Patent Description:
Conventional mass spectrometric analysis may be performed blindly such as top-n (n most intense, least intense) Data Dependent Acquisition ("DDA"), MSE, HDMSE or SWATH Data Independent Acquisition ("DIA").

Alternatively, conventional mass spectrometric analysis may be performed in a targeted manner through Data Dependent Acquisition inclusion or exclusion lists which require prior knowledge of the elution time and mass to charge ratio of the targeted compounds.

McQueen et al. (D1) is concerned with information-dependent LC-MS/MS acquisition with exclusion lists potentially generated on-the-fly.

<CIT> (D2) is concerned with data-dependent acquisition by mass spectrometry.

Crowell at al. (D3) is concerned with increasing confidence of LC-MS identifications by utilizing ion mobility spectrometry.

It is desired to provide an improved method of mass spectrometry.

According to an aspect there is provided a method of mass spectrometry as claimed in claim <NUM>.

In embodiments, the method may further comprise updating the target list so as to no longer select precursor or parent ions which are associated with previously identified parent compounds and/or may comprise updating the target list to select precursor or parent ions which are not associated with previously identified parent compounds.

In embodiments, the method may further comprise processing the target list and generating an initial time line, e.g. for the multiple cycles of operation. The method may further comprise sorting target ions by chromatographic retention or elution time and/or the intensity of the A<NUM> molecular ion of each charge group. The step of generating the initial time line may further comprise using peptide ionisation rank information. The step of generating the initial time line may further comprise prioritizing higher ionizing peptides from lower molecular weight proteins.

Each cycle of operation includes mass filtering the parent ions based on the target list so that selected ions having mass to charge ratios within a first mass to charge ratio range are onwardly transmitted to a fragmentation or reaction device. Each cycle of operation may further include fragmenting or reacting the selected ions in or within the fragmentation or reaction device so as to form fragment or product ions. Each cycle of operation includes obtaining parent ion and/or fragment or product ion mass spectral data. The step of comparing or checking the target list involves comparing or checking the target list based on the ion mass spectral data. The step of comparing or checking the target list may further include identifying parent compounds using ion mass spectral data.

In embodiments, the target list may further comprise a predicted fragmentation pattern derived from a model. The model may include at least one of: a mass to charge ratio model; a chromatographic retention or elution time model; an ion mobility drift time model; and a fragmentation model.

In embodiments, each cycle of operation may further include separating and/or selecting parent ions and/or fragment or product ions according to their ion mobility. The method may further comprise adjusting a first ion mobility drift time range used to select parent ions and/or fragment or product ions and/or adjusting the width of a first ion mobility drift time range used to select parent ions and/or fragment or product ions in response to the updated model.

In embodiments, the model may be updated based on at least one of: a derived relationship between (i) modelled chromatographic retention or elution times and (ii) operational or experimental chromatographic retention or elution times; and a derived relationship between (i) modelled ion mobility drift times and (ii) operational or experimental ion mobility drift times. The derived relationship may be derived using a line of best fit (e.g. least squares).

According to an embodiment there is provided a system and method for the simultaneous acquisition of both global and highly-selective targeted mass spectrometry analysis of the entire component complement of both simple and complex mixtures.

The method may utilize enhanced modelling of the physicochemical attributes of biomolecules in conjunction with the increased peak capacity afforded by highly orthogonal workflows encompassing very high pressure liquid chromatography separations, high ion transfer, ion mobility and increased mass resolution using either a hybrid DDA/MSE or a HD-DDA/HD-MSE acquisition strategy.

According to an example workflow target compounds for proteomics analysis are input as a. fasta file of the proteome or proteins of interest as well as the enzyme used for enzymatic degradation.

According to an example workflow target compounds for small molecules such as metabolites and lipids are input as a. xml file optionally including a description and elemental composition.

Additional information may be included such as the gradient length, gradient slope, buffer composition, column type, mass resolving power and ion mobility separation ON/OFF. The additional information may be presented as input into a "Simulator" which comprises a series of modelling algorithms producing a target component list containing each compound predicted elution time, mass to charge ratio values (isotopes and charge groups) and cross-sectional area if ion mobility separation is employed.

The targeted list drives which ions are selected as well as the width of the isolation window during the Data Dependent Acquisition phase of a hybrid acquisition. Included in the embedded acquisition computer are the complete precursor and product ion envelopes for each predicted compound.

Upon completion of the Data Dependent Acquisition phase of a hybrid acquisition, the acquired ion list may be compared against that of the targets and if validated the chromatographic retention time and ion mobility drift time models are recalculated and the ion selection windows in mass to charge ratio, chromatographic retention time and ion mobility drift time may be adjusted accordingly.

