Systems and methods of analysis of isobaric tagging experiments

Abstract

There is provided methods and systems of quantification of isobaric tagging experiments. A provided method comprises: obtaining a first set of mass spectrometry data of a sample, wherein the sample comprises a plurality of isobarically labelled analytes, determining, from the first set of mass spectrometry data, a respective predicted mass of a complementary ion of a selected isobarically labelled analyte of the plurality of isobarically labelled analytes, obtaining mass spectrometer output of a fragmented portion of the sample, said portion containing the selected isobarically labelled analyte, applying a windowed super resolution algorithm to the mass spectrometer output to generate a second set of mass spectrometry data, wherein the window of the windowed super resolution algorithm is determined based on the predicted mass of the complementary ion, and quantifying the analyte present in the sample from the second set of mass spectrometry data.

Description

[0001] SYSTEMS AND METHODS OF ANALYSIS OF ISOBARIC TAGGING EXPERIMENTS

[0002] Field of the invention

[0003] The present disclosure relates to improved systems and methods of analysis of isobaric tagging experiments, such as quantification in complementary ion techniques.

[0004] Background of the invention

[0005] The use of mass tags (also termed mass labels) that are cleavably attached to an associated molecule of interest has proven to be a powerful technique for chemical analysis using mass spectrometry. The tags are typically used for the identification and quantification of biological macromolecules, such as proteins, peptides and nucleic acids. The approach of using Tandem Mass Tags, marketed as TMT or iTRAQ (Isobaric Tagging for Relative Quantitation), is described in WO01 / 68664 and Thompson et al Anal. Chem. 2003, 75, 1895- 1904. A TMT label is composed of four moieties, a mass reporter, a cleavable linker, a balancer, and a protein reactive group. The chemical structures of all the tags are identical but each contains isotopes substituted at various positions, such that the mass reporter and balancer moieties have different molecular masses in each tag. The combined moieties of the tags have the same total molecular weights and structure so that during chromatographic or electrophoretic separation and in single MS mode, molecules labelled with different tags are indistinguishable. In a typical MS / MS experiment a TMT labeled precursor ion upon fragmentation would typically cleave at the cleavable linker yielding the reporter ions from which quantification data can be derived.

[0006] An important modification to the TMT method is TMT complementary ion quantification (Johnson et al, J. Proteome Res., 2021 , 20, 3043-3052). Here, rather than quantifying from the reporter ions, the tagged peptide minus the reporter ion is generated at a low fragmentation energy and is measured. After separation of the reporter, the tag still contains a “balancer” component, which normally serves to equilibrate the mass of all tagged ions, but without the reporter component this creates a mirrored distribution of complementary ion channels. These channels may have relative intensities similar to the reporter ion distribution, and so may be used for quantitation. An advantage is that because they still have the original peptide attached, they are more robust to interferences from co-isolated peptides. The cost however is that as the complementary ion is much heavier than the reporter, but with the same mass difference between channels, vastly higher resolution is required to resolve the channels. Whilst this has been achieved for 8 channel TMT methods with 1 Da spacing, the equivalent 16 channel spacing, that requires 50K resolution normally, might easily require 500K resolution if applied to an ion ten-times heavier. Figure 1 a shows the TMTPro family of TMT type isobaric labels, along with the formation of the TMT reporter ion and the complementary ion, and the effect of an interferent coisolated peptide, both on the reporter ion intensities which are artificially inflated, and the generation of additional complementary ions.

[0007] Typically, isobaric labelling experiments (such as TMT experiments) are run using Fourier transform mass spectrometry (FTMS) analyzers, such as Orbitrap™ FT instruments, which excel at delivering high resolution at low masses (or mass-to-charge ratios). However, the acquisition time required to achieve such resolution restricts the acquisition rate and limits the number of measurements. In FT mass spectrometry, the mass resolution is inversely proportional to the square root of the mass-to-charge (m / z) value and proportional to the acquisition time. As such, in the case of TMTc experiments in order to resolve the much heavier complementary ions longer acquisition times are needed, often making it impractical for coupling with chromatographic separation. Therefore, current applications are limited to TMTc ions separated by 1 Da, which drastically limits the degree of multiplexing. Figure 1 b shows an example of the of TMTc m / z spectral region acquired on the Exploris 480 Orbitrap system, at the resolution settings of 240 and 480K at mass 200 (corresponding to transient lengths of 512ms and 1000ms respectively) failing to achieve the baseline resolution. As such, it can be seen from the labels outlined in figure 1 a out of 12 possible TMTpro complementary ions only 8 channels can be used.

[0008] Summary of the invention

[0009] It is an object of the present disclosure to overcome some of the limitations of existing isobaric tagging analysis techniques described above.

[0010] In particular, the present disclosure provides a method of analysing Fourier transform mass spectrometry data of isobaric tagging experiments that allows targeted super resolution techniques to be applied to low resolution mass spectrometry data to allow resolving of complementary ion regions. It has been realized by the inventors that by specifically targeting the application of super resolution techniques using appropriate windows low resolution mass spectrometry data may still be used to disambiguate reporter ion intensities based on the presence of complementary ions.

[0011] In a first aspect there is provided a method of quantification for an isobaric tagging experiment. The method comprises obtaining a first set of mass spectrometry data (such as a mass spectrum) of a sample, wherein the sample comprises a plurality of isobarically labelled (or tagged) analytes; determining, from the first set of mass spectrometry data, a respective predicted mass of a complementary ion of a selected isobarically labelled analyte of the plurality of isobarically labelled analytes; obtaining mass spectrometer output (sucha as a transient or transient signal) of a fragmented portion of the sample, said portion containing the selected isobarically labelled analyte; and applying a windowed super resolution algorithm (such as phase-constrained spectral deconvolution algorithm) to the mass spectrometer output to generate a second set of mass spectrometry data, wherein the window of the windowed super resolution algorithm is determined based on the predicted mass of the complementary ion. The method may further comprise quantifying the analyte present in the sample from the second set of mass spectrometry data (such as determining the relative abundance and or an amount of the analyte present in the sample). Typically each isobarically labelled analyte is labelled with a respective isobaric mass tag. The isobaric mass tag may be any one of: a tandem mass tag; an mTRAQ tag; an iTRAQ tag; a SILAC tag; or a Metal-coded Affinity Tag (MeCAT).

[0012] The complementary ion usually comprises a balancer region of the isobaric tag attached to the selected analyte.

[0013] The super resolution algorithm may be arranged (for example by selection of suitable parameters and / or transient length) such that peaks having a separation of 0.01 Da are resolved in the second mass spectrometry data. In some cases the threshold of resolution may be set lower than 0.01 Da, such as 0.001 Da.

[0014] In some embodiments obtaining a first set of mass spectrometry data of a sample comprises operating a mass spectrometer to generate the first set of mass spectrometry data of the sample, and obtaining mass spectrometer output of a fragmented portion of the sample comprises: fragmenting a portion of the sample, the portion containing said analyte; and generating mass spectrometer output of the fragmented portion of the sample.

[0015] In some embodiments the portion of the sample containing the analyte comprises ions selected from the sample having a mass within a range the including mass of the isobarically labelled analyte.

[0016] The method may be used as part of DDA process. For example, the method may further comprise: selecting one or more further isobarically labelled analytes of the plurality of isobarically labelled analytes. Where for each further isobarically labelled analyte, the method comprises determining, from the first set of mass spectrometry data, a respective further predicted mass of a complementary ion the further isobarically labelled analyte of the plurality; obtaining respective further mass spectrometer output of a further fragmented portion of the sample, said further portion containing the further isobarically labelled analyte; applying the windowed super resolution algorithm to the respective further mass spectrometer output to generate a respective further second set of mass spectrometry data, wherein the window of the windowed super resolution algorithm is determined based on the respective further predicted mass of a complementary ion of the isobaric label of the further analyte; and quantifying the further analyte present in the sample from the respective further second set of mass spectrometry data.

[0017] Alternatively, the method may be used as part of DIA process. For example, wherein said portion comprises the plurality of analytes, the method may further comprise: selecting one or more further isobarically labelled analytes of the plurality of isobarically labelled analytes, and for each further isobarically labelled analyte: determining, from the first set of mass spectrometry data, a respective further predicted mass of a complementary ion of the further isobarically labelled analyte; applying the windowed super resolution algorithm to the mass spectrometer output to generate a respective further second set of mass spectrometry data, wherein a window of the windowed super resolution algorithm is determined based on the respective further predicted mass of a complementary ion of the further isobarically labelled analyte; and quantifying the further isobarically labelled analyte present in the sample from the respective further second set of mass spectrometry data.

[0018] In some embodiments the super resolution algorithm may be the PhiSDM algorithm.

[0019] In some embodiments the method comprises generating, using a separation device (such as a liquid chromatography separation device), a mass stream, wherein the sample is a portion of the mass stream.

[0020] In some embodiments the method is used as part of a method of operating a mass spectrometer. Here the method may comprise generating, using a separation device, a mass stream; and sequentially analysing respective samples of the mass stream in a mass spectrometry apparatus by, for each respective sample, generating a first set of mass spectrometry data of the sample, wherein the sample comprises a plurality of tandem mass tag labelled analytes, and applying the method of the first aspect (or one of its embodiments).

