Patent Publication Number: US-9905405-B1

Title: Method of generating an inclusion list for targeted mass spectrometric analysis

Description:
FIELD OF THE INVENTION 
     This invention relates to mass spectrometry based quantitation. More specifically, this invention relates to generating an inclusion list for targeted mass spectrometric analysis using results from analysis of corresponding isobarically labeled peptides. 
     BACKGROUND OF THE INVENTION 
     Protein quantitation using mass spectrometry requires integration of sample preparation, instrumentation, and software. Strategies to improve sensitivity and comprehensiveness generally require large sample quantities and multi-dimensional fractionation, which sacrifices throughput. Alternately, efforts to improve the sensitivity and throughput of protein quantification necessarily limit the number of features that can be monitored. For this reason, proteomics research is typically divided into two categories: discovery and targeted proteomics. 
     Discovery proteomics experiments are intended to identify as many proteins as possible across a broad dynamic range. This often requires depletion of highly abundant proteins, enrichment of relevant fractions, and fractionation to decrease sample complexity. 
     Quantitative discovery proteomics experiments often utilize isotopic labeling methods, such as labeling with isobaric tags and isotope-coded affinity tags (ICAT) to quantify the proteins. Isobaric tags, which are commercially available in the form of tandem mass tags (TMT) reagents (sold by Thermo Fisher Scientific) and isobaric tags for relative and absolute quantitation (iTRAQ) reagents (sold by AB Sciex), have been repeatedly demonstrated as a facile means of obtaining relative protein quantitation in both small and large scale proteomics studies while providing the powerful capability of simultaneously comparing up to ten different treatments, time points, or samples. These protein labeling strategies incorporate isotopes into proteins and peptides, resulting in distinct mass shifts but otherwise identical (among peptides labeled with different isotopomers of a reagent set) chemical properties. This allows several samples to be labeled and combined prior to processing and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. This multiplexing reduces sample processing variability, improves specificity by quantifying the proteins from each condition simultaneously, and requires less liquid chromatography-mass spectrometry (LC-MS) and data analysis time. 
     While there is some cost associated with the mass tagging kits, tens of thousands of proteins can be identified and quantified across multiple samples (representing, for example, different disease states) in a highly efficient multiplexed fashion with a single LCMS experiment. Numerous high importance and significantly regulated protein targets of interest often emerge from these studies and become the subject of future routine analyses using highly sensitive and robust targeted techniques, without the added expense or steps of isobaric labeling. 
     Targeted proteomics experiments are typically designed to quantify less than one hundred proteins with very high precision, sensitivity, specificity and throughput. Targeted MS quantitation strategies use specialized workflows and instruments to improve the specificity and quantification of a limited number of features across hundreds or thousands of samples. These methods typically minimize the amount of sample preparation to improve precision and throughput. 
     Targeted quantitative proteomic workflows typically involve protein denaturation, reduction, alkylation, digestion and desalting prior to LC-MS/MS analysis on a mass spectrometer instrument capable of quantifying peptides by monitoring specific mass windows for peptides of interest, fragmenting the isolated peptide(s), and then quantifying several fragment ions that are specific for the peptide of interest. This acquisition strategy, of which selective reaction monitoring (SRM) is a common example, together with chromatographic retention time information, provides very high sensitivity, specificity, dynamic range and throughput. 
     Unfortunately, current workflows suffer from a severe disconnection between isobarically labeled discovery quantitation and routine targeted label-free quantitation of significant peptides. As the isobaric labeling alters not only the mass of the peptide but also its charge (when ionized) and hydrophobicity, targeting a highly regulated peptide from an isobaric experiment is not straightforward. Yet, scheduling of analytes using their retention time is important for reproducible quantitation when the list of targeted peptides grows long. This often necessitates an intermediate validation step using a label-free quantitative technique such as data independent acquisition (DIA) or MS1 based discovery quantitation which can be costly in terms of performance, sample, instrument time, and reagents. While it is possible to use label-free discovery proteomics and then directly transition to targeted routine quantitation of key peptides, multiple serial analyses must be performed to deliver the same information acquired in a single multiplexed isobaric labeling experiment. 
