U.S. patent application number 10/047548 was filed with the patent office on 2002-08-15 for integrated system for analysis of biomolecules.
Invention is credited to Gruber, Karl A., Nelson, Randall W., Tubbs, Kemmons A..
Application Number | 20020110904 10/047548 |
Document ID | / |
Family ID | 26949279 |
Filed Date | 2002-08-15 |
United States Patent
Application |
20020110904 |
Kind Code |
A1 |
Nelson, Randall W. ; et
al. |
August 15, 2002 |
Integrated system for analysis of biomolecules
Abstract
The present invention provides an integrated system capable of
selectively retrieving and concentrating specific biomolecules from
biological media for subsequent high-performance analyses,
quantifying targeted proteins, recognizing variants of targeted
biomolecules (e.g., splice variants, point mutations and
post-translational modifications) and elucidating their nature,
analyzing for, and identifying, ligands interacting with targeted
biomolecules, and high-throughput screening of large populations of
samples using a single, unified, economical, multiplexed and
parallel processing platform. The preferred embodiment of the
integrated system comprises molecular traps, such as affinity
microcolumns, derivatized mass spectrometer targets, mass
spectrometers capable of multi-sample input and robotics with
processing/data analysis interactive database. The present
invention also includes methods and processes for use of the
individual components and the integrated system in biological
applications. Furthermore, the preferred embodiment of the present
invention provides for the preparation and/or processing of
multiple separate devices and/or samples to accomplish high
throughput analysis.
Inventors: |
Nelson, Randall W.;
(Phoenix, AZ) ; Tubbs, Kemmons A.; (Mesa, AZ)
; Gruber, Karl A.; (Tempe, AZ) |
Correspondence
Address: |
The Halvorson Law Firm
Ste 1
405 W. Southern Ave.
Tempe
AZ
85282
US
|
Family ID: |
26949279 |
Appl. No.: |
10/047548 |
Filed: |
January 15, 2002 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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60262530 |
Jan 18, 2001 |
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60262852 |
Jan 18, 2001 |
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Current U.S.
Class: |
435/287.2 ;
702/19 |
Current CPC
Class: |
B01J 20/28097 20130101;
G01N 33/545 20130101; B01J 20/3204 20130101; B01J 20/3208 20130101;
Y10T 436/255 20150115; G01N 30/02 20130101; B01J 20/3242 20130101;
H01J 49/40 20130101; G01N 33/6845 20130101; B01J 20/281 20130101;
B01J 20/3259 20130101; B01D 15/3804 20130101; B01J 20/3272
20130101; H01J 49/164 20130101; B01J 2220/54 20130101; G01N 30/48
20130101; B01J 20/286 20130101; B01J 20/32 20130101; B82Y 30/00
20130101; G01N 33/54366 20130101; G01N 2570/00 20130101; B01J
2220/64 20130101; B01J 20/3282 20130101; G01N 30/02 20130101; B01J
20/3274 20130101; G01N 30/6095 20130101; G01N 33/6803 20130101;
B01J 20/3265 20130101 |
Class at
Publication: |
435/287.2 ;
702/19 |
International
Class: |
C12M 001/34; G06F
019/00; G01N 033/48; G01N 033/50 |
Claims
1. A high throughput integrated system for qualitative and
quantitative biomolecules analysis comprising; a) a robotic
platform fitted with multiple, spatially arrayed affinity
microcolumns, b) a mass spectrometer target having a spatial array
corresponding to the same spatial array as the affinity
microcolumns, and, c) a mass spectrometer capable of accepting the
spatially arrayed target.
2. The system of claim 1 wherein the spatial array comprises
between 4 and 1536 elements.
3. The system of claim 1 wherein the robotic platform further
comprises multiple processing stages.
4. The system of claim 1 wherein if the affinity microcolumns
receive specific biological molecules in a biological media, the
specific biological molecules are retrieved via affinity
interaction.
5. The system of claim 1 wherein the mass spectrometer target has
modifying activity.
6. The system of claim 1 wherein the mass spectrometer is a
matrix-assisted laser desorption/ionization time-of-flight mass
spectrometer.
7. The system of claim 3 wherein at least one of the multiple
processing stages is for the selective isolation of specific
biological molecules present in a biological media using affinity
microcolumns.
8. The system of claim 3 wherein at least one of the multiple
processing stages is for rinsing the affinity microcolumns free of
non-specifically retained compounds.
9. The system of claim 3 wherein at least one of the multiple
processing stages is for the deposition of selectively retained
biological molecules onto a mass spectrometer target.
10. The system of claim 1 wherein if multiple different samples of
biological media are presented, then they are processed relatively
simultaneously and in parallel using the robotic platform fitted
with multiple, spatially arrayed affinity microcolumns and the mass
spectrometer target having a spatial array corresponding to the
same spatial array as the affinity microcolumns.