The on-the-fly tuning of the attribute modelling algorithms allows for ever increasing precision in predicting the location of the targeted compounds in the impending three dimensional space of mass to charge ratio, chromatographic retention time and ion mobility drift time.

It will be understood that mass to charge ratio, cross-sectional area (and with respect to reverse phase chromatography hydrophobicity) are all physico-chemical constants.

The three-dimensional space between any pair of known compounds should be predictable and as such may be utilised to both validate identity and re-order, re-structure or amend the look-up table for future precursor ion selection.

According to an embodiment the target list may be continually updated to select upcoming precursor ions not associated with previously identified parent compounds. In the example of a proteomics experiment of, for example, a total cellular extract or a bio-fluid there are many known proteins whose peptides can be used as molecular beacons for the on-the-fly tuning of the modelling algorithm.

Given that the proteins in these experiments have been digested with an enzyme of known selectivity, then the algorithm may know with increasing precision where each previously identified protein's companion peptides will elute in chromatographic retention time and/or ion mobility drift time and chromatographic retention time. This continuing knowledge allows the algorithm to recurrently update the lookup table to ensure the greatest depth of coverage with respect to validating the presence of the proteins on the targeted include list while still spending enough time in the global HD-MSE (ion mobility) mode of acquisition for accurate area-under-the-curve quantification. Once the targeted proteins have been identified, the global HD-MSE data along with the highly accurate prediction models for ion mobility drift time and chromatographic retention time may be exploited to maximize sequence coverage as well as to query for known chemical or post-translational modifications or possible sequence variants.

According to another aspect there is provided a mass spectrometer as claimed in claim <NUM>.

According to an embodiment the mass spectrometer may further comprise:.

The mass spectrometer may further comprise either:.

According to an embodiment the mass spectrometer further comprises a device arranged and adapted to supply an AC or RF voltage to the electrodes. The AC or RF voltage may have an amplitude selected from the group consisting of: (i) < about <NUM> V peak to peak; (ii) about <NUM>-<NUM> V peak to peak; (iii) about <NUM>-<NUM> V peak to peak; (iv) about <NUM>-<NUM> V peak to peak; (v) about <NUM>-<NUM> V peak to peak; (vi) about <NUM>-<NUM> V peak to peak; (vii) about <NUM>-<NUM> V peak to peak; (viii) about <NUM>-<NUM> V peak to peak; (ix) about <NUM>-<NUM> V peak to peak; (x) about <NUM>-<NUM> V peak to peak; and (xi) > about <NUM> V peak to peak.

The AC or RF voltage may have a frequency selected from the group consisting of: (i) < about <NUM>; (ii) about <NUM>-<NUM>; (iii) about <NUM>-<NUM>; (iv) about <NUM>-<NUM>; (v) about <NUM>-<NUM>; (vi) about <NUM>-<NUM>; (vii) about <NUM>-<NUM>; (viii) about <NUM>-<NUM>; (ix) about <NUM>-<NUM>; (x) about <NUM>-<NUM>; (xi) about <NUM>-<NUM>; (xii) about <NUM>-<NUM>; (xiii) about <NUM>-<NUM>; (xiv) about <NUM>-<NUM>; (xv) about <NUM>-<NUM>; (xvi) about <NUM>-<NUM>; (xvii) about <NUM>-<NUM>; (xviii) about <NUM>-<NUM>; (xix) about <NUM>-<NUM>; (xx) about <NUM>-<NUM>; (xxi) about <NUM>-<NUM>; (xxii) about <NUM>-<NUM>; (xxiii) about <NUM>-<NUM>; (xxiv) about <NUM>-<NUM>; and (xxv) > about <NUM>.

The mass spectrometer may also comprise a chromatography or other separation device upstream of an ion source. According to an embodiment the chromatography separation device comprises a liquid chromatography or gas chromatography device. According to another embodiment the separation device may comprise: (i) a Capillary Electrophoresis ("CE") separation device; (ii) a Capillary Electrochromatography ("CEC") separation device; (iii) a substantially rigid ceramic-based multilayer microfluidic substrate ("ceramic tile") separation device; or (iv) a supercritical fluid chromatography separation device.

The ion guide may be maintained at a pressure selected from the group consisting of: (i) < about <NUM> mbar; (ii) about <NUM>-<NUM> mbar; (iii) about <NUM>-<NUM> mbar; (iv) about <NUM>-<NUM> mbar; (v) about <NUM>-<NUM> mbar; (vi) about <NUM>-<NUM> mbar; (vii) about <NUM>-<NUM> mbar; (viii) about <NUM>-<NUM> mbar; and (ix) > about <NUM> mbar.