     What is needed is a method and system for translating directly from multiplexed isobaric labeling discovery quantitation to routine label-free targeted quantitation without an intermediate validation step. 
     SUMMARY 
     Methods and systems are disclosed herein for translating the results of an isobaric labeling experiment into an inclusion list for targeted mass spectrometric quantitation. In accordance with one embodiment of the present invention, a method of generating an inclusion list for targeted mass spectrometric analysis is disclosed. The method includes receiving, at a computer, experimentally-acquired data for a plurality of isobarically-labeled peptides of interest. The data includes, for each one of the isobarically-labeled peptides, a mass-to-charge ratio (m/z), a charge state, and a chromatographic retention time. The method also includes determining, via the computer, for each one of the isobarically-labeled peptides, predicted properties for a corresponding unlabeled peptide. The predicted properties include a predicted m/z, a predicted charge state, and a predicted chromatographic retention time. The method further includes storing the predicted properties for each corresponding unlabeled peptide to the inclusion list. The predicted chromatographic retention time for the corresponding unlabeled peptide is determined based on hydrophobicity indices of the isobarically-labeled peptide and the corresponding unlabeled peptide, and chromatographic conditions for the targeted mass spectrometric analysis. 
     In one embodiment, the predicted properties further include a predicted fragment ion m/z. 
     The experimentally-acquired data may also include an amino acid sequence of each peptide. 
     In one embodiment, the predicted chromatographic retention time for the corresponding unlabeled peptide is determined further based on its relation to an experimentally-acquired chromatographic retention time of a reference peptide. The reference peptide can be, but is not limited to, at least one peptide of a peptide retention time calibration (PRTC) mixture. 
     The isobarically-labeled peptides can be, but are not limited to, tandem mass tag (TMT)-labeled peptides, isobaric tags for relative and absolute quantitation (iTRAQ)-labeled peptides, Combinatorial Isobaric Mass Tags (CMTs), or N,N-Dimethylated Leucine (DiLeu) isobaric tags. 
     In one embodiment, the targeted mass spectrometric analysis comprises MS n  quantitation. The MS n  quantitation can be, but is not limited to, parallel reaction monitoring (PRM), selected reaction monitoring (SRM) or synchronous precursor selection (SPS). 
     In one embodiment, the hydrophobicity index of the corresponding unlabeled peptide is calculated using a sequence-specific retention time calculation tool. 
     In another embodiment of the present invention, a method of generating an inclusion list for targeted mass spectrometric analysis is provided. The method includes receiving, at a computer, experimentally-acquired data for a plurality of isobarically-labeled peptides of interest. The data includes, for each one of the isobarically-labeled peptides, a m/z, a charge state, and a chromatographic retention time. The method also includes determining, via the computer, for each one of the isobarically-labeled peptides, predicted properties for a corresponding unlabeled peptide. The predicted properties include a predicted m/z, a predicted charge state, a predicted fragment ion m/z, and a predicted chromatographic retention time. The method further includes storing the predicted properties for each corresponding unlabeled peptide to the inclusion list. The predicted chromatographic retention time for the corresponding unlabeled peptide is determined based on hydrophobicity indices of the isobarically-labeled peptide and the corresponding unlabeled peptide, chromatographic conditions for the targeted mass spectrometric analysis, and on its relation to an experimentally-acquired chromatographic retention time of a reference peptide. 
     In another embodiment of the present invention, a method of translating directly from multiplexed isobaric label quantitation to unlabeled targeted quantitation is provided. The method includes acquiring retention times, charge states, and m/z for a plurality of isobarically-labeled peptides of interest. The method also includes calculating hydrophobicity indices of the isobarically-labeled peptides based on the acquired retention times. The method further includes calculating the hydrophobicity indices of corresponding label-free form of the peptides based on the hydrophobicity indices of the isobarically-labeled peptides. The method also includes determining predicted retention times, m/z values, and charge states for the label-free peptides based on the calculated hydrophobicity indices of the label-free form of the peptides. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows a broad overview of the process for generating an inclusion list for targeted mass spectrometric analysis, in accordance with one embodiment of the present invention. 
