U.S. patent application number 15/293517 was filed with the patent office on 2017-02-02 for data independent acquisition of product ion spectra and reference spectra library matching.
The applicant listed for this patent is DH Technologies Development Pte. Ltd., ETH Zurich. Invention is credited to Rudolf Aebersold, Ronald F. Bonner, Ludovic Gillet, Pedro Jose Navarro Alvarez, Lukas Reiter, Oliver Rinner, Stephen A. Tate.
Application Number | 20170032948 15/293517 |
Document ID | / |
Family ID | 44906224 |
Filed Date | 2017-02-02 |
United States Patent
Application |
20170032948 |
Kind Code |
A1 |
Bonner; Ronald F. ; et
al. |
February 2, 2017 |
Data Independent Acquisition of Product Ion Spectra and Reference
Spectra Library Matching
Abstract
Systems and methods are disclosed for analyzing a sample using
overlapping precursor isolation windows. A mass analyzer of a
tandem mass spectrometer is instructed to select and fragment at
least two overlapping precursor isolation windows across a
precursor ion mass range of a sample using a processor. The tandem
mass spectrometer includes a mass analyzer that allows overlapping
precursor isolation windows across the mass range of the
sample.
Inventors: |
Bonner; Ronald F.;
(Newmarket, CA) ; Tate; Stephen A.; (Barrie,
CA) ; Aebersold; Rudolf; (Zurich, CH) ;
Navarro Alvarez; Pedro Jose; (Zurich, CH) ; Rinner;
Oliver; (Zurich, CH) ; Reiter; Lukas; (Wil,
CH) ; Gillet; Ludovic; (Zurich, CH) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
DH Technologies Development Pte. Ltd.
ETH Zurich |
SINGAPORE
Zurich |
|
SG
CH |
|
|
Family ID: |
44906224 |
Appl. No.: |
15/293517 |
Filed: |
October 14, 2016 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H01J 49/0045 20130101;
G16C 20/90 20190201; H01J 49/004 20130101; G01N 30/7233 20130101;
H01J 49/0031 20130101; H01J 49/0036 20130101; H01J 49/42 20130101;
G16C 20/20 20190201; G16B 40/10 20190201 |
International
Class: |
H01J 49/00 20060101
H01J049/00; G01N 30/72 20060101 G01N030/72 |
Foreign Application Data
Date |
Code |
Application Number |
Sep 15, 2010 |
EP |
10009595.9 |
Claims
1. A system for analyzing a sample using overlapping precursor
isolation windows, comprising: a tandem mass spectrometer that
includes a mass analyzer that allows overlapping precursor
isolation windows across a mass range of a sample; and a processor
in communication with the tandem mass spectrometer that instructs
the mass analyzer to select and fragment at least two overlapping
precursor isolation windows across the precursor ion mass range of
the sample.
2. The system of claim 1, wherein the at least two overlapping
precursor isolation windows are overlapped to ensure that all
isotopic forms of a compound are present in at least one precursor
isolation window.
3. The system of claim 1, wherein the at least two overlapping
precursor isolation windows are overlapped to ensure all precursor
ions across the precursor ion mass range are selected.
4. The system of claim 1, wherein each of the at least two
overlapping precursor isolation windows has a width >10 amu.
5. The system of claim 1, wherein the mass analyzer allows
overlapping precursor isolation windows across a mass range of a
sample by moving a single precursor isolation window in a step wise
manner across the mass range with precursor isolation window
overlap between steps, producing consecutive overlapping precursor
isolation windows.
6. The system of claim 5, wherein the precursor isolation window
overlap of the consecutive overlapping precursor isolation windows
is reduced to a minimum value experimentally determined to match a
fragment ion transmission profile achievable by the mass
analyzer.
7. The system of claim 6, wherein the precursor isolation window
overlap of the consecutive overlapping precursor isolation windows
is reduced to the minimum value to maintain a minimal size for the
single precursor isolation window, a minimal number of consecutive
overlapping precursor isolation windows to cover the mass range of
the sample, and a minimal dwell time between cyclic acquisitions of
the mass range of the sample.
8. A method for analyzing a sample using overlapping precursor
isolation windows, comprising: instructing a mass analyzer of a
tandem mass spectrometer to select and fragment at least two
overlapping precursor isolation windows across a precursor ion mass
range of a sample using a processor, wherein the tandem mass
spectrometer includes a mass analyzer that allows overlapping
precursor isolation windows across the mass range of the
sample.
9. The method of claim 8, wherein the at least two overlapping
precursor isolation windows are overlapped to ensure that all
isotopic forms of a compound are present in at least one precursor
isolation window.
10. The method of claim 8, wherein the at least two overlapping
precursor isolation windows are overlapped to ensure all precursor
ions across the precursor ion mass range are selected.
11. The method of claim 8, wherein each of the at least two
overlapping precursor isolation windows has a width >10 amu.
12. The method of claim 8, wherein the mass analyzer selects and
fragments at least two overlapping precursor isolation windows
across the precursor ion mass range of a sample by moving a single
precursor isolation window in a step wise manner across the mass
range with precursor isolation window overlap between steps,
producing consecutive overlapping precursor isolation windows.
13. The method of claim 12, wherein the precursor isolation window
overlap of the consecutive overlapping precursor isolation windows
is reduced to a minimum value experimentally determined to match a
fragment ion transmission profile achievable by the mass
analyzer.
14. The method of claim 13, the precursor isolation window overlap
of the consecutive overlapping precursor isolation windows is
reduced to the minimum value to maintain a minimal size for the
single precursor isolation window, a minimal number of consecutive
overlapping precursor isolation windows to cover the mass range of
the sample, and a minimal dwell time between cyclic acquisitions of
the mass range of the sample.
15. A computer program product, comprising a non-transitory
tangible computer-readable storage medium whose contents include a
program with instructions being executed on a processor so as to
perform a method for analyzing a sample using overlapping precursor
isolation windows, the method comprising: providing a system,
wherein the system comprises one or more distinct software modules,
and wherein the distinct software modules comprise a measurement
module; and instructing a mass analyzer of a tandem mass
spectrometer to select and fragment at least two overlapping
precursor isolation windows across a precursor ion mass range of a
sample using measurement module, wherein the tandem mass
spectrometer includes a mass analyzer that allows overlapping
precursor isolation windows across the mass range of the
sample.