According to an embodiment analyte ions may be subjected to Electron Transfer Dissociation ("ETD") fragmentation in an Electron Transfer Dissociation fragmentation device. Analyte ions may be caused to interact with ETD reagent ions within an ion guide or fragmentation device.

According to an embodiment in order to effect Electron Transfer Dissociation either: (a) analyte ions are fragmented or are induced to dissociate and form product or fragment ions upon interacting with reagent ions; and/or (b) electrons are transferred from one or more reagent anions or negatively charged ions to one or more multiply charged analyte cations or positively charged ions whereupon at least some of the multiply charged analyte cations or positively charged ions are induced to dissociate and form product or fragment ions; and/or (c) analyte ions are fragmented or are induced to dissociate and form product or fragment ions upon interacting with neutral reagent gas molecules or atoms or a non-ionic reagent gas; and/or (d) electrons are transferred from one or more neutral, non-ionic or uncharged basic gases or vapours to one or more multiply charged analyte cations or positively charged ions whereupon at least some of the multiply charged analyte cations or positively charged ions are induced to dissociate and form product or fragment ions; and/or (e) electrons are transferred from one or more neutral, non-ionic or uncharged superbase reagent gases or vapours to one or more multiply charged analyte cations or positively charged ions whereupon at least some of the multiply charge analyte cations or positively charged ions are induced to dissociate and form product or fragment ions; and/or (f) electrons are transferred from one or more neutral, non-ionic or uncharged alkali metal gases or vapours to one or more multiply charged analyte cations or positively charged ions whereupon at least some of the multiply charged analyte cations or positively charged ions are induced to dissociate and form product or fragment ions; and/or (g) electrons are transferred from one or more neutral, non-ionic or uncharged gases, vapours or atoms to one or more multiply charged analyte cations or positively charged ions whereupon at least some of the multiply charged analyte cations or positively charged ions are induced to dissociate and form product or fragment ions, wherein the one or more neutral, non-ionic or uncharged gases, vapours or atoms are selected from the group consisting of: (i) sodium vapour or atoms; (ii) lithium vapour or atoms; (iii) potassium vapour or atoms; (iv) rubidium vapour or atoms; (v) caesium vapour or atoms; (vi) francium vapour or atoms; (vii) C<NUM> vapour or atoms; and (viii) magnesium vapour or atoms.

The multiply charged analyte cations or positively charged ions may comprise peptides, polypeptides, proteins or biomolecules.

According to an embodiment in order to effect Electron Transfer Dissociation: (a) the reagent anions or negatively charged ions are derived from a polyaromatic hydrocarbon or a substituted polyaromatic hydrocarbon; and/or (b) the reagent anions or negatively charged ions are derived from the group consisting of: (i) anthracene; (ii) <NUM>,<NUM> diphenyl-anthracene; (iii) naphthalene; (iv) fluorine; (v) phenanthrene; (vi) pyrene; (vii) fluoranthene; (viii) chrysene; (ix) triphenylene; (x) perylene; (xi) acridine; (xii) <NUM>,<NUM>' dipyridyl; (xiii) <NUM>,<NUM>' biquinoline; (xiv) <NUM>-anthracenecarbonitrile; (xv) dibenzothiophene; (xvi) <NUM>,<NUM>'-phenanthroline; (xvii) <NUM>' anthracenecarbonitrile; and (xviii) anthraquinone; and/or (c) the reagent ions or negatively charged ions comprise azobenzene anions or azobenzene radical anions.

According to an embodiment the process of Electron Transfer Dissociation fragmentation comprises interacting analyte ions with reagent ions, wherein the reagent ions comprise dicyanobenzene, <NUM>-nitrotoluene or azulene.

According to an example workflow target compounds for proteomics analysis are input as a. fasta file of the proteome or proteins of interest as well as the enzyme used for enzymatic degradation in a manner as shown in <FIG>.

Target compounds for small molecules such as metabolites and lipids may be input as a. xml file optionally including a description and elemental composition.

Additional information may be included such as the gradient length, gradient slope, buffer composition, column type, mass resolving power, and whether ion mobility separation is ON/OFF. The data may be input into the "Simulator" which may comprise a series of modelling algorithms which produces a target component list containing each compound predicted chromatographic elution time tr, mass to charge ratio values (isotopes and charge groups) and optionally also cross-sectional area if ion mobility separation ("IMS") is employed.

The targeted list drives which ions are selected as well as the width of the isolation window during a Data Dependent Acquisition portion of a hybrid acquisition. Included in the embedded acquisition computer are the complete precursor and product ion envelopes for each predicted compound.

