorescent members.
9. The method of claim 8, wherein said generating comprises in
vitro translation.
10. The method of claim 1, further comprising labeling said members
of said library with a fluorophore.
11. The method of claim 10, wherein said labeling comprises in
vitro translation labeling using a fluorescent amino acid analogue,
labeling by inserting a sequence for a fluorescent protein into a
cDNA or post translational labeling.
12. The method of claim 1, wherein said members of said library
comprise fluorescent proteins.
13. The method of claim 1, wherein said members of said library
comprise fluorescently tagged amino acids.
14. The method of claim 1, wherein said members of said library
comprise fluorescently labeled peptides.
15. The method of claim 1, wherein said sample comprises a
plurality of unique probes, each unique probe comprising a unique
fluorescent tag, each unique probe having a unique binding
site.
16. The method of claim 1, wherein when binding of a probe and a
member is present, said method further comprises identifying the
member with which the probe has formed a bond.
17. The method of claim 1, wherein said sample further comprises a
second fluorescently labeled probe, said first fluorescently
labeled probe and said second fluorescently labeled probe being
capable of binding to two different unique binding sites.
18. The method of claim 1, wherein said sample further comprises a
second probe capable of binding to a unique site on a target, said
unique site being created when said first probe binds to the
target.
19. The method of claim 1, wherein said at least one fluorescent
tag is attached to a second probe, said second probe being capable
of binding to a unique site on at least one of a target and the
first probe when said first probe is bound to the target, said
unique site being created when said first probe binds to the
target.
20. The method of claim 19, wherein said unique site is derived
from a change in at least one of the primary, secondary and
tertiary structure of at least one of the target and the first
probe.
21. The method of claim 19, wherein said unique site is created by
the addition of a moiety to the target.
22. The method of claim 19, wherein said unique site is created by
at least one of phosphorylation, glycosylation, alkylation,
acylation, acetylation, and ubiquitination.
23. The method of claim 19, wherein said unique site is created by
proteolysis.
24. The method of claim 19, wherein said unique site is selected
from the group consisting of a phosphotyrosine, phosphoserine, or a
combination thereof.
25. The method of claim 1, wherein said members comprise a binding
site created by at least one of phosphorylation, glycosylation,
proteolysis, and ubiquitination.
26. The method of claim 1, wherein at least one of said probe and
said member is attached to a bead.
27. The method of claim 1, wherein said probe is attached to said
bead and said fluorescent tag is attached to said member.
28. The method of claim 1, wherein said member is attached to said
bead and said fluorescent tag is attached to said probe.
29. The method of claim 1, wherein said analyzing comprises
determining at least one of the size of the fluorescence intensity
fluctuations and the duration of the correlation of the
fluorescence fluctuation.
30. The method of claim 1, wherein said analyzing comprises
determining a correlation function comprising at least one of the
crosscorrelation function of said sample and an autocorrelation
function of said sample.
31. The method of claim 30, wherein said analyzing further
comprises determining the decay time of the correlation
function.
32. The method of claim 30, wherein said analyzing further
comprises determining the time zero value of the correlation
function.
33. The method of claim 1, wherein said analyzing comprises at
least one of a moment analysis, Fourier transform analysis, and a
power spectrum analysis.
34. The method of claim 1, wherein when binding is present, said
method further comprising determining at least one of the diffusion
coefficient of a probe-member complex, the number of probe-member
complexes in the sample, and the stoichiometry of the probe-member
complex.
35. The method of claim 1, wherein said sample further comprises a
plurality of unique probes, wherein each unique probe comprises a
unique fluorophore.
36. The method of claim 1, wherein said sample further comprises a
plurality of different size beads, a plurality of probes and a
plurality of members of said library, at least one of said probes
and said members being attached to said beads.
37. The method of claim 35, wherein said members are attached to
said beads and said probes comprise a fluorescent tag.
38. The method of claim 35, wherein said probes are attached to
said beads and said members comprise a fluorescent tag.
39. The method of claim 1, wherein said sample further comprises a
second fluorescent tag different from said first fluorescent
tag.
40. The method of claim 38, wherein said first fluorescent tag is
attached to said probe and said second fluorescent tag is attached
to said member.
41. The method of claim 38, wherein said first fluorescent tag is
attached to said first probe and said second fluorescent tag is
attached to at least one of a second probe and a bead.
42. The method of claim 38, wherein said first fluorescent tag is
attached to said member and said second fluorescent tag is attached
to at least one of said probe and a bead.
43. The method of claim 38, wherein said sample further comprises a
plurality of different size beads and at least one of said probe
and said member is attached to said beads.
44. The method of claim 42, wherein said sample further comprises a
plurality of unique probes, each unique probe being attached to a
different size bead.
45. The method of claim 42, wherein said first fluorescent tag is
attached to said probe and said second fluorescent tag is attached
to said unknown target.
46. The method of claim 42, wherein said first fluorescent tag is
attached to said first probe and said second fluorescent tag is
attached to at least one of a second probe and said beads.
47. The method of claim 1, wherein said sample comprises a
crosslinking agent.
48. The method of claim 1, wherein at least one of said probe, said
member, and said fluorescent tag comprises a crosslinking
agent.
49. The method of claim 1, further comprising determining at least
one of a true autocorrelation function and a true crosscorrelation
function of said sample.
50. The method of claim 1 further comprising flowing said sample
through a sample chamber.
51. The method of claim 1, wherein said method is automated.
52. A method of assaying for the equilibrium interaction of a probe
and an unknown target, said method comprising: exciting a sample
with radiation, said sample comprising at least one unknown target,
at least one probe, and at least one fluorescent tag; measuring the
fluorescence from a subvolume of said sample; and analyzing the
fluctuations of said fluorescence.
53. The method of claim 52, wherein at least one of said probe and
said unknown target comprises said fluorescent tag.
54. The method of claim 52, wherein said fluorescent tag is
attached to said probe.
55. The method of claim 52, wherein said fluorescent tag is
attached to said unknown target.
56. The method of claim 52, wherein when binding is present, said
method further comprises identifying the unknown target with which
the probe has formed a bond.
57. The method of claim 52, wherein said unknown target comprises a
product resulting from pathogen infection.
58. The method of claim 52, wherein said unknown target comprises a
toxin.
59. A method of assaying for a pathogen in a sample, said method
comprising: exciting a sample with radiation, said sample
comprising at least one pathogen; at least one probe, and at least
one fluorescent tag; measuring the fluorescence from a subvolume of
said sample; and analyzing the fluctuations of said
fluorescence.
60. A method of assaying for the presence of a pathogen component
in a sample, said method comprising: exciting a sample with
radiation, said sample comprising at least one probe capable of
binding a predetermined pathogen component, and at least one
fluorescent tag; measuring the fluorescence from a subvolume of
said sample; analyzing the fluctuations of said fluorescence; and
determining the presence or absence of said pathogen component.
61. The method of claim 60, further comprising identifying said
pathogen.
62. The method of claim 60, wherein said sample comprises a
plurality of unique fluorescently tagged probes, each unique probe
comprising a unique fluorophore, each unique probe being capable of
binding to a unique pathogen component.
63. The method of claim 60, wherein said sample further comprises a
second fluorescent tag comprising a fluorophore different from the
fluorophore of said first fluorescent tag.
64. The method of claim 60, wherein said analyzing comprises at
least one of determining the crosscorrelation function of said
sample and determining the autocorrelation function of said
sample.
65. The method of claim 60, wherein said pathogen component
comprises a bacterium.
66. The method of claim 60, wherein said pathogen component
comprises a virus.
67. The method of claim 60, wherein said pathogen component is
selected from the group consisting of pathogen, pathogen fragment,
pathogen nucleic acid, pathogen protein, pathogen carbohydrate, and
combinations thereof.
68. The method of claim 60, wherein said pathogen component is
selected from the group consisting of pathogen spore, pathogen
toxin, metabolic product of pathogen, and combinations thereof.
69. The method of claim 60, wherein said pathogen component is a
pathogen and said probe is capable of binding to a pathogen.
70. A method of assaying for the presence of a toxin in a sample,
said method comprising: exciting a sample with radiation, said
sample comprising at least one probe capable of binding a
predetermined toxin, and at least one fluorescent tag; measuring
the fluorescence from a subvolume of said sample; analyzing the
fluctuations of said fluorescence; and determining the presence or
absence of said toxin.
71. The method of claim 70, wherein said toxin is ricin.
72. The method of claim 71, wherein said probe and said fluorescent
tag comprise fluorescently tagged human serum albumin
galactose.
73 The method of claim 72 wherein said probe and said fluorescent
tag comprise fluorescently tagged human serum albumin
galactose.
74. A method of identifying a probe capable of binding to a known
pathogen, said method comprising: a. exciting a sample with
radiation, said sample comprising at least one known pathogen, at
least one probe, and at least one fluorescent tag; c. measuring the
fluorescence emitted by the sample; and d. analyzing the
fluctuations of said fluorescence.
75. A kit comprising: a first probe comprising ricin, a fluorescent
tag attached to said ricin; and a second probe bound to said first
probe, said second probe being adapted to bind ricin.
76. The kit of claim 75, wherein said second probe comprises human
serum albumin galactose.
77. The kit of claim 75, further comprising a second fluorescent
tag.
78. The kit of claim 75, wherein said second fluorescent tag is
attached to said second probe.
79. A method of assaying for the presence of molecular interactions
of a probe and a target, said method comprising a. exciting a
sample with radiation, said sample comprising i. a plurality of
unique mass adding components each unique mass adding component
having a unique mass, ii. a plurality of targets, iii. a plurality
of fluorescent tags, and iv. a plurality of probes; and b.
measuring the fluorescence emitted by the sample; and c. analyzing
the fluctuations of said fluorescence.
80. The method of claim 79, wherein said fluorescent tags are
attached to said mass adding component.
81. The method of claim 79, wherein said fluorescent tags are
attached to said probes.
82. The method of claim 79, wherein said fluorescent tags are
attached to said targets.
83. The method of claim 79, wherein said probes are attached to
said mass adding component.
84. The method of claim 79, wherein said fluorescent tags are
attached to said probes and said probes are attached to said mass
adding component.
85. The method of claim 79, wherein said fluorescent tags are
attached to said mass adding component and said probes are attached
to said mass adding component.
86. The method of claim 79, wherein said plurality of fluorescent
tags comprise a plurality of unique fluorescent tags.
87. A kit comprising: a plurality of unique beads, each unique bead
having a different size; a plurality of probes adapted to bind to a
unique target, said probes being attached to said beads; and a
plurality of fluorescent tags.
88. The kit of claim 87, wherein said fluorescent tags comprise
unique fluorophores.
89. The kit of claim 87, further comprising a second probe.
90. The kit of claim 87, wherein said fluorescent tags are attached
to said second probe.
91. The kit of claim 87, wherein said fluorescent tags are attached
to at least one of said beads and said probes.
92. A method of determining a true correlation function of a
sample, the method comprising obtaining a measured correlation
function of the sample from a fluorescence correlation spectroscopy
instrument and applying a correction algorithm to the measured
correlation function.
93. The method of claim 92 wherein the spectroscopy instrument
includes an excitation source, a first detector, and a second
detector.
94. The method of claim 92 wherein the measured correlation
function is an autocorrelation function.
95. The method of claim 92 wherein the measured correlation
function is a crosscorrelation function.
96. The method of claim 92 wherein the correction algorithm adjusts
the measured correlation function based on a bleed through
coefficient.
97. The method of claim 96 wherein the correction algorithm is
further based on a first average of the fluorescence intensities
measured at the first detector and a second average of the
fluorescence intensities measured at the second detector.
98. The method of claim 92, wherein said sample comprises at least
a portion of the members of a library, a pathogen, a toxin or a
combination thereof.
99. A method of determining a true autocorrelation function of a
sample, the method comprising: obtaining a first measured
autocorrelation function of the sample from a first detector of a
fluorescence correlation spectroscopy instrument; obtaining a
second measured autocorrelation function of the sample from a
second detector of the instrument; obtaining a measured
crosscorrelation function between the first detector and the second
detector of the instrument; and determining the true
autocorrelation function of the fluorescence measured at the first
detector.
100. A method of determining a true crosscorrelation function of a
sample, the method comprising: obtaining a first measured
correlation function of the sample from a first detector of a
fluorescence correlation spectroscopy instrument; obtaining a
second measured correlation function of the sample from a second
detector of the instrument; obtaining a measured crosscorrelation
function between the first detector and the second detector of the
instrument; determining a true crosscorrelation function.
101. An article of manufacture comprising a computer readable
medium having stored therein a computer program for determining a
true correlation function of a sample, the computer program
comprising: a first code segment for obtaining a measured
correlation function of the sample; and a second code segment for
applying a correction algorithm to the measured correlation
function.
102. The article of claim 101 wherein the measured correlation
function is an autocorrelation function.
103. The article of claim 101 wherein the measured correlation
function is a crosscorrelation function.
104. The article of claim 101 wherein the correction algorithm
adjusts the measured correlation function based on a crosstalk
parameter between the first and the second detectors.
105. The article of claim 104 wherein the correction algorithm is
further based on a first average of the fluorescence intensities
measured at the first detector and a second average of the
fluorescence intensities measured at the second detector.