16. The computer program product of claim 15, wherein the at least
two overlapping precursor isolation windows are overlapped to
ensure that all isotopic forms of a compound are present in at
least one precursor isolation window.
17. The computer program product of claim 15, wherein the at least
two overlapping precursor isolation windows are overlapped to
ensure all precursor ions across the precursor ion mass range are
selected.
18. The computer program product of claim 15, wherein each of the
at least two overlapping precursor isolation windows has a width
>10 amu.
19. The computer program product of claim 15, wherein the mass
analyzer selects and fragments at least two overlapping precursor
isolation windows across the precursor ion mass range of a sample
by moving a single precursor isolation window in a step wise manner
across the mass range with precursor isolation window overlap
between steps, producing consecutive overlapping precursor
isolation windows.
20. The computer program product of claim 19, wherein the precursor
isolation window overlap of the consecutive overlapping precursor
isolation windows is reduced to a minimum value experimentally
determined to match a fragment ion transmission profile achievable
by the mass analyzer.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application is a continuation of U.S. patent
application Ser. No. 15/098,196, filed Apr. 13, 2016, which is a
continuation of U.S. patent application Ser. No. 14/741,948, filed
Jun. 17, 2015, now U.S. Pat. No. 9,343,278, which is a continuation
of U.S. patent application Ser. No. 14/329,645, filed Jul. 11,
2014, now U.S. Pat. No. 9,099,288, which is a continuation of U.S.
patent application Ser. No. 13/819,769, filed as Application No.
PCT/IB2011/002139 on Sep. 14, 2011, now U.S. Pat. No. 8,809,770,
which claims the benefit of U.S. Provisional Patent Application No.
61/383,137, filed Sep. 15, 2010 and European Patent Application No.
10009595.9, filed Sep. 15, 2010, the disclosures of which are
incorporated by reference herein in their entireties.
INTRODUCTION
[0002] Mass Spectrometry has been used for many years to identify
and quantitate compounds in complex mixtures. Typical compounds can
include, but are not limited to, proteins, peptides, pharmaceutical
compounds, and derivatives such as metabolites, drugs of abuse,
pesticides, etc. A common mass spectrometry technique is tandem
mass spectrometry. In tandem mass spectrometry a precursor ion is
selected by a mass analyzer, fragmented in some way and the
fragments analyzed in a second mass analyzer or in a second scan of
the first analyzer. The fragments produced can be used for
identification or quantitation.
[0003] A common technique for quantitation is selected reaction
monitoring (SRM). SRM has been used for a long while to quantitate
small molecules and more recently has been applied to peptides,
proteins, and other biological compounds such as lipids and
carbohydrates. SRM is typically performed on a triple quadrupole
instrument, where the first and second mass analyzers have a mass
isolation peak width of about 0.7, and one or more combinations of
precursor and fragment masses (known as transitions) are monitored
during a liquid chromatography coupled to mass spectrometry (LC-MS)
analysis.
[0004] Despite its sensitivity and robustness, SRM has, at least,
the following issues that limit its application:
[0005] 1. The compounds to be measured must be defined prior to
data acquisition and the transitions to be monitored must be
determined, either from empirical fragment spectra of the compounds
of interest or from libraries of such spectra.
[0006] 2. The information obtained is incomplete since the number
of transitions, and thus compounds that can be measured during a
single analysis is limited for a number of reasons. The
chromatographic peak must be well defined since quantitation is
based on the height or area of peaks in the chromatograms of the
transitions, i.e. a plot of the response for the transition vs.
time. Thus it is necessary to keep the time spent measuring a set
of transitions as low as possible. The sensitivity (the smallest
amount of material that can be detected) depends on the length of
time (the dwell time) spent monitoring a transition so better
sensitivity takes more time meaning that fewer compounds can be
analyzed. Confidence that the correct compound has been identified
usually requires that several transitions be measured and the
responses compared to those expected from the standard spectrum.
This is particularly true if the mass transmission windows are
relatively wide so that in complex mixtures one or more precursors
or fragments could be selected at the same time and interfere with
measurement of the target fragment ion(s). Precise and accurate
quantitation requires inclusion of an authentic standard material,
typically an isotopically labeled form of the target compound,
which generates different transitions that can be distinguished
from the target compound; these must also be monitored thus
reducing the overall number of compounds that can be analyzed.
[0007] 3. Further, the data available is limited to that defined
before the analysis is performed. Therefore, it is often necessary
to re-analyze the sample to generate additional data, if different
or additional transitions must be monitored to improve the accuracy
of confidence of the quantitation, or if additional data is
required to detect different compounds or modified forms of the
target compounds.
[0008] 4. Since only a limited number of compounds can be analyzed
at one time, obtaining data for all the compounds present in a
sample requires many separate analyses.
[0009] One alternative acquisition method alternates scans with
high and low fragmentation that are then processed to determine the
precursors (low energy) and fragments (high energy) that belong
together. Quantitation based on ion traces extracted from this data
(similar to SRM) is prone to interferences since in complex
mixtures many ions can be fragmented at the same time.
[0010] Other alternative acquisition methods select small mass
windows that are stepped across a mass range of interest, but
complete coverage of the entire mass range requires numerous
analyses and takes a considerable amount of time.
[0011] Thus there is a tradeoff between the number of compounds
that can be analyzed in the same analysis, and hence the sample
throughput if complete coverage is required, the sensitivity, and
the likelihood of detecting interferences that degrade the
quantitation behavior.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] The skilled artisan will understand that the drawings,
described below, are for illustration purposes only. The drawings
are not intended to limit the scope of the present teachings in any
way.
[0013] FIG. 1 is a block diagram that illustrates a computer
system, upon which embodiments of the present teachings may be
implemented.
[0014] FIG. 2 is a schematic diagram showing how data is acquired
for a complete mass range using step-wise precursor ion selection
windows of a mass analyzer, in accordance with various
embodiments.
[0015] FIG. 3 is an exemplary plot showing the mass traces
extracted from the ion traces of FIG. 2 for fragments determined
from a reference spectra library, in accordance with various
embodiments.