Description
[0001] This application is a continuation-in-part of pending
provisional applications 60/262,530 and 60/262,852, both filed on
Jan. 17, 2001.
FIELD OF THE INVENTION
[0002] The present invention is related to the field of proteomics.
More specifically, the present invention is a method and device for
rapid identification and characterization of biomolecules recovered
from biological media. Additionally, the present invention includes
the ability to process numerous different samples simultaneously
(high throughput analysis).
BACKGROUND OF THE INVENTION
[0003] Recent advances in human genome sequencing have propelled
the biological sciences into several new and exciting arenas of
investigation. One of these arenas, proteomics, is largely viewed
as the next wave of concerted, worldwide biological research.
Proteomics is the investigation of gene products (proteins), their
various different forms and interacting partners and the dynamics
(time) of their regulation and processing. In short, proteomics is
the study of proteins as they function in their native environment
with the overall intention of gaining a further, if not complete,
understanding of their biological function. Such studies are
essential in understanding such things as the mechanisms behind
genetic disorders or the influences of drug mediated therapies, as
well as potentially becoming the underlying foundation for further
clinical and diagnostic analyses.
[0004] There are several challenges intrinsic to the analysis of
proteins. First, and foremost, any protein considered relevant
enough to be analyzed resides in vivo in a complex biological
environment or media. Oftentimes, a protein of interest is present
in the media at relatively low levels and is essentially masked
from analysis by a large abundance of other biomolecules, e.g.,
proteins, nucleic acids, carbohydrates, lipids and the like.
Technologies currently employed in proteomics are only able to
overcome this fundamental problem by first fractionating the entire
biological media using the old technology of two-dimensional (2D)
sodium dodecyl sulphate--polyacrylamide gel electrophoresis
(SDS-PAGE), wherein numerous proteins are simultaneously migrated
using a gel medium in two dimensions, i.e., as a function of
isoelectric point and molecular size. In order to ensure migration
in a predictable manner, the proteins are first reduced and
denatured, a process that destroys the overall structures of the
proteins and voids their functionality.
[0005] Present day state-of-the-art proteomics involves the
identification of the proteins separated using 2D-PAGE. In this
process, gel spots containing separated proteins are excised from
the gel medium and treated with a high-specificity enzyme (most
commonly trypsin) to fragment the proteins. The resulting fragments
are then subjected to high-accuracy mass analysis using either
electrospray ionization (ESI) or matrix-assisted laser
desorption/ionization time-of-flight (MALDI-TOF) mass
spectrometries (MS). The resulting data, in the form of absolute
molecular weights of the fragments, and knowledge of the enzyme
specificity are used in silico to search genomic or protein
databases for information correlating to the empirical data on the
fragments. Analytical methods and searching protocols, refined over
the past seven years, have evolved to a point where only a few
proteolytic fragments, determined with high mass accuracy, are
needed to identify a gel-separated protein as being present in a
certain gene.
[0006] However, identification of the gene responsible for
producing a protein is only the first step in the overall much
larger process of determining complete protein structure and,
finally, function. Numerous questions can be asked of protein
structure/function that cannot be answered by the 2D-PAGE/MS
approaches. One major issue deals with the primary structure of the
protein. During the commonly practiced identification process, at
most, fifty percent of the protein sequence is viewed, leaving at
least fifty percent of the protein unanalyzed. Given that
potentially numerous splice variants, point mutations, and
post-translational modifications exist for any given protein, many
variants and modifications present within a protein will ultimately
be missed during the identification process. As such, proteins are
not viewed in the full structural detail needed to differentiate
(normal) functional variants from (disease-causing) disfunctional
variants.
[0007] Furthermore, current identification processes make no
provision for protein quantitation. Because many disease states are
created or indicated by elevated or decreased levels of specific
proteins and/or their variants, protein quantitation is an
essential component of proteomics. Presently, protein quantitation
from gels is performed using staining approaches that inherently
have a relatively high degree of variability, and thus inaccuracy.
The staining approaches can be replaced using isotope-coded
affinity tags (ICAT) in conjunction with mass spectrometric
quantification of proteolytic fragments generated from 2D-PAGE.
However, the ICAT approach is still subjective to the
aforementioned protein variants, in that these structural variants
will yield mass-shifted proteolytic fragments that will not be
included in the quantification process. Likewise, other approaches,
such as ELISA (enzyme-linked immunosorbant assay) and RIA
(radioimmunoassay), are equally subjected to the complications of
quantifying a specific protein (i.e., the functional variant) in
the presence of its variants. Lacking the ability to resolve a
target protein from its variants, these techniques will essentially
monitor all protein variants as a single compound; a process that
is oftentimes misleading in that a disease may be caused/indicated
by elevated level of only a single variant, not the cumulative
level of all the variants.