Upon completion of a Data Dependent Acquisition portion of a hybrid acquisition, the acquired ion list may be compared against that of the targets and if validated the chromatographic retention time and ion mobility drift time models are recalculated and the ion selection windows in mass to charge ratio, retention and drift time may be adjusted accordingly.

The on-the-fly tuning of the attribute modelling algorithms allows for ever increasing precision in predicting the location of the targeted compounds in the impending three dimensional space of mass to charge ratio, chromatographic retention time tr and ion mobility drift time td.

It will be understood that mass to charge ratio and cross-sectional area (and with respect to reverse phase chromatography hydrophobicity) are physico-chemical constants.

The three-dimensional space between any pair of known compounds should be predictable and as such may be utilised to both validate identity and re-order, re-structure or amend a look-up table for future precursor ion selection.

According to an embodiment the target list may be continually updated to select upcoming precursor ions not associated with previously identified parent compounds. In the example of a proteomics experiment of, for example, a total cellular extract or a bio-fluid there will be many known proteins whose peptides can be used as molecular beacons for the on-the-fly tuning of the modelling algorithm.

Given that the proteins in these experiments have been digested with an enzyme of known selectivity, then the algorithm according to an embodiment may know with increasing precision where each previously identified protein's companion peptides will elute in chromatographic retention time and/or ion mobility drift time and chromatographic retention time. This continuing knowledge allows the algorithm to recurrently update the lookup table to ensure the greatest depth of coverage with respect to validating the presence of the proteins on the targeted include list while still spending enough time in a global HD-MSE (ion mobility) mode of acquisition for accurate area-under-the-curve quantification. Once the targeted proteins have been identified, the global HD-MSE data along with the highly accurate prediction models for ion mobility drift time and chromatographic retention time may be exploited to maximize sequence coverage as well as to query for known chemical or post-translational modifications or possible sequence variants.

For small molecule applications like lipids or metabolites the input may be a formatted *. opa file which optionally includes a name, description, elemental composition and if known, charge-state(s) and fragmentation pattern(s).

For a proteomics experiments the input may comprise a *. fasta file containing the target protein(s) sequence(s).

Various retention-time prediction models for different types of biological compounds are known.

A prediction model for chromatographic retention time and ion mobility drift time, isotope and charge distributions, fragmentation pathways, product ion coverage, ionization efficiency and n-linked glycosylation's for similar classes of biological compounds has been developed.

The targeting file as well as a number of user defined inputs (e.g. gradient slope and length, on-column load, IMS on/off and mass resolving power etc.) may be inputted into the "Simulator" and a target list may be generated.

The targeted list may then be processed by the "Scheduler". The "Scheduler" may generate an initial time line for intelligent time-based acquisition. Target ions may be sorted by retention-time (ascending) and intensity of the A<NUM> isotope (descending) of each charge group (ionization and charge distribution models).

The "Scheduler" may attempt to maximize the number of proteins that can be identified per unit time by restricting which peptides of a protein can be targeted in a given time interval. The peptide ionization model in the "Simulator" annotates each peptide to a protein with its ionization index number (best-to-least). Given that the best chance of identifying a protein in a complex sample is to select for targeted analysis it's best ionizing peptide, the "Scheduler" uses each peptides' ionization rank to assist in the creation of the initial time line. The "Scheduler" also takes into consideration the number of peptides generated from each protein and may prioritize the higher ionizing peptides from lower molecular weight proteins given that the number of opportunities for targeted selection is limited. Placement on the initial time line does not guarantee targeted selection only the opportunity for selection as such the time line or targeted list has to be dynamic.

This can be accomplished utilizing a number of different embodiments. According to an embodiment this may be accomplished on-the-fly where the product ion spectra of the target compounds resides in the acquisition computer internal to the mass analyzer.

According to an embodiment this may be accomplished by acquisition intervals where the product ion spectra of the target compounds resides on a second processing computer.

With respect to acquisition intervals the processing algorithm may start after a user or algorithmically defined time interval has passed. According to an embodiment in an automated fashion the processing software may wait until <NUM>/<NUM>th of the gradient elution time has passed. The data may then be extracted and processed. Validated target peptides are then used for updating the chromatographic retention time, ion mobility drift time and fragmentation models. Regardless of the variation in change of each predicted attribute (initial model to nth iteration) the models may be continually updated with each time block.

The constant re-modeling according to an embodiment corrects for any variations in temperature, pump performance, mixing or any other gradient creations problems that may arise during the analysis.