106. An article of manufacture comprising a computer readable
medium having stored therein a computer program for determining a
true correlation function of a sample, the computer program
comprising: a first code segment for obtaining a first measured
autocorrelation function of the sample from a first detector of a
fluorescence correlation spectroscopy instrument, a second measured
autocorrelation function of the sample from a second detector of
the instrument, and a measured crosscorrelation function between
the first detector and the second detector of the instrument; a
second code segment for determining the true autocorrelation
function of the fluorescence measured at the first detector.
107. A system for determining a true correlation function of a
sample, the system comprising a memory device for storing
information related to the sample and a processor programmed with
instruction to obtain a measured correlation function of the sample
from a fluorescence correlation spectroscopy instrument and apply a
correction algorithm to the measured correlation function.
108. A fluorescence correlation spectroscopy instrument for
determining a true correlation function of a sample, the instrument
comprising: an excitation source; a first detector and a second
detector for measuring fluorescence of the sample; a memory device
for storing information related to the sample; and a processor
programmed with instruction to obtain a measured correlation
function of the sample from a fluorescence correlation spectroscopy
instrument and apply a correction algorithm to the measured
correlation function.
109. A method of determining a true fluorescence intensity of a
sample, the method comprising obtaining a measured fluorescence
intensity of the sample from a first detector of a fluorescence
correlation spectroscopy and applying a correction algorithm to the
measured fluorescence intensity.
110. The method of claim 109 wherein the correction algorithm
adjusts the measured fluorescence intensity based on a
bleed-through coefficient between the first detector and a second
detector of a fluorescence correlation spectroscopy.
111. The method of claim 110 wherein the correction algorithm is
further based on a second measured fluorescence intensity of the
sample from the second detector.
112. A method of determining a true fluorescence intensity of a
sample, the method comprising: measuring a first fluorescence
intensity of the sample at a first detector of a fluorescence
correlation spectroscopy instrument and a second fluorescence
intensity the sample at a second detector of a fluorescence
correlation spectroscopy instrument; and determining at least one
of a true fluorescence intensity of the fluorescence measured at
the first detector and the true fluorescence intensity of the
fluorescence measured at the second detector.
113. The method of claim 112 further comprising generating a true
autocorrelation curve, based on the first true fluorescence
intensity.
114. The method of claim 112 further comprising generating a true
crosscorrelation curve, based on the first and second true
fluorescence intensities.
115. An article of manufacture comprising a computer readable
medium having stored therein a computer program for determining a
true fluorescence intensity of a sample measured by a fluorescence
correlation spectroscopy instrument.
116. A fluorescence correlation spectroscopy instrument for
determining a true fluorescence intensity of a sample, the
instrument comprising: an excitation source; a first detector and a
second detector for detecting a first measured fluorescence and a
second measured fluorescence of the sample; a memory device for
storing computer code; and a processor for executing the computer
code to obtain the true fluorescence intensity, based on the first
and the second measured fluorescence.
117. The instrument of claim 116 wherein the memory device is an
EPROM.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to U.S. Provisional
Application Serial No. 60/461,394, filed Apr. 8, 2003, U.S.
Provisional Application Serial No. 60/400,503 filed Aug. 1, 2002,
and U.S. Provisional Application Serial No. 60/430,273 filed Dec.
2, 2002.
BACKGROUND
[0002] The invention relates to assaying for the interaction of a
target and a probe using fluorescence correlation spectroscopy.
[0003] Various scientific disciplines related to the biological
sciences seek to detect the presence of molecules, understand
molecular interactions, and determine the properties and functions
of molecules. The Human Genome Project has provided a library of
all proteins expressed in the human body. Understanding the
molecular interactions of these expressed proteins and evaluating
the function of expressed proteins has the potential to lead to the
development of new drugs and new drug therapies. Likewise, the
threat posed by the potential use of pathogens against populations
as a form of biological warfare has highlighted the need to detect
pathogens.
[0004] Numerous assay techniques have been developed to assist the
study of molecular interactions including, e.g., Enzyme-Linked
Immunosorbent Assays (ELISA), Radio-Immunoassays (RIA),
fluorescence assays, dynamic light scattering, mass spectrometry,
yeast 2-hybrid, phage display, and calorimetric assays. Many of
these assay techniques require specialized preparation,
purification, separation and amplification of the sample to be
tested. Some of these assay techniques also require relatively
large amounts of sample and are time consuming to conduct.
Accordingly, there exists a need for development of methods of
measuring molecular interactions and that are relatively simple to
implement and can be conducted on a relatively small amount of
sample.
[0005] Fluorescence correlation spectroscopy (FCS) is a single
molecule detection method that measures the fluctuations in
fluorescence intensity in a small (e.g., femtoliter) confocal
volume. FCS employs a tightly focused laser beam to define the
confocal volume. The diffusion of fluorescently labeled particles
into and out of the illuminated volume determines the fluorescence
intensity fluctuation patterns. From this data, one can extract
both qualitative information and quantitative information on the
molecule being studied. Such qualitative information includes,
e.g., the presence or absence of molecular interaction; such
quantitative information includes diffusion time, stoichiometry of
the interactions, concentration of the interacting particles and
the kinetics of the interaction.
[0006] FCS has been used to study a variety of properties of single
molecules including translational diffusion and transport, chemical
kinetics, molecular aggregation, ligand binding, enzymatic
activity, and nucleic acid interactions.
SUMMARY
[0007] In a first aspect the invention features a method of
assaying for the equilibrium interaction of a probe and an unknown
target, the method including exciting a sample at with radiation,
the sample including at least a portion of the members of a
library, at least one probe, and at least one fluorescent tag,
measuring the fluorescence from a subvolume of the sample, and
analyzing the fluctuations of the fluorescence. In one embodiment
the method further includes selecting additional portions of the
library, sequentially exciting an additional portion of the library
with radiation, measuring the fluorescence of a subvolume of the
additional portion, and analyzing the fluctuations of the
fluorescence. In some embodiments, the sample includes a plurality
of fluorescent tags, the fluorescent tags being attached to the
members.
[0008] In one embodiment the method further includes separating at
least one of the members of the portion of the library from at
least one other member of the portion of the library, and repeating
the method on the at least one separated member.
[0009] In some embodiments, the members include the fluorescent
tag. In other embodiments the fluorescent tag is attached to the
probe.
[0010] In another embodiment the method further includes generating
a library. In one embodiment the method includes generating a
library that includes fluorescent members. In some embodiments the
generating includes in vitro translation. In other embodiments the
method further includes labeling the members of the library with a
fluorophore. In some embodiments the labeling includes in vitro
translation labeling using a fluorescent amino acid analogue,
labeling by inserting a sequence for a fluorescent protein into a
cDNA or post translational labeling.
[0011] In some embodiments the members of the library include
fluorescent proteins. In other embodiments the members of the
library include fluorescently tagged amino acids. In other
embodiments the members of the library include fluorescently
labeled peptides.
[0012] In one embodiment the sample includes a plurality of unique
probes, each unique probe including a unique fluorescent tag, each
unique probe having a unique binding site.
[0013] In other embodiments when binding of a probe and a member is
present, the method further includes identifying the member with
which the probe has formed a bond.
[0014] the sample further includes a second fluorescently labeled
probe, the first fluorescently labeled probe and the second
fluorescently labeled probe being capable of binding to two
different unique binding sites.
[0015] In one embodiment the sample further includes a second probe
capable of binding to a unique site on a target, the unique site
being created when the first probe binds to the target.
[0016] In other embodiments the at least one fluorescent tag is
attached to a second probe, the second probe being capable of
binding to a unique site on at least one of a target and the first
probe when the first probe is bound to the target, the unique site
being created when the first probe binds to the target. In some
embodiments the unique site is derived from a change in at least
one of the primary, secondary and tertiary structure of at least
one of the target and the first probe. In another embodiment the
unique site is created by the addition of a moiety to the target.
In other embodiments the unique site is created by at least one of
phosphorylation, glycosylation, alkylation, acylation, acetylation,
and ubiquitination. the unique site is created by proteolysis. In
other embodiments the unique site is selected from the group
consisting of a phosphotyrosine, phosphoserine, or a combination
thereof.
[0017] In one embodiment the members include a binding site created
by at least one of phosphorylation, glycosylation, proteolysis, and
ubiquitination.
[0018] In some embodiments at least one of the probe and the member
is attached to a bead. In other embodiments the probe is attached
to the bead and the fluorescent tag is attached to the member. In
another embodiment the member is attached to the bead and the
fluorescent tag is attached to the probe.
[0019] In one embodiment the analyzing includes determining at
least one of the size of the fluorescence intensity fluctuations
and the duration of the correlation of the fluorescence
fluctuation. In other embodiments the analyzing includes
determining a correlation function including at least one of the
crosscorrelation function of the sample and an autocorrelation
function of the sample. In another embodiment the analyzing further
includes determining the decay time of the correlation function. In
some embodiments the analyzing further includes determining the
time zero value of the correlation function. In other embodiments
the analyzing includes at least one of a moment analysis, Fourier
transform analysis, and a power spectrum analysis.
[0020] In one embodiment when binding is present, the method
further including determining at least one of the diffusion
coefficient of a probe-member complex, the number of probe-member
complexes in the sample, and the stoichiometry of the probe-member
complex.
[0021] In some embodiments the sample further includes a plurality
of unique probes, wherein each unique probe includes a unique
fluorophore. In other embodiments the sample further includes a
plurality of different size beads, a plurality of probes and a
plurality of members of the library, at least one of the probes and
the members being attached to the beads. In one embodiment the
members are attached to the beads and the probes include a
fluorescent tag. In other embodiment the probes are attached to the
beads and the members include a fluorescent tag.
[0022] In other embodiments the sample further includes a second
fluorescent tag different from the first fluorescent tag. In other
embodiments the first fluorescent tag is attached to the probe and
the second fluorescent tag is attached to the member. In some
embodiments the first fluorescent tag is attached to the first
probe and the second fluorescent tag is attached to at least one of
a second probe and a bead. In another embodiment the first
fluorescent tag is attached to the member and the second
fluorescent tag is attached to at least one of the probe and a
bead.
[0023] In one embodiment the sample further includes a plurality of
different size beads and at least one of the probe and the member
is attached to the beads. In other embodiments the sample further
includes a plurality of unique probes, each unique probe being
attached to a different size bead. In some embodiments the first
fluorescent tag is attached to the probe and the second fluorescent
tag is attached to the unknown target. In other embodiments first
fluorescent tag is attached to the first probe and the second
fluorescent tag is attached to at least one of a second probe and
the beads.
[0024] In another embodiment the sample includes a crosslinking
agent. In some embodiments at least one of the probe, the member,
and the fluorescent tag includes a crosslinking agent.
[0025] In another embodiments the method further includes obtaining
at least one of a true autocorrelation function and a true
crosscorrelation function of the sample.
[0026] In some embodiments further includes flowing the sample
through a sample chamber. In other embodiments the method is
automated.
[0027] In some embodiments the method further includes determining
the true autocorrelation function (G.sub.1T) of the fluorescence of
the sample measured at a first detector of a fluorescence
correlation spectroscopy instrument having a first detector, a
second detector and an excitation source, using the following
equation or its equivalent 1 G 1 T = - 2 < I 1 > < I 2
> R + 2 < I 2 > 2 G 2 + < I 1 > 2 G 1 - 2 < I 1
> < I 2 > + 2 < I 2 > 2 + < I 1 > 2
[0028] where G.sub.1T is the true autocorrelation function of the
fluorescence measured at the first detector, .rho. is the bleed
through coefficient of the second detector into the first detector,
<I.sub.1> is the time averaged intensity in the first
detector, <I.sub.2> is the time averaged intensity in the
second detector, R is a measured crosscorrelation function between
the first detector and the second detector, and G.sub.1 and G.sub.2
are measured autocorrelation functions of the first detector and
the second detector, respectively.
[0029] In other embodiments the method further includes determining
the true autocorrelation function (G.sub.2T) of the fluorescence of
the sample measured at a second detector of a fluorescence
correlation spectroscopy instrument having a first detector, a
second detector and an excitation source, using the following
equation or its equivalent 2 G 2 T = - 2 r < I 1 > < I 2
> R + < I 2 > 2 G 2 + r 2 < I 1 > 2 G 1 - 2 r < I
1 > < I 2 > + < I 2 > 2 + r 2 < I 1 > 2
[0030] where G.sub.2T is the true autocorrelation function of the
fluorescence measured at the second detector, r is the bleed
through of the first detector into the second detector and
<I.sub.1>, <I.sub.2>, R, G.sub.1 and G.sub.2 are as
described above.
[0031] In one embodiment, the method further includes determining
the true crosscorrelation function (R.sub.T) of the fluorescence of
the sample measured at a first detector of a fluorescence
correlation spectroscopy instrument having a first detector, a
second detector and an excitation source, using the following
equation or its equivalent 3 R T = < I 1 > < I 2 > R (
1 + r ) - < I 2 > 2 G 2 - r < I 1 > 2 G 1 < I 1 >
< I 2 > ( 1 + r ) - < I 2 > 2 - r < I 1 > 2
[0032] where R.sub.T is the true crosscorrelation function of the
fluorescence measured at the first and second detectors,
<I.sub.1>, <I.sub.2>, R, G.sub.1 and G.sub.2 are as
described above.