[0008] Moreover, the 2D-PAGE/MS and immunoassay approaches make no
provision for exploring protein-ligand (e.g., other proteins,
nucleic acids or compounds of biological relevance) interactions.
Because denaturing conditions are used during protein 2D-PAGE
separation, all protein-ligand interactions are disrupted, and thus
are out of the realm of investigation using the identification
approach. Alternatively, standard immunoassays, although performed
under native conditions, do not include in the analysis a
structural identification (i.e., an intrinsic physical property)
component necessary for exact protein identification. Thus, other
approaches are used in the analysis of protein-ligand interactions.
The most frequently used of these are the yeast two-hybrid (Y2H)
and phage display approaches, which use in vivo molecular
recognition events to trigger the expression of genes that produce
reporter proteins indicating a biomolecular interaction, or
selectively amplify high-affinity binding partners, respectively.
Other instrumental approaches rely on biosensors utilizing
universal physical properties or tags (e.g., surface plasmon
resonance or fluorescence) as modes of detection. The two major
limitations of these approaches is that they are generally slow and
that interacting partners pulled from biological media are detected
indirectly, yielding no specific or identifying information about
the binding partner.
[0009] Lastly, none of the aforementioned approaches are favorable
to large-scale, high-throughput analysis of specific proteins,
their variants and their interacting partners in large populations
of subjects. All of the aforementioned approaches require several
hours (2D-PAGE) to several weeks (Y2H) to perform on a single
sample. As such, time and monetary expenses preclude application to
the hundreds-to-thousands of samples (originating from
hundreds-to-thousands of individuals) necessary in proteomic,
clinical, and diagnostic applications.
[0010] To date, there are no universal, integrated systems capable
of the high-throughput analysis of proteins for all of the
aforementioned reasons. Thus, there exists a pressing need for new
and novel technologies able to analyze native proteins present in
their natural environment. Encompassed in these technologies are:
1) the ability to selectively retrieve and concentrate specific
proteins from biological media for subsequent high-performance
analyses, 2) the ability to quantify targeted proteins, 3) the
ability to recognize variants of targeted proteins (e.g., splice
variants, point mutations and posttranslational modifications) and
to elucidate their nature, 4) the capability to analyze for, and
identify, ligands interacting with targeted proteins, and, 5) the
potential for high-throughput screening of large populations of
samples using a single, economical platform.
[0011] All publications and patent applications are herein
incorporated by reference to the same extent as if each individual
publication or patent application was specifically and individually
indicated to be incorporated by reference. Although the present
invention has been described in some detail by way of illustration
and example for purposes of clarity and understanding, it will be
apparent that certain changes and modifications may be practiced
within the scope of the appended claims.
SUMMARY OF INVENTION
[0012] It is an object of the present invention to provide an
integrated system capable of selectively retrieving and
concentrating specific biomolecules from biological media for
subsequent high-performance analyses, quantifying targeted
proteins, recognizing variants of targeted biomolecules (e.g.,
splice variants, point mutations and posttranslational
modifications) and elucidating their nature, analyzing for, and
identifying, ligands interacting with targeted biomolecules, and
high-throughput screening of large populations of samples using a
single, unified, economical, multiplexed and parallel processing
platform.
[0013] It is another embodiment of the present invention to provide
an integrated system that comprises molecular traps, such as
affinity microcolumns, derivatized mass spectrometer targets, mass
spectrometers capable of multi-sample input and robotics with
processing/data analysis interactive database software that
accomplish the high throughput analysis.
[0014] It is yet another object of the present invention to provide
individual components for the integrated system, such as molecular
traps, derivatized targets and the like.
[0015] It is a further object of the present invention to provide a
high throughput embodiment of the present invention that uses
robotics for serial preparation and parallel processing of a large
number of samples simultaneously.
[0016] It is yet a further object of the present invention to
provide methods and processes for use of the individual components
and the integrated system in biological applications.
[0017] It is still yet another object of the present invention to
provide a device and method for the identification of point
mutations and variants of analytes using an integrated system using
high throughput analysis.
[0018] It is yet another object of the present invention to provide
an integrated system capable of quantifying specific functional
variants of a protein while in the presence of dysfunctional,
mass-shifted variants.
[0019] The novel features that are considered characteristic of the
invention are set forth with particularity in the appended claims.
The invention itself, however, both as to its structure and its
operation together with the additional objects and advantages
thereof will shown in FIG. 5b. The concentration range was spanned
with good linearity (R.sup.2=0.999) with overall standard deviation
of the line of <2%.