         FIG. 2  is a diagram illustrating the workflow involved in generating an inclusion list for targeted mass spectrometric analysis, in accordance with one embodiment of the present invention. 
         FIGS. 3A-3C  are a series of graphs showing a method of generating an inclusion list for targeted mass spectrometric analysis, in accordance with one embodiment of the present invention. 
         FIG. 4  is a flowchart illustrating a method of generating an inclusion for targeted mass spectrometric analysis, in accordance with one embodiment of the present invention 
         FIG. 5  shows the data for generating an inclusion list, beginning with the quantitative results of TMT-labeled peptides of interest to a list of corresponding label-free predicted properties. The experimental retention times for the label-free peptides are shown on the right-most column of the table. 
     
    
    
     DETAILED DESCRIPTION OF EMBODIMENTS 
     Embodiments of the present invention are directed to systems and methods of translating the results of an isobaric labeling experiment directly into an inclusion list for label-free targeted mass spectrometric analysis or quantitation. 
     As used herein, the term “retention time” refers to the time elapsed from when a sample is first introduced into a chromatography column and is eluted from the chromatography column. 
       FIG. 1  shows a broad overview of the process for generating an inclusion list for targeted mass spectrometric analysis, in accordance with one embodiment of the present invention. The first step involves receiving data generated in an isobaric multiplexed discovery quantitation study. Generally described, isobaric multiplexed discovery quantitation experiments involve separately preparing a number of samples, enzymatically digesting the samples to produce cleaved peptides, adding a different reagent from an isobaric labeling reagent set to each one of the samples to label the peptides contained therein, combining the labeled sample, and then analyzing the combined sample by tandem or MSn mass spectrometry. Fragmentation of the co-eluting labeled peptides yields characteristic low-mass reporter ions, with each reporter ion species corresponding to a different one of the combined samples. The reporter ion intensities in the product ion spectra may be used to determine the relative amounts of specific peptides in the samples. In one illustrative example, the samples include a first group of samples extracted from biological tissue or fluids of diseased animals/humans, and a second of samples extracted from biological tissue or fluids of healthy (control) animals/humans, and the experiment is intended to identify peptides that are differentially expressed (i.e., present in higher or lower amounts) in one group relative to another; the identified peptides may be further investigated as biomarker candidates. The spectral data generated by the mass spectrometer is processed by data analysis software (e.g., Proteome Discoverer software from Thermo Fisher Scientific) to provide a list of labeled peptides identified in the samples, and the relative amounts of the labeled peptides across the individual samples. The list will further include, for each labeled peptide, the retention time, precursor ion mass-to-charge ratio (m/z) and charge state. This list may be processed in an automated, semi-automated, or fully manual fashion to select a set of peptides of interest (e.g., those showing a high degree of differentiation between disease and control group samples) for label-free targeted analysis. 
     It should be recognized that while the foregoing example describes labeling peptides produced by proteolytic digestion, other implementations may forego digestion and instead utilize labeling of intact proteins contained in the sample. 
     The peptide list derived by performing a multiplexed discovery quantitation experiment and selecting peptides of interest from the results, as described above, includes properties (retention time, m/z, charge state) measured for the labeled versions of the peptides of interest, i.e., the peptide bonded to a labeling moiety. In order to set up a targeted quantitation experiment to measure label-free peptides, the properties for the label-free versions of the peptides of interest need to be determined. Embodiments of the present invention obviate the need for an intermediate validation step using a label-free quantitative technique such as DIA or MS1 based discovery quantitation, which can be costly in terms of performance, sample, instrument time, and reagents, and permits direct translation from multiplexed discovery quantitation to routine label-free targeted quantitation. 
       FIG. 2  is a diagram illustrating the workflow involved in generating an inclusion list for targeted mass spectrometric analysis, in accordance with one embodiment of the present invention. A multiplexed discovery experiment  10  using isobarically-labeled samples outputs the isobarically-labeled discovery quantitation results  15 . These results comprise but are not limited to a list of identified peptides and corresponding properties (m/z values, charge states, and retention times) determined for the labeled version of the peptides which, in the manned discussed below, may be used to calculate properties to be used for label-free targeted quantitation. 