[0021] In a second aspect there is provided method of quantification, the method comprising: obtaining a first set of mass spectrometry data of a sample, wherein the sample comprises a mix of two or more sub-samples, each sub-sample being labelled with a respective isobaric mass tag (such as a tandem mass tag) and comprising respective amounts of a first analyte and a second analyte, calculating an expected isotopic distribution for the first analyte; determining, from the first set of mass spectrometry data, one or more expected complementary ion doublets of the first analyte, obtaining mass spectrometer output of a fragmented portion of the sample, said portion containing two or more isotopes of the first analyte, applying a windowed super resolution algorithm to the mass spectrometer output to generate a second set of mass spectrometry data, wherein one or more windows of the windowed super resolution algorithm is determined based on the one or more expected complementary ion doublets, and quantifying, based on the expected isotopic distribution for the first analyte, an amount of the second analyte present in a sub-sample, from the second set of mass spectrometry data. The first and / or the second analytes may be peptides. Here the expected isotopic distribution for the first analyte may be calculated based on the peptide sequence (such as by using an averagine or fractional averagine model).

[0022] Here, said quantifying may comprise correcting a reporter ion intensity corresponding to the first and second analyte, to remove the contribution of the two or more isotopes of the first analyte. Quantifying typically comprises determining a relative abundance (and / or absolute amount) of the second analyte present in the sample.

[0023] The isobaric mass tags used may include any of: tandem mass tags; TRAQ tags; iTRAQ tags; SILAC tags; or Metal-coded Affinity Tags (MeCAT, or any combination thereof. Typically, the complementary ion comprises a balancer region of the tandem mass tag attached to the selected analyte.

[0024] In some embodiments obtaining a first set of mass spectrometry data of a sample comprises operating a mass spectrometer to generate the first set of mass spectrometry data of the sample. Here, obtaining mass spectrometer output of a fragmented portion of the sample comprises: fragmenting a portion of the sample, the portion containing at least some of the isotopes of the first and second analytes; and generating mass spectrometer output of the fragmented portion of the sample. The portion of the sample containing the analyte may comprise some or all of the isotopic envelope of the first analyte.

[0025] In some embodiments the super resolution algorithm may be the PhiSDM algorithm. The super resolution algorithm may be arranged (for example by selection of suitable parameters and / or transient length) such that peaks having a separation of 0.01 Da are resolved in the second mass spectrometry data. In some cases the threshold of resolution may be set lower than 0.01 Da, such as 0.001 Da.

[0026] In some embodiments the method comprises generating, using a separation device (such as a liquid chromatography separation device), a mass stream, wherein the sample is a portion of the mass stream.

[0027] In some embodiments the methods are used as part of a method of operating a mass spectrometer. Here the method may comprise generating, using a separation device, a mass stream; and sequentially analysing respective samples of the mass stream in a mass spectrometry apparatus by, for each respective sample, generating a first set of mass spectrometry data of the sample, wherein the sample comprises a plurality of tandem mass tag labelled analytes, and applying the method of the first or second aspect (or one of their embodiments).

[0028] According to a third aspect of the present disclosure, there is provided a system adapted to carry out above-mentioned first (or second) aspect or any embodiment thereof.

[0029] To that end there is provided a system of quantification for an isobaric tagging experiment, the system comprising a memory and one or more processors configured to carry out the steps of obtaining a first set of mass spectrometry data (such as a mass spectrum) of a sample, wherein the sample comprises a plurality of isobarically labelled (or tagged) analytes; determining, from the first set of mass spectrometry data, a respective predicted mass of a complementary ion of a selected isobarically labelled analyte of the plurality of isobarically labelled analytes; obtaining mass spectrometer output (sucha as a transient or transient signal) of a fragmented portion of the sample, said portion containing the selected isobarically labelled analyte; and applying a windowed super resolution algorithm (such as phase-constrained spectral deconvolution algorithm) to the mass spectrometer output to generate a second set of mass spectrometry data, wherein the window of the windowed super resolution algorithm is determined based on the predicted mass of the complementary ion. The method may further comprise quantifying the analyte present in the sample from the second set of mass spectrometry data (such as determining the relative abundance and or an amount of the analyte present in the sample).

[0030] Similarly, there is provided a further system of quantification, the system comprising a memory and one or more processors configured to carry out the steps of obtaining a first set of mass spectrometry data of a sample, wherein the sample comprises a mix of two or more sub-samples, each sub-sample being labelled with a respective isobaric mass tag (such as a tandem mass tag) and comprises respective amounts of a first analyte and a second analyte, calculating an expected isotopic distribution for the first analyte; determining, from the first set of mass spectrometry data, one or more expected complementary ion doublets of the first analyte, obtaining mass spectrometer output of a fragmented portion of the sample, said portion containing two or more isotopes of the first analyte, applying a windowed super resolution algorithm to the mass spectrometer output to generate a second set of mass spectrometry data, wherein one or more windows of the windowed super resolution algorithm is determined based on the one or more expected complementary ion doublets, and quantifying, based on the expected isotopic distribution for the first analyte, an amount of the second analyte present in a sub-sample, from the second set of mass spectrometry data.

[0031] According to a fourth aspect of the present disclosure, there is provided a computer program which, when executed by one or more processors, causes the one or more processors to carry out the above-mentioned first (or second) aspect or any embodiment thereof. The computer program may be stored on a computer readable medium. Brief of the

[0032] Embodiments of the present disclosure will now be described, by way of example only, with reference to the accompanying drawings, in which:

[0033] Figure 1 a schematically illustrates the TMTPro isobaric tagging system;

[0034] Figure 1 b illustrates mass spectrometer resolution issues of the prior art;

[0035] Figure 2 shows a schematic arrangement of a typical Orbitrap (TM) mass spectrometer;

[0036] Figure 3 shows an example scenario where a tandem mass spectrometry arrangement is used for analysing a sample of isobarically labelled peptides;

[0037] Figure 4 schematically shows an analysis system which may be used in embodiments;

[0038] Figure 5a schematically illustrates a method carried out by an analysis system, such as the analysis systems of figures 3 and 4;

[0039] Figures 6a-c show data from a real time DDA LC-MS TMTc experiment;

[0040] Figure 7 shows a number of complementary ion doublets formed by isotopes of an interferent peptide;

[0041] Figure 8 schematically illustrates a method carried out by an analysis system, such as the analysis systems of figures 3 and 4;

[0042] Figure 9 schematically illustrates an example of a computer system;

[0043] Detailed description of embodiments of the invention

[0044] In the description that follows and in the figures, certain embodiments of the invention are described. However, it will be appreciated that the invention is not limited to the embodiments that are described and that some embodiments may not include all of the features that are described below. It will be evident, however, that various modifications and changes may be made herein without departing from the broader spirit and scope of the invention as set forth in the appended claims. Figure 2 shows a schematic arrangement of a typical Orbitrap (TM) mass spectrometer. The arrangement of figure 2 is described in detailed in commonly assigned WO-A-02 / 078046 the entire contents of which are incorporated herein by reference, and will not be described in detail here. A brief description of figure 2 is, however, included in order to understand the use and purpose of the mass spectrometer better.

[0045] As seen in figure 2, the mass spectrometer 10 includes a continuous or pulsed ion source 20 which generates gas-phase ions. These pass through an RF-only S-lens 30, which is a stacked-ring (RF) ion guide, at a low to medium vacuum pressure. The ions are focused by the S-lens 30 into an injection flatapole 35 which injects the ions into a bent flatapole 40 with an axial field. The bent flatapole 40 guides (charged) ions along a curved path through it whilst unwanted neutral molecules such as entrained solvent molecules are not guided along the curved path and are lost.

[0046] An ion gate (TK lens) 45 is located at the distal end of the bent flatapole 40 and controls the passage of the ions from the bent flatapole 40 into a downstream quadrupole mass filter 50. The quadrupole mass filter 50 is typically but not necessarily segmented and serves as a band pass filter, allowing passage of a selected mass number or limited mass range whilst excluding ions of other mass to charge ratios (m / z). In other words, the mass filter 50 extracts only those ions within a window of m / z ratios of interest. The quadrupole mass filter 50 can also be operated in a wide-band transmission mode. The quadrupole mass filter 50 is located in a high-vacuum region of the spectrometer, e.g. with a pressure of 1x10-4 mbar or less, or 5x10-5 mbar or less. Ions then pass through a quadrupole exit lens / split lens arrangement 52 and into a transfer multipole 54. The transfer multipole 54 guides the mass-filtered ions from the quadrupole mass filter 50 into a curved linear ion trap (C-trap) 60, which stores ions in a trapping volume through application of an RF potential to a set of rods (typically quadrupole, hexapole or octapole).

[0047] Ions are held in the linear trap 60 in a potential well, the bottom of which may be located adjacent to an exit electrode thereof. Ions are ejected out of the linear trap 60 into a lens arrangement 70 by applying a DC pulse to the exit electrode of the linear trap 60. Ions pass through the lens arrangement 70 along a line that is curved to avoid gas carry-over, and into an electrostatic trap 80 (also known as a mass analyser). In Figure 2, the electrostatic trap 80 is the so-called “Orbitrap”include type, which contains a split outer electrode 84, 85 and an inner electrode 90.

[0048] In operation, a voltage pulse is applied to the exit electrode of the linear trap 60 so as to release trapped ions. The ions arrive at the entrance to the electrostatic trap 80 as a sequence of short, energetic packets, each packet comprising ions of a similar m / z ratio.

[0049] The ions enter the electrostatic trap 80 as coherent bunches and are squeezed towards the central electrode 90. The ions are then trapped in an electrostatic field such that they oscillate along the central electrode with the frequencies depending on their m / z ratios. Image currents are detected by the first outer electrode 84 and the second outer electrode 85, providing first harmonic transient signal 81 and second harmonic transient signal 82 respectively. These two signals are then processed by a differential amplifier 100 and provide a transient image current signal 101 (herein referred to as the transient).