[0020] With reference to FIG. 6, a bar analysis of the data shown
in FIG. 4 using the standard curve constructed in FIG. 5 is
illustrated. Each spectrum for the 88 samples from FIG. 4 was
normalized to the equine .beta..sub.2m signal through baseline
integration, and the normalized integral for the human
.beta..sub.2m signal determined. Repetitive analyses were performed
for each same individual and were averaged and the standard
deviation calculated. The values of the averaged integrals were
substituted in the equation derived from the standard curve and the
concentration of human .beta..sub.2m was calculated for each
individual. The range of concentrations determined was from 0.75 to
1.25 mg/L. It is essential to note that by excluding mass-shifted
variants (e.g.,+146 Da, due to glycated b2m variant, which is
dysfunctional), that these values indicate the true concentration
of functional b2m present in each individual, rather than the
combined concentration of functional and dysfunctional
variants.
EXAMPLE 3
High Throughput Screening for Genetic and Posttranslational
Variants
[0021] With reference to FIG. 7, a qualitative high-throughput
screening of transthyretin (TTR) for posttranslational modification
(PTM) and point mutations (PM) was performed using the integrated
system and methods described herein. Aliquots of diluted (5-fold)
human plasma samples collected from six individuals were prepared
for parallel screening on a 96-well plate. Each well received a 15
.mu.L plasma aliquot (the samples from the six individuals were
randomized on the 96-well plate), and 135 .mu.L of HBS buffer.
Parallel sampling processing entailed simultaneous
incubation/capture of the 96 samples on 96 anti-TTR derivatized
microcolumns. The polyclonal anti-TTR microcolumns were made via
glutaraldehyde-mediated coupling of the antibodies to
amino-coated/modified microcolumns. Captured proteins were eluted
from the microcolumn array with a small volume of MALDI matrix
(saturated ACCA solution) and stamped onto a MALDI target array
surface comprised of self-assembled monolayers (SAM) chemically
masked to make hydrophilic/hydrophobic contrast targets. Each
sample spot on the target array was analyzed using mass
spectrometry and the relative TTR abundance determined by an
automated MALDI-TOF mass spectrometric analysis
[0022] FIG. 2 is an illustration of a high-throughput
semi-quantitative analysis of beta-2-microglobulin (.beta..sub.2m)
from human plasma samples using the integrated system and methods
described in this invention.
[0023] FIG. 3 shows bar graph analysis of the data shown in FIG.
2.
[0024] FIG. 4 is an illustration of a high-throughput quantitative
analysis of .beta..sub.2m from human plasma samples using the
integrated system and methods described in this invention.
[0025] FIGS. 5a and 5b illustrate the construction of a calibration
curve from the data for the standard samples shown in FIG. 4 and
for the purpose of determining the .beta..sub.2m concentrations in
the human plasma samples screened via the high-throughput analysis
using the integrated system and methods described in this
invention.
[0026] FIG. 6 shows bar analysis of the data shown in FIG. 4 using
the standard curve constructed in FIG. 5.
[0027] FIG. 7 is an illustration of a qualitative high-throughput
screening of transthyretin (TTR) for posttranslational modification
(PTM) and point mutations (PM) using the integrated system and
methods described in this invention.
[0028] FIG. 8 illustrates identification of the posttranslational
modifications and point mutations observed in the high-throughput
TTR analysis using the integrated system and methods described in
this invention.
[0029] FIG. 9 illustrates the identification of point mutation via
incorporation of derivatized mass spectrometer target platforms in
the system and methods described in this invention.
[0030] FIG. 10 illustrates the use of a high-resolution reflectron
mass spectrometry as part of the integrated system and methods
described in this invention in determining the identity of the
point mutations detected in the analysis of the plasma samples
shown in FIG. 9.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
EXAMPLE 1
An Integrated Mass Spectrometric Immunoassay System
[0031] The present invention provides an integrated system capable
of selectively retrieving and concentrating specific biomolecules
from biological media for subsequent high-performance analyses,
quantifying targeted proteins, recognizing variants of targeted
biomolecules (e.g., splice variants, point mutations and
post-translational modifications) and elucidating their nature,
analyzing for, and identifying, ligands interacting with targeted
biomolecules, and high-throughput screening of large populations of
samples using a single, unified, economical, multiplexed and
parallel processing platform.
[0032] The preferred embodiment of the integrated system comprises
molecular traps, such as affinity microcolumns, derivatized mass
spectrometer targets, mass spectrometers capable of multi-sample
input and robotics with processing/data analysis interactive
database. The present invention also includes methods and processes
for use of the individual components and the integrated system in
biological applications. Furthermore, the preferred embodiment of
the present invention provides for the preparation and/or
processing of multiple separate devices and/or samples to
accomplish high throughput analysis.