[0016] FIG. 4 is a schematic diagram showing a system for storing
an electronic record of all product ion spectra of all detectable
compounds of a sample, in accordance with various embodiments.
[0017] FIG. 5 is an exemplary flowchart showing a method for
storing an electronic record of all product ion spectra of all
detectable compounds of a sample, in accordance with various
embodiments.
[0018] FIG. 6 is a schematic diagram of a system that includes one
or more distinct software modules that performs a method for
storing an electronic record of all product ion spectra of all
detectable compounds of a sample, in accordance with various
embodiments.
[0019] Before one or more embodiments of the present teachings are
described in detail, one skilled in the art will appreciate that
the present teachings are not limited in their application to the
details of construction, the arrangements of components, and the
arrangement of steps set forth in the following detailed
description or illustrated in the drawings. Also, it is to be
understood that the phraseology and terminology used herein is for
the purpose of description and should not be regarded as
limiting.
DESCRIPTION OF VARIOUS EMBODIMENTS
Computer-Implemented System
[0020] FIG. 1 is a block diagram that illustrates a computer system
100, upon which embodiments of the present teachings may be
implemented. Computer system 100 includes a bus 102 or other
communication mechanism for communicating information, and a
processor 104 coupled with bus 102 for processing information.
Computer system 100 also includes a memory 106, which can be a
random access memory (RAM) or other dynamic storage device, coupled
to bus 102 for storing instructions to be executed by processor
104. Memory 106 also may be used for storing temporary variables or
other intermediate information during execution of instructions to
be executed by processor 104. Computer system 100 further includes
a read only memory (ROM) 108 or other static storage device coupled
to bus 102 for storing static information and instructions for
processor 104. A storage device 110, such as a magnetic disk or
optical disk, is provided and coupled to bus 102 for storing
information and instructions.
[0021] Computer system 100 may be coupled via bus 102 to a display
112, such as a cathode ray tube (CRT) or liquid crystal display
(LCD), for displaying information to a computer user. An input
device 114, including alphanumeric and other keys, is coupled to
bus 102 for communicating information and command selections to
processor 104. Another type of user input device is cursor control
116, such as a mouse, a trackball or cursor direction keys for
communicating direction information and command selections to
processor 104 and for controlling cursor movement on display 112.
This input device typically has two degrees of freedom in two axes,
a first axis (i.e., x) and a second axis (i.e., y), that allows the
device to specify positions in a plane.
[0022] A computer system 100 can perform the present teachings.
Consistent with certain implementations of the present teachings,
results are provided by computer system 100 in response to
processor 104 executing one or more sequences of one or more
instructions contained in memory 106. Such instructions may be read
into memory 106 from another computer-readable medium, such as
storage device 110. Execution of the sequences of instructions
contained in memory 106 causes processor 104 to perform the process
described herein. Alternatively hard-wired circuitry may be used in
place of or in combination with software instructions to implement
the present teachings. Thus implementations of the present
teachings are not limited to any specific combination of hardware
circuitry and software.
[0023] The term "computer-readable medium" as used herein refers to
any media that participates in providing instructions to processor
104 for execution. Such a medium may take many forms, including but
not limited to, non-volatile media, volatile media, and
transmission media. Non-volatile media includes, for example,
optical or magnetic disks, such as storage device 110. Volatile
media includes dynamic memory, such as memory 106. Transmission
media includes coaxial cables, copper wire, and fiber optics,
including the wires that comprise bus 102.
[0024] Common forms of computer-readable media include, for
example, a floppy disk, a flexible disk, hard disk, magnetic tape,
or any other magnetic medium, a CD-ROM, digital video disc (DVD), a
Blu-ray Disc, any other optical medium, a thumb drive, a memory
card, a RAM, PROM, and EPROM, a FLASH-EPROM, any other memory chip
or cartridge, or any other tangible medium from which a computer
can read.
[0025] Various forms of computer readable media may be involved in
carrying one or more sequences of one or more instructions to
processor 104 for execution. For example, the instructions may
initially be carried on the magnetic disk of a remote computer. The
remote computer can load the instructions into its dynamic memory
and send the instructions over a telephone line using a modem. A
modem local to computer system 100 can receive the data on the
telephone line and use an infra-red transmitter to convert the data
to an infra-red signal. An infra-red detector coupled to bus 102
can receive the data carried in the infra-red signal and place the
data on bus 102. Bus 102 carries the data to memory 106, from which
processor 104 retrieves and executes the instructions. The
instructions received by memory 106 may optionally be stored on
storage device 110 either before or after execution by processor
104.
[0026] In accordance with various embodiments, instructions
configured to be executed by a processor to perform a method are
stored on a computer-readable medium. The computer-readable medium
can be a device that stores digital information. For example, a
computer-readable medium includes a compact disc read-only memory
(CD-ROM) as is known in the art for storing software. The
computer-readable medium is accessed by a processor suitable for
executing instructions configured to be executed.
[0027] The following descriptions of various implementations of the
present teachings have been presented for purposes of illustration
and description. It is not exhaustive and does not limit the
present teachings to the precise form disclosed. Modifications and
variations are possible in light of the above teachings or may be
acquired from practicing of the present teachings. Additionally,
the described implementation includes software but the present
teachings may be implemented as a combination of hardware and
software or in hardware alone. The present teachings may be
implemented with both object-oriented and non-object-oriented
programming systems.
Systems and Methods of Data Processing
[0028] As described above, in traditional mass spectrometry methods
there is a tradeoff between the number of compounds that can be
analyzed in the same analysis and the sensitivity and the
likelihood of detecting interferences that degrade the quantitation
behavior.
[0029] Thus there is a need for a method that provides a complete
record of all detectable compounds present in a complex mixture
that can be used to quantitate known compounds, determine and
quantitate modified forms of the known compounds, or to determine
the type and location of unknown modification. Further, the record
should be stored so that these operations can be performed at the
time that data is acquired or at some later time. Such a record
enables the complete analysis of all compounds that can be detected
with the separation device and mass spectrometer system used.
[0030] This method allows dynamic quantitative target transitions
and modified forms of the target compounds (such as metabolites or
post-translational modifications) to be determined without
re-acquiring data on the sample.