[0050] Therefore, the transient 101 comprises a superposition of one or more periodic signals (or harmonic spectral components). Each periodic signal corresponds to the oscillation of a respective coherent packet of ions within the mass analyser with a respective characteristic frequency determined by the m / z ratio of the ions.

[0051] In particular, the angular frequency a> of an ion moving along the central electrode is determined by the following equation in which k is an instrumental constant and m / z is the mass-to-charge ratio of the ion: A discrete Fourier transform of the transient is then used to identify the characteristic frequencies (and therefore the m / z ratios) present. It will be appreciated that the resolution of a DFT is inversely proportional to the length of transient. As such, it follows that for a first pair of ions with weights A and A+1 and another pair of ions with weights 10A and 10A+1 (for some value of A) a much longer transient is required to resolve the second pair as compare d to the first pair, despite the ions in each pair both being separated by 1 Da.

[0052] The instrument may be operable in various mode of operation, including a MS1 mode of operation and an MS2 mode of operation.

[0053] In the MS1 (or “full mass scan”) mode of operation, the mass filter 50 is operated in its transmission mode of operation, e.g. so that a wide m / z range (e.g. full mass range) of unfragmented (“precursor” or “parent”) ions are analysed in the electrostatic trap 80.

[0054] In the MS2 mode of operation, the mass filter 50 is operated in its filtering mode of operation and the ions are further fragmented (in a fragmentation chamber 95), e.g. so that a selected narrow m / z range of precursor ions are fragmented and the resulting fragment (“product” or “daughter”) ions are analysed in the electrostatic trap 80. In the MS2 mode of operation, the centre of the mass filter’s (narrow) m / z window can be sequentially altered between each of a plurality of different m / z values, e.g. so as to sequentially select (and fragment) each of a plurality of different precursor ions with respective different m / z. In a data dependent acquisition (DDA) MS2 mode of operation, the plurality of different m / z values may correspond to a plurality of different precursor ions identified from corresponding MS1 data (i.e. a full mass scan). In a data independent acquisition (DIA) MS2 mode of operation, the plurality of different m / z values may be taken from a predetermined (fixed) list, i.e. without reference to MS1 data.

[0055] The instrument may also be operable in one or more higher order fragmentation (MSN) modes of operation, such as for example an MS3 mode of operation, whereby precursor ions are fragmented, at least some of the resulting fragment ions are themselves fragmented, and the second-generation fragment ions (“granddaughter ions”) are analysed in the electrostatic trap 80.

[0056] It will be appreciated that the mass spectrometer 10 outlined above serves merely as an exemplar as to how the transient 101 may be generated. The embodiments presented below may use any suitable transient 101 produced by any mass spectrometer 10. In particular, whilst the mass spectrometer described above is an Orbitrap (TM) mass spectrometer, a particular example of a mass spectrometer that uses an orbital trapping electrostatic trap, the described below are not limited to such a mass spectrometer.

[0057] In Figure 3 there is shown an example scenario 300 where a tandem mass spectrometry arrangement 310 is used for analysing a sample 314 of isobarically labelled peptides.

[0058] In this example three initial samples 312 have been obtained, each initial sample 312 comprising various analytes (in this example peptides). Each initial sample 312 is labelled with a corresponding isobaric label 313 (or tag). Each isobaric label 313 (or tag) comprises at least a reporter region and a balancer region such that each labelled analyte molecule comprises (at least) a reporter region, a balancer region, and an analyte molecule (e.g. a peptide molecule). As the isobaric labels 313 correspond to the initial samples 312 it will be understood that all of the labelled analyte molecules in a given initial sample 312 have the same reporter region, which is different to the reporter regions of the labelled analyte molecules in the other initial samples 312. Being isobaric labels the labels all have the same molecular mass.

[0059] As a consequence, the labelled peptide molecules of peptide A in one initial sample 312 have the same molecular mass as the labelled peptide molecules of peptide A in another initial sample 312. However, the reporter regions of the labelled peptide molecules of peptide A in one initial sample 312 have a different molecular mass to the reporter regions of the labelled peptide molecules of peptide A in another initial sample 312.

[0060] The initial samples 312 are mixed to form a mixed sample 314 which is provided to a mass spectrometer arrangement 310 for analysis. The mass spectrometer arrangement is (or comprises) a mass spectrometer, such as the mass spectrometer 10 described above. It will be appreciated that the mass spectrometer arrangement 310 may be operating as part of a separation experiment. As such, the mass spectrometer arrangement 310 may also comprise a separation device. In other words, the mixed sample 314 may be subject to a separation device, such as a liquid chromatography device. The mass spectrometer 10 may therefore receive one or more elutions from the mixed sample 314. The mass spectrometer arrangement 310 is configured to initially analysed the mixed sample in an MS1 mode of operation, so as to provide MS1 data. The MS1 data may include one or more ion peaks, with each ion peak corresponding to labelled peptide (or analyte) ions having a particular m / z (i.e. a particular precursor).

[0061] As shown in figure 3 the MS1 data 320 shows a number of peaks (indicated as centroids for clarity) each corresponding to a different peptide species present in the mixed sample 314. The reported masses of the peaks correspond to the mass of the peptide species in addition to the mass of the isobaric label 313. In this initial stage a given peak may comprise contributions from more than one initial sample 312.

[0062] In this example one or more peptide species (or precursors or analytes) of interest 322 are identified from the MS1 data 320. The labelled peptide ions are then analysed by the mass spectrometer arrangement 310 in the MS2 mode of operation, so as to provide MS2 data 325. Each precursor of interest identified 322 from the MS1 data 320 may be used to define an m / z window 321 for the mass filter 50. The mass filter 50 may then sequentially step through each m / z window 321 corresponding to each precursor of interest 322. In this MS2 mode of operation, the mass filtered labelled analyte ions are sequentially fragmented. When labelled analyte ions are fragmented, reporter ions are typically be produced (where a reporter ion is an ion of a reporter region) together with analyte molecule fragment ions. Complementary ions are also typically produced (where a complementary ion is an ion of a combined balancer region and analyte molecule). The mass spectrometry arrangement 310 analyses the resulting ions to generate the MS2 data 325. As discussed above the mass spectrometry arrangement comprises a Fourier Transform type Mass Spectrometer (FTMS). The FT mass spectrometer may be the same as the mass spectrometer used to generate the MS1 data. Alternatively, the mass spectrometer arrangement may comprise separate mass spectrometers for generating the MS1 and MS2 data. The mass spectrometer arrangement used for generating the MS1 data may be a non FTMS, such as a time-of-flight mass spectrometer. The MS2 data 325 is usually initially in the form of a transient signal 101 . As set out above the length of the transient signal determines the standard resolving power at a particular mass in the resulting mass spectrum.

[0063] Figure 3 shows the MS2 data 325 as a mass spectrum generated at such a standard resolving power. The MS2 mass spectrum 325 comprises peaks at a first mass 326 and a second mass 327 corresponding to the reporter ion masses of the isobaric label 313 of the first initial sample 312 and the isobaric label 313 of the second initial sample 312 respectively (shown as centroids for clarity). Such peaks 326; 327 are typically interpreted as indicating the relative amounts of the peptide of interest 322 in the first initial sample 312 and the second initial sample 312 respectively. However, in this example the second initial sample 312 comprises a further peptide 323 that is of a similar mass of the peptide of interest 322. In particular, the further peptide has a mass within the m / z window 321 chosen around the peptide of interest and as such was co-isolated with the peptide of interest when generating the MS2 data 325. As this further peptide 323 was labelled along with the other peptides in the second initial sample 312 this further peptide 323 was labelled with the same mass region as the other peptides in the second initial sample 325. As such, the peak for the reporter ion mass of the second initial sample actually represents the amount of both the peptide of interest 322 and the further peptide 323 in the second sample 312.

[0064] In order to distinguish between the contribution from the peptide of interest 322 and the further peptide 323 typically the peaks of the complementary ions would be examined. Whilst the masses of the reporter ions for the peptide of interest 322 and the further peptide 323 will be the same for those peptides originating in the second sample 312, the masses of the corresponding complementary ions will not. This is because the complementary ions relation to the second sample 312 will comprise a common balancer region with a constant mass, and the peptide itself for which the mass will be different between the peptide of interest 322 and the further peptide 323. However, the difference in mass between the complementary ion of the peptide of interest 322 and the further peptide 323 will necessarily be small as the similar masses of the peptides was what resulted in their co-isolation. As shown by the non-resolved peaks 328 of the complementary ions in figure 3 the standard resolving power of a short transient is often not sufficient. Here the masses of the actual complementary ions are shown as the centroid lines, whereas the MS2 data 325 is shown as a dotted line 328, indicating the inability to resolve the two doublets.

[0065] In the present disclosure the MS2 data 325 is provided to an analysis system 350 along with an indication of the peptide of interest 322. The analysis system 350 is arranged to determine (or calculate or otherwise predict) the expected mass of the complementary ion corresponding to the peptide of interest 322. It will be appreciated that the complementary ion mass can be calculated based on the mass of the labelled peptide of interest 322, the mass of the reporter ion, and the mass of any cleavable linker region in the isobaric label. Similarly, the charge of the complementary ion can be calculated from the charge of the labelled peptide of interest ion. Both the mass of the labelled peptide of interest 322 and the charge of the labelled peptide of interest 322 ion can be obtained from the MS1 data 320.