[0033] A major component of the system of the present invention is
the isolation or retrieval of specific analytes from their
surrounding biological media in a biological sample. This is
accomplished using a molecular trap. In a preferred embodiment of
the molecular trap, the retrieval process entails repetitively
flowing the biological sample through devices that have affinity
receptors located on surfaces with a high surface area. The
affinity receptors are selected to capture specific analytes, and
can be, e.g., proteins (natural or recombinant), nucleic acids (DNA
or RNA), antibodies, chelators, ion-exchange moieties or low
molecular weight organic or inorganic compounds such as
antibiotics, drugs or enzyme inhibitors. In the high throughput
embodiment, these molecular traps are formed into miniature
columns, affinity microcolumns, thereby allowing numerous molecular
traps to be located side-by-side and taking up minimal amount of
physical volume.
[0034] The molecular trapping process is accomplished by allowing
sufficient physical contact between the affinity receptors located
on the molecular traps and the analyte contained in the biological
sample. The affinity receptors capture, or isolate, the specific
analytes using an affinity interaction between the affinity
receptors and the specific analytes. After the specific analytes
are captured, residual or non-captured compounds are washed free of
the molecular traps using a series of rinses. The capture and rinse
processes result in the concentrating of the specific analytes into
a low volume of the affinity microcolumns.
[0035] After the specific analytes have been captured, they are
eluted from the molecular traps using a small volume of a buffer
capable of disrupting the affinity interaction. The eluted specific
analytes are then stamped directly onto a mass spectrometry target
platform for either mass spectrometry or for further processing,
e.g., enzymatic/chemical modification via utilization of
bioreactive MS target arrays, followed by subsequent preparation
for mass spectrometry. Automated mass spectrometry, preferably
matrix-assisted laser desorption/ionization (MALDI) or electrospray
ionization (ESI) in conjunction with time-of-flight, quadrupole
ion-trap, Fourier transform ion cyclotron resonance (FT-ICR),
magnetic/electric sector, or combinations thereof, mass analyzers,
then follows with either the specific analyte or modified fragments
detected with high precision. Software capable of recognizing
differences between samples, or from a standard, is used to aid in
the analysis and organization into database of the large numbers of
samples.
[0036] The high throughput embodiment of the present invention uses
robotics for serial preparation and parallel processing of a large
number of samples. The use of microcolumns in capturing the
specific analytes enables an arrayed format, as mentioned above,
that is ideal for such high-throughput processing since it
minimizes the physical volume occupied by the microcolumn array.
Use of affinity microcolumns with appropriately configured robotics
allows multiple samples to be prepared, processed, start-to-finish,
simultaneously on a unified platform thereby enabling high
throughput of samples. Specifically, all capture, separation and
elution steps are performed within the microcolumns managed by the
robotics system. This is in contrast to the use of other affinity
capture methods (using, e.g., beaded media) where
mechanical/physical means (e.g., centrifugation, magnetic or vacuum
separation) are used to separate the specific analyte from the
biological fluid and rinse buffers. Oftentimes this physical
separation needs to be performed singularly, resulting in the
disruption of a parallel processing sequence, as well as the
ordering of the array. Because these mechanical/physical means are
not necessary when using the microcolumns, parallel-processing
sequences can be used without disruption and the integrity of an
ordered spatial array is maintained throughout the entire process.
Most conveniently, multiple preparations/analyses are performed
serially and in parallel using robotics fitted to commonly used
spatial arrays, e.g., 4-, 16-, 48-, 96-, 384- or 1536-well
micro-titer plate formats.
[0037] With reference to FIG. 1a the integrated system for
high-throughput analysis of biomolecules from biological media
comprises a prestation wherein pre-analysis processing, such as
preparation of the array of molecular traps, is accomplished. From
the prestation, the array of molecular traps are accessed by an
initiation/reservoir/sample station or relocated to a use station
for sample processing.
[0038] The initiation/reservoir/sample station is where sample
media is located. Preferably, multiple samples are loaded into the
initiation/reservoir/sample station and spatially arranged in an
array commensurate with the array of molecular trap with one sample
for each molecular trap in the array of molecular traps.
[0039] From the initiation/reservoir/sample station, the array of
samples is automatically relocated to a use station. The use
station is where the sample, and specific analytes contained
therein are processed. In one embodiment, one end of the array of
molecular traps is lowered into the sample and sample is drawn into
each molecular trap. Since each molecular trap has affinity reagent
located on surfaces of the molecular trap, drawing the sample into
the molecular trap contacts any specific analyte sought after with
the affinity reagent. Each molecular trap may have different
affinity reagents from that of other molecular traps, thereby
enabling the targeting of different specific analytes from the same
or different media. By drawing sample into the molecular traps,
specific analyte is placed into contact with the affinity reagent,
which, through the affinity interaction, effectively captures the
specific analyte. Sample material may be drawn into the molecular
trap singly or multiple times. After sufficient specific analyte
has been captured by the molecular trap, residual, non-captured,
media are washed away with at least one rinse. (However, other
embodiments may not require a rinse step.) After non-targeted
compounds have been washed away when desired, captured specific
analyte are eluted from the molecular traps by contacting them with
a solution selected to interrupt the affinity interaction. Finally,
the eluted specific analytes are relocated to a target array by
stamping them onto the target array.