[0033] In another aspect, the invention features a method of
assaying for the equilibrium interaction of a probe and an unknown
target, the method including exciting a sample with radiation, the
sample including at least one unknown target, at least one probe,
and at least one fluorescent tag, measuring the fluorescence from a
subvolume of the sample, and analyzing the fluctuations of the
fluorescence. In some embodiments the fluorescent tag is attached
to the unknown target. In other embodiments when binding is
present, the method further includes identifying the unknown target
with which the probe has formed a bond.
[0034] In some embodiments the unknown target includes a product
resulting from pathogen infection. In other embodiments the unknown
target includes a toxin.
[0035] In another aspect, the invention features a method of
assaying for a pathogen in a sample, the method including exciting
a sample with radiation, the sample including a pathogen, at least
one probe, and at least one fluorescent tag, measuring the
fluorescence from a subvolume of the sample, and analyzing the
fluctuations of the fluorescence.
[0036] In a second aspect, the invention features a method of
assaying for the presence of a pathogen component in a sample, the
method including exciting a sample with radiation, the sample
including at least one probe capable of binding a predetermined
pathogen component, and at least one fluorescent tag, measuring the
fluorescence from a subvolume of the sample, analyzing the
fluctuations of the fluorescence, and determining the presence or
absence of the pathogen component. In some embodiments the method
further includes identifying the pathogen.
[0037] In one embodiment the pathogen component includes a
bacterium. In other embodiments the pathogen component includes a
virus. In another embodiment the pathogen component is selected
from the group consisting of pathogen, pathogen fragment, pathogen
nucleic acid, pathogen protein, pathogen carbohydrate, and
combinations thereof. In some embodiments the pathogen component is
selected from the group consisting of pathogen spore, pathogen
toxin, metabolic product of pathogen, and combinations thereof. In
other embodiments the pathogen component is a pathogen and the
probe is capable of binding to a pathogen.
[0038] In some embodiments the sample includes a plurality of
unique fluorescently tagged probes, each unique probe including a
unique fluorophore, each unique probe being capable of binding to a
unique pathogen component.
[0039] In another embodiment the analyzing includes determining at
least one of a crosscorrelation function of the sample and
determining an autocorrelation function of the sample.
[0040] In a third aspect, the invention features a method of
assaying for the presence of a toxin in a sample, the method
including exciting a sample with radiation, the sample including at
least one probe capable of binding a predetermined toxin, and at
least one fluorescent tag, measuring the fluorescence from a
subvolume of the sample, analyzing the fluctuations of the
fluorescence, and determining the presence or absence of the toxin.
In one embodiment the toxin is ricin. In some embodiments the probe
and the fluorescent tag include fluorescently tagged human serum
albumin galactose.
[0041] In a fourth aspect, the invention features a method of
identifying a probe capable of binding to a known pathogen, the
method including exciting a sample with radiation, the sample
including at least one known pathogen, at least one probe, and at
least one fluorescent tag, measuring the fluorescence emitted by
the sample, and analyzing the fluctuations of the fluorescence.
[0042] In a fifth aspect, the invention features a kit including a
first probe including ricin, a fluorescent tag attached to the
ricin, and a second probe bound to the first probe, the second
probe being adapted to bind ricin. In some embodiments the second
probe includes human serum albumin galactose. In other embodiments
the kit further includes a second fluorescent tag. In one
embodiment the second fluorescent tag is attached to the second
probe.
[0043] In a sixth aspect, the invention features a method of
assaying for the presence of molecular interactions of a probe and
a target, the method including exciting a sample with radiation,
the sample including a plurality of unique mass adding components
each unique mass adding component having a unique mass, a plurality
of targets, a plurality of fluorescent tags, and a plurality of
probes, and measuring the fluorescence emitted by the sample, and
analyzing the fluctuations of the fluorescence. In some
embodiments, the fluorescent tags are attached to the mass adding
component. In other embodiments, the fluorescent tags are attached
to the probes. In some embodiments, the fluorescent tags are
attached to the targets. In another embodiment, the probes are
attached to the mass-adding component. In one embodiment the
fluorescent tags are attached to the probes and the probes are
attached to the mass adding component. In another embodiment, the
fluorescent tags are attached to the mass adding component and the
probes are attached to the mass adding component. In some
embodiments, the plurality of fluorescent tags include a plurality
of unique fluorescent tags.
[0044] In one embodiment, the kit includes a plurality of unique
beads, each unique bead having a different size, a plurality of
probes adapted to bind to a unique target, the probes being
attached to the beads, and a plurality of fluorescent tags. In one
embodiment, the fluorescent tags include unique fluorophores. In
other embodiments the kit further includes a second probe. In some
embodiments, the fluorescent tags are attached to at least one of
the beads and the probes.
[0045] In a seventh aspect, the invention features a method of
determining a true correlation function of a sample, the method
including obtaining a measured correlation function of the sample
from a fluorescence correlation spectroscopy instrument and
applying a correction algorithm to the measured correlation
function. In one embodiment, the spectroscopy instrument includes
an excitation source, a first detector, and a second detector. In
some embodiments the measured correlation function is an
autocorrelation function. In other embodiments the measured
correlation function is a crosscorrelation function. In one
embodiment, the correction algorithm adjusts the measured
correlation function based on a bleed through coefficient.
[0046] In other embodiments the correction algorithm is further
based on a first average of the fluorescence intensities measured
at the first detector and a second average of the fluorescence
intensities measured at the second detector.
[0047] In one embodiment, the invention features a method of
determining a true autocorrelation function of a sample, the method
including obtaining a first measured autocorrelation function
(G.sub.1) of the sample from a first detector of a fluorescence
correlation spectroscopy instrument, obtaining a second measured
autocorrelation function (G.sub.2) of the sample from a second
detector of the instrument, obtaining a measured crosscorrelation
function (R) between the first detector and the second detector of
the instrument, calculating a first time averaged intensity
(I.sub.1) of the fluorescence at the first detector, calculating a
second time averaged intensity (I.sub.2) of the fluorescence at the
second detector, determining the true autocorrelation function
(G.sub.1T) of the fluorescence measured at the first detector using
the following equation or its equivalent 4 G 1 T = - 2 < I 1
> < I 2 > R + 2 < I 2 > 2 G 2 + < I 1 > 2 G 1
- 2 < I 1 > < I 2 > + 2 < I 2 > 2 + < I 1 >
2
[0048] where .rho. is a bleed-through coefficient of the second
detector into the first detector.
[0049] In another embodiment, the method of determining a true
autocorrelation function of a sample includes obtaining a first
measured autocorrelation function (G.sub.1) of the sample from a
first detector of a fluorescence correlation spectroscopy
instrument, obtaining a second measured autocorrelation function
(G.sub.2) of the sample from a second detector of the instrument,
obtaining a measured crosscorrelation function (R) between the
first detector and the second detector of the instrument,
calculating a first time averaged intensity (I.sub.1) of the
fluorescence at the first detector, calculating a second time
averaged intensity (I.sub.2) of the fluorescence at the second
detector, determining a true autocorrelation function (G.sub.2T) of
the fluorescence measured at the second detector using the
following equation or its equivalent 5 G 2 T t = - 2 r < I 1
> < I 2 > R + < I 2 > 2 G 2 + r 2 < I 1 > 2 G
1 - 2 r < I 1 > < I 2 > + < I 2 > 2 + r 2 < I
1 > 2
[0050] where r is a bleed-through coefficient of first detector
into the second detector.
[0051] In other embodiments, the method of determining a true
crosscorrelation function of a sample includes obtaining a first
measured correlation function (G.sub.1) of the sample from a first
detector of a fluorescence correlation spectroscopy instrument,
obtaining a second measured correlation function (G.sub.2) of the
sample from a second detector of the instrument, obtaining a
measured crosscorrelation function (R) between the first detector
and the second detector of the instrument, calculating a first time
averaged intensity (I.sub.1) of the fluorescence at the first
detector, calculating a second time averaged intensity (I.sub.2) of
the fluorescence at the second detector, determining a true
crosscorrelation function (R.sub.T) using the following equation or
its equivalent 6 R T = < I 1 > < I 2 > R ( 1 + r ) -
< I 2 > 2 G 2 - r < I 1 > 2 G 1 < I 1 > < I 2
> ( 1 + r ) - < I 2 > 2 - r < I 1 > 2
[0052] where .rho. is a bleed-through coefficient of the second
detector into the first detector, and r is a bleed-through
coefficient of the first detector into the second detector.
[0053] In an eighth aspect, the invention features an article of
manufacture that includes a computer readable medium having stored
therein a computer program for determining a true correlation
function of a sample, the computer program including a first code
segment for obtaining a measured correlation function of the
sample, and a second code segment for applying a correction
algorithm to the measured correlation function. In one embodiment,
the measured correlation function is an autocorrelation function.
In other embodiments, the measured correlation function is a
crosscorrelation function. In some embodiments the correction
algorithm adjusts the measured correlation function based on a
crosstalk parameter between the first and the second detectors. In
other embodiments the correction algorithm is further based on a
first average of the fluorescence intensities measured at the first
detector and a second average of the fluorescence intensities
measured at the second detector.
[0054] In a ninth aspect the invention features an article of
manufacture including a computer readable medium having stored
therein a computer program for determining a true correlation
function of a sample, the computer program including a first code
segment for obtaining a first measured autocorrelation function
(G.sub.1) of the sample from a first detector of a fluorescence
correlation spectroscopy instrument, a second measured
autocorrelation function (G.sub.2) of the sample from a second
detector of the instrument, and a measured crosscorrelation
function (R) between the first detector and the second detector of
the instrument, a second code segment for calculating a first time
averaged intensity (I.sub.1) of the fluorescence at the first
detector and a second time averaged intensity (I.sub.2) of the
fluorescence at the second detector, a third code segment for
determining the true autocorrelation function (G.sub.1T) of the
fluorescence measured at the first detector using the following
equation or its equivalent 7 G 1 T = - 2 < I 1 > < I 2
> R + 2 < I 2 > 2 G 2 + < I 1 > 2 G 1 - 2 < I 1
> < I 2 > + 2 < I 2 > 2 + < I 1 > 2
[0055] where .rho. is a bleed-through coefficient of the second
detector into the first detector. In one embodiment, the article
further includes a fourth code segment for determining a second
true autocorrelation function (G.sub.2T) of the fluorescence
measured at the second detector using the following equation or its
equivalent: 8 G 2 T = - 2 r < I 1 > < I 2 > R + < I
2 > 2 G 2 + r 2 < I 1 > 2 G 1 - 2 r < I 1 > < I 2
> + < I 2 > 2 + r 2 < I 1 > 2
[0056] where r is a bleed-through coefficient of the first detector
into the second detector. In some embodiments the article further
includes a fifth code segment for determining a true
crosscorrelation function (R.sub.T) using the following equation or
its equivalent: 9 R T = < I 1 > < I 2 > R ( 1 + r ) -
< I 2 > 2 G 2 - r < I 1 > 2 G 1 < I 1 > < I 2
> ( 1 + r ) - < I 2 > 2 - r < I 1 > 2 .
[0057] In one embodiment, the article of manufacture includes a
computer readable medium having stored therein a computer program
for determining a true correlation function of a sample, the
computer program including a first code segment for obtaining a
first measured correlation function (G.sub.1) of the sample from a
first detector of a fluorescence correlation spectroscopy
instrument, a second measured correlation function (G.sub.2) of the
sample from a second detector of the instrument, and a measured
crosscorrelation function (R) between the first detector and the
second detector of the instrument, a second code segment for
calculating a first time averaged intensity (I.sub.1) of the
fluorescence at the first detector and a second time averaged
intensity (I.sub.2) of the fluorescence at the second detector, a
third code segment for determining the true autocorrelation
function (G.sub.2T) of the fluorescence measured at the second
detector using the following equation or its equivalents 10 G 2 T =
- 2 r < I 1 > < I 2 > R + < I 2 > 2 G 2 + r 2
< I 1 > 2 G 1 - 2 r < I 1 > < I 2 > + < I 2
> 2 + r 2 < I 1 > 2
[0058] where r is a bleed-through coefficient of the first detector
into the second detector.
[0059] In another embodiment, the article of manufacture including
a computer readable medium having stored therein a computer program
for determining a true correlation function of a sample, the
computer program including a first code segment for obtaining a
first measured correlation function (G.sub.1) of the sample from a
first detector of a fluorescence correlation spectroscopy
instrument, a second measured correlation function (G.sub.2) of the
sample from a second detector of the instrument, and a measured
crosscorrelation function (R) between the first detector and the
second detector of the instrument, a second code segment for
calculating a first time averaged intensity (I.sub.1) of the
fluorescence at the first detector and a second time averaged
intensity (I.sub.2) of the fluorescence at the second detector, a
third code segment for determining the true crosscorrelation
function (R.sub.T) using the following equation or its equivalent
11 R T = < I 1 > < I 2 > R ( 1 + r ) - < I 2 > 2
G 2 - r < I 1 > 2 G 1 < I 1 > < I 2 > ( 1 + r ) -
< I 2 > 2 - r < I 1 > 2 .
[0060] where .rho. is a bleed-through coefficient of the second
detector into the first detector and r is a bleed-through
coefficient of the first detector into the second detector.
[0061] In a tenth aspect, the invention features a system for
determining a true correlation function of a sample, the system
including a memory device for storing information related to the
sample and a processor programmed with instruction to obtain a
measured correlation function of the sample from a fluorescence
correlation spectroscopy instrument and apply a correction
algorithm to the measured correlation function.