[0031] In various embodiments, systems and methods provide a method
for generating a record of all detectable compounds and comprise a
novel combination of a data acquisition method that generates the
fragment spectra of all compounds and targeted data analysis
methods.
[0032] Current selected reaction monitoring (SRM) methodology
requires lengthy preparatory work to devise the method prior to the
sample injection (including the reference spectra library
generation); it allows monitoring transitions of a limited number
of peptides per injection; it requires extensive data analysis by
reference library matching to confirm the identity of the peptides
monitored; and it requires new data acquisition to improve
quantification accuracy (by replacing contaminated transitions by
new ones) and/or to expand the quantification to new transitions
and/or analytes not monitored in the original data set.
[0033] In various embodiments, systems and methods address the
current limitations of the SRM approach and enable the probing of
entire proteomes iteratively and recursively from a single sample
injection. Although these systems and methods address the current
limitations of the SRM approach, they are not limited in any way to
SRM or the type of experiments for which SRM is applied. These
systems and methods comprise a combination of a novel LC-MS
acquisition set-up together with a bioinformatic pipeline for the
data analysis. Details of various embodiments are presented
below:
Method Set-Up
[0034] Contrary to SRM, various embodiments do not require any
preliminary method design prior to the sample injection. Since the
LC-MS acquisition can cover the complete analyte content of a
sample across the recorded mass and retention time ranges (see
below), the data can be mined a posteriori for any compound of
interest. The retention time and mass ranges may be set to generate
information for ranges of particular interest.
LC-MS Acquisition Method
[0035] In various embodiments an acquisition method covers all
compounds detectable with the chromatography and mass range used;
these can be broad and generic to detect as many compounds as
possible or can be adjusted to focus on compounds or types of
compounds of particular interest. A wide window of precursor ions,
for example >10, >15, >20 amu, is selected and fragmented
to generate a fragment spectrum of all precursor present in the
window. The window is moved in a step wise manner to cover the rest
of the precursor space, for example, with a window width of 25 amu
the first window may cover 100-125, the second 125-150, the third
150-175, and so on.
[0036] The windows can be overlapped to make sure that all the
isotopic forms of a compound are present together in at least one
window. It is beneficial for the windows to have relatively square
shapes so that overlap can be kept small and minimize the number of
windows required.
[0037] Thus the time required to acquire data for the entire mass
range depends on the number of and accumulation time of windows and
not the number of precursors to be fragmented. The time is short
enough to maintain the fidelity of peaks produced by the
separation.
[0038] Generating product ion spectra for the entire mass range is
repeated one or more times depending on whether a separation system
is used. A mass spectrum of all unfragmented precursor ions can be
included as part of the cycle. All of the acquired data is stored
for later mining. The width of the windows can be constant or can
be varied.
[0039] FIG. 2 is a schematic diagram 200 showing how data is
acquired for a complete mass range using step-wise precursor ion
selection windows of a mass analyzer, in accordance with various
embodiments. Diagram 200 depicts an LC-MS method in which a data
independent acquisition of full fragment ion spectra is obtained by
panning isolation windows of a mass analyzer, step by step, across
the entire mass range 220 repeatedly during an entire
chromatography 230. Diagram 200 is an LC-MS map, for example. Note
that the dotted line before the beginning of each cycle in diagram
200 depicts the optional acquisition of a high-resolution, accurate
mass survey (MS1) scan that can also be used to re-associate the
fragment ions to the precursor they originate from, if needed for
the analysis processes.
[0040] The data of diagram 200 can be interpreted by combining the
product ion spectra acquired for each isolation window into
separate MS2 maps. MS2 map 240 is an exemplary combination of all
the product ion spectra for isolation window 210. MS2 map 240
includes ion traces 250 plotted as a function of mass over charge
(m/z), retention time and signal intensity. Symbol 260 identifies
ion traces 250 of fragments belonging to corresponding analytes.
Symbol 270 identifies ion traces 250 of fragments determined from a
reference spectra library.
[0041] FIG. 3 is an exemplary plot 300 showing the mass traces
extracted from the ion traces of FIG. 2 for fragments determined
from a reference spectra library, in accordance with various
embodiments.
[0042] In various embodiments, an LC-MS acquisition method
comprises the monitoring of product ions resulting from the
fragmentation of ion precursors as follows:
Complete Content Coverage For All the Analytes of a Sample:
[0043] 1) Data independent acquisition upon stepping of the
isolation window of the mass analyzer:
[0044] Instead of monitoring a few discrete precursors/transitions
per run, MS information is acquired in a data independent manner,
on the full mass range and through the entire chromatography,
irrespective of the content of the sample. In various embodiments,
this can be achieved by stepping the precursor ion selection window
of the mass analyzer step by step through the complete mass range
(see FIG. 2), instead of focusing on pre-determined or targeted
precursors. The cycle time (or dwell time) of these measurements is
thus determined by the number of steps necessary to cover the
complete mass range (FIG. 2) rather than by the number of
transitions to be monitored as in SRM. Such step-wise,
data-independent fragmentation measurements allow the acquisition
of the complete information on the analytes/precursors contained in
a sample in one single run. In effect, this data acquisition method
can generate a complete fragment ion map for all the analytes
present in the sample and relate the fragment ion spectra back to
the precursor ion selection window in which the fragment ion
spectra were acquired.
[0045] 2) Widening of the selection window of the first mass
analyzer:
[0046] 2a) It is almost impossible, even at the narrowest selection
window achievable by the mass analyzer, to ensure that only the
precursor of interest, free of contaminants, is selected for
fragmentation. Therefore, in various embodiments, an opposite
approach is used: widening the precursor isolation windows of the
mass analyzer and thus including multiple precursors co-eluting and
contributing to the fragmentation pattern recorded during the
analysis. The interpretation of complex product ion spectra
resulting from multiple precursors' fragmentation is described
below in the data analysis section.
[0047] 2b) Collateral positive effects of widening the selection
window of the mass analyzer as practiced in various embodiments,
are (i) the shortening of the cycle time mentioned in point (1) and
thus the acquisition of better defined and resolved chromatographic
elution profiles for the precursors monitored; and (ii) an
increased signal intensity for the fragments since the entire
isotopic pattern of the precursor now participates in the
fragmentation, and not only the mono-isotopic peak as in SRM.