[0040] The target array is then automatically relocated to a
storing/loading station that is capable of containing at least one
target array. From the storing/loading station, the target array is
loaded into an automated mass spectrometer capable of multi-sample
input and automatic processing/data analysis using interactive
database.
[0041] Additionally, there may be a post-station for sample
processing or additional analysis subsequent to mass spectrometric
analysis.
[0042] With reference to FIG. 1b, a preferred embodiment of the use
station further comprises a microcolumn manifold to which the array
of molecular traps is attached. The microcolumn manifold attaches
to a robotic head that is able to mechanically draw and expel
biological media, rinses and MS matrices into/out of the attached
microcolumn array. The manifold/robotic head combination is able to
physically move the array of molecular traps between each
processing station to accomplish a selected task, e.g, affinity
isolation from biological media, rinse of extraneous compounds and
deposition of extracted biomolecules for MS analysis. This physical
movement of the microcolumn manifold may be in a rectangular (xy)
or circular (carousel) manner. Alternatively, the microcolumn
manifold in the use station may be stationary and the processing
stations relocated under the array of molecular traps. Similar to
the physical movement of the microcolumn array described above, the
physical movement of the processing stations may be in a
rectangular (xy) or circular (carousel) manner. Additionally, the
microcolumn manifold/robotic head is capable of z-axis movement to
facilitate motion over objects (e.g., titer plates, rinse basins
and MS targets) present on the processing station.
[0043] An example using the integrated system is described
below.
[0044] With reference to FIG. 2, a high-throughput
semi-quantitative analysis of beta-2-microglobulin (.beta..sub.2m)
from human plasma samples using the integrated system and methods
herein was performed. Aliquots of diluted (5 fold) human plasma
samples collected from six individuals were prepared for parallel
screening on a 96-well sample plate. Each well received a 15-.mu.L
plasma aliquot (the samples from the six individuals were
randomized on the 96-well plate), 7.5 .mu.L of equine plasma
(undiluted, containing equine,.beta..sub.2m,
MW.sub.eq..beta.2m=11,396.6, MW.sub.hum..beta.2m=11,729.2) and 128
.mu.L of HBS (0.01 HEPES, pH 7.4, 0.15 M NaCl, 0.005% (v/v)
polysorbate 20, 3 mM EDTA) buffer. Eight of the 96 samples were
chosen at random and 0.5 .mu.L of 10.sup.-2 mg/mL solution of
.beta..sub.2m was added to four of them and 1 .mu.L of the same
.beta..sub.2m solution to the other four wells. Parallel sample
processing entailed simultaneous incubation/capture of the 96
samples on 96 anti-.beta..sub.2m derivitized microcolumns. The
polyclonal anti-.beta..sub.2m microcolumns were made via
carboxymethyl dextran (CMD)-EDC mediated coupling of the antibody
to aminocoated/modified microcolumns. Captured proteins were eluted
from the microcolumns with a small volume of MALDI matrix
(saturated aqueous solution of .alpha.-cyano-4-hydroxycinnamic acid
(ACCA), in 33% (v/v) acetonitrile, 0.2% (v/v) trifluoroacetic acid)
and stamped onto a MALDI target array surface comprised of
self-assembled monolayers (SAM) chemically masked to make
hydrophilic/hydrophobic contrast target arrays. Each sample spot on
the target array was analyzed using mass spectrometry and the
relative .beta..sub.2m abundance determined by an automated
MALDI-TOF mass spectrometric analysis software routine. The mass
spectra resulting from the high-throughput analysis of the 96
samples are shown in FIG. 2. Spectra taken from the samples that
had the .beta..sub.2m standard solution added are shaded.
[0045] With reference to FIG. 3, which is a bar graph analysis of
the data shown in FIG. 2, each spectrum shown in FIG. 2 was
normalized to the equine .beta..sub.2m signal through baseline
integration, and the normalized integral for the human
.beta..sub.2m signal determined. All .beta..sub.2m integrals from
spectra obtained from samples from the same individual were
averaged and the standard deviation calculated. In the same way,
the integrals for the samples spiked with 0.5 and 1.0 .mu.L
solution of 10.sup.-2 mg/mL .beta..sub.2m were calculated and
averaged. Plotted in this figure are the average values of the
normalized human .beta..sub.2m integrals for the samples from the
six individuals and the spiked samples. The bar graph clearly
establishes increased .beta..sub.2m levels in the spiked samples,
illustrating the value of the high-throughput semi-quantitative
analysis performed with the system and methods described in this
invention in establishing increased .beta..sub.2m levels in human
blood that are associated with various disease states.