[0062] In another aspect, the invention features a fluorescence
correlation spectroscopy instrument for determining a true
correlation function of a sample, the device including an
excitation source, a first detector and a second detector for
measuring fluorescence of the sample, a memory device for storing
information related to the sample, and a processor programmed with
instruction to obtain a measured correlation function of the sample
from a fluorescence correlation spectroscopy instrument and apply a
correction algorithm to the measured correlation function.
[0063] In another embodiment, the method of determining a true
fluorescence intensity of a sample includes obtaining a measured
fluorescence intensity of the sample from a first detector of a
fluorescence correlation spectroscopy and applying a correction
algorithm to the measured fluorescence intensity. In one
embodiment, the correction algorithm adjusts the measured
fluorescence intensity based on a bleed-through coefficient between
the first detector and a second detector of a fluorescence
correlation spectroscopy. In other embodiments, the correction
algorithm is further based on a second measured fluorescence
intensity of the sample from the second detector.
[0064] In one embodiment, the method of determining a true
fluorescence intensity of a sample includes measuring a first
fluorescence intensity (I.sub.1) of the sample at a first detector
of a fluorescence correlation spectroscopy instrument and a second
fluorescence intensity (I.sub.2) of the sample at a second detector
of a fluorescence correlation spectroscopy instrument, determining
a first true fluorescence intensity (X) of the fluorescence
measured at the first detector using the following equation: 12 X =
I 1 - I 2 1 - r
[0065] where .rho. is a first bleed-through coefficient of the
second detector into the first detector and r is a second
bleed-through coefficient of the first detector into the second
detector.
[0066] In another embodiment, the method of determining a true
fluorescence intensity of a sample, the method including measuring
a first measured fluorescence intensity (I.sub.1) and a second
measured fluorescence intensity (I.sub.2) of the sample from the
first and second detectors, respectively, determining the true
fluorescence intensity fluorescence intensity (Y) of the
fluorescence measured at the second detector using the following
equation 13 Y = I 2 - rI 1 1 - r
[0067] where .rho. is a first bleed-through coefficient of the
second detector into the first detector and r is a second
bleed-through coefficient of the first detector into the second
detector.
[0068] In one embodiment, the method further includes generating a
true autocorrelation curve, based on the first true fluorescence
intensity.
[0069] In another embodiment, the method further includes
generating a true crosscorrelation curve, based on the first and
second true fluorescence intensities.
[0070] In one embodiment, the article of manufacture includes a
computer readable medium having stored therein a computer program
for determining a true fluorescence intensity of a sample, the
computer program including a first code segment for obtaining a
first bleed-through coefficient (.rho.) of a second fluorescence
spectroscopy detector into a first fluorescence spectroscopy
detector and a second bleed-through coefficient (r) of the first
detector into the second detector, a second code segment for
measuring a first measured fluorescence intensity (I.sub.1) and a
second measure fluorescence intensity (I.sub.2) of the sample from
the first and second detectors, respectively, a third code segment
for determining a first true fluorescence intensity (X) of the
fluorescence measured at the first detector using the following
equation: 14 X = I 1 - I 2 1 - r .
[0071] In other embodiments, the article of manufacture includes a
computer readable medium having stored therein a computer program
for determining a true fluorescence intensity of a sample, the
computer program including a first code segment for obtaining a
first bleed-through coefficient (.rho.) of a second fluorescence
spectroscopy detector into a first fluorescence spectroscopy
detector and a second bleed-through coefficient (r) of the first
detector into the second detector, a second code segment for
measuring a first measured fluorescence intensity (I.sub.1) and a
second measure fluorescence intensity (I.sub.2) of the sample from
the first and second detectors, respectively, and a third code
segment for determining a true fluorescence intensity (Y) of the
fluorescence measured at the second detector using the following
equation 15 Y = I 2 - rI 1 1 - r .
[0072] In another embodiment, the fluorescence correlation
spectroscopy instrument for determining a true fluorescence
intensity of a sample includes an excitation source, a first
detector and a second detector for detecting a first measured
fluorescence (I.sub.1) and a second measured fluorescence (I.sub.2)
of the sample, a memory device for storing computer code, and a
processor for executing the computer code to obtain the true
fluorescence intensity, based on the first and the second measured
fluorescence.
[0073] In one embodiment, the computer code includes instructions
for determining a true fluorescence intensity (X) of the
fluorescence measured at the first detector using the following
equation: 16 X = I 1 - I 2 1 - r
[0074] where .rho. is a bleed-through coefficient of detector two
into detector one and r is a bleed-through coefficient of detector
one into detector two.
[0075] In some embodiments, the computer code includes instructions
for determining a true fluorescence intensity (Y) of the
fluorescence measured at the second detector using the following
equation: 17 Y = I 2 - rI 1 1 - r .
[0076] where .rho. is a bleed-through coefficient of detector two
into detector one and r is a bleed-through coefficient of detector
one into detector two.
[0077] In one embodiment the memory device is an EPROM.
[0078] The invention features a method for studying macromolecular
interactions such as protein-protein, protein-DNA, protein-RNA,
DNA-DNA, RNA-DNA, and RNA-RNA interactions using fluorescence
correlation spectroscopy. The method can be used to determine the
stoichiometric nature of a molecule (e.g., the number of binding
sites on a molecule), the molecular mass of a molecule, the number
of fluorescent particles in a sample, and combinations thereof. The
method can be used to identify which members of a library bind to a
predetermined probe, as well as which probes bind to a
predetermined target.
[0079] The invention also features the ability to identify novel
binding partners to a specific target, e.g., proteins, and to
detect the presence and/or determine the identity of a target in a
sample containing unknown targets.
[0080] The invention also features a method of determining a true
autocorrelation function and a true crosscorrelation function.
[0081] The invention also features kits including reagents for
assaying known and unknown targets.
[0082] Other features and advantages will be apparent from the
following description of the preferred embodiments and from the
claims.
GLOSSARY
[0083] In reference to the invention, these terms have the meanings
set forth below:
[0084] The term "probe" means any known component with a binding
site.
[0085] The term "fluorescent tag" or "fluorescently tagged" means
the presence of a fluorophore and includes fluorophore,
fluorophore-containing moieties that are capable of binding to
other moieties, and combinations thereof.
[0086] The term "assay" means determining the presence or absence
of a target, the amount of a target, or both.
[0087] The term "library" means a number of related members that
differ from each other in some aspect of their chemical
structure.
[0088] The term "target" means a component to which a binding site
of the probe binds.
[0089] The term "unknown target" means a component to which it is
not known whether or not the probe binds.
[0090] The term "particle" means a fluorescent tag.
BRIEF DESCRIPTION OF THE DRAWINGS
[0091] FIG. 1A illustrates the fluorescence intensity fluctuations
over time of Example 1.
[0092] FIG. 1B illustrates the crosscorrelation curve of Example
1.
[0093] FIG. 2A illustrates the fluorescence intensity fluctuations
of Example 2.
[0094] FIG. 2B illustrates the crosscorrelation curve corresponding
to the data of FIG. 2A.
[0095] FIG. 3A illustrates the fluorescence intensity fluctuations
of Example 3.
[0096] FIG. 3B illustrates the crosscorrelation curve that results
from the data in FIG. 3A.
[0097] FIG. 4A illustrates fluorescence intensity fluctuations of
Example 4.
[0098] FIG. 4B illustrates the autocorrelation curve for the data
collected in FIG. 4A.
[0099] FIG. 5A illustrates the autocorrelation curve of Example
5.
[0100] FIG. 5B illustrates the use of the parameter estimates for
determining the fraction of slow diffusing particles (F.sub.2Np) at
each IgG concentration.
[0101] FIG. 5C illustrates the use of parameter estimates from the
analysis of the autocorrelation curve of FIG. 5A to determine
stoichiometry.
[0102] FIG. 6A illustrates the autocorrelation curves from
untreated (solid line) and NGF-treated (dotted line) A875 cells of
Example 6.
[0103] FIG. 6B illustrates theoretical curves for monomers, dimers,
trimers and tetramers as a function of fractional occupancy.
[0104] FIG. 7 illustrates the autocorrelation curves of Example
7.
[0105] FIG. 8 illustrates the autocorrelation curves of Example
8.
[0106] FIG. 9 illustrates the crosscorrelation data collected for
Example 9
[0107] FIG. 9A illustrates the crosscorrelation data collected for
Example 9 before applying the cross-talk correction algorithm.
[0108] FIG. 9B illustrates the crosscorrelation data collected for
Example 9 after applying the correction algorithm.
[0109] FIG. 10A illustrates autocorrelation data for Example 10
before applying the cross-talk correction algorithm
[0110] FIG. 10B illustrates autocorrelation data for Example 10
after applying the cross-talk correction algorithm.
[0111] FIG. 11 illustrates moment analysis on intensity fluctuation
data for Example 11.
[0112] FIG. 12A illustrates the power spectrum of a Fourier
transform of intensity fluctuation data for Example 12.
[0113] FIG. 12B illustrates the amplitude spectrum of a Fourier
transform of intensity fluctuation data for Example 12.
DETAILED DESCRIPTION
[0114] The present invention provides a method of screening members
of a library (e.g., proteins produced from a cDNA library) using
fluorescence correlation spectroscopy. The method includes
screening a sample that includes a sub-volume of the library, at
least one probe and at least one fluorescent tag to determine
whether a probe binds to a member of the library under equilibrium
conditions. Depending on the results of the screening, the method
optionally includes conducting separation and screening processes
on the subvolume of the library or additional subvolumes of the
library until the identity of a member that binds with the probe
can be established. Any suitable method for separating and
screening a library to identify the individual members of the
library can be used.
[0115] The method determines the presence or absence of binding
between a member (or members) of the library and a probe (or
probes) by analyzing the fluctuations in fluorescence emitted by a
subvolume of the sample. Analysis of the measured fluctuations can
provide information about various properties of the sample
including, e.g., the presence or absence of binding between the
probe and a member, the number of binding sites available on a
member, diffusion coefficients, diffusion time, number of
fluorescently tagged complexes present in the subvolume of the
sample, the number of members to which a probe binds in a sample,
counts per member, average intensity, aggregation state chemical
concentration, chemical reaction kinetics, stoichiometry and
combinations thereof. These properties can be determined for
members in solution, as well as in the plasma membrane of a living
cell.
[0116] The method can also be used to assay for molecular
interactions between an unknown target and a probe in a sample that
includes at least one probe, at least one unknown target and at
least one fluorescent tag, and to determine the presence or absence
of binding between a probe and an unknown target by analyzing the
fluctuations in fluorescence emitted by a subvolume of the
sample.
[0117] The method also is suitable for a variety of applications
including, e.g., analyzing samples thought to contain a pathogen or
toxin, screening sterilized samples for infection, continuous
monitoring of a sample stream for potential targets, and
combinations thereof.
[0118] Analysis of the measured fluctuations of a sample can
provide the same information about a system that includes an
unknown target, pathogen, or toxins as set forth above with respect
to members of a library.
I. Fluorescence Correlation Spectroscopy (FCS)
[0119] The fluorescence of a sample can be measured using an FCS
instrument, which generally includes at least one light source,
light focusing device adapted to focus light emitted by the light
source on a sample, at least one detector capable of detecting
light, and a correlator coupled to the detector, the correlator
being capable of processing data received at said detector and
providing data including autocorrelation data, crosscorrelation
data, or a combination thereof. In the case of crosscorrelation, at
least two detectors configured to measure around two distinct
wavelength maxima are required. Suitable FCS instruments are
described, e.g., in U.S. patent application Ser. No. 60/461,394
entitled, "Fluorescence Correlation Spectroscopy Instrument and
Method of Using the Same," and incorporated herein. Other suitable
FCS instruments are described, e.g., in Bulseco, D. A. and Wolf, D.
E. (2003). "Fluorescence Correlation Spectroscopy." Video
Microscopy, Second Edition. Sluder, G. and Wolf, D. Eds. Academic
Press, New York.;_Magde, D., E. L. Elson, and W. W. Webb,
Fluorescence correlation spectroscopy. II. An experimental
realization. Biopolymers, 1974. 13(1): p. 29-61.; Rigler, R.,
Fluorescence correlations, single molecule detection and large
number screening. Applications in biotechnology. J Biotechnol,
1995. 41(2-3): p. 177-86 and incorporated herein.
[0120] The fluorescence measured by the system can be analyzed
using various techniques including, e.g., fluorescence correlation
spectroscopy in an autocorrelation mode, fluorescence correlation
spectroscopy in a crosscorrelation mode, Moments analysis, Fourier
transform analysis, which includes power spectrum analysis and
amplitude analysis, and combinations thereof.
[0121] Fluorescence correlation spectroscopy (FCS) is a technique
that is used to extract relevant information from the intensity
fluctuations of fluorescent tags that diffuse through or are driven
through the confocal volume of an FCS instrument. FCS measures the
decay of temporal correlation in fluorescence intensity in the
confocal volume. FCS can be run in an autocorrelation mode, a
crosscorrelation mode or both modes, sequentially or
simultaneously.