[0066] In particular, the mass of the complementary ion MCPis typically determined by subtracting from the peptide ion mass MPthe mass of the reporter ion MR, the mass of the cleavable linker ML(typically a CO ion).

[0067] MCP = Mp- MR- ML

[0068] The the charge of the complementary ion ZCPis typically one less than the charge of the labelled peptide ion.

[0069] ZP.ZCP= ZP- 1 Additionally, or alternatively the complementary ion mass can be calculated based on the mass of the peptide of interest and the mass of the known balancer region of the isobaric label.

[0070] The analysis system 350 is arranged to generate (or determine) a mass window around (or including) the complementary ion mass. Such a mass window is usually defined as a set mass (or number of Fourier Transform bins) either side of the complementary ion mass. A suitable window may be determined by the user for the particular experiment, however for a given isobaric TMTc doublet a window from a few tens to a few hundreds of bins is usual. The analysis system is also arranged to apply a windowed super resolution algorithm to the MS2 data 325 using the determined mass window. In this way it will be appreciated that the analysis system generates a super resolution mass spectrum 330 for (or within) the determined window from the MS2 data 325.

[0071] A super resolution mass spectrum 330 is a mass spectrum with a greater resolving power than that of a discrete Fourier transform of the transient signal. An example of a super resolution algorithm which generates such a super resolution mass spectrum from a given transient is the PhiSDM algorithm (also known as 4>SDM) as described in US2016314951 (A1 ) and Grinfeld, Dmitry, Aizikov, Konstantin, Kreutzmann, Arne, Damoc, Eugen, Makarov, Alexander; 2016; “Phase-Constrained Spectrum Deconvolution for Fourier Transform Mass Spectrometry” Analytical chemistry (89) 10.1021 / acs.analchem.6b03636 both of which are hereby incorporated by reference in their entirety. Such super resolution algorithms (or methods) typically use additional constraints to improve the resolving power of a Fourier transform based mass spectrum. PhiSDM applies a phase constraint when deconvolving an initial Fourier transform mass spectrum onto a fixed frequency grid finer than the grid of the initial Fourier transform. As such, the PhiSDM method may also be seen as a type of phase constrained deconvolution algorithm.

[0072] It will be appreciated by the skilled person that super resolution algorithms (such as PhiSDM) may be windowed. In particular, the super resolution algorithm may be applied just (or solely) to a mass window of interest. In this way the windowed super resolution algorithm will generate a super resolution mass spectrum just (or solely) within the mass window of interest. US2016314951 (A1 ) and “Phase-Constrained Spectrum Deconvolution for Fourier Transform Mass Spectrometry” ibid, both describe how such windowing may be carried out in practice and as such we do not describe this further herein. However, it will be appreciated that by using a windowed super resolution algorithm the processing power (and / or time taken) to generate the super resolution spectrum is greatly reduced, at the expense of a more limited mass range being represented in the resulting mass spectrum.

[0073] Other suitable deconvolution algorithms include any of:

[0074] • Filter Diagonalization Method (FDM) described in (Aizikov et al. J Am Soc Mass Spectrom 2006, 17, 836-843 and Martini et al. Int. J. Mass spectrum. 2014;

[0075] • The method described in K Aizikov, D Grinfeld - US Patent 10,840,073, 2020 "Methods and apparatus for obtaining enhanced mass spectrometric data"; and The Prony method described in R. Roya; B. G. Sumpterc; G. A. Pfefferd; S. K. Graye ; Noidc, D. W. "Novel methods for spectral analysis." Phys. Rep. 1991 , 205, 109-152.

[0076] Equally, deconvolution methods where the window is defined in terms of a seed value corresponding to the predicted m / z value of the peak of interest may be used. Examples of these include: Least Squares in Frequency Domain by R. A. Grothe (US 2009 / 0278037); and Least Squares in Time Domain described in Kozhinov, A. N. et al. Super-Resolution Mass Spectrometry Enables Rapid, Accurate, and Highly Multiplexed Proteomics at the MS2 Level. Anal. Chem (2023).

[0077] As shown in figure 3 the super resolution mass spectrum 330 generated by the analysis system 350 in this example enables the complementary ions of the peptide of interest from the second sample, and the complementary ions of the co-isolated peptide from the second sample to be resolved. The relative intensities of the peaks for the complementary ion of the peptide of interest from the second sample, and the complementary ion of the co-isolated peptide from the second sample enable the contributions of the peptide of interest from the second sample and the co-isolated peptide from the second sample to the peak of the reporter ion for the second sample in the MS2 data 325 to be determined. In this way it will be understood that the amount of the peptide of interest 322 in the second sample 312 may be quantified. The use of such resolved complementary ions to enable quantification in cases of co-isolated analytes is a well-known application of the TMTc technique.

[0078] In the present disclosure it has been realized that by using a windowed application of a super resolution algorithm (such as PhiSDM) a relatively short FTMS transient may be generated at the MS2 stage. Whilst such a short transient would ordinarily not enable the heavy complementary ions to be resolved the windowed super resolution algorithm mitigates this, avoiding the need for using long transients (with correspondingly long acquisition times) which in some case may simply not be compatible with the separation techniques used to generate the samples in the first place. Furthermore, by predicting the masses of the complementary ions of interest and using a windowed approach, the high computational requirements of such super resolution algorithms are greatly reduced, as only the window (or windows) of interest are further resolved. This also avoids having to apply the super resolution algorithm to the entire MS2 spectrum which may be computationally infeasible, or may require significant runtime which again may be simply incompatible with the separation techniques used to generate the samples in the first place. In particular, where liquid chromatography is used as a separation technique the same mass spectrometry arrangement may need to be used on multiple mixed samples sequentially, where each mixed sample corresponds to a respective elution from the liquid chromatography system. Where the elutions are close together in retention time the available time for transient acquisition and applying the super resolution algorithm is limited to the time between the two elutions. As such, the present disclosure allowing both shorter acquisition times and requiring only limited post processing time enables the use of FTMS mass spectrometry techniques in a wider range of LC-MS experiments where isobaric tagging is used. Indeed by using these techniques isobaric multiplets where the reporter ions whose mass differ by less than 0.01 Da may be accurately resolved using short transients suitable for LC-MS type experiments.

[0079] Figure 4 schematically shows an analysis system 350 which may be used in embodiments.

[0080] The analysis system comprises a mass spectrometry input module 410, a complementary ion mass module 420, a super resolution module 430, and an optional quantification module 440.

[0081] The mass spectrometry input module 410 is arranged to obtain a first set of mass spectrometry data 320 of a sample 314. The sample 314 comprises a plurality of isobarically labelled analytes. The sample 314 is typically a mixed sample as described above. In other words the sample usually corresponds to (or comprises) two or more sub-samples 312, where each sub-sample 312 the analytes in said sub-sample 312 have been labelled with a respective isobaric tag 313. Here the isobaric tag 313 for a given sub-sample 312 is different to the isobaric tag 313 for each other sub-sample 312. As noted above, the isobaric tags 313 may be any of tandem mass tags, ITRAQ tags; mTRAQ tags and so on.

[0082] The first set of mass spectrometry data 320 indicates relative intensities (or quantities, or relative abundances) for ions of the isobarically labelled analytes in the sample 314. In this way the first set of mass spectrometry data 320 usually corresponds to MS1 data (or mass spectrometry data generated by a mass spectrometer operating in an MS1 mode).

[0083] The first set of mass spectrometry data 320 can be represented in the form of one or more mass channels. Each mass channel corresponds to a respective mass value (or mass to charge ratio, referred to herein as m / z value) at which ionic species of the same mass (or mass to charge ratio) are detected in a mass spectrometer arrangement. Each m / z value corresponds to a respective ionic species and is equal to the molecular mass of the respective ionic species divided by the absolute elemental charge of the respective ionic species. In this case the ionic species are ions of the labelled analytes The first set of mass spectrometry data comprises one or more intensity values with each intensity value appearing for a respective m / z value (or channel). Each intensity value correlates to the relative abundance (or quantity) of the ionic species (or ions of the given labelled analyte) corresponding to the respective m / z value as measured by the mass spectrometer arrangement 310 from the sample 314. Each intensity value may be proportional to the relative abundance of the ionic species corresponding to the respective m / z value. The intensity (or relative abundance) measured by the mass spectrometer arrangement 310 for a given mass channel correlates to the relative abundance of ionic species having the mass (or mass-to-charge ration m / z) detected by the mass spectrometer arrangement 310. It will be appreciated that mass spectrometry data (and by extension mass spectra) may be represented in any one of a number of different forms. It will be appreciated that the first set of mass spectrometry data does not need to be plotted in the form of a graph. Indeed, the first set of mass spectrometry data may be represented in any suitable form. For example, the first set of mass spectrometry data 320 may be represented a list comprising the one or more intensity values and the one or more m / z values. In some cases the first set of mass spectrometry data 320 may simply be represented as a list of centroids (or local maxima), each centroid being represented as an m / z value and intensity value pair.

[0084] As there are many techniques commonly used in the art for obtaining such centroids from mass spectrometry data these will not be discussed further herein. However, it will be appreciated that the techniques described herein may be performed on lists of centroids forming mass spectrometry data, or on raw mass spectrometry data where suitable techniques are used to identify the intensity maxima (or centroids).