The targeted list resides both in the acquisition computer internal to the mass analyzer and external in the processing computer. Once updated the internal targeted ion list may be updated and transmitted back to the acquisition computer. Given the lack of elemental variability in biomolecules there will exist instances where a targeted ion is not what was predicted regardless of the accuracy of the models' prediction. Understanding that time is critical in maximizing the selectivity of targeting, and in some experiments ion mobility separation is not employed in precursor ion selection prior to Data Dependent Acquisition, in an example hybrid workflow ion mobility separation is employed in the MS1 channel (survey Data Dependent Acquisition, low-energy DIA) as such the processing algorithm first looks at the drift time associated to the selected precursor if the drift time is within the match window the product ion spectra are compared for validation else the processing algorithm moves on to the next targeted precursor. In instances where there is no ion mobility separation employed the processing algorithm compares all product ion spectra for every targeted precursor against its predicted compound.

<FIG> shows details of the "Simulator" including the input of mass spectrometry parameters, liquid chromatography parameters and a target compound list.

<FIG> shows the mass to charge ratio versus chromatographic retention time tr relating to <NUM>,<NUM> peptides from <NUM> yeast proteins.

<FIG> shows the mass to charge ratio versus chromatographic retention time tr relating to a single protein GRP78. Ions having a <NUM>+, <NUM>+ and <NUM>+ charge state are indicated.

<FIG> shows the mass to charge ratio versus simulated chromatographic retention time and <FIG> shows the mass to charge ratio versus experimental chromatographic retention time.

<FIG> shows a least squares fit of experimental chromatographic retention time versus simulated chromatographic retention time.

<FIG> shows a least squares fit of experimental ion mobility drift time versus simulated ion mobility drift time.

<FIG> shows a plot of mass to charge ratio versus corrected simulated ion mobility drift time. <FIG> shows a plot of mass to charge ratio versus corrected simulated chromatographic retention time.

It is noted that the corrected simulated data as shown in <FIG> exhibits a better correlation between mass to charge ratio and chromatographic retention time than the initial simulated data shown in <FIG>. In particular, the data shown in <FIG> now passes through the origin and the range of chromatographic retention times has been lengthened.

<FIG> shows a plot of mass to charge ratio versus corrected simulated ion mobility drift time and <FIG> shows a plot of mass to charge ratio versus corrected simulated chromatographic retention time wherein the plots are limited to the five best ionizing A<NUM>.

It is apparent from comparing <FIG> and from comparing <FIG> that limiting to the five best ionizing A<NUM> ions results in a further significant improvement in predicting or modeling the relationship between expected chromatographic retention time and expected ion mobility drift time and mass to charge ratio.

<FIG> shows z-distribution and ionisation model updates from matched sequences of mass to charge ratio, chromatographic retention time tr, ion mobility drift time td and charge state z.

<FIG> shows how the elution time may be segmented into user defined or algorithmically derived time blocks. During Time Block <NUM> (<NUM>-<NUM> mins) there are <NUM> mass to charge values from <NUM> proteins. Restricting the intact protein molecular weight MW range to <NUM>-<NUM> kDa limits the set to <NUM> target ions from <NUM> proteins.

During Time Block <NUM> (<NUM>-<NUM> mins) there are <NUM> mass to charge values from <NUM> proteins. Restricting the intact protein molecular weight MW range to <NUM>-<NUM> kDa limits the set to <NUM> target ions from <NUM> proteins. At this point <NUM> proteins and their associated mass to charge ratios are removed since two peptides to each protein have already been validated.

In the <NUM>-<NUM> minute time block <NUM> Heat Shock proteins were identified and validated and their remaining peptides were removed from the time line.

<FIG> illustrates the matched data and shows how the top three Heat Shock Proteins which were identified match corresponding target proteins.

Claim 1:
A method of mass spectrometry comprising:
ionising a sample eluting from a separation device in order to generate a plurality of parent ions;
generating a target list of ions, wherein said target list comprises a predicted mass to charge ratio and at least one of: a predicted chromatographic retention or elution time; and a predicted ion mobility drift time, cross-sectional area or other data relating to ion mobility, derived from a model;
performing multiple cycles of operation as said sample elutes from said separation device, wherein each cycle of operation includes:
mass filtering said parent ions based on said target list so that selected ions having mass to charge ratios within a first mass to charge ratio range are onwardly transmitted to a fragmentation or reaction device;
obtaining parent ion and/or fragment or product ion mass spectral data;
comparing or checking said target list based on the ion mass spectral data and updating said model based on said comparing or checking; and
adjusting said first mass to charge ratio range that is used to select ions for onward transmission to said fragmentation or reaction device and adjusting the width of said first mass to charge ratio range that is used to select ions for onward transmission to said fragmentation or reaction device in response to said updated model.