[0122] Correlation techniques characterize an event by at least two
parameters. In the case of fluorescent tags, which are herein
sometimes referred to as "particles," correlation data provides the
number of independent particles present in the sample and, in the
case of diffusion, whether or not the particles are exhibiting a
diffusion coefficient (i.e., diffusion time) that is characteristic
of the particle or the complex formed by a particle, probe, target
and combinations thereof. The relaxation time for correlation
relates to stochastic processes of randomization such as the
diffusion or the rate of driven flow of targets through the
confocal volume, while the size of these fluctuations relates to
the number of particles involved in the stochastic process. The
binding of two fluorescently tagged probes on the same target
results in an increase in the amplitude (R) of the correlation when
FCS is conducted in crosscorrelation mode.
[0123] Autocorrelation measures the persistence of a single
fluorescent particle in the confocal volume. More specifically,
autocorrelation measures the correlation between the intensity of
the fluorescence at time r=O with all subsequent times. Specific
binding of a single probe to a target may result in a change in the
diffusion time (.tau..sub.D) of the target and probe complex. These
changes can be detected using a fluorescence correlation
spectroscopy instrument functioning in the autocorrelation mode.
Autocorrelation functions also can be used to analyze the
fluctuations in fluorescence intensity to yield information on
other properties of the particles and targets in the sample
including, e.g., aggregation state chemical concentration, chemical
reaction kinetics, stoichiometry and combinations thereof. This
information can be obtained on targets in solution, as well as in
the plasma membrane of living cells.
[0124] Autocorrelation measures a change in intensity, .delta.I(t),
about the average intensity, and a change in intensity,
.delta.I(t+.tau.), around the mean of the intensity of the sample
at some time .tau. later. Statistical analysis of fluorescence
intensity fluctuations results in an autocorrelation curve, which
shows the decay of temporal correlation in fluorescence intensity
over time. The autocorrelation function G(.tau.) is given by 18 G (
) = 1 + < I ( t ) * I ( t + ) < I > 2 , ( 1 )
[0125] where .delta.I refers to the deviation of the intensity
about the mean, t is the true time, .tau. is the incremental time,
I is the intensity of the fluctuation, and where < > refers
to averaging over all times t.
[0126] The value of the autocorrelation function at time .tau.=0 is
the reciprocal of the average number of particles in the sample,
and can be used as a measure of complexing or aggregation of the
particles.
[0127] Crosscorrelation temporally correlates the intensity
fluctuations of two different (i.e., unique) fluorophores with
distinct excitation and emission properties. Coincidence of these
fluorophores on the same macromolecule is detected as a change in
amplitude of the crosscorrelation function, R, at short time
points, .tau., which is directly proportional to the concentration
of dual-tagged fluorescent particles. The crosscorrelation function
is given by: 19 r ( ) = < I i ( t ) * I j ( t + ) > SD i * SD
j ( 2 )
[0128] The correlation function of Equation 2 is the form commonly
used in statistics. The correlation function goes to 1 for perfect
crosscorrelation and to 0 for no crosscorrelation. Instrumentally,
it is simpler to define the crosscorrelation function in a manner
analogous to Equation 1 for the autocorrelation function R(.tau.).
20 R ( ) = 1 + < I i ( t ) * I j ( t + ) > < I > i *
< I j > ( 3 )
[0129] where I.sub.i refers to the intensity in channel one, and
I.sub.j refers to the intensity in channel two. All other aspects
of the notation are the same as those used to describe Equation 1.
This form is simpler to calculate in real-time from an ongoing data
stream and has the further advantage that when I.sub.i=I.sub.j,
then R(.tau.)=G(.tau.).
[0130] Equations 1-3 represent the statistical analysis of the
fluctuations. Determination of specific molecular properties from
these equations requires a knowledge of the physical causes of the
fluctuation. If the dependence of the correlation function on these
molecular properties is physically modeled, then nonlinear
regression can be used to fit the data to the model. For instance,
in the case of multiple component three dimensional (3D) solution
diffusion coupled with intersystem crossing between fluorescence
molecular singlet and triplet states, the autocorrelation function
is given by Equation 4. 21 G ( ) = 1 + ( 1 N ) ( 1 - T + T exp ( -
/ T ) ) ( i F i ( 1 + / D i ) ( 1 + / K 2 D i ) 1 / 2 ) ( 4 )
[0131] where N is the number of particles, T is the triplet state
fraction, .tau..sub.T is the triplet state correlation time,
F.sub.i particle fraction, and .tau..sub.Di diffusion time for
diffusing particle species i. The structure parameter, K.sup.2
where K=.omega..sub.2/.omega.- .sub.1 (.omega..sub.2 and
.omega..sub.1 being the exp(-2) beam radii in the z and x
directions respectively) is determined separately and held constant
for each fit.
II. Correlation
[0132] Various permutations of a target-probe-fluorescent tag
system can be used to study the binding properties of a target
using fluorescence correlation spectroscopy. For ease of
discussion, the following examples of the various embodiments of
the system and methods that employ the systems will be described
with reference to an unknown target. It is to be understood,
however, that the discussion is also applicable to members of a
library, known targets, pathogens, toxins and combinations
thereof.
A. Autocorrelation
[0133] Various permutations of a target-probe-fluorescent tag
system can be used to study the binding properties of a target
using fluorescence correlation spectroscopy in an autocorrelation
mode. The system includes at least one unknown target, at least one
probe and at least one fluorescent tag. At least one of the unknown
target, the probe, or the complex formed when an unknown target is
bound to a probe (i.e., the probe-target complex) includes a
fluorescent tag. The components of the system are selected such
that the diffusion coefficient of the fluorescently tagged
component changes when a molecular interaction, such as
probe-target binding, occurs (which is reflected in an increase in
the decay time of the correlation function), the particle number
(N) changes due to crosslinking, or a combination thereof. Various
system configurations are suitable.
[0134] In one embodiment, the unknown target(s) of the system
includes a fluorescent tag. A probe is added to the system, and, if
binding between the probe and a fluorescently tagged unknown target
occurs, the diffusion coefficient of the fluorescently tagged
unknown target changes. If the probe has multiple binding sites to
which the unknown target can bind, the particle number will also
change.
[0135] In another embodiment, the probe of the system includes a
fluorescent tag and, when the fluorescently tagged probe is added
to a sample that includes an unknown target, if binding of the
probe and an unknown target occurs, the diffusion coefficient of
the fluorescently tagged probe changes. If the unknown target has
multiple binding sites to which the probe can bind, the particle
number will also change.
[0136] In another embodiment, a first probe is selected such that
binding of the first probe to an unknown target creates a site to
which a second probe that includes a fluorescent tag can bind. When
the first probe is added to a sample that includes the unknown
target, and if binding between the first probe and the unknown
target occurs, the second fluorescently tagged probe will bind to
the newly created binding site, and the diffusion coefficient of
the second fluorescently tagged probe will change. If the unknown
target has multiple binding sites to which the second probe can
bind, the particle number will also change. If the first probe does
not bind to an unknown target, the second probe will not be capable
of binding to the unknown target and the diffusion coefficient of
the second probe will not change.
[0137] The newly created site can be derived from a change in at
least one of the primary, secondary and tertiary structure of the
unknown target. The new site can also be created by various
mechanisms including, e.g., the addition of a moiety to the target,
phosphorylation, glycosylation, alkylation, acylation, acetylation,
and ubiquitination, and the cleavage of a moiety, e.g.,
proteolysis. For example, a fluorescently labeled probe can be
selected to recognize a specific site on a target created when an
enzymatic reaction occurs. The enzymatic reaction causes specific
events to occur that create a novel binding site to which the
specific probe can bind. Enzymatic reactions can be induced
naturally (e.g., in the cell) or after addition of an inducing
agent (e.g., in an assay system). Examples of suitable sites that
can be created as a result of probe binding include
phosphotyrosine, phosphoserine, and combinations thereof, as well
as all of the added moieties as described above to specific
glycolipid or glycoprotein sites.
[0138] If a probe, a fluorescent tag, or an unknown target is bound
to a mass-adding component such as a bead, and the components of
the system are selected such that a binding event corresponds with
the fluorescent tag of the system being associated with the bead,
the increased mass of the complex imparted by the bead will cause a
change in the diffusion coefficient of the fluorescent tag that is
more pronounced relative to the change in the diffusion coefficient
in the absence of the bead. If the binding event causes multiple
fluorescent tags to bind to a single component, e.g., an unknown
target, a bead or a probe, the particle number will also change.
For ease of discussion, the mass-adding component will be referred
to herein as a bead, however, it is to be understood that any
mass-adding component that does not interfere with the desired
molecular interactions of the components of the system can be used.
Other suitable mass-adding components include, e.g., crosslinking
agents, biotin/avidin complexes, biotin/strepavidin complexes,
whole antibody molecules, complexes of whole antibodies, polymeric
amino acids, nucleic acids, carbohydrates, specific resins composed
of mass adding components, and combinations thereof.
[0139] Examples of useful bead components include quantum dots,
inactivated bacteria, microspheres of polymers (e.g. polystyrene),
alginate, acrylamide, agarose, and sepharose. Suitable beads are
commercially available from Molecular Probes (Eugene, Oreg.),
Quantum Dot (Hayward, Calif.) and Bangs Laboratories (Fishers,
Ind.). Particularly useful beads are available, e.g., under the
trade designation PROACTIVE from Bangs Laboratories and under the
trade designations QUANTUM-PLEX protein coated microspheres (e.g.
coated with streptavidin, protein A, or antibodies) and QDOT
Strepavidin and QDOT 655 Protein A Conjugate all of which are
available from Quantum Dot.
[0140] In one embodiment, the system includes a probe attached to a
bead, a number of unknown targets that include a common epitope,
and a fluorescent tag. The fluorescent tag is capable of binding to
the common epitope. If a probe binds to an unknown target, the
diffusion coefficient of the fluorescent tag bound to the epitope
will change. If the probe has multiple binding sites to which the
unknown target can bind, the particle number will change. If the
bead has multiple probes capable of binding the unknown target
attached to it, then the particle number will change. The
fluorescent tag can be added prior to or subsequent to the binding
of an unknown target to a probe.
[0141] In other embodiments, the method includes a competitive
assay in which the sample includes two probes, one of which is
fluorescently tagged and the other of which is not fluorescently
tagged. The two probes are bound to each other. The unknown target
in the sample is not fluorescently tagged. The presence or absence
of the unknown target is determined by detecting competition,
between the unknown target and the fluorescently tagged probe, for
binding sites on the non-tagged probe. The fluorescently tagged
probe can be a fluorescently tagged target or a fluorescently
tagged probe that is known to competitively bind to the same
binding site as the target. Alternatively, the presence or absence
of the unknown target is determined by detecting competition
between the unknown target and the non-tagged probe for binding
sites on the fluorescently tagged probe.
B. Crosscorrelation
[0142] Various system configurations can be used to study the
binding properties of an unknown target using fluorescence
correlation spectroscopy in crosscorrelation mode. The system is
selected to enable the study of the coincidence of two fluorophores
that emit radiation having maxima at two different wavelengths on
the same complex using FCS. The two fluorophores of the system can
be located on the various components of the system including an
unknown target, one or more probes, a bead, and combinations
thereof.
[0143] In one embodiment, the sample includes a number of unknown
targets each of which includes a first fluorescent tag, and at
least one probe that includes a second fluorescent tag. If a probe
binds to an unknown target, then two fluorescent tags are present
on the same complex, which causes the fluctuations detected at the
two different detectors to be correlated.
[0144] In another embodiment, two fluorescently tagged probes
capable of binding with two unique sites are added to a sample that
includes unknown target. Each probe includes a different
fluorescent tag and the coincidence of both fluorescent tags on an
unknown target causes the fluctuations detected at the two
different detectors to be correlated.
[0145] In another embodiment, the sample includes a number of
unknown targets, each of which includes a common epitope and a
unique binding site. A first fluorescent tag capable of binding to
the epitope is added to the sample such that all of the unknown
targets with the common epitope become labeled with the first
fluorescent tag. The addition of a second fluorescently tagged
probe and the binding of the second probe with an unique binding
site on the unknown target results in the coincidence of two
fluorescent tags on the same complex, which causes the fluctuations
detected at the two different detectors to be correlated.
[0146] In another embodiment, the unknown target or a first probe
includes a first fluorescent tag and the binding of the first probe
to the unknown target results in the creation of a new binding site
to which a second probe is capable of binding. Addition of a second
fluorescent tag in the form of a fluorescently tagged second probe
and binding of the second probe to the newly created binding site
results in the coincidence of two fluorescent tags on the same
complex, which causes the fluctuations detected at the two
different detectors to be correlated. Examples of useful methods by
which a binding site is created have been described above.
[0147] In other embodiments, the probe, unknown target, fluorescent
tag or a combination thereof is attached to a bead. In one
embodiment, the probe is attached to a bead and at least one of the
probe and the bead includes a first fluorescent tag. When the
probe-bead complex is added to a sample and a fluorescently tagged
unknown target binds to the probe, there is a coincidence of two
fluorescent tags on the same complex, which causes the fluctuations
detected at the two different detectors to be correlated.
[0148] In another embodiment, the unknown target is attached to a
bead and at least one of the unknown target and the bead include a
fluorescent tag. A fluorescently tagged probe is added to the
sample and, if binding occurs between the probe and the unknown
target, there is a coincidence of two fluorescent tags on the same
complex, which causes the fluctuations detected at the two
different detectors to be correlated.