[0085] The mass spectrometry input module 410 may be arranged to receive the first mass spectrometry data 320 from an external source (such as the mass spectrometer arrangement 310 or an external storage device). Alternatively, the mass spectrometry input module 410 may be arranged to receive output from the mass spectrometer, such as a transient (or transient signal). As such, the mass spectrometry input module 410 may be arranged to generate the first set of mass spectrometry data 320 from the received output (such as by applying a discreet Fourier transform to the transient).

[0086] The mass spectrometry input module 410 is further arranged to receive mass spectrometer output 325 of a fragmented portion of the sample. The mass spectrometer output 325 of a fragmented portion of the sample is usually generated by a mass spectrometry arrangement operating in an MS2 mode. The output 325 of a fragmented portion of the sample is output from a FTMS type mass spectrometer (such as those previously discussed). As such the output of a fragmented portion of the sample comprises (or is typically in the form of) a transient 101 . Additionally, or alternatively the output of a fragmented portion of the sample may comprise the Fourier coefficients (or a Fourier representation) of the transient. Any suitable representation of the transient 101 may be used such that the selected super resolution algorithm (discussed shortly below) may be applied to the output 325 of a fragmented portion of the sample.

[0087] The complementary ion mass module 420 is arranged to determine from the first set of mass spectrometry data 320, a predicted mass 425 of a complementary ion of an isobarically labelled analyte represented in the first set of mass spectrometry data 320. As set out above, the predicted mass 425 of the complementary ion may be determined based on the mass of the isobarically analyte of interest, the mass of the corresponding reporter region, and the mass of any cleavable linker region in the isobaric label. The isobarically labelled analyte may be selected by a user. Alternatively, the complementary ion mass module 420 may be arranged to automatically identify one or more isobarically labelled analytes from the first set of mass spectrometry data 320 and determine the predicted masses of the respective complementary ions.

[0088] The super resolution module 430 is arranged to apply a windowed super resolution algorithm to the mass spectrometer output 325 of a fragmented portion of the sample to generate a second set of mass spectrometry data 330. Here, the fragment portion of the sample 314 is fragmented from a portion that contains (or comprises) a given isobarically labelled analyte. The window of the windowed super resolution algorithm is determined based on the predicted mass 425 of the complementary ion of the given isobarically labelled analyte. It will be appreciated that the portion may contain a plurality of isobarically labelled analytes. As such, the super resolution module 430 may be arranged to apply the windowed super resolution algorithm to the mass spectrometer output for a plurality of windows, each window being determined (or corresponding to) a respective isobarically labelled analyte. Additionally, or alternatively the respective windows for two or more analytes may overlap. Overlapping windows may be combined (or merged) into a single window. The single window may be a union of the constituent windows. In other words overlapping windows may be combined into a single windows encompassing all of the masses in either window. As such, the windowed super resolution algorithm may be applied for a single window corresponding to two or more isobarically labelled analytes.

[0089] As discussed above the output of applying the windowed super resolution algorithm is mass spectrometry data for (or within) the given mass window at a resolution greater than the characteristic resolution of the mass spectrometer output. In this way it will be understood that the generated second set of mass spectrometry data 325 comprises one or more super resolution subsets of mass spectrometry data each corresponding to a respective mass window. The second set of mass spectrometry data 325 may also comprise mass spectrometry data at the characteristic (or standard resolution) for mass ranges outside the one or more windows.

[0090] As such the second set of mass spectrometry data 325 usually comprises mass spectrometry data at the standard resolution for at least the mass range including the reporter ions and mass spectrometry data at the super resolution for a mass range (or ranges) including at least one complementary ion. The mass spectrometry data at the standard resolution may be generated by the super resolution module 430 by applying a Fourier transform to the mass spectrometer output. Additionally, or alternatively the mass spectrometry data at the standard resolution may have been received (or obtained) by the mass spectrometry input module 410 as part of the mass spectrometer output.

[0091] As discussed above any suitable windowed super resolution algorithm may be used. Typically, the super resolution algorithm comprises a phase constrained deconvolution algorithm. An example of such a suitable super resolution algorithm is PhiSDM described above.

[0092] The optional quantification module 440 is arranged to quantify a given isobarically labelled analyte present in the sample from the second set of mass spectrometry data 330. In particular, the quantification module 440 is typically arranged to determine the amount (or relative abundance) of a given analyte having a given isobaric label based on the reported intensity of the reporter ion corresponding to said isobaric label, and the intensities of the complementary ions in the second set of mass spectrometry data 330. It will be appreciated that such quantification would be well understood by the skilled person from convention complementary ion labelling experiments such as TMTc. However, in this case such standard quantification is enabled by the super resolution mass spectrometry data for the complementary ions generated by the super resolution module. The quantification module 440 may be arranged to provide an output 450 of the quantification to a user. Such an output 450 may comprise any of: a relative abundance of the isobarically labelled analyte present in the sample; an amount of the isobarically labelled analyte in the sample; a proportion of the isobarically labelled analyte in the sample etc.

[0093] It will also be understood that the quantification module 440 is considered optional as the quantification may take place elsewhere based on the generated second mass spectrometry data.

[0094] Figure 5a schematically illustrates a method 500 carried out by an analysis system, such as the analysis system 350 of figures 3 and 4.

[0095] At a step 510 a first set of mass spectrometry data of a sample is obtained. The sample is typically a mixed sample as described above. In other words, the sample usually corresponds to (or comprises) two or more subsamples, where each sub-sample the analytes in said sub-sample have been labelled with a respective isobaric tag. Here the isobaric tag for a given subsample is different to the isobaric tag for each other sub-sample. As noted above, the isobaric tags may be any of tandem mass tags, ITRAQ tags; mTRAQ tags and so on. The step 410 may be carried out by the mass spectrometry input module 410 described above

[0096] The first set of mass spectrometry data indicates relative intensities (or quantities, or relative abundances) for ions of the isobarically labelled analytes in the sample. In this way the first set of mass spectrometry data usually corresponds to MS1 data (or mass spectrometry data generated by a mass spectrometer operating in an MS1 mode).

[0097] The step 510 may comprise receiving the first set of mass spectrometry data from a mass spectrometer arrangement. Alternatively, however, the step 510 may comprise operating a mass spectrometer arrangement to generate the first set of mass spectrometry data of the sample. As previously indicated the sample may be an elution from a separation device (such as a chromatographic separation device). Therefore, in some examples the step 510 may comprise operating the mass spectrometer as part of an LC-MS experiment. For example the step 510 may comprise generating, using a separation device, a mass stream, wherein the sample is a portion of the mass stream.

[0098] At a step 520 a respective predicted mass of a complementary ion of a selected isobarically labelled analyte of the plurality of isobarically labelled analytes is determined from the first set of mass spectrometry data. The step 520 may be carried out by the complementary ion mass module 420 described above. As set out previously the predicted mass of the complementary ion may be determined based on the mass of the isobarically analyte of interest, the mass of the corresponding reporter region, and the mass of any cleavable linker region in the isobaric label.

[0099] At a step 530 a mass spectrometer output of a fragmented portion of the sample is obtained. Here the portion contains the selected isobarically labelled analyte. The step 530 may be carried out by the mass spectrometry input module 410 described above. The output of a fragmented portion of the sample is output from a FTMS type mass spectrometer (such as those previously discussed). As such the output of a fragmented portion of the sample comprises (or is typically in the form of) a transient. Additionally, or alternatively the output of a fragmented portion of the sample may comprise the Fourier coefficients (or a Fourier representation) of the transient.

[0100] The step 530 may comprise receiving the mass spectrometer output from a mass spectrometer arrangement. Alternatively, however, the step 530 may comprise operating a mass spectrometer arrangement to generate the mass spectrometry output. In particular, the step 530 may comprise operating the mass spectrometry arrangement to fragment a portion of the sample containing said analyte, and operating the mass spectrometry arrangement to generate mass spectrometer output of the fragmented portion of the sample.

[0101] At a step 540 a windowed super resolution algorithm is applied to the mass spectrometer output to generate a second set of mass spectrometry data. The step 540 may be carried out by the super resolution module 430 described above. The mass window of the windowed super resolution algorithm is determined in the step 440 based on the predicted mass of the complementary ion. The mass window is typically calculated as a pre-determined mass (or number of Fourier transform bins) either side of the complementary ion mass, as described above. As discussed above any suitable windowed super resolution algorithm may be used. Typically, the super resolution algorithm comprises a phase constrained deconvolution algorithm. An example of such a suitable super resolution algorithm is PhiSDM described above.

[0102] At an optional step 550 the analyte present in the sample is quantified based on the second set of mass spectrometry data. The step 450 may be carried out by the quantification module 440 above. Typically, the step 450 comprises determining the amount (or relative abundance) of the selected analyte having a given isobaric label based on the reported intensity of the reporter ion corresponding to said isobaric label, and the intensities of the complementary ions in the second set of mass spectrometry data. Whilst the method 500 described above is set out in relation to one selected analyte (which may for example be a user selected analyte of interest), it will be appreciated that the method can be applied in an iterative fashion. For example, in one variant the steps 520 - 550 may be iterated over all of the analytes identified in the first set of mass spectrometry data. This variant is indicated using the dash-dotted lines. In particular, in such a variant a further step 590 of selecting the next isobarically labelled analyte may be introduced. This selection is typically just based on the order in which the isobarically labelled analytes are identified in the first mass spectrometry data, but it will be appreciated that any order could be used. This is an example of a workflow known as data driven acquisition (DDA) in the art. In particular, the MS2 data referred to in the step 530 is acquired iteratively on a per analyte basis.