     When performing a targeted experiment to quantify label-free peptides, it is highly advantageous to reliably predict retention times for the target analytes, such that the instrument may be operated to monitor only those analytes that are expected to elute from the chromatographic column at specific points in chromatographic time. This practice avoids wasting instrument time caused by monitoring transitions corresponding to analytes whose presence would not be expected. 
     The hydrophobicity index, a semi-empirical metric, is one type of retention-time prediction index. A value of the hydrophobicity index may be calculated for each peptide based on the peptide m/z, charge state, and chromatographic retention time. Peptide retention times that are observed in reverse-phase high pressure liquid chromatograph are found to depend on peptide hydrophobicity and can be modeled in terms of the hydrophobicity index. 
     In one embodiment, a hydrophobicity index for each identified and quantified peptide sequence of interest may be calculated using a sequence-specific retention time calculator tool that estimates retention times from the amino acid composition and sequence of a peptide (e.g., the SSRCalc algorithm described in Krokhin, “Sequence-Specific Retention Calculator. Algorithm for Peptide Retention Prediction in Ion-Pair RP-HPLC: Application to 300- and 100-A Pore Size C18 Sorbents, Analytical Chemistry, Vol. 78, No. 22, pp. 7785-95 (2006), which is incorporated herein by reference). An optional external library  20  containing only previously observed charge states for transitions or fragments of these peptides can also be used for determining their predicted retention times  25  but is not required. An inclusion list  30  with peptide parent m/z, charge state, and retention time is supplied to run a targeted quantitation experiment  35 . 
     As noted above, the inclusion list is a compilation or listing of one or more peptides, m/z values, charge states, and retention times which have been identified and selected for MS/MS or MS n  analysis. In a MS n  scan, specific ions detected in a survey scan are selected to enter a collision chamber. The ability to define the ions—by the inclusion list—for MS n  allows data to be acquired for specific precursors. The series of fragments that is generated in the collision chamber is then analyzed again by mass spectrometry, and the resulting spectrum is recorded and may be used to identify the amino acid sequence of the particular peptide. This sequence, together with other information such as the peptide mass, may then be used to identify the protein. The ions subjected to MS n  cycles may be user defined or determined automatically by the spectrometer. 
       FIGS. 3A-3C  are a series of graphs showing a method of generating an inclusion list for targeted mass spectrometric analysis, in accordance with one embodiment of the present invention. 
       FIG. 3A  is a graph showing the experimental retention time vs. hydrophobicity indices (HIs) for isobarically labeled peptides. The HIs for the isobarically labeled peptides—TMT labeled peptides, in this example—were determined by using an equation for linearization of the HI of the TMT labeled peptides and their retention times. In one embodiment, the equation for the linear fit or linearization of the HI is provided on the upper left section of  FIG. 3A . 
       FIG. 3B  is a graph showing the experimental HI values vs. experimental retention times for the isobarically labeled peptides. The experimental HI values for the isobarically labeled peptides (“TMT-HI”) were calculated using the equation in  FIG. 3A  for linearization. The “ΔHI” is the individually adjusted HI index for each TMT labeled peptide which yields an HI index for the unlabeled counterpart peptides (“Unlabeled-HI”). 
       FIG. 3C  is a graph of the predicted retention time vs. HI for the unlabeled peptides. The predicted retention time for the unlabeled peptides were calculated using the equation for linearization as previously determined in  FIG. 3A . 
     In an exemplary application of the methodology described in connection with  FIGS. 3A-3C , a TMT-labeled peptide (or other suitably labeled peptide) identified from the discovery quantitation MS data and having determined to be of interest, such as IVAVTGAEAQK because of its relative quantitation values, is selected for subsequent targeted quantitation. 