[0149] In another embodiment, the probe is attached to a bead and
at least one of the probe and the bead includes a first fluorescent
tag. When an unknown target binds to the probe, the binding creates
a site for a second probe to bind. Addition of a fluorescently
tagged second probe and binding of the second probe to the newly
created site on the unknown target causes a coincidence of two
fluorescent tags on the same complex, which causes the fluctuations
detected at the two different detectors to be correlated.
[0150] In another embodiment, the unknown target is attached to a
bead and at least one of the unknown target and the bead includes a
first fluorescent tag. When a probe binds to the unknown target,
the binding creates a site for a second probe to bind. Addition of
a fluorescently tagged second probe and binding of the second probe
to the newly created site on the unknown target causes a
coincidence of two fluorescent tags on the same complex, which
causes the fluctuations detected at the two different detectors to
be correlated.
[0151] The enzymatic reactions that add or remove moieties
described above with respect to autocorrelation can also be used in
crosscorrelation mode to create binding sites recognized by
specific probes.
C. Multiplexing
[0152] The complexity of the system and the detail of the
information obtained from the system can be increased by including
multiple bead sizes, multiple unique fluorophores, multiple unique
probes, and combinations thereof. Systems that include multiple
bead sizes, multiple unique fluorophores, multiple unique probes
and combinations thereof can be analyzed according to
autocorrelation, crosscorrelation and combinations thereof. The
embodiments described above with respect to autocorrelation and
crosscorrelation can all be modified to include multiple bead
sizes, multiple unique fluorophores, multiple unique probes, and
combinations thereof, which enables the simultaneous study of
multiple molecular interactions.
[0153] In one embodiment, multiple unique probes are added to a
sample of unknown targets to simultaneously determine the presence
or absence of binding of one or more of the probes to the unknown
targets. Each unique probe includes a unique fluorophore. Changes
in the diffusion coefficients or particle numbers of one or more of
the fluorescently tagged probes simultaneously provide information
about the nature of the unknown targets in the sample. If no
changes occur for any of the unique probes, for example, it can be
determined that none of the unknown targets include any of the
binding sites associated with the unique probes. Likewise if
probe-unknown target binding occurs, the diffusion coefficient of
the unique fluorophore(s) associated with the complex will change,
which will provide the identity of the probe that has become bound
to an unknown target, which in turn provides information about the
nature of the unknown target. This information can be gained from
each unique fluorescent tagged probe that exhibits a change in
diffusion constant. In this embodiment, the FCS instrument used to
measure the fluorescence includes a sufficient number of detectors
to detect the unique emission wavelength emitted by each unique
fluorophore. In other embodiments, the system that includes a
number of unique fluorescent tags can be configured for
crosscorrelation analysis. Such systems configurations additionally
include, e.g., unknown targets having the same fluorescent tag and
beads having the same fluorescent tag.
[0154] If the unknown target is attached to a bead, the change in
the diffusion coefficient of the fluorescently tagged probe that
binds the unknown target can be more pronounced.
[0155] In another embodiment, multiple unique probes having
different binding properties, are attached to beads. When the
bead-probe complexes are added to a sample that includes a number
of unknown targets, each of which includes a unique fluorescent
tag, binding between a probe and an unknown target will be
evidenced by a change in the diffusion coefficient for the
fluorescently tagged target and can be detected at the detector
associated with the emission wavelength of the fluorophore of the
target. In other embodiments, the system can be configured for
crosscorrelation analysis by including the same fluorescent tag on
the probes or beads of the system.
[0156] In other embodiments, the sample includes a number of unique
probes that include unique fluorescent tags and are capable of
creating a new unique binding site when bound to a target.
Introduction of a second probe that is capable of binding to the
newly created site will cause a change in the diffusion coefficient
of the unique fluorescent probes. The system optionally can be
configured for crosscorrelation analysis by including the same
fluorescent tag on at least one of the second probe and the unknown
target.
[0157] In other embodiments, a number of different sized beads are
added to the system. Each size bead has a known characteristic
diffusion coefficient. Unique probes having unique binding
characteristics are attached to each bead size such that each bead
size has a unique binding characteristic associated with it. When
the beads are added to a sample of fluorescently tagged unknown
targets, a binding event is detected in an autocorrelation mode as
a change in the diffusion coefficient of the fluorescently tagged
unknown target. The new diffusion coefficient of the fluorescently
tagged unknown target corresponds to the diffusion coefficient of a
particular bead size, which in turn allows the determination of
binding properties of the unknown target bound to the bead. In this
embodiment, the fluorophores of the fluorescent tags can be the
same. In another embodiment, at least one of the bead or the unique
probes includes a unique fluorescent tag. When more than one unique
fluorescent tag is present in the sample, the spectroscopy
instrument includes a sufficient number of detectors (i.e.,
detection channels) to detect the unique fluorescent tags in
autocorrelation mode.
[0158] In another embodiment, the system includes different sized
beads, which include unique fluorescent tags corresponding to the
size of the bead, and unique probes attached to the beads. The
system optionally can be configured for crosscorrelation analysis
where the unknown targets include the same fluorescent tag. When
more than one unique fluorescent tag is present in the sample, the
spectroscopy instrument includes a sufficient number of detectors
to detect the unique fluorescent tags in autocorrelation and
crosscorrelation modes.
III. The Probe
[0159] The probe includes at least one binding site. Where multiple
binding sites are present on a probe, the multiple binding sites
can include, e.g., multiple binding sites for the same site of
interest, multiple unique binding sites capable of binding unique
sites of interest, and combinations thereof. The binding site of
the probe and the properties of the probe can determine the
specificity of the probe and the nature of the information that can
be obtained when a binding event occurs with the probe.
[0160] Useful probes include, e.g., probes to which binding is
desired, probes capable of binding to a site of interest, and
combinations thereof.
[0161] Any suitable probe can be used. Suitable probes include,
e.g., macromolecules (e.g., proteins, peptides, polynucleic acids,
and polysaccharides), molecules (e.g., amino acids, nucleic acids,
and saccharides), and combinations thereof. Useful macromolecules
include, e.g., antibodies, receptor proteins, lectins, hormones,
protein A, protein G, avidin, enzymes, and combinations
thereof.
[0162] Suitable probes are commercially available from a variety of
sources including, e.g., Sigma Biochemicals (St. Louis, Mo.),
Molecular Probes (Eugene, Oreg.), and Vector Laboratories
(Burlingame, Calif.).
[0163] The probe can optionally include a fluorescent tag. Useful
fluorescent tags and methods of making the same are described below
and incorporated herein.
[0164] The probe can optionally include a bead or other component
that increases the mass of the probe. Useful methods of making the
same are described below and incorporated herein. Beads suitable
for macromolecular and molecular attachment are commercially
available from Sigma Biochemicals (St. Louis, Mo.), Molecular
Probes (Eugene, Oreg.), and Bangs Laboratories (Fishers, Ind.).
Examples of useful mass adding components are described above and
incorporated herein.
[0165] One useful method of determining the specificity of a probe,
and whether the probe exhibits a suitable specificity for a binding
site of interest, involves using FCS including, e.g.,
autocorrelation and crosscorrelation. The prepared probe is added
to a sample that includes a target of interest, i.e., a target that
includes a known binding site. The sample also includes a
fluorescent tag and the components of the system are selected such
that binding between the probe and the target corresponds to a
detectable change in the diffusion coefficient of the fluorescent
tag, change in particle number or a combination thereof. Measuring
and analyzing the behavior of the known probe and its known target
can verify specificity and selectivity of probes, i.e., if the
probe binds to its target.
A. Probes for Pathogen Detection
[0166] Various probes can be prepared for use in detecting
pathogens. Antigens of the pathogens, for example, can be detected
using specific antibody probes and nucleic acid sequences of the
pathogen can be detected using specific oligonucleotide probes. The
probes preferably are selected to target glycoproteins, proteins,
nucleic acids, or combinations thereof, which may include specific
portions of the pathogen, a spore of the pathogen, toxins,
metabolic products of the pathogen, biological responses induced by
the pathogen. The specific probe-sets can be prepared based on
genomic data, the characterization of the expressed proteome, and
clinical data on outcomes of infection.
[0167] Oligonucleotide probes can be designed based on information
obtained using Polymerase Chain Reaction, PCR, and the analysis of
genomic data for variable and conserved regions of DNA in related
pathogen species. Antibody probes can be designed for unique
antigens expressed by specific pathogens as determined by genomic
and proteomic database analysis. Pathogenic virulence can often be
traced to unique expression of one or more proteins or
glycoproteins. Such unique expression of one or more proteins or
glycoproteins can serve as a specific probe target.
[0168] Once selective probes have been identified and binding
conditions optimized, combinations of probes can be selected to
produce putative probe-sets. Suitable probe-sets include, e.g., two
DNA specific probes, two antigen specific probes, and one DNA
specific probe and one antigen specific probe.
[0169] For pathogen applications, a probe-set can be created to
include at least two probes for each pathogen. The probes can be
designed to detect the pathogen, toxins secreted by the pathogen
and combinations thereof. For Bacillus anthracis, for example,
suitable probes include probes capable of binding the protective
antigen (PA) of anthrax, anthrax lethal factor (LF), pXO1 plasmid,
pXO2 plasmid, and combinations thereof. Probes to PA or LF can
detect products of Bacillus anthracis, and pXO1 and pXO2 probes can
detect the presence of viable bacteria in the sample. Commercially
available probes can be used as components of these probe-sets
including, e.g. antibodies against B. anthracis, PA and LF.
[0170] Variola major virus simulant, vaccinia can be used to
identify and test probe-sets for the detection and identification
of viral pathogens. Probes can be designed to specifically bind
target DNA sequences and target viral coat proteins. Polymerase
Chain Reaction has been used to distinguish between variola and
vaccinia virus, which indicates that specific oligonucleotide
probes can be used to specifically bind unique viral DNA targets.
The preferred vaccinia primer, 5'-ATG ACA CGA TTA CCA ATA-3' will
be used as a probe to determine if vaccinia virus can be detected
using FCS. A second primer (5'-CTA GAC TTT GTT CTC TG-3') which
also binds to vaccinia DNA sequences will be used as a second DNA
probe for FCS crosscorrelation analysis. Further genome analysis
will be conducted to determine if other DNA sequences can serve as
specific targets. Commercial antibodies are available for vaccinia
virus, and will be tested for suitability as a FCS probe for viral
coat proteins.
IV. The Target
[0171] The target can include any target of interest. The target
can be unknown or known. Unknown targets include those targets to
which it is not known whether or not the probe binds. Known targets
include those targets to which a binding site of a probe of
interest binds. Examples of suitable targets include macromolecules
(e.g., proteins, peptides, polynucleic acids, and polysaccharides),
molecules (e.g., amino acids, nucleic acids, and saccharides), and
combinations thereof. Useful macromolecules include, e.g.,
antibodies, receptor proteins, lectins, hormones, protein A,
protein G, avidin, enzymes, and combinations thereof.
[0172] The target can be a library, a portion of a library, a
member of a library or a combination thereof Suitable libraries
include, e.g., apatamer libraries, phage display libraries,
antibody libraries, peptide libraries, and translated cDNA
libraries. Examples of members of a library include proteins,
peptides, polynucleic acids, organic polymers, polysaccharides,
amino acids, nucleic acids, and saccharides.
[0173] The target can optionally include a fluorescent tag. Useful
fluorescent tags and methods of attaching fluorescent tags to
components such as targets are described below and incorporated
herein. The members of an expressed cDNA library can be labeled
with a fluorescent tag during translation or post-translation.
Suitable post-translational labeling methods include, e.g.,
modifying lysine amino groups or cysteine thiol groups with a
reactive fluorescent moiety. Examples of amine reactive groups
include, e.g., isothiocyanate, n-succidimidyl ester, and sulfonyl
chloride. Examples of thiol reactive groups include acetamides and
maleamides. Other post translational labeling methods are
described, e.g., in G. T. Hermanson, Bioconjugate Techniques, 1996
(Academic Press, Inc., San Diego, Calif., pp. 785) and incorporated
herein. Post translational labeling can target either endogenous
sites on the protein or exogenous sites added for the specific
purpose of targeting the fluorescent label.
[0174] In another method, the members of an expressed cDNA library
can be labeled during an in vitro translation (IVT) method, i.e.,
incorporating a fluorescent label during the translation from cDNA
to proteins. In one such method a fluorescent amino acid (e.g.,
fluorescently modified lysine) is incorporated into the proteins
produced during translation. A useful example of a fluorophore for
labeling lysine is bodipy. A useful bodipy labeled lysine is
commercially available from ProMega (Madison, Wis.).
[0175] In another method, the members of an expressed cDNA library
can be labeled at the in vitro translation step by incorporating
the cDNA sequence for a fluorescent protein into the DNA clone.
When the fluorescent cDNA sequence is subsequently translated, the
expressed components will be fluorescently tagged.
[0176] In other methods, the members of the library can be modified
to include a common epitope. The epitope is selected such that a
probe is capable of binding to the epitope. Various methods of
modifying a library such that the members include a common epitope
tag are well known
[0177] Other suitable targets include organisms including e.g.,
pathogens (e.g., bacterial, viral, rickettsia), pathogen
components, toxins, and macromolecules associated with an organism.
Examples of pathogen components include pathogens, pathogen
fragments, pathogen nucleic acids, pathogen proteins, pathogen
carbohydrates, pathogen spores, pathogen toxins, metabolic products
of pathogens, and combinations thereof.