[0103] An alternative workflow to a DDA workflow is a data independent acquisition (DIA) workflow. An example of a DIA workflow shown the variant method 501 of figure 5b. In the variant method 501 step with the same reference numerals as the corresponding steps in method 500 are the same except where noted below.

[0104] In a DIA type workflow mass spectrometry data from an initial MS1 experiment performed on a sample is analyzed by mass region (or range). As such the first mass spectrometry data obtained in the step 510 corresponds to a given mass region (or range) of an MS1 experiment. The labelled analyte ions reported (or present) in the first mass spectrometry data may already have been identified. Alternatively, the step 510 may comprise identifying the labelled analyte ions reported (or present) in the first mass spectrometry data.

[0105] The step 520 comprises for each isobarically labelled analyte ion reported (or present) in the first mass spectrometry data, determining a predicted mass of the respective complementary ion.

[0106] The portion of the sample used to obtain the mass spectrometer output in the step 530 is a portion corresponding to the given mass range of the first mass spectrometry data. In this way the portion of the sample contains or comprises all of the labelled analyte ions reported (or present) in the first mass spectrometry data.

[0107] In the step 540 the windowed super resolution algorithm is applied to the mass spectrometer output using one or more mass windows. The one or more mass windows are determined from the predicted masses of the complementary ions for all of the labelled analyte ions reported (or present) in the first mass spectrometry data. The one or more mass windows may comprise a respective mass window around each predicted mass of the complementary ions. In this way the mass windows may be calculated asset out above in relation to figure 4a. However, as noted above mass windows may overlap. Overlapping windows may be combined (or merged) into a single window. The single window may be a union of the constituent windows. In other words overlapping windows may be combined into a single windows encompassing all of the masses in either window. As such, a given mass window in the one or more mass windows may correspond to two or more analytes.

[0108] The step 540 may comprise applying the windowed super resolution algorithm to the mass spectrometer output for each mass window. It will be appreciated that this would be beneficial where parallel processing may be used and the windowed super resolution algorithm may be applied for each window concurrently. Alternatively, the windowed super resolution algorithm may be applied for all of the windows. This may be achieved by using various step functions as a windowing function for example.

[0109] In any case the second set of mass spectrometry data generated in step 540 comprises super resolution mass spectrometry data for each of the mass window regions.

[0110] The step 550 comprises quantifying one or more (typically all) of the labelled analytes present in the first mass spectrometry data based on the second mass spectrometry data. As discussed above such quantification is well- known in isobaric tagging experiments (such as TMTc experiments) and is not discussed further herein. The steps are then typically repeated for each further mass range available from the MS1 experiment.

[0111] Figures 6a-c show data from a real time DDA LC-MS TMTc experiment. The total ion chromatogram 600 is shown with an MS1 peak for the labelled peptide ion at m / z = 378.2663 and the charge state Z = 2+. The peptide mixture is labelled using the TMTPro reagent system (a form of TMTc). The labelled peptide labelled peptide ion at m / z = 378.2663 and the charge state Z = 2+ is selected for MS2 analysis and figures 6a-c show the resulting MS2 spectrum 650 at a resolution of 480k.

[0112] As can be seen 8 TMTc (or complementary) ions 651 ; 652; 653; 654; 655; 656; 657; 658 are apparent from the standard resolution MS2 spectrum 650 at masses of 594.39, 595.39, 596.39, 597.39, 598.40, 599.40, 600.41 , and 601 .41 Da respectively. By using the systems and methods of the present disclosure above a super resolution algorithm (in this case PhiSDM) was applied to a 200 bin window (using the refined Fourier Transform grid defined by the super resolution algorithm) around each complementary ion.

[0113] Figures 6b and 6c show the standard resolution MS2 peaks 660 for the eight (or complementary) ions 651 ; 652; 653; 654; 655; 656; 657; 658, along with the super resolution peaks 670 for four of the peaks 652; 655; 656; 657. As can be seen from the super resolution peaks these actually contain pairs of isobaric species (at m / z 595.39, 598.40, 599.40, and 600.41 Da), not resolved at the standard resolution. The super resolution windows however allow the peaks separated by less than 0.01 Da (at m / z 595.39, 598.40, 599.40, and 600.41 Da) to be resolved. As such a 12-plex quantification is enabled using the method of the present disclosure here via the resolution of the isobaric doublets of TMTc ions.

[0114] It will be appreciated that the above systems and methods may be applied to scenarios where a co-isolated, interfering analyte (such as a peptide) has a plurality of isotopes present in the MS2 data.

[0115] This may be understood by considering a variant of the example scenario 300 shown in figure 3 (described above) where a tandem mass spectrometry arrangement 310 is used for analysing a sample 314 of isobarically labelled peptides.

[0116] In this variant example three initial samples 312 have been obtained, each initial sample 312 comprising two analytes (in this example peptides), which shall be referred to as the first analyte and the second analyte. Each initial sample 312 is labelled with a corresponding isobaric label 313 (or tag). Each isobaric label 313 (or tag) comprises at least a reporter region and a balancer region such that each labelled analyte molecule comprises (at least) a reporter region, a balancer region, and an analyte molecule (e.g. a peptide molecule). As the isobaric labels 313 correspond to the initial samples 312 it will be understood that all of the labelled analyte molecules in a given initial sample 312 have the same reporter region, which is different to the reporter regions of the labelled analyte molecules in the other initial samples 312. Being isobaric labels the labels all have the same molecular mass.

[0117] However, in this example the first analyte is present in each sample as a plurality of different isotopes. As a consequence, for a given isotope of the first analyte the labelled peptide molecules of peptide A (the first analyte) in one initial sample 312 have the same molecular mass as the labelled peptide molecules of the same isotope of peptide A in another initial sample 312. However, the reporter regions of the labelled peptide molecules of peptide A in one initial sample 312 have a different molecular mass to the reporter regions of the labelled peptide molecules of peptide A in another initial sample 312. Equally the labelled peptide molecules of peptide A (the first analyte) in one initial sample 312 have a different molecular mass to the labelled peptide molecules of a different isotope of peptide A in another initial sample 312.

[0118] Conversely for the same label the reporter regions of the labelled peptide molecules of peptide A in one initial sample 312 have the same molecular mass as the reporter regions of the labelled peptide molecules of peptide B in the same initial sample 312.

[0119] Consequently, in the MS2 data produced after fragmenting the sample as discussed previously above, the peak for the reporter ions of a given label may comprise contributions from both the first analyte and the second analyte. In particular the contribution from the first analyte may correspond to multiple isotopes of the first analyte each labelled with the first label.

[0120] As discussed previously analysis of the intensities of the complementary ions of the first and second analyte may be used to determine the respective contributions of the first and second analyte to the peak for the reporter ions of a given label, and therefore the relative abundances of the first and second analytes in the first labelled sample.

[0121] However, due to the isotopic nature of the balancer regions of the labels differently labelled complementary ions of the first analyte may overlap causing such complementary ion analysis (without use of the present disclosure) to fail.

[0122] As an example, taking the first analyte to be a human insulin beta chain peptide with the sequence FVNQHLCGSHLVEALYLVCGERGFFYTPKT, then the relative intensities and m / z values of the 9 most abundant isotopes are:

[0123] Table 1 - Human insulin beta chain peptide isotopes The well-known TMTproC isobaric tagging system has 12 labels (or tags or channels) each having the following balancer region m / z values:

[0124] Table 2 - TMTc complementary ion masses

[0125] As such, were the first analyte to be present in all 12 channels then 20 possible complementary ions may be expected. The masses of these complementary ions and the contribution from each channel is shown the table 3

[0126]

[0127] Table 3 - Complementary ion masses and relative contributions from each channel

[0128] As shown in figure 7, eight of these expected complementary ion masses form doublets that would require prohibitively long MS2 transient generation times to resolve.

[0129] However, as discussed above by using a super resolution algorithm windowed around the masses of the predicted doublets the corresponding complementary ion peaks may be resolved. This allows the relative intensities Ic of each complementary ion peak g to be calculated.

[0130] It will be appreciated that a given complementary ion peak intensity lcgis composed of:

[0131] Where is the intensity of the i-th channel and Q is the relative abundance of the i-th peptide isotope.

[0132] In this way the relative intensities Icgof each complementary ion peak g , and therefore the contributions corresponding to that complementary ion may be determined by deconvolution providing an estimate of the relative abundances of the isotopes of the analyte can be determined. It will be understood that if the identity of the analyte (or peptide) is known a person skilled in the art may model the isotopic envelope P, and thus obtain an estimate of the relative isotopic abundances, using the atomic composition based on the analyte’s primary sequence. Alternatively, the averagine or fractional averagine models may be used to approximate the relative isotopic abundances. Further discussion of the avergine model may be found in Senko M. W.; Beu S. C.; Mclafferty F. W. Determination of monoisotopic masses and ion populations for large biomolecules from resolved isotopic distributions. J. Am. Soc. Mass Spectrom. 1995, 6, 229-233. 10.1016 / 1044-0305(95)00017-8. Further discussions of the fractional avergine model may be found in Renard B. Y.; Kirchner M.; Steen H.; Steen J. A.; Hamprecht F. A. NITPICK: peak identification for mass spectrometry data. BMC Bioinformatics 2008, 9, 355 10.1186 / 1471 -2105-9-355. Additionally, it will be appreciated that the balancer region of many isobaric tags, present in the complementary ion, typically comprise multiple hydrogen and oxygen atoms each having their own heavier isotopes. It may therefore be further advantageous to further adjust the relative abundances Ptto account for this (or compensate for their effect).