     First, the intact mass of the corresponding unlabeled peptide is calculated from its sequence (IVAVTGAEAQK). The molecular weight of each amino acid (I, V, A, V, T, G, A, E, A, Q, G,) in the sequence can be found in any chemical table. The sum of the molecular weights of n amino acids, minus n−1 water molecules, adds up to the intact mass of the unlabeled peptide. Next, the charge state(s) of the unlabeled form of the peptide is (are) predicted based on its sequence or provided by referencing an external database or library such as NIST/EPA/NIH Mass Spectral Library, a peptide repository such as PeptideAtlas, which may be accessed at http://www.peptideatlas.org, or by tools like SSRCalc (http://hs2.proteome.ca/SSRCalc/SSRCalc.html). With the intact mass and expected charge state value, an m/z value for the unlabeled peptide can be readily computed. 
     Subsequently, using the retention time prediction outlined in  FIGS. 3A-3C , a predicted retention time for the unlabeled version of the peptide can be determined. Briefly, the observed retention times for all TMT-labeled peptides identified in the discovery quantitation experiment are plotted against their calculated hydrophobicity index (HI) values (expressed as % ACN). As shown in  FIG. 3A , these values are linearized and then adjusted to give the HI values of the unlabeled counterpart peptides which are less than those of the labeled (TMT) peptides, as seen in  FIG. 3B . From these HI values (expressed in % ACN) for the unlabeled peptides their retention times on a given gradient can be predicted. In  FIG. 3C , these values are linearized using the same equation as for the TMT-labeled peptides determined previously to give the predicted retention time on the same gradient. Together with the m/z value and charge state, there is significant information to build a targeted inclusion list to quantify these peptides by techniques such as PRM. 
     By way of example using the equation for linearization of the HI of the TMT labeled peptides (y=5.2042x+0.4274) and experimental retention time for the TMT-labeled sequence in  FIG. 4 , in one embodiment of the present invention, the HI-labeled for IVAVTGAEAQK is calculated to be approximately 11.45% ACN. From  FIG. 3B , the empirically adjusted HI for the labeled HI is adjusted to give the HI for the unlabeled counterpart peptide which is approximately 5.1210% ACN. Applying the empirically derived linearized equation above for the gradient from the TMP experiment empirically derived TMT: y=5.2042x+0.4274, where y is the predicted retention time (in minutes), x=HI % ACN of the unlabeled peptide, 5.2042 is the slope (retention time empirical/% ACN) and 0.4274 is the delay (in minutes), the predicted retention time=5.2042 (5.1210)+0.4274, which is equal to approximately 27.078. 
     The following illustrates another example of the present invention for predicting the retention time where the TMT linearized equation is not used when the gradient is different. In this example, the gradient time is 60 minutes (Δy=60 minutes), and the initial and final concentrations of ACN are 1 and 31%, respectively (i.e., Δx=30% ACN). The slope=Δy/Δx=60 minutes/30% ACN=2 minutes/% ACN. Using the general equation y=mx+b, where y is the predicted retention time, m is the slope or intercept, x is the HI value for the unlabeled peptide, and b is, in this example, 0.5 minutes for the delay or adjustment in minutes, the predicted retention time (y)=(2 minutes/% ACN)*5.1210% ACN+0.5 minutes, which is approximately 10.74 minutes. 
     In the example of IVAVTGAEAQK, the charge state is predicted to be +2 for the unlabeled peptide, in this case equal to the TMT-labeled counterpart, such that the m/z value for the unlabeled peptide reflects only the mass difference of the TMT label on the N-terminus and lysine. In contrast, a dramatic change in retention time of approximately 35 minutes is predicted for the unlabeled peptide, and the observed retention time (for the unlabeled peptide in label free experiments) is within 90 seconds of this prediction, as shown in the sequence data of  FIG. 5 . 
     It is also important to supply information about the solvent system (e.g., ACN, methanol, water, or an ion pairing agent such as TFA or FA), specifically mobile phase composition to ensure accurate HI calculations. 