[0178] Useful target organisms include, e.g., Bacillus cereus,
Bacillus subtilis, various strains of non-pathogenic E. coli, and
vaccinia virus.
[0179] Useful target pathogens include, e.g., Bacillus anthracis
and Variola major.
[0180] Useful target toxins include, e.g., toxins of plant, insect,
animal, pathogenic and non-pathogenic origin. Examples of a plant
toxins include ricin toxin from Ricinus communis.
V. Fluorescent Tags
[0181] The fluorescent tag includes a fluorophore and can be a
fluorophore, fluorophore-containing moieties that are capable of
binding to other moieties (e.g., fluorescently tagged probes and
fluorescently tagged beads), and combinations thereof.
[0182] Examples of useful fluorophores include NBD (i.e.,
N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)), rhodamine, fluorescein,
eosin, erythrosine, dansyl and acridine orange. Examples of
suitable commercially available reactive fluorophores include,
fluorescein isothiocyanate, tetramethylrhodamine isothiocyanate,
fluorphores available under the BODIPY series of trade designations
from Molecular Probes (Eugene, Oreg.) including, e.g., BODIPY FL
succinimidyl ester of
4,4-difluoro-5,7-dimethyl-4-bora-3a,4a-diaza-s-indacene-3-propionic
acid, BODIPY R6G
4,4-difluoro-5-phenyl-4-bora-3a,4a-diaza-s-indacene-3-propioni- c
acid, succinimidyl ester, BODIPY TR-X, BODIPY 630/650-X, BODIPY
650/665-X, BODIPY FL Br.sub.2 SE, BODIPY 500/510, BODIPY FL
C.sub.5, BODIPY FL SE, BODIPY FL SSE, BODIPY FL AEBSF, BODIPY FL-X,
BODIPY FL-X SE, BODIPY FL CASE, BODIPY TMR-X SE, BODIPY 530/550,
BODIPY 530/550 SE, BODIPY 530/550 EDA, BODIPY R6G SE, BODIPY R6G-X
SE, BODIPY 581/591 SE, BODIPY 576/589 SE, BODIPY 650/665-X SE,
BODIPY 564/570, BODIPY 564/570 SE, BODIPY 493/503 SE, BODIPY
559/568 SE, BODIPY TR-X, SE, and BODIPY 630/650-X SE; the Cy series
of trade designations including, e.g., Cy3.5 monofunctional
NHS-ester, Cy5.5 monofunctional NHS-ester, Cy3 monofunctional
NHS-ester, Cy5 monofunctional NHS-ester, and Cy7 monofunctional
NHS-ester all of which are commercially available from Amersham
Biosciences (Buckinghamshire, England); and the ALEXA FLUOR series
of trade designations including, e.g., ALEXA FLUOR 488 carboxylic
acid succinimidyl ester mixed isomers, ALEXA FLUOR 555 carboxylic
acid succinimidyl ester, ALEXA FLUOR 647 carboxylic acid
succinimidyl ester, ALEXA FLUOR 350, 405, 430, 500, 514, 532, 546,
555, 568, 594, 610, 633, 647, 660, 680, 700, and 750 all of which
are commercially available from Molecular Probes (Eugene,
Oreg.).
[0183] Useful protocols for labeling proteins and other
biomolecules with fluorophores can be found in, e.g., R. Haugland,
Handbook of Fluorescent Probes and Research Products (Ninth Ed.
2002) and G. T. Hermanson, Bioconjugate Techniques (1996), and
incorporated herein.
VI. Crosslinking Agent
[0184] The system can optionally include a crosslinking agent. The
crosslinking agent includes at least two binding sites and is
capable of binding at least two components including, e.g., probe,
target, and combinations thereof, to form a crosslinked structure.
The component to which the crosslinking agent binds can optionally
include multiple binding sites to which the crosslinking agent can
bind. Crosslinking can manifest itself as an increase in the mass
of the complex, a decrease in the number of particles and
combinations thereof.
[0185] The crosslinking agent can function to aggregate the at
least two components. Where at least one of the two components
includes a fluorescent tag, the fluorescently tagged component
exhibits an increase in mass, which can be detected as a change in
the diffusion coefficient of the fluorescently tagged component.
The aggregation of at least two fluorescently tagged components can
also be detected as a decrease in the number of independently
moving fluorescently tagged components in the system.
[0186] At least one of the components of the system (e.g., probe,
target, bead, and combinations thereof) can function as the
crosslinking agent. Alternatively, the crosslinking agent can be an
additional component of the system. Suitable crosslinking agents
include, e.g., the probe, the target, a mass adding component,
lectins against a component of the system, antibodies to a
component of the system (e.g., the probe or the target), and
combinations thereof.
VII. Stoichiometry
[0187] Macromolecular stoichiometry, i.e., the quantitative
proportions with which two macromolecules interact, of a target can
be determined from autocorrelation data. Starting with Equation 4,
macromolecular stoichiometry can be calculated if it is assumed
that intersystem crossing and particle diffusion are independent
sources of fluctuation. The first occurs in the microsecond (.mu.s)
time domain and results from intersystem crossing of fluorophores
between the singlet and triplet states. The second occurs in the
millisecond (ms) time domain, and results from the diffusion of
particles into and out of the confocal volume. Fluctuations between
singlet and triplet states are therefore governed by the number of
the fluorophores in the confocal volume while diffusional
fluctuations are governed by the number of particles. This leads to
a simplified form of equation (4). If this assumption is made,
Equation 4 can be rearranged to yield Equation 5 22 G ( ) = 1 + T N
M exp ( - / T ) + 1 - T N P ( i F i ( 1 + / D i ) ( 1 + / K 2 D i )
1 / 2 ) ( 5 )
[0188] which can be further simplified to Equation 6 23 G ( ) = 1 +
T N M ' exp ( - / T ) + 1 N P ' ( i F i ( 1 + / D i ) ( 1 + / K 2 D
i ) 1 / 2 ) ( 6 )
[0189] by defining N.sub.M=N'.sub.MT and N.sub.P=N'.sub.P(1-T).
[0190] One method of determining the molecule stoichiometry of a
target employs the autocorrelation data and a calibration factor,
r, which is the number of fluorophores per fluorescently tagged
probe. The calibration factor, r, is calculated according to the
following equation (7) 24 r = N M ' N P ' ( 7 )
[0191] where N'.sub.M is the number of fluorophore molecules and
N'.sub.P is the total number of diffusing particles and includes
slow diffusing complexes (F.sub.2) (i.e., a complex of a
fluorescently tagged probe bound to the target of the probe) and
fast diffusing particles (F.sub.1), (i.e., fluorescently tagged
probes that are uncomplexed (i.e., unbound)) obtained from the
autocorrelation data. Stoichiometry (S) is defined conceptually as
25 S = Number of Fabs in slow complex Number of complexes
[0192] where S is given by 26 S = Total Fabs - fast diffusing Fabs
Number of complexes
[0193] such that the general relationship for stoichiometry can be
written as 27 S = N M ' / r - F 1 N P ' F 2 N P ' ( 8 )
[0194] where F.sub.1N'.sub.P defines the total number of fast
diffusing particles, i.e., uncomplexed fluorescently tagged probes,
and F.sub.2N'.sub.P defines the total number of slow diffusing
complexes formed. This analysis is carried out with tagged probe at
constant concentration, and exposed to a range of target
concentrations. S is obtained with Equation 8 for each target
concentration using the parameter values obtained by fitting to
Equation 6 and the calibration factor determined with Equation
7
VIII. Number of Independently Moving Fluorescent Particles
[0195] A given detector detects the class of fluorescent tags in
the sample that fluoresce at a given set of wavelengths. If the
fluorescent tags become complexed as a result of molecular
interactions (e.g., between probe, target, crosslinking agent and
combinations thereof) then the number of such independently moving
fluorescent tags decreases. The number of such independently moving
fluorescent tags, referred to herein as the particle number
(N.sub.P), present in the sample can be determined from the
autocorrelation curve generated from the autocorrelation data.
G(0), which is the value G(t) of the autocorrelation curve at
time=0, and which is inversely proportional to the number of
particles (N.sub.P) in the system. This value is typically
calculated from the curve fit to the autocorrelation data since the
actual 0 time point obtained experimentally is dominated by shot
noise. The 0 time point of the autocorrelation function increases
as the number of particles decreases. To determine the number of
particles of interest in the confocal volume, the particle of
interest must include a fluorescent tag. If the fluorescently
tagged particles form an aggregate, the number of free
fluorescently tagged particles will decrease resulting in a shift
in the 0 time point of the autocorrelation function and a
corresponding decrease in the number of particles in the
system.
IX. The Crosscorrelation Correction Algorithm
[0196] Emission bleed-through between detectors occurs in FCS
systems. Emission bleed-through occurs when detector configuration
allows detection of both fluorophores in a single detector channel
and leads to artifactual crosscorrelation of two signals. As a
result, the measured autocorrelation and crosscorrelation functions
differ from the true autocorrelation and crosscorrelation functions
(i.e., those correlation functions that would be obtained in the
absence of bleed through). Because of the high rates of data
acquisition it is difficult to correct for bleed-through during
acquisition. The present inventors have discovered that the three
measured correlation functions (i.e., two autocorrelation functions
and one crosscorrelation function) are linear combinations of the
three true (i.e. bleed-through corrected) correlation functions.
Correction for bleed-through becomes a matter of solving this set
of three simultaneous linear equations.
[0197] To correct for this bleed through and to obtain the true
autocorrelation and crosscorrelation functions, the autocorrelation
and crosscorrelation data obtained for a sample is preferably
further analyzed using algorithms that correct for crossover
emission detected in the two detectors. For the autocorrelation
function of a first detector, the data is preferably subjected to
the following algorithm 28 G 1 T = - 2 < I 1 > < I 2 >
R + 2 < I 2 > 2 G 2 + < I 1 > 2 G 1 - 2 < I 1 >
< I 2 > + 2 < I 2 > 2 + < I 1 > 2 ( 9 )
[0198] where G.sub.1T is the true autocorrelation function of the
fluorescence measured at the first detector, .rho. is the bleed
through coefficient of detector two into detector one,
<I.sub.1> is the time averaged intensity in detector one,
<I.sub.2> is the time averaged intensity in detector two, R
is the measured crosscorrelation function for detectors one and
two, and G.sub.1 and G.sub.2 are the measured autocorrelation
functions of detector one and detector two, respectively.
[0199] For the autocorrelation function of the second detector, the
data is preferably subjected to the following algorithm 29 G 2 T =
- 2 r < I 1 > < I 2 > R + < I 2 > 2 G 2 + r 2
< I 1 > 2 G 1 - 2 r < I 1 > < I 2 > + < I 2
> 2 + r 2 < I 1 > 2 ( 10 )
[0200] where G.sub.2T is the true autocorrelation function of the
fluorescence measured at the second detector, r is the bleed
through coefficient of detector one into detector two, and R,
<I.sub.1>, <I.sub.2>, G.sub.1, and G.sub.2 are as
described above.
[0201] For the crosscorrelation function, the data is preferably
subjected to the following algorithm 30 R T = < I 1 > < I
2 > R ( 1 + r ) - < I 2 > 2 G 2 - r < I 1 > 2 G 1
< I 1 > < I 2 > ( 1 + r ) - < I 2 > 2 - r < I
1 > 2 ( 11 )
[0202] where R.sub.T is the true crosscorrelation function of the
fluorescence measured at the first and second detectors, R is the
measured crosscorrelation function of detector one and detector
two, and r, .rho., <I.sub.1>, <I.sub.2>, G.sub.1, and
G.sub.2 are as described above.
[0203] The bleed through coefficient, .rho., is experimentally
determined by taking a first fluorophore and measuring its average
intensity in detector two divided by its average intensity measured
in detector one.
[0204] The bleed through of detector one into detector two, r, is
experimentally determined by taking a second fluorophore and
measuring its average intensity in detector one divided by its
average intensity measured in detector two.
[0205] Equations (9)-(11) assume that there is no difference
between the crosscorrelation of detector channel one with detector
channel two, R.sub.12, and the crosscorrelation of detector channel
two with detector channel one, R.sub.21. While this is both
theoretically and practically true, one can, in fact determine
R.sub.12 and R.sub.21 separately in which case equations (9)-(11)
can be replaced with equivalent corresponding equations (9a),
(10a), (11a) and (11b): 31 G 1 T = - < I 1 > < I 2 > (
R 12 + R 21 ) + 2 < I 2 > 2 G 2 + < I 1 > 2 G 1 - 2
< I 1 > < I 2 > + 2 < I 2 > 2 + < I 1 > 2 (
9 a ) G 2 T = - r < I 1 > < I 2 > ( R 12 + R 21 ) +
< I 2 > 2 G 2 + r 2 < I 1 > 2 G 1 - 2 r < I 1 >
< I 2 > + < I 2 > 2 + r 2 < I 1 > 2 ( 10 a ) R 12
T = < I 1 > < I 2 > ( R 12 + r R 21 ) - < I 2 > 2
G 2 - r < I 1 > 2 G 1 < I 1 > < I 2 > ( 1 + r ) -
< I 2 > 2 - r < I 1 > 2 ( 11 a ) R 21 T = < I 1 >
< I 2 > ( R 21 + r R 12 ) - < I 2 > 2 G 2 - r < I 1
> 2 G 1 < I 1 > < I 2 > ( 1 + r ) - < I 2 > 2
- r < I 1 > 2 . ( 11 b )
[0206] In another embodiment, the bleed through emission can be
corrected for on the measured signals at the detector channels
(i.e., detector channels one and two). The true signals X and Y for
detector channel one and two, respectively is obtained by measuring
the signals I.sub.1 and I.sub.2 for detector channels one and two,
determining the bleed through coefficient, .rho., i.e., the
fraction of the signal in detector channel one due to the signals
from detector channel two, determining the bleed through r, i.e.,
fraction of the signal in detector channel two that is due to the
signals in detector channel one, correcting the signal in channel
one using the equation 32 X = I 1 - I 2 1 - r
[0207] and optionally, additionally, or alternatively correcting
the signal in channel two using the equation 33 Y = I 2 - r I 1 1 -
r .