[0133] For example, in the case of the TMTpro label set deuterated reporter regions are available (also having deuterated balancer regions). By using such deuterated labels and subtracting the (typically small) contribution from naturally occurring deuterium using the averagine model, the complementary ions may be spread over a wider m / z range.

[0134] As such, with the contributions to the complementary ion intensities from each labelled isotope of the first analyte determined, the overall contribution of the first analyte to a given reporter ion intensity may be determined. Thus, the interference caused by the first analyte may be removed and the contribution to a reporter ion intensity of a second analyte determined by a process of elimination. In this way the relative (or absolute) abundance of the second analyte in a given labelled sample may be ascertained.

[0135] It will be understood that where there are multiple interfering analytes with given isotope distribution the above technique may be applied for each analyte to eliminate the interference from said analyte.

[0136] Figure 8 schematically illustrates a method 800 carried out by an analysis system, such as the analysis system 350 of figures 3 and 4.

[0137] At a step 810 a first set of mass spectrometry data of a sample is obtained. The sample is typically a mixed sample as described above. In other words, the sample corresponds to (or comprises) two or more sub-samples, each sub-sample being labelled with a respective isobaric mass tag and comprising respective amounts of a first analyte and a second analyte. The first analyte is present in the form of a distribution of isotopes of the first analyte. As noted above, the isobaric tags may be any of tandem mass tags, ITRAQ tags; mTRAQ tags and so on. The step 810 may be carried out by the mass spectrometry input module 410 described above The first set of mass spectrometry data indicates relative intensities (or quantities, or relative abundances) for ions of the isobarically labelled analytes in the sample. In this way the first set of mass spectrometry data usually corresponds to MS1 data (or mass spectrometry data generated by a mass spectrometer operating in an MS1 mode).

[0138] The step 810 may comprise receiving the first set of mass spectrometry data from a mass spectrometer arrangement. Alternatively, however, the step 810 may comprise operating a mass spectrometer arrangement to generate the first set of mass spectrometry data of the sample. As previously indicated the sample may be an elution from a separation device (such as a chromatographic separation device). Therefore, in some examples the step 810 may comprise operating the mass spectrometer as part of an LC-MS experiment. For example the step 810 may comprise generating, using a separation device, a mass stream, wherein the sample is a portion of the mass stream.

[0139] At a step 815 an expected isotopic distribution for the first analyte is calculated. The step 815 may comprise modelling the isotopic envelope of the first analyte based on its composition (or sequence in the case of a peptide). In this way the estimate of the relative isotopic abundances may be obtained. Alternatively, the averagine model may be used to approximate the relative isotopic abundances and thus obtain the expected isotopic distribution.

[0140] At a step 820 one or more expected complementary ion doublets of the first analyte are determined. The step 820 may be carried out by the complementary ion mass module 420 described above. The step 820 may comprise determining expected complementary ion masses based on the masses of the isotopes of first analyte, the masses of the corresponding reporter regions, and the masses of any cleavable linker regions in the isobaric labels. Pairs of complementary ion masses that are within an expected resolution threshold (or limit) of the mass spectrometer instrument 10 (or the MS mode of operation of the mass spectrometer instrument 10) may be identified as forming a complementary ion doublet. At a step 830 a mass spectrometer output of a fragmented portion of the sample is obtained. Here the portion contains some or all of the isotopic envelope of the first analyte. The step 830 may be carried out by the mass spectrometry input module 410 described above. The output of a fragmented portion of the sample is output from a FTMS type mass spectrometer (such as those previously discussed). As such the output of a fragmented portion of the sample comprises (or is typically in the form of) a transient. Additionally, or alternatively the output of a fragmented portion of the sample may comprise the Fourier coefficients (or a Fourier representation) of the transient.

[0141] The step 830 may comprise receiving the mass spectrometer output from a mass spectrometer arrangement. Alternatively, however, the step 830 may comprise operating a mass spectrometer arrangement to generate the mass spectrometry output. In particular, the step 530 may comprise operating the mass spectrometry arrangement to fragment a portion of the sample containing said analyte, and operating the mass spectrometry arrangement to generate mass spectrometer output of the fragmented portion of the sample.

[0142] At a step 840 a windowed super resolution algorithm is applied to the mass spectrometer output to generate a second set of mass spectrometry data. The step 840 may be carried out by the super resolution module 430 described above. The mass windows of the windowed super resolution algorithm are determined in the step 840 based on based on the one or more expected complementary ion doublets. Typically, there is a mass window for each identified doublet. The mass window is typically calculated as a pre-determined mass (or number of Fourier transform bins) either side of one of the complementary ion masses of the doublet (or their average), as described above. As discussed above any suitable windowed super resolution algorithm may be used. Typically, the super resolution algorithm comprises a phase constrained deconvolution algorithm. An example of such a suitable super resolution algorithm is PhiSDM described above.

[0143] At an optional step 850 the second analyte present in at least one subsample is quantified based on the expected isotopic distribution for the first analyte. The step 850 may be carried out by the quantification module 440 above. In particular the step 850 typically comprises deconvolving the complementary ion intensities from the second mass spectrometry data using the expected isotopic distribution to determine the contribution of isotopes of the first analyte to one or more reporter ion intensities. The step 850 may comprises correcting a reporter ion intensity corresponding to the first and second analyte, to remove the contribution of the two or more isotopes of the first analyte.

[0144] It will be understood that the above-described methods may be particular useful when working with peptides in higher charge states. For example, going back to the human insulin beta chain peptide above, a charge state of 4, shifts the spectrum to the 940 Da region. The distance between two adjacent isobaric complementary ion peaks is therefore ~0.001575 Da, requiring a minimum effective resolution of >600k to resolve. To achieve the baseline resolution necessary for accurate quantification, at least twice that resolution would be needed. For a typical FTMS device such a resolution would, in the absence of the methods of the present disclosure, usually require a transient duration of at least 2 seconds, rendering the technique of limited usability. Additionally, only a fraction of existing devices are capable of producing stable signals on such a timescale. Similarly, applying a super resolution algorithm to the entire mass spectrum would require substantial compute power and is infeasible to do in realtime.

[0145] However, the application of the methods of the present disclosure can achieve this resolution with significantly shorter transients, without the high computational penalty. In such a way existing FTMS devices can easily be used to provide a scanning speed compatible with bottom-up proteomics experiments.

[0146] Figure 10 schematically illustrates an example of a computer system 1000. The system 1000 comprises a computer 1020. The computer 1020 comprises: a storage medium 1040, a memory 1060, a processor 1080, an interface 1100, a user output interface 1120, a user input interface 1140 and a network interface 1160, which are all linked together over one or more communication buses 1180. The storage medium 1040 may be any form of non-volatile data storage device such as one or more of a hard disk drive, a magnetic disc, an optical disc, a ROM, etc. The storage medium 1040 may store an operating system for the processor 1080 to execute in order for the computer 1020 to function. The storage medium 1040 may also store one or more computer programs (or software or instructions or code).

[0147] The memory 1060 may be any random access memory (storage unit or volatile storage medium) suitable for storing data and / or computer programs (or software or instructions or code).

[0148] The processor 1080 may be any data processing unit suitable for executing one or more computer programs (such as those stored on the storage medium 1040 and / or in the memory 1060), some of which may be computer programs according to embodiments or computer programs that, when executed by the processor 1080, cause the processor 1080 to carry out a method according to an embodiment and configure the system 1000 to be a system according to an embodiment. The processor 1080 may comprise a single data processing unit or multiple data processing units operating in parallel or in cooperation with each other. The processor 1080, in carrying out data processing operations for embodiments, may store data to and / or read data from the storage medium 1040 and / or the memory 1060.

[0149] The interface 1100 may be any unit for providing an interface to a device 1220 external to, or removable from, the computer 1020. The device 1220 may be a data storage device, for example, one or more of an optical disc, a magnetic disc, a solid-state-storage device, etc. The device 1220 may have processing capabilities - for example, the device may be a smart card. The interface 1100 may therefore access data from, or provide data to, or interface with, the device 1220 in accordance with one or more commands that it receives from the processor 1080.

[0150] The user input interface 1140 is arranged to receive input from a user, or operator, of the system 1000. The user may provide this input via one or more input devices of the system 1000, such as a mouse (or other pointing device) 1260 and / or a keyboard 1240, that are connected to, or in communication with, the user input interface 1140. However, it will be appreciated that the user may provide input to the computer 102 via one or more additional or alternative input devices (such as a touch screen). The computer 1020 may store the input received from the input devices via the user input interface 1140 in the memory 1060 for the processor 1080 to subsequently access and process, or may pass it straight to the processor 1080, so that the processor 1080 can respond to the user input accordingly.

[0151] The user output interface 1120 is arranged to provide a graphical / visual and / or audio output to a user, or operator, of the system 1000. As such, the processor 1080 may be arranged to instruct the user output interface 1120 to form an image / video signal representing a desired graphical output, and to provide this signal to a monitor (or screen or display unit) 1200 of the system 1000 that is connected to the user output interface 1120. Additionally or alternatively, the processor 1080 may be arranged to instruct the user output interface 1120 to form an audio signal representing a desired audio output, and to provide this signal to one or more speakers 1210 of the system 1000 that is connected to the user output interface 1120.

[0152] Finally, the network interface 1160 provides functionality for the computer 1020 to download data from and / or upload data to one or more data communication networks.