EXAMPLE 2
High Throughput Protein Quantification in the Presence of
Variants
[0046] With reference to FIG. 4, a high-throughput quantitative
analysis of .beta..sub.2m from human plasma samples was performed
using the integrated system and methods described herein. The
samples from six individuals were prepared as described in FIG. 2.
Eighty-eight wells of the 96-well sample plate received 15 .mu.L
plasma aliquots (the samples from the six individuals were
randomized on the 96-well plate), 7.5 .mu.L of equine plasma
(undiluted) and 128 .mu.L of HBS buffer. A series of dilutions of a
7.6.times.10.sup.-4 mg/mL standard solution of purified human
.beta..sub.2m were prepared (spanning a concentration range of
7.6.times.10.sup.-4 to 1.14.times.10.sup.-4 mg/mL) and used as
samples (15 .mu.L of each) in the last column (8 wells) on the
96-well plate. Parallel sampling processing and MALDI-TOF MS
analysis was performed as described for FIG. 2, using the
polyclonal anti-.beta..sub.2m microcolumns. The mass spectra
resulting from the high-throughput analysis of the 88 samples and
the 8 standards are shown in this figure. Spectra taken from the
standard samples are shaded.
[0047] With reference to FIGS. 5a and 5b, a calibration curve is
constructed from the data for the standard samples shown in FIG. 4.
The calibration curve is for the purpose of determining the
.beta..sub.2m concentrations in the human plasma samples screened
via the high-throughput analysis using the integrated system and
methods described herein. Representative spectra of the data for
each standard used to generate the working curve are shown in FIG.
5a. Each spectrum was normalized to the equine .beta..sub.2m signal
through baseline integration over the m/z range of 11,390-11,410
Da, and normalized integrals for the human .beta..sub.2m signals
(m/z range=11,720-11,740 Da) determined. Integrals from five
spectra taken for each calibration standard were averaged and the
standard deviation calculated. A calibration (standard) curve was
constructed by plotting the average of the normalized integrals for
each standard vs. the human .beta..sub.2m concentration in the
standard sample (adjusted for the human plasma dilution factor).
The working curve generated is shown in FIG. 5b. The concentration
range was spanned with good linearity (R.sup.2=0.999) with overall
standard deviation of the line of <2%.
[0048] With reference to FIG. 6, a bar analysis of the data shown
in FIG. 4 using the standard curve constructed in FIG. 5 is
illustrated. Each spectrum for the 88 samples from FIG. 4 was
normalized to the equine .beta..sub.2m signal through baseline
integration, and the normalized integral for the human
.beta..sub.2m signal determined. Repetitive analyses were performed
for each same individual and were averaged and the standard
deviation calculated. The values of the averaged integrals were
substituted in the equation derived from the standard curve and the
concentration of human .beta..sub.2m was calculated for each
individual. The range of concentrations determined was from 0.75 to
1.25 mg/L. It is essential to note that by excluding mass-shifted
variants (e.g.,+146 Da, due to glycated b2m variant, which is
dysfunctional), that these values indicate the true concentration
of functional b2m present in each individual, rather than the
combined concentration of functional and dysfunctional
variants.
EXAMPLE 3
High Throughput Screening for Genetic and Posttranslational
Variants
[0049] With reference to FIG. 7, a qualitative high-throughput
screening of transthyretin (TTR) for posttranslational modification
(PTM) and point mutations (PM) was performed using the integrated
system and methods described herein. Aliquots of diluted (5-fold)
human plasma samples collected from six individuals were prepared
for parallel screening on a 96-well plate. Each well received a 15
.mu.L plasma aliquot (the samples from the six individuals were
randomized on the 96-well plate), and 135 .mu.L of HBS buffer.
Parallel sampling processing entailed simultaneous
incubation/capture of the 96 samples on 96 anti-TTR derivatized
microcolumns. The polyclonal anti-TTR microcolumns were made via
glutaraldehyde-mediated coupling of the antibodies to
amino-coated/modified microcolumns. Captured proteins were eluted
from the microcolumn array with a small volume of MALDI matrix
(saturated ACCA solution) and stamped onto a MALDI target array
surface comprised of self-assembled monolayers (SAM) chemically
masked to make hydrophilic/hydrophobic contrast targets. Each
sample spot on the target array was analyzed using mass
spectrometry and the relative TTR abundance determined by an
automated MALDI-TOF mass spectrometric analysis software routine.
The mass spectra resulting from the high-throughput analysis of the
96 samples are shown in FIG. 7. In all of the spectra, the TTR
signal is accompanied by another signal at higher mass, indicating
posttranslationally processed TTR form. In addition, all spectra
resulting from the analysis of one plasma sample showed two
additional signals at masses .about.30 Da higher than the two
"original" TTR signal.