Gain in Confidence for the Peptide Identifications:
[0048] 3) Acquisition of full product ion spectra, instead of
monitoring a few product ions for a given precursor as in classical
SRM experiments. A series of full product ion (MS2) spectra is
acquired across the elution of a precursor allowing better
confidence in the precursor identification to be achieved by
matching the complete fragmentation pattern of a full MS2 spectra
to a reference spectrum from a library, rather than a few ion
fragments.
[0049] In summary, in various embodiments an LC-MS method results
in the acquisition of a series of MS2 maps that can cover the
complete mass range and chromatographic profile and that can be
processed as pseudo-SRM traces acquired on wide isolation windows
(FIGS. 2-3) instead of few transitions per precursor.
[0050] Consecutive MS2 maps may be acquired with some precursor
isolation window overlap to ensure transfer of the complete
isotopic pattern of any given precursor ion in at least one
isolation window and thereby to maintain optimal correlation
between parent and fragment isotopes peaks at any LC time point.
This overlap may be reduced to a minimum value, which can be
experimentally determined to best match the fragment ion
transmission profile achievable on the ion selection devices used
in the mass spectrometer. Reducing the overlap between consecutive
isolation windows allows to maintain a minimal size for the
windows, a minimal number of windows to cover a given m/z range and
a minimal dwell time between the cyclic isolation window
acquisitions.
[0051] Various embodiments include the following MS acquisition
methods in various combinations; and alone and together with
various combinations of the data analyses principles described
further below:
[0052] 1) The cyclic acquisition of full fragmentation (MS2)
spectra of precursor ions upon stepping the precursor isolation
window of the mass analyzer in a content-independent manner (see
FIG. 2). The acquisition does not include, e.g., focusing the
precursor isolation windows onto the masses of pre-determined
(e.g., data dependent acquisition/shotgun) or targeted (e.g.,
inclusion lists or SRM) precursor ions.
[0053] 2) The deliberate search of these MS2 spectra for multiple
parent precursors concomitantly selected within the parent ion
precursor isolation windows and concomitantly participating in the
observed fragmentation pattern, by various embodiments of the
inventions described in the data analysis section. In other words,
in various embodiments a search is not conducted for the precursor
ions. A search is conducted for the fragments in the window that is
expected to contain the precursor ion.
[0054] 3) The use of overlapping windows for the precursor
selection.
[0055] Overlapping windows can be used in various embodiments to
insure (i) that all the precursor ions are properly selected, even
in the case of non-ideal mass analyzers and (ii) that the percursor
ions at the border of the mass analyzer/selection windows get their
whole or substantially whole isotopic pattern selected for
fragmentation within a same isolation window.
[0056] 4) The use of fixed and/or variable widths for the precursor
isolation windows during the same acquisition run. In various
embodiments, fixed and/or variable widths are used for the
precursor isolation windows during the same cycle (i.e., set of
scans across the mass range. The use of larger windows allows for
the shortening of the cycle time of the acquisition in the less
crowded parts of the mass/chromatographic space (i.e., where the
least number of analytes are expected). The use of a narrower
window can allow for an increased dynamic range of analysis in the
most complex parts of the mass/chromatographic space. Indeed,
narrower windows contain fewer precursor ions to fragment and
therefore have lower chance to include precursors with large
differences in abundances.
[0057] 5) The use of single and/or multiple (variable or discrete)
collision energies per precursor selection windows during the same
acquisition run. The increasing or decreasing fragment ion
intensities acquired during such multiple collision energy
experiments can be checked for co-elution and correlated to
reference fragment ion intensities from spectra libraries and can
strengthen the identification of fragment ion peak groups that
originate from the same parent ion (see the data analysis
section).
[0058] 6) The use offixed and/or variable time per precursor
isolation windows for the acquisition of the MS2 spectra during the
same acquisition run. Since the signals can be reported as counts
over acquisition time (e.g., cts/msec), the variable acquisition
time can still be used for quantification purposes (as in "dynamic"
or "scheduled" SRM). Longer acquisition times can allow the
monitoring of low abundant precursors with more sensitivity.
Various Embodiments Concerning the Bioinformatics/Data Analysis
Pipeline
[0059] The data analysis comprises the use of fragment ion elution
information and data mining of reference spectra libraries.
Reference spectra libraries of proteotypic peptides (MS-observable
peptides uniquely found in one protein and therefore qualitatively
and quantitatively unambiguously characterizing that protein) may
be generated for entire organisms using pools of synthetic peptides
(Picotti et al, Nat Methods 2010) and/or from prior extensive MS
sequencing proteomic analyses performed on those organisms.
Similarly, the reference spectra libraries of other analytes may be
generated from synthetic analyte references and/or from prior
analytes MS analyses. Importantly, once the reference fragment ion
libraries have been generated they can be used perpetually.
[0060] Since the LC-MS data comprises full product ion spectra
acquired from wide precursor selection windows, the data processing
is modified to account for multiple precursors potentially
participating in the fragmentation patterns observed in the
recorded MS2 spectra and for the presence of all fragment ions.
Searching for Precursors a Posteriori
[0061] Contrary to the SRM approach, where the precursors of
interest have to be selected prior to the sample injection, a
"complete content coverage" acquisition approach enables one to
search and quantify, a posteriori in the LC-MS/MS dataset, and in
various embodiments any analyte present in the spectra library. The
data analysis comprises the extraction of the fragment mass traces
(determined from the reference spectra library and/or from in
silico predictions) of the precursor of interest from a series of
full product ion spectra acquired in the expected selection window
(m/z) of that precursor (see FIGS. 2-3).
[0062] The confidence in the precursor identification can be
scored, for example, based on the mass accuracy and/or the relative
intensities of the acquired product ion fragments compared to that
of the reference (or predicted) fragmentation spectrum, on the
number of matched fragments, on the similar chromatographic
characteristics (co-elution, peak shape, etc.) of the extracted ion
traces of these fragments. Probabilities for the identifications
can be determined, for example, by searching (and scoring)
similarly for decoy precursor fragment ions from the same LC-MS
dataset. The relative quantification can be performed by
integration of the product ions traces across the chromatographic
elution of the precursor. In various embodiments, use is made of
differently isotopically labeled reference analytes (similarly
identified, quantified and scored) to achieve absolute
quantification of the corresponding precursors of interest.