[0153] It will be appreciated that the architecture of the system 1000 illustrated in figure 10 and described above is merely exemplary and that other computer systems 1000 with different architectures (for example with fewer components than shown in figure 10 or with additional and / or alternative components than shown in figure 10) may be used in embodiments. As examples, the computer system 1000 could comprise one or more of: a personal computer; a server computer; a mobile telephone; a tablet; a laptop; a television set; a set top box; a games console; other mobile devices or consumer electronics devices; an in-car entertainment system; an in-car navigation system; etc. The systems and methods described in relation to figures 3-5 may each be implemented as (or executed with) one or more computer systems such as the system 1000 described above. Similarly, the navigation clients referred to above may be implemented as (or executed with) one or more computer systems such as the system 1000. Where data is obtained from particular experimental apparatus (such as mass spectrometers and mass spectrometer arrangements) the computer system 100 may be arranged to suitably control, or trigger or otherwise cause the experimental apparatus to generate the data.

[0154] It will be appreciated that the methods described have been shown as individual steps carried out in a specific order. However, the skilled person will appreciate that these steps may be combined or carried out in a different order whilst still achieving the desired result.

[0155] It will be appreciated that embodiments may be implemented using a variety of different information processing systems. In particular, although the figures and the discussion thereof provide an exemplary computing system and methods, these are presented merely to provide a useful reference in discussing various aspects. Embodiments may be carried out on any suitable data processing device, such as a personal computer, laptop, personal digital assistant, mobile telephone, set top box, television, server computer, etc. Of course, the description of the systems and methods has been simplified for purposes of discussion, and they are just one of many different types of system and method that may be used for embodiments. It will be appreciated that the boundaries between logic blocks are merely illustrative and that alternative embodiments may merge logic blocks or elements, or may impose an alternate decomposition of functionality upon various logic blocks or elements.

[0156] It will be appreciated that the above-mentioned functionality may be implemented as one or more corresponding modules as hardware and / or software. For example, the above-mentioned functionality may be implemented as one or more software components for execution by a processor of the system. Alternatively, the above-mentioned functionality may be implemented as hardware, such as on one or more field-programmable-gate-arrays (FPGAs), and / or one or more application-specific-integrated-circuits (ASICs), and / or one or more digital-signal-processors (DSPs), and / or other hardware arrangements. Method steps implemented in flowcharts contained herein, or as described above, may each be implemented by corresponding respective modules; multiple method steps implemented in flowcharts contained herein, or as described above, may be implemented together by a single module.

[0157] It will be appreciated that, insofar as embodiments are implemented by a computer program, then a storage medium and a transmission medium carrying the computer program form aspects. The computer program may have one or more program instructions, or program code, which, when executed by a computer carries out an embodiment. The term “program” as used herein, may be a sequence of instructions designed for execution on a computer system, and may include a subroutine, a function, a procedure, a module, an object method, an object implementation, an executable application, an applet, a servlet, source code, object code, a shared library, a dynamic linked library, and / or other sequences of instructions designed for execution on a computer system. The storage medium may be a magnetic disc (such as a hard drive or a floppy disc), an optical disc (such as a CD-ROM, a DVD-ROM or a BluRay disc), or a memory (such as a ROM, a RAM, EEPROM, EPROM, Flash memory or a portable / removable memory device), etc. The transmission medium may be a communications signal, a data broadcast, a communications link between two or more computers, etc.

Claims

CLAIMS1 . A method of quantification, the method comprising: obtaining a first set of mass spectrometry data of a sample, wherein the sample comprises a mix of two or more sub-samples, each sub-sample being labelled with a respective isobaric mass tag and comprising respective amounts of a first analyte and a second analyte, calculating an expected isotopic distribution for the first analyte; determining, from the first set of mass spectrometry data, one or more expected complementary ion doublets of the first analyte, obtaining mass spectrometer output of a fragmented portion of the sample, said portion containing two or more isotopes of the first analyte, applying a windowed super resolution algorithm to the mass spectrometer output to generate a second set of mass spectrometry data, wherein one or more windows of the windowed super resolution algorithm is determined based on the one or more expected complementary ion doublets, and quantifying, based on the expected isotopic distribution for the first analyte, an amount of the second analyte present in a sub-sample, from the second set of mass spectrometry data.

2. The method of claim 1 wherein said quantifying comprises correcting a reporter ion intensity corresponding to the first and second analyte, to remove the contribution of the two or more isotopes of the first analyte.

3. The method of any preceding claim wherein quantifying comprises determining a relative abundance of the second analyte present in the sample.

4. The method of any preceding claim wherein quantifying comprises determining an amount of the second analyte present in the sample.

5. The method of any preceding claim wherein obtaining a first set of mass spectrometry data of a sample comprises operating a mass spectrometer to generate the first set of mass spectrometry data of the sample, and wherein obtaining mass spectrometer output of a fragmented portion of the sample comprises: fragmenting a portion of the sample, the portion containing at least some of the isotopes of the first and second analytes; and generating mass spectrometer output of the fragmented portion of the sample.

6. The method of claim 5 wherein the portion of the sample containing the analyte comprises some or all of the isotopic envelope of the first analyte.

7. The method of any preceding claim wherein the first analyte is a peptide.

8. The method of claim 7 wherein the expected isotopic distribution for the first analyte is calculated based on the peptide sequence.

9. The method of any one of claims 1 -7 wherein the expected isotopic distribution for the first analyte is calculated using an averagine model.

10. A method of quantification, the method comprising: obtaining a first set of mass spectrometry data of a sample, wherein the sample comprises a plurality of isobarically labelled analytes, determining, from the first set of mass spectrometry data, a respective predicted mass of a complementary ion of a selected isobarically labelled analyte of the plurality of isobarically labelled analytes, obtaining mass spectrometer output of a fragmented portion of the sample, said portion containing the selected isobarically labelled analyte,applying a windowed super resolution algorithm to the mass spectrometer output to generate a second set of mass spectrometry data, wherein the window of the windowed super resolution algorithm is determined based on the predicted mass of the complementary ion, and quantifying the analyte present in the sample from the second set of mass spectrometry data.11 . The method of any preceding claim wherein each isobarically labelled analyte is labelled with a respective isobaric mass tag.

12. The method of claim 11 wherein the isobaric mass tags are tandem mass tags or any one or more of: mTRAQ tags; iTRAQ tags;SILAC tags; andMetal-coded Affinity Tags (MeCAT).

13. The method of claim 11 or 12 wherein the complementary ion comprises a balancer region of the isobaric tag attached to the selected analyte.

14. The method of any preceding claim wherein the super resolution algorithm comprises a phase-constrained spectral deconvolution algorithm.

15. The method of any preceding claim the method comprising generating, using a separation device, a mass stream, wherein the sample is a portion of the mass stream.

16. The method of any preceding claim wherein the separation device is a liquid chromatography separation device.

17. The method of any preceding claim wherein the super resolution algorithm is arranged such that peaks having a separation of 0.01 Da are resolved in the second mass spectrometry data.

18. The method of any preceding claim when dependent on claim 10 wherein quantifying comprises determining a relative abundance of the analyte present in the sample.

19. The method of any preceding claim when dependent on claim 10 wherein quantifying comprises determining an amount of the analyte present in the sample.

20. The method of any preceding claim when dependent on claim 10 wherein obtaining a first set of mass spectrometry data of a sample comprises operating a mass spectrometer to generate the first set of mass spectrometry data of the sample, and wherein obtaining mass spectrometer output of a fragmented portion of the sample comprises: fragmenting a portion of the sample, the portion containing said analyte; and generating mass spectrometer output of the fragmented portion of the sample.21 . The method of any preceding claim when dependent on claim 10 wherein the portion of the sample containing the analyte comprises ions selected from the sample having a mass within a range the including mass of the isobarically labelled analyte.

22. The method of any preceding claim when dependent on claim 10 further comprising:selecting one or more further isobarically labelled analytes of the plurality of isobarically labelled analytes for each further isobarically labelled analyte: determining, from the first set of mass spectrometry data, a respective further predicted mass of a complementary ion the further isobarically labelled analyte of the plurality obtaining respective further mass spectrometer output of a further fragmented portion of the sample, said further portion containing the further isobarically labelled analyte, applying the windowed super resolution algorithm to the respective further mass spectrometer output to generate a respective further second set of mass spectrometry data, wherein the window of the windowed super resolution algorithm is determined based on the respective further predicted mass of a complementary ion of the isobaric label of the further analyte; and quantifying the further analyte present in the sample from the respective further second set of mass spectrometry data.

23. The method of any one of claims 10 to 21 when dependent on claim 10, wherein said portion comprises the plurality of analytes, the method further comprising: selecting one or more further isobarically labelled analytes of the plurality of isobarically labelled analytes for each further isobarically labelled analyte: determining, from the first set of mass spectrometry data, a respective further predicted mass of a complementary ion of the further isobarically labelled analyte;applying the windowed super resolution algorithm to the mass spectrometer output to generate a respective further second set of mass spectrometry data, wherein a window of the windowed super resolution algorithm is determined based on the respective further predicted mass of a complementary ion of the further isobarically labelled analyte; and quantifying the further isobarically labelled analyte present in the sample from the respective further second set of mass spectrometry data.

24. An apparatus arranged to carry out a method according to any one of claims 1 to 23.

25. A computer-readable medium storing a computer program which, when executed by a computer, causes the computer to carry out a method according to any one of claims 1 to 23.

Images