X. Other Properties of the System
A. Flow
[0208] The sample can be provided in the confocal volume of the FCS
instrument in a variety of forms including, e.g., a well, cuvette,
flow chamber, and capillary tube. In the case of a flow chamber,
the sample flows through the confocal volume. The flow can be the
result of a variety of forces including, e.g., pressure (e.g., a
hydrostatic flow where the velocity of the particle is independent
of the size of the particle), and applied voltage, e.g.,
electrophoretic flow, where the velocity of the particle is
dependent on the size of the particle.
B. High Throughput and Automated Systems
[0209] In another aspect, high throughput screening methodologies,
such as screening libraries by selection of subvolumes can be
utilized to identify probe-member binding pairs, i.e., binding
events between a probe and member of a library. For example, a
stock of library members can be divided into subvolumes such that
each subvolume contains a portion of the members of the library.
Each subvolume solution is then screened utilizing an array (e.g.,
multiple sample chambers containing members of the library (i.e.,
potential targets)). Upon detection of a binding event, the
subvolume can be sub-divided again and screened repeatedly until
the member that binds to the probe is identified.
[0210] The system can also be automated. Suitable automated systems
include those robotic systems developed for solution phase
chemistries. These automated systems include automated workstations
including, e.g., the automated synthesis apparatus developed by
Takeda Chemical Industries, LTD. (Osaka, Japan) and the many
robotic systems that utilize robotic arms (Zymate II, Zymark
Corporation, Hopkinton, Mass.; Orca, Hewlett-Packard, Palo Alto,
Calif.). Suitable automated systems include, e.g., providing (e.g.,
sequentially or simultaneously) multiple samples to a sample
detection volume of an FCS instrument. Suitable automated systems
also include automated liquid handling including, e.g., including
probes, buffers, targets, fluorescent tags and combinations
thereof.
C. The Sample
[0211] The sample can be obtained from a variety of sources
including, e.g., samples obtained by swabbing (e.g., cheek swab,
nose swab, and eye swab), biological samples including, e.g.,
bodily fluids (e.g., blood, urine, saliva, and ear wax),
environmental samples including, e.g., water, air, and soil, and
combinations thereof.
XI. Kits
[0212] The reagents of the system including, e.g., at least one
probe and at least one fluorescent tag, can be included in a kit
for assaying for the presence of an unknown or a known target. The
probes can be capable of binding to a predetermined target or site
on a macromolecule. The fluorescent tag can be attached to the
probe. The kit can optionally include a bead or a plurality of
beads. At least one probe can be attached to the bead. The bead can
optionally include a fluorescent tag. The kits can include multiple
fluorescent tags having unique fluorophores.
[0213] One useful kit includes fluorescently tagged human serum
albumin galactose probe. Another useful kit includes a human serum
albumin galactose probe and a fluorescently labeled ricin probe.
Such kits are useful for assaying for toxin including, e.g.,
ricin.
[0214] The invention will now be described by way of the following
examples.
EXAMPLES
Test Procedures
[0215] Test procedures used in the examples include the
following.
FCS Instrumentation
[0216] The samples were analyzed using a fluorescence correlation
spectroscopy instrument configured to distinct fluorescence
emission at different wavelengths and a data processing program
capable of autocorrelation, crosscorrelation, Fourier transform and
Moment analyses.
Example 1
[0217] Bacteria of an unknown strain were tagged nonspecifically
with a lipophilic fluorescent dye, DiIC16. A specific antibody for
E. coli strain K-12 was tagged with ALEXA-546. The tagged antibody
is not specific for the bacteria of the unknown strain and
therefore does not bind to it. The fluorescently tagged bacteria
and the fluorescently tagged antibody for E. coli were measured in
two unique detection channels (i.e., channels 1 and 2) tuned to a
wavelength for detecting ALEXA-546 and DiIC16, respectively. There
were no coincident peaks in detection channels 1 and 2 and
crosscorrelation did not occur. FIG. 1A illustrates the absences of
coincident peaks in detection channels 1 and 2. The peaks in
detection channel 2 represent two bacteria moving through the
confocal detection volume. The lack of coincident peaks in
detection channel 1 suggests that the ALEXA-546 tagged antibody for
E. coli does not bind to the fluorescently tagged bacterial strain.
FIG. 1B illustrates the absence of a positive crosscorrelation
curve due to the lack of coincident peaks in detection channels 1
and 2.
Example 2
[0218] E. coli strain K-12 tagged with ALEXA-594 (sold under the
trade designation BIOPARTICLES, Product# D23370) were purchased
from Molecular Probes (Eugene, Oreg.). An E. coli specific antibody
that was conjugated to ALEXA-546 and that specifically recognizes
binding sites on the K-12 strain of E. coli was used as a second
probe. The antibody was incubated with E. coli for 5 minutes at
room temperature so as to achieve equilibrium binding. The
ALEXA-594 and ALEXA 546 were measured in unique detection channels
1 and 2, which were tuned to a wavelength for detecting ALEXA-594
and ALEXA-546, respectively, and when signal peaks were coincident
between both detection channels, a crosscorrelation curve resulted.
FIG. 2A illustrates a single coincident peak at detection channels
1 and 2, which represents the movement of a single bacterium
through the confocal detection volume. FIG. 2B illustrates the
crosscorrelation curve that results from coincident peaks shown in
FIG. 2A.
Example 3
[0219] E. coli strain K-12 tagged with ALEXA-594 (sold under the
trade designation BIOPARTICLES, Product# D23370) were purchased
from Molecular Probes (Eugene, Oreg.). An E. coli specific antibody
that had been conjugated to ALEXA-546 and that specifically
recognizes binding sites on the K-12 strain of E. coli was used as
a second probe. The antibody was incubated with E. coli for 5
minutes at room temperature so as to achieve equilibrium binding.
The ALEXA-594 and ALEXA 546 were measured in two unique detection
channels 1 and 2, which were tuned to a wavelength for detecting
ALEXA-594 and ALEXA-546, respectively. When signal peaks were
coincident between both detection channels, a crosscorrelation
curve resulted. FIG. 3A illustrates two coincident peaks at
detection channels 1 and 2, which represent two bacteria moving
through the confocal detection volume. FIG. 3B illustrates the
crosscorrelation curve that results from coincident peaks shown in
FIG. 3A.
Example 4
[0220] Antibodies for E. coli were tagged with ALEXA-546 and added
to a sample chamber that included E. coli and incubated for 5
minutes to achieve equilibrium. Autocorrelation data were collected
for the sample. FIG. 4A illustrates two peaks, which represent
individual bacteria moving through the detection volume. FIG. 4B
illustrates the autocorrelation curve for the data collected in
FIG. 4A.
Example 5
[0221] Fab fragments of whole antibody were tagged with Rhodamine
(Rh-Fab). Rh-Fab binds specifically to antibody (IgG) but the
number of specific binding sites was not known. To determine the
number of binding sites on IgG for Rh-Fab, 10 nM of Rh-Fab was
titrated with increasing concentration of IgG and allowed to
equilibrate. FIG. 5A illustrates the autocorrelation curves of
Rh-Fab alone (20) and in the presence of 4 .mu.M IgG (24). Data
were fit to Equation 6 and best fit regression lines and residuals
(top panel) displayed. FIG. 5B illustrates the use of the parameter
estimates obtained from this analysis to determine the fraction of
slow diffusing particles (F2Np) at each IgG concentration. The
number of slow diffusing particles increases as IgG increased, and
saturated when all binding sites were occupied. FIG. 5C illustrates
the use of paramenter estimates from the analysis of
autocorrelation curves (FIG. SA) in Equations 7 and 8 to determine
stoichiometry of binding Rh-Fab to IgG. The number of Rh-Fab bound
to IgG was determined using Equation 9, and plotted for each IgG
concentration tested. This analysis shows that there are about 6
Rh-Fab bound to each IgG at low IgG concentrations, and about 2
Rh-Fab bound at high IgG concentrations.
Example 6
[0222] The low affinity nerve growth factor receptor, gp75, which
binds to nerve growth factor (NGF) were expressed endogenously in
A875 cells. A875 cells were placed in a cell culture chamber
overnight and allowed to attach to the surface of the chamber. Cell
were either left untreated, or exposed to 180 nM of NGF for 5
minutes to reach binding equilibrium. FIG. 6A illustrates the
autocorrelation curves from untreated (30) and NGF-treated (34)
A875 cells. Data were fit to Equation 6 and best fit regression
lines and residuals (top panel) displayed. FIG. 6B illustrates
theoretical curves for monomers 36, dimmers 38, trimers 40 and
tetramers 42 as a function of fractional occupancy. The parameter
estimates obtained from this analysis were used in Equation 8 to
determine that the results of the stoichiometry calculations for
untreated (1.12) and NGF-treated (0.94) were not different, which
suggests that gp75 are receptor monomers in A875 cells.
Example 7
[0223] Ricin was fluorescently labeled with ALEXA-546 to facilitate
assay development. FIG. 7 illustrates ALEXA-546 conjugated ricin
alone (50), in the presence of anti-ricin antibody (54), and in the
presence of anti-ricin antibody that has been pre-incubated with
unlabeled ricin (58) for 5 minutes at room temperature to reach
equilibrium. When ALEXA-546 conjugated ricin binds to the
anti-ricin antibody, there is a decrease in number of free
particles (N) and a rightward shift in the diffusion time,
indicating a slower diffusing (larger) particle. When anti-ricin
antibody is preincubated with unlabeled ricin, the ricin binding
sites are blocked, which prevents binding of ALEXA-546 conjugated
ricin to the ricin antibody.
Example 8
[0224] FIG. 8 illustrates Ricin tagged with ALEXA-546 (A1546-ricin)
and prebound to galactose conjugated to Human Serum Albumin
(HSA-gal) (60) for at least 5 minutes at room temperature to
achieve equilibrium. Untagged ricin was added and incubated for 15
minutes at room temperature to achieve equilibrium displacement of
A1546-ricin from HSA-galactose and a shift in the autocorrelation
curve (64).
Example 9
[0225] FIG. 9 illustrates the crosscorrelation data collected on
bacteria particles labeled with both ALEXA-594 and ALEXA-546. The
top panel (FIG. 9A) illustrates the crosscorrelation data as it
appears before applying the cross-talk correction algorithm. The
bottom panel (FIG. 9B) illustrates the same data after applying the
correction algorithm (Equation 11). The slower diffusion time,
which represents the bacterial particle diffusion, fits to 6 ms for
both data sets.
Example 10
[0226] FIG. 10 illustrates correction of autocorrelation data using
the correction algorithm on bacteria particles labeled with both
ALEXA-594 and ALEXA-546. FIG. 10A illustrates the autocorrelation
data as it appears before applying the cross-talk correction
algorithm. FIG. 10B illustrates the same data after applying the
correction algorithm (Equation 9, for detector channel 1). The same
analysis can be applied to data collected in detector channel 2
using Equation 10.
Example 11
[0227] FIG. 11 illustrates Moment analysis of the fluorescence
intensity fluctuations of ALEXA-546 tagged ricin either alone or
bound to HSA-Galactose (data of Example 8). Moment analysis allows
us to obtain a value for the particle number (N.sub.P) without
having to calculate the autocorrelation function. The data
collected is subjected to the following general algorithm 34 < I
2 > - < I > 2 < I > 2 ( 12 )
[0228] where I is the fluorescence intensity for the
autocorrelation data being analyzed, <I> is the time averaged
intensity (i.e. the first moment), and <I.sup.2> is the time
averaged intensity squared (i.e. the second moment. Moment analysis
of ricin alone resulted in a value of 1/N.sub.P=0.00014. Moment
analysis of ricin bound to HSA-Galactose resulted in a value of
1/N.sub.P=0.007. FIG. 11 illustrates the analysis of the
autocorrelation function of ricin alone (B) and ricin bound to
HSA-Galactose (A). The arrows indicate 1+1/N.sub.P calculated by
Moment analysis.
Example 12
[0229] FIG. 12 illustrates Fourier transform analysis of the
fluorescence intensity fluctuations of ALEXA-546 tagged ricin alone
(60) and bound to HSA-Galactose (64) (data of Example 8). FIG. 12A
shows the power spectrum of the Fourier Transform (FFT function,
Origin 5.0, OriginLab, Northampton, Mass.). The data collected is
subjected to the following general algorithm. 35 ( I i - < I
> < I > ) ( 13 )
[0230] where I.sub.i is the intensity value at each time point and
<I> is the time averaged intensity. FIG. 12B shows the
amplitude of the Fourier Transform.
[0231] Other embodiments are within the claims.
* * * * *