Gain in Confidence for the Peptide Identifications:
[0063] A series of full product ion (MS2) spectra can be extracted
around the elution of the best scoring fragment ion peak group
candidates to achieve better confidence in the precursor
identification by matching the complete fragmentation pattern of a
full MS2 spectrum to a reference spectrum from a library, rather
than a few ion fragments.
[0064] The data mining strategy described above uses an unbiased
extraction, from the LC-MS/MS dataset, of reference fragment ion
traces (from spectra libraries). The full product ion maps are,
therefore, mined for the identification of multiple precursors,
since those are extracted with fragment ion traces of independent
matches from the library. Therefore this does not restrict the
search number of precursors co-eluting within the selection window
of the mass analyzer and can allow for the identification of
multiple precursors within the same product ion spectra.
Alternative Data Processing by MS2 Feature Extraction
[0065] Another data processing embodiment comprises a de novo
feature extraction of all or substantially all of the fragment ion
signals from the reconstituted MS2 maps (FIG. 2). The co-eluting
fragment ion signals can then be grouped and searched by reference
spectra library matching (or eventually against a database of
pre-computed theoretical fragment ions of analytes) to determine
their precursor(s) of origin. In various embodiments, the method
proceeds by iteration of precursor identification and subtraction
of the product ion signals of that precursor across its elution to
increase the sensitivity of the analysis and uncover ion fragments
of precursors of lower abundances.
[0066] Various embodiments include the following data analysis
principles in various combinations; and alone and together with
various combinations of the MS acquisitions principles described
further above:
[0067] 1) The extraction of the fragment mass traces (determined
from the reference spectra library or from in silico predictions)
of the precursor of interest from the series of full product ion
spectra acquired in the expected selection window (or windows, for
modified or multiple charge states peptides) of that precursor (see
FIGS. 2-3)
[0068] 2) The identification of the analytes by scoring the
extracted fragment ion traces based on parameters such as, for
example: (i) co-elution of the extracted fragment ion traces, (ii)
correlation of their peak shapes, (iii) correlation of their
relative intensities with those from a reference spectra library
(or from in silico predictions), (iv) proximity to the expected
reference chromatographic retention time, (v) co-elution and peak
shape correlation of the fragment ion traces of multiple charge
states of the same precursor, (vi) co-elution, peak shape and
relative intensity correlation with the fragment ion traces of one
or more differently isotopically labeled reference(s) (e.g., heavy
or light reference analyte for a light or an heavy endogenous
sample respectively), (vii) co-elution and peak shape correlation
of the fragment ion traces obtained from the windows acquired at
various collision energies, (viii) correlation of the relative
intensities of the fragments ions obtained from the windows
acquired at various collision energies with those a reference
spectra library (or from in silico predictions), and (ix)
combinations of two or more of the above.
[0069] 3) The discrimination of true from false positives
identifications by false discovery rate evaluation upon searching
(and scoring) similarly the same LC-MS/MS dataset for decoy
precursor fragment ions. The decoy hits can substantially be used
to optimize the combination of one or more of the scores mentioned
above using machine learning techniques (e.g., semi-supervised
learning) and to estimate a false discovery rate by assuming that
they resemble the null distribution of identifications.
[0070] 4) The use of the co-eluting fragment ion intensities to
quantify the identified analytes contained in the sample.
[0071] 5) The "refinement" and the re-searching (e.g., in multiple
iterations) of the acquired data by substantially removing, across
their chromatographic elution, the contaminated fragment ion traces
or those of already identified analytes.
[0072] 6) The extraction of pre-computed theoretical fragment mass
traces of any precursor of interest from the series of full product
ion spectra acquired in the expected selection window (or windows,
for modified or multiple charge states peptides) of that precursor
(e.g., for the acquisition and refinement of spectra libraries of
natural or synthetic compounds)
[0073] 7) The de novo "feature extraction" of the fragment ion
signals from the reconstituted MS2 maps (FIG. 2); the grouping and
scoring of those fragment ion signals as, e.g., described above
(point 2); the searching of those by reference spectra library
matching (or eventually against a database of pre-computed
theoretical fragment ions of analytes) to determine their
precursor(s) of origin; the quantification of the identified
analytes based on their co-eluting fragment ion intensities.
[0074] In summary, various embodiments can allow for (i) the
exhaustive acquisition of the product ion spectra of all analytes
present in a sample, in a single LC-MS injection or analysis, (ii)
the complete identification and quantitative analysis of those by a
specific data mining strategy, and (iii) the refinement and/or
complementation of those analyses by iterative data mining. This
combined LC-MS acquisition and data processing methodology
constitutes therefore a significant improvement over the
traditional approach in terms of data consistency, identification
rates and quantification speed. These inventions enable the
acquisition of complete proteome maps and the methods for the
qualitative and quantitative data mining of those.
[0075] The potential applications of these inventions are
essentially the same as those of SRM quantitative proteomics and
include any biotechnical, biomedical, pharmaceutical and biological
applications that rely on qualitative and quantitative LC-MS
analysis. The approaches are, for example, in various embodiments
particularly suited to perform the analysis of a high number of
candidate precursors (e.g., peptides) of interest in complex
samples that may be available only in limited amounts (e.g.,
complete organisms, cells, organs, bodily fluids, etc.).
[0076] Various embodiments include the following applications,
among others: [0077] Rapid acquisition and refinement of spectra
libraries of natural or synthetic compounds (e.g., peptides).
[0078] Qualitative and quantitative analysis of natural or
synthetic compounds of interest (e.g., in the context of specific
analytes or biomarkers measurements, or to analyze the composition
of protein complexes). [0079] Qualitative and quantitative analysis
of naturally or artificially modified analytes that share fragment
ions with their non-modified counter-parts (e.g., proteins/peptides
with post-translational modifications, reacted with activity-based
probes, or chemically cross-linked proteins/peptides), or whose
modification share fragment ions (e.g., ubiquitin or ubiquitin-like
molecules) or common reporter ions or by using the (positive or
negative) mass difference that this modification brings to the
fragment ions of those analytes. [0080] Qualitative and
quantitative analysis of all detectable analytes present in spectra
libraries or de novo identified (see data analysis section) (e.g.,
in the context of partial or complete proteome analyses). [0081]
The capacity to refine and/or complement of those qualitative and
quantitative analyses by iterative data mining of the acquired
datasets.