       FIG. 4  is a flowchart  400  illustrating the method of generating an inclusion list for targeted mass spectrometric analysis, which was shown in the graphs of  FIGS. 3A-3C , in accordance with one embodiment of the present invention. In step  410 , the HIs for the TMT labeled peptides are calculated and, in step  420 , are linearized by applying a linear fit to experimentally-acquired retention times. In step  430 , the HIs for the TMT labeled peptides are adjusted to account for the absence of the TMT labeling. In other words, the HI index for each TMT labeled peptide is individually adjusted to yield HIs for the corresponding unlabeled counterpart peptides. In step  440 , retention times for the corresponding unlabeled peptides are predicted using the equation for linear fit as previously determined. As a result, these retention times are independent of gradient length, depending only on HI and solvent composition. To further accommodate potentially different chromatographic conditions between the labeled and unlabeled experiments, reference peptides (e.g., PRTC) can be employed as retention time landmarks to refine predicted retention times for disparate gradients. 
     Additional predictive power of the chromatographic retention times for the corresponding unlabeled peptides can be obtained by relation to experimentally-acquired chromatographic retention times of reference peptides. The reference peptides can be, but are not limited to, at least one peptide of a peptide retention time calibration (PRTC) mixtures. The PRTC mixture contains fifteen synthetic heavy peptides mixed at an equimolar ratio that elute across the chromatographic gradient. The observed retention times and hydrophobicity index for these reference peptides may be used to refine the predicted retention times of the unlabeled targeted peptides especially if different chromatography conditions such as column and gradient length are employed. 
     Targeted quantitation experiments may be performed on a variety of mass spectrometer instruments such as, but not limited to, a triple quadrupole, linear ion trap, Orbitrap, or time-of-flight mass spectrometers, using data acquisition techniques which may include Single Ion Monitoring (SIM), Selected Reaction Monitoring (SRM), Parallel Reaction Monitoring (PRM), synchronous precursor selection (SPS), or any such multiplexed MS n  quantitation technique. 
       FIG. 5  shows the data for generating an inclusion list, beginning with the quantitative results of TMT-labeled peptides of interest  40 , including m/z values, charge state, and experimentally observed retention times, to a list of corresponding predicted properties  50 . A comparison between the predicted  50  and experimental  55  results shows that the methods of the present invention provide highly accurate retention time values to enable label-free targeted quantitation. The results of the TMT discovery quantitation experiment in Proteome Discoverer or similar software furnish the requisite information for generation of an inclusion list including but not limited to the peptide sequence, parent m/z value, and charge state(s). Together with the adjusted retention time values from the methods described above and optionally supplemented with information on charge state obtained from a global publically available database containing nearly all human peptides, a complete inclusion list is automatically produced. 
     Prior to commencing a PRM, MRM, or SIM type experiment the inclusion list comprising at a minimum the m/z value and charge state, but also often the retention type of targeted peptides, must be supplied to the mass spectrometer. Scheduling acquisition according to the peptide&#39;s retention time enables the quantitation of significantly more targets. The instrument specific inclusion list is automatically generated by the methods of the present invention. For MRM based quantitation, the inclusion list must also include fragment information, and an additional verification step may be required to determine peptide specific transitions, as the fragmentation pattern can be label specific. 
     The advantages of the present invention include the use of isobarically labeled multiplexed discovery quantitation as a template to build a method for routine and highly sensitive targeted quantitation without the need for additional intensive validation steps or complex libraries containing fragmentation data. Not only are the methods described herein instrument independent, but the present invention also allows for the use of varied chromatography as isobaric labelling is typically run on longer gradients (e.g. 4 hours) while typical label-free targeted experiments use far shorter gradients (e.g. 60 minutes). The present invention also affords the power to adjust for these disparate gradient lengths and or the use of fractionation allowing easy and effective translation from multiplexed discovery quantitation to routine label-free targeted quantitation. 
     The present invention has been described in terms of specific embodiments incorporating details to facilitate the understanding of the principles of construction and operation of the invention. As such, references herein to specific embodiments and details thereof are not intended to limit the scope of the claims appended hereto. It will be apparent to those skilled in the art that modifications can be made in the embodiments chosen for illustration without departing from the spirit and scope of the invention.