[0050] With reference to FIG. 8, identification of the
posttranslational modifications and point mutations observed in the
high-throughput TTR analysis was performed using the integrated
system and methods described herein. Shown are representative
spectra resulting from analysis of samples from two individuals,
showing the existence of two and four TTR signals, respectively. In
the upper spectrum, two signals attributable to TTR are observed.
The signals correspond well to the theoretically calculated mass of
TTR (MW.sub.TTR=13,762) and that of an oxidized TTR variant
(TTR.sub.OX) resulting from cysteinylation at Cys10 (introducing a
mass shift of +119 Da). In the lower spectrum, in addition to the
above-mentioned two TTR signals, two additional peaks at masses
.about.30 Da higher than the two "original" TTR signal are
observed. The identity of the point mutation is described in the
next Example.
EXAMPLE 4
High Throughput Identification of Point Mutations
[0051] With reference to FIG. 9, point mutations were identified by
incorporating protease-derivatized mass spectrometer target array
platforms into the system and using the methods described herein.
The samples used were the same ones utilized for FIG. 8. TTR from
diluted (50-fold, in HBS) human plasma was captured via polyclonal
anti-TTR microcolumns, as described in FIG. 7. Instead of matrix
elution, the captured proteins were eluted with a small volume of
10 mM HCl onto trypsin-conjugated targets containing buffered
target spots (50 mM TRIS buffer pH 9.5) for sample pH modulation
(buffer exchange). Shown in this figure are mass spectra resulting
from a twenty-minute trypsin digest done at 40.degree. C. of the
proteins eluted from the anti-TTR microcolumns. The resulting two
tryptic peptide maps localize the mutation in the tryptic
fragment-12 (T.sub.12), containing residues 104-127. A database
search points to two possible TTR mutations in this region of the
sequence: Ala109.fwdarw.Thr [DNA base change GCC.fwdarw.ACC],
.DELTA.m=30.011 Da, and Thr119.fwdarw.Met [DNA base change
ACG.fwdarw.ATG], .DELTA.m=29.992 Da. The identification of the
correct mutation is shown in FIG. 10.
[0052] With reference to FIG. 10, high-resolution reflectron mass
spectrometry forms a part of the integrated system and methods
described herein in determining the identity of the point mutations
detected in the analysis of the plasma samples shown in FIG. 9. The
monoisotopic signal for the tryptic digest fragment T.sub.12
(104-127) in normal (native) TTR shows at m/z=2644.922, denoting
.DELTA.m=29.988 Da difference with the monoisotopic signal for the
mutant TTR. Accordingly, the point mutations is assigned to
Thr119.fwdarw.Met, .DELTA.m=29.992 Da. This TTR point mutation
results in a so-called "Chicago prealbumin" variant, a non-amyloid
mutation. The results shown in FIGS. 7, 8, 9, and 10 in combination
illustrate the use of the system and the methods described herein
in identifying posttranslational modifications and point mutations
via concerted high-throughput screening analyses of biological
samples.
[0053] The novel features that are considered characteristic of the
invention are set forth with particularity in the appended claims.
The invention itself, however, both as to its structure and its
operation together with the additional objects and advantages
thereof will best be understood from the following description of
the preferred embodiment of the present invention when read in
conjunction with the accompanying drawings. Unless specifically
noted, it is intended that the words and phrases in the
specification and claims be given the ordinary and accustomed
meaning to those of ordinary skill in the applicable art or arts.
If any other meaning is intended, the specification will
specifically state that a special meaning is being applied to a
word or phrase. Likewise, the use of the words "function" or
"means" in the Description of Preferred Embodiments is not intended
to indicate a desire to invoke the special provision of 35 U.S.C.
.sctn.112, paragraph 6 to define the invention. To the contrary, if
the provisions of 35 U.S.C. .sctn.112, paragraph 6, are sought to
be invoked to define the invention(s), the claims will specifically
state the phrases "means for" or "step for" and a function, without
also reciting in such phrases any structure, material, or act in
support of the function. Even when the claims recite a "means for"
or "step for" performing a function, if they also recite any
structure, material or acts in support of that means of step, then
the intention is not to invoke the provisions of 35 U.S.C.
.sctn.112, paragraph 6. Moreover, even if the provisions of 35
U.S.C. .sctn.112, paragraph 6, are invoked to define the
inventions, it is intended that the inventions not be limited only
to the specific structure, material or acts that are described in
the preferred embodiments, but in addition, include any and all
structures, materials or acts that perform the claimed function,
along with any and all known or later-developed equivalent
structures, materials or acts for performing the claimed
function.
* * * * *