[0082] These various embodiments can pave the way for the complete
qualitative and quantitative analysis of entire metabolome/proteome
of complex samples and in a high throughput manner.
Quantitative Data Processing
[0083] In various embodiments, all of the fragment data acquired
from a single precursor mass window can be processed together. Even
though the data may contain fragments from one or more precursor
ions (compounds), it can be processed to quantitate the compound of
interest or search for modified forms of such compounds.
[0084] The precursor mass of the compound of interest and a set of
expected fragments at high resolution and mass accuracy are
obtained from a library, or by analyzing an authentic standard form
of the compound, or obtained from a previous analysis (whether the
compounds are known or not), or by prediction using known
fragmentation rules. The set of fragments can be selected based on
their expected intensity, the likelihood that that they are unique
to the compound of interest, or other features. For the window(s)
containing the expected precursor mass, the set of fragment masses
are used to generate ion traces, for example chromatograms, that
include one or more peaks
[0085] The traces are scored to determine the correct or most
likely peak. The score can be based on information from the mass
spectrum such as: how well the detected mass of the sample fragment
ions match the expected masses of the predetermined product ions;
how well the relative intensities of the sample fragment ions match
the relative intensities of the predetermined product ions; that
the measured sample ions are in the correct isotopic form, usually
that they are monoisotopic; that the precursor and fragment ions
have the expected charge state.
[0086] If a separation step is included, the score can be based on
additional information such as: how well the detected ion traces
match each other in shape and position. If different isotopic forms
of the sample are analyzed, such as a combination of labeled and
native forms, data from the different forms can be used to further
refine the score. If one or more fragments in the set receive poor
scores because there is an interference, they can be excluded from
the set and, if desired, replaced with another fragment from the
predetermined spectrum.
[0087] Ions that receive acceptable scores can be used to generate
quantitative values for the target compound that can be compared to
similar values from other samples, such as members of a time course
study, groups of samples that have been treated or prepared
differently, groups of samples from healthy or diseased subjects,
etc. As all fragment ions from all detected precursor exist in the
data, in various embodiments optimal quantitation can be performed
by using alternative fragment ions which reduce error in
measurement.
[0088] Since the acquired data includes fragments from all
detectable compounds, it can be mined for any number of compounds
and the scoring can generate quantitative values.
Qualitative Data Processing
[0089] In various embodiments, the data can be further mined to
extract qualitative information about the compounds present in the
sample. Modified forms can be detected by locating the same set of
fragment ions at unexpected retention times in the same precursor
window or in different windows, for example. The window can be
determined based on the expected mass difference caused by the
modification. In various embodiments, modified forms can be
detected by locating ions that are characteristic of the
modification.
[0090] Once a modified form is detected the type and location of
the modification can be determined in a number of ways. For
example, the type and location of the modification can be
determined by predicting ions that depend on the position or type
of the modification and generating and scoring traces extracted
from the data for those predicted masses. In various embodiments,
the type and location of the modification can be determined by
generating a spectrum from the data and interpreting that
spectrum.
[0091] Further, the data from each window can be processed to
determine or identify related ions and thereby extract the spectrum
of known or unknown compounds that can be interpreted to determine
the identity of the compound.
Tandem Mass Spectrometry System
[0092] FIG. 4 is a schematic diagram showing a system 400 for
storing an electronic record of all product ion spectra of all
detectable compounds of a sample, in accordance with various
embodiments. System 400 includes tandem mass spectrometer 410 and
processor 420. Processor 420 can be, but is not limited to, a
computer, microprocessor, or any device capable of sending and
receiving control signals and data from mass spectrometer 410 and
processing data.
[0093] Tandem mass spectrometer 410 can include one or more
physical mass analyzers that perform two or more mass analyses. A
mass analyzer of a tandem mass spectrometer can include , but is
not limited to, a time-of-flight (TOF), quadrupole, an ion trap, a
linear ion trap, an orbitrap, or a Fourier transform mass analyzer.
Tandem mass spectrometer 410 can also include a separation device
(not shown). The separation device can perform a separation
technique that includes, but is not limited to, liquid
chromatography, gas chromatography, capillary electrophoresis, or
ion mobility. Tandem mass spectrometer 410 can include separating
mass spectrometry stages or steps in space or time,
respectively.
[0094] Tandem mass spectrometer 410 performs a plurality of product
ion scans one or more times across a mass range using a plurality
of mass selection windows. The plurality of product ion scans are
performed in a single sample analysis. A single sample analysis is,
for example, a single sample injection. From the plurality of
product ion scans, tandem mass spectrometer 410 produces all sample
product ion spectra of all detectable compounds for each mass
selection window.
[0095] Processor 420 is in communication with tandem mass
spectrometer 410. Processor 420 receives all the sample product ion
spectra for each mass selection window from tandem mass
spectrometer 410. Processor 420 then stores all sample product ion
spectra for each mass selection window as an electronic record of
all detectable compounds of the sample. The electronic record is
used to characterize compounds known at the time the electronic
record is stored or to characterize compounds that became known
after the electronic record was stored.
[0096] In various embodiments, each mass selection window of the
plurality of mass selection windows has a width greater than 10
atomic mass units (amu), or a width greater than 15 amu.
[0097] In various embodiments, at least two mass selection windows
of the plurality of mass selection windows have different
widths.
[0098] In various embodiments, all sample product ion spectra for
one or more mass selection windows from the electronic record are
searched for predetermined product ion spectra from a reference
library. For example, processor 420 receives predetermined product
ion spectra corresponding to known compounds. Processor 420
receives all sample product ion spectra for one or more mass
selection windows from the electronic record. Processor 420 then
compares predetermined product ions of the predetermined product
ion spectra to sample product ions of said all sample product ion
spectra for one or more mass selection windows. One or more
matching sample product ions from the comparison characterize the
known compounds detectable in the sample. The known compounds
include, for example, any compound that gives reproducible product
ion spectra.
[0099] In various embodiments, the known compounds include one or
more of peptides, proteins, complete proteomes, endogenous
metabolites, lipids, or carbohydrates.
[0100] In various embodiments, the known compounds include one or
more compounds of biological, pharmaceutical, environmental,
forensic, or industrial importance. The one or more compounds of
biological, pharmaceutical, environmental, forensic, or industrial
importance can include, but are not limited to, one or more of
pesticides, herbicides, fungicides, industrial chemicals, drugs of
abuse, dopants or explosives.
[0101] In various embodiments, the predetermined product ion
spectra are computationally generated by applying empirical or a
priori fragmentation or modification rules to the known
compounds.
[0102] In various embodiments, the predetermined product ion
spectra are obtained from the analysis of authentic standard
compounds, either isolated from a naturally occurring source or
chemically synthesized.
[0103] In various embodiments, the predetermined product ion
spectra are obtained from public or proprietary spectral
libraries.
[0104] In various embodiments, the predetermined product ion
spectra are obtained from a prior analysis of a representative
sample with or without identification of compounds corresponding to
the predetermined product ion spectra.
[0105] In various embodiments, the search for predetermined product
ion spectra from a reference library includes calculating a score.
For example, processor 420 compares predetermined product ions of
the predetermined product ion spectra to sample product ions of all
sample product ion spectra for one or more mass selection windows
by calculating a score that represents how well the predetermined
product ions and the sample product ions match. The score can, for
example, can include comparing ion masses and relative intensities.
In various embodiments, the score includes determining that the
sample precursor ion has the expected isotopic form. In various
embodiments, the score can include information on the expected
charge state of the precursor and fragment ions.
[0106] In various embodiments, a separation device separates sample
compounds of the single sample analysis over time. Tandem mass
spectrometer 410 performs a plurality of product ion scans on the
single sample analysis as the sample compounds are being separated.
In various embodiments, processor 420 further calculates a score
for the match based on comparing peak shapes of ion traces or
detection time similarity of matching sample product ions.
[0107] In various embodiments, processor 420 further uses one or
more matching sample product ions from the comparison of the search
to calculate a quantitative value for compounds of the sample. The
quantitative value is, for example, calculated using an intensity
of the one or more matching sample product ions in the sample
product ion spectra. In various embodiments, the quantitative value
is calculated using an intensity or areas of one or more matching
ion trace peaks.
[0108] In various embodiments, processor 420 further uses one or
more matching sample product ions from the comparison of the search
to identify a modified form of one or more compounds of the known
compounds. A modified form is identified by finding the one or more
matching sample product ions in the same mass selection window or
in different mass selection windows, for example. A different mass
selection window is determined from the mass of an expected
modification, for example.
[0109] In various embodiments, the modified form is identified by
finding a mass corresponding to the one or more matching sample
product ions adjusted by the mass of a modification. The
modification is a known modification, is caused by known reactions,
or is suggested by other experiments, for example.
[0110] In various embodiments, the modified form is identified by
finding a mass characteristic of modified parts of the known
compounds.
[0111] In various embodiments, the modified form is identified by
finding complex composite spectra from conjoined molecules.
[0112] In various embodiments, processor 420 further extracts a
spectrum of an identified modified form from the electronic record
in order to characterize a type and location of the modification in
the identified modified form.
[0113] In various forms, processor 420 further uses the
predetermined product ions and the modification to predict masses
that would indicate the site of the modification and generates a
score for each said mass to determine the location of the
modification.
Tandem Mass Spectrometry Method
[0114] FIG. 5 is an exemplary flowchart showing a method 500 for
storing an electronic record of all product ion spectra of all
detectable compounds of a sample, in accordance with various
embodiments.
[0115] In step 510 of method 500, a plurality of product ion scans
are performed on a tandem mass spectrometer one or more times in a
single sample analysis across a mass range using a plurality of
mass selection windows. All sample product ion spectra of all
detectable compounds for each mass selection window are
produced.
[0116] In step 520, all sample product ion spectra for each mass
selection window are received from the tandem mass spectrometer
using a processor.
[0117] In step 530, all sample product ion spectra for each mass
selection window are stored as an electronic record of all
detectable compounds of the sample using the processor. The
electronic record is used to characterize compounds known at the
time the electronic record is stored or to characterize compounds
that became known after the electronic record was stored.
Tandem Mass Spectrometry Computer Program Product
[0118] In various embodiments, a computer program product includes
a tangible computer-readable storage medium whose contents include
a program with instructions being executed on a processor so as to
perform a method for storing an electronic record of all product
ion spectra of all detectable compounds of a sample. This method is
performed by a system that includes one or more distinct software
modules.
[0119] FIG. 6 is a schematic diagram of a system 600 that includes
one or more distinct software modules that performs a method for
storing an electronic record of all product ion spectra of all
detectable compounds of a sample, in accordance with various
embodiments. System 600 includes a measurement module 610 and a
storage module 620.
[0120] Measurement module 610 receives from a tandem mass
spectrometer all sample product ion spectra of all detectable
compounds for each mass selection window of a mass range. The
tandem mass spectrometer produces the sample product ion spectra by
performing a plurality of product ion scans one or more times in a
single sample analysis across the mass range using a plurality of
mass selection windows.
[0121] Storage module 620 stores all sample product ion spectra for
each mass selection window as an electronic record of all
detectable compounds of the sample. The electronic record is used
to characterize compounds known at the time the electronic record
is stored or to characterize compounds that became known after the
electronic record was stored.
[0122] While the present teachings are described in conjunction
with various embodiments, it is not intended that the present
teachings be limited to such embodiments. On the contrary, the
present teachings encompass various alternatives, modifications,
and equivalents, as will be appreciated by those of skill in the
art.
[0123] Further, in describing various embodiments, the
specification may have presented a method and/or process as a
particular sequence of steps. However, to the extent that the
method or process does not rely on the particular order of steps
set forth herein, the method or process should not be limited to
the particular sequence of steps described. As one of ordinary
skill in the art would appreciate, other sequences of steps may be
possible. Therefore, the particular order of the steps set forth in
the specification should not be construed as limitations on the
claims. In addition, the claims directed to the method and/or
process should not be limited to the performance of their steps in
the order written, and one skilled in the art can readily
appreciate that the sequences may be varied and still remain within
the spirit and scope of the various embodiments.
* * * * *