Combining low- and high-energy tandem mass spectra for optimized peptide quantification with isobaric tags

Isobaric tagging, via TMT or iTRAQ, is widely used in quantitative proteomics. To date, tandem mass spectrometric analysis of isobarically-labeled peptides with hybrid ion trap–orbitrap (LTQ-OT) instruments has been mainly carried out with higher-energy C-trap dissociation (HCD) or pulsed q dissociation (PQD). HCD provides good fragmentation of the reporter-ions, but peptide sequence-ion recovery is generally poor compared to collision-induced dissociation (CID). Herein, we describe an approach where CID and HCD spectra are combined. The approach ensures efficiently both identification and relative quantification of proteins. Tandem mass tags (TMTs) were used to label digests of human plasma and LC-MS/MS was performed with an LTQ-OT instrument. Different HCD collision energies were tested. The benefits to use CID and HCD with respect to HCD alone were demonstrated in terms of number of identifications, subsequent number of quantifiable proteins, and quantification accuracy. A program was developed to merge the peptide sequence-ion m/z range from CID spectra and the reporter-ion m/z range from HCD spectra, and alternatively to separate both spectral data into different files. As parallel CID in the LTQ almost doesn't affect the analysis duty cycle, the procedure should become a standard for quantitative analyses of proteins with isobaric tagging using LTQ-OT instruments.     

Precursor-ion mass re-estimation improves peptide identification on hybrid instruments

Mass spectrometry-based proteomics experiments have become an important tool for studying biological systems. Identifying the proteins in complex mixtures by assigning peptide fragmentation spectra to peptide sequences is an important step in the proteomics process. The 1-2 ppm mass-accuracy of hybrid instruments, like the LTQ-FT, has been cited as a key factor in their ability to identify a larger number of peptides with greater confidence than competing instruments. However, in replicate experiments of an 18-protein mixture, we note parent masses deviate 171 ppm, on average, for ion-trap data directed identifications and 8 ppm, on average, for preview Fourier transform (FT) data directed identifications. These deviations are neither caused by poor calibration nor by excessive ion-loading and are most likely due to errors in parent mass estimation. To improve these deviations, we introduce msPrefix, a program to re-estimate a peptide's parent mass from an associated high-accuracy full-scan survey spectrum. In 18-protein mixture experiments, msPrefix parent mass estimates deviate only 1 ppm, on average, from the identified peptides. In a cell lysate experiment searched with a tolerance of 50 ppm, 2295 peptides were confidently identified using native data and 4560 using msPrefixed data. Likewise, in a plasma experiment searched with a tolerance of 50 ppm, 326 peptides were identified using native data and 1216 using msPrefixed data. msPrefix is also able to determine which MS/MS spectra were possibly derived from multiple precursor ions. In complex mixture experiments, we demonstrate that more than 50% of triggered MS/MS may have had multiple precursor ions and note that spectra with multiple candidate ions are less likely to result in an identification using TANDEM. These results demonstrate integration of msPrefix into traditional shotgun proteomics workflows significantly improves identification results.     

Optimization and use of peptide mass measurement accuracy in shotgun proteomics

Mass spectrometers that provide high mass accuracy such as FT-ICR instruments are increasingly used in proteomic studies. Although the importance of accurately determined molecular masses for the identification of biomolecules is generally accepted, its role in the analysis of shotgun proteomic data has not been thoroughly studied. To gain insight into this role, we used a hybrid linear quadrupole ion trap/FT-ICR (LTQ FT) mass spectrometer for LC-MS/MS analysis of a highly complex peptide mixture derived from a fraction of the yeast proteome. We applied three data-dependent MS/MS acquisition methods. The FT-ICR part of the hybrid mass spectrometer was either not exploited, used only for survey MS scans, or also used for acquiring selected ion monitoring scans to optimize mass accuracy. MS/MS data were assigned with the SEQUEST algorithm, and peptide identifications were validated by estimating the number of incorrect assignments using the composite target/decoy database search strategy. We developed a simple mass calibration strategy exploiting polydimethylcyclosiloxane background ions as calibrant ions. This strategy allowed us to substantially improve mass accuracy without reducing the number of MS/MS spectra acquired in an LC-MS/MS run. The benefits of high mass accuracy were greatest for assigning MS/MS spectra with low signal-to-noise ratios and for assigning phosphopeptides. Confident peptide identification rates from these data sets could be doubled by the use of mass accuracy information. It was also shown that improving mass accuracy at a cost to the MS/MS acquisition rate substantially lowered the sensitivity of LC-MS/MS analyses. The use of FT-ICR selected ion monitoring scans to maximize mass accuracy reduced the number of protein identifications by 40%.     

Characterization of a high field Orbitrap mass spectrometer for proteome analysis

The field of proteomics continues to be driven by improvements in analytical technology, notably in peptide separation, quantitative MS, and informatics. In this study, we have characterized a hybrid linear ion trap high field Orbitrap mass spectrometer (Orbitrap Elite) for proteomic applications. The very high resolution available on this instrument allows 95% of all peptide masses to be measured with sub‐ppm accuracy that in turn improves protein identification by database searching. We further confirm again that mass accuracy in tandem mass spectra is a valuable parameter for improving the success of protein identification. The new CID rapid scan type of the Orbitrap Elite achieves similar performance as higher energy collision induced dissociation fragmentation and both allow the identification of hundreds of proteins from as little as 0.1 ng of protein digest on column. The new instrument outperforms its predecessor the Orbitrap Velos by a considerable margin on each metric assessed that makes it a valuable and versatile tool for MS‐based proteomics.     

A tool to evaluate correspondence between extraction ion chromatographic peaks and peptide‐spectrum matches in shotgun proteomics experiments

Chromatographed peptide signals form the basis of further data processing that eventually results in functional information derived from data‐dependent bottom‐up proteomics assays. We seek to rank LC/MS parent ions by the quality of their extracted ion chromatograms. Ranked extracted ion chromatograms act as an intuitive physical/chemical preselection filter to improve the quality of MS/MS fragment scans submitted for database search. We identify more than 4900 proteins when considering detector shifts of less than 7 ppm. High quality parent ions for which the database search yields no hits become candidates for subsequent unrestricted analysis for PTMs. Following this rational approach, we prioritize identification of more than 5000 spectrum matches from modified peptides and confirmed the presence of acetylaldehyde‐modified His/Lys. We present a logical workflow that scores data‐dependent selected ion chromatograms and leverage information about semianalytical LC/LC dimension prior to MS. Our method can be successfully used to identify unexpected modifications in peptides with excellent chromatography characteristics, independent of fragmentation pattern and activation methods. We illustrate analysis of ion chromatograms detected in two different modes by RF linear ion trap and electrostatic field orbitrap.     

Top-down protein sequencing and MS3 on a hybrid linear quadrupole ion trap-orbitrap mass spectrometer

Top-down proteomics, the analysis of intact proteins (instead of first digesting them to peptides), has the potential to become a powerful tool for mass spectrometric protein characterization. Requirements for extremely high mass resolution, accuracy, and ability to efficiently fragment large ions have often limited top-down analyses to custom built FT-ICR mass analyzers. Here we explore the hybrid linear ion trap (LTQ)-Orbitrap, a novel, high performance, and compact mass spectrometric analyzer, for top-down proteomics. Protein standards from 10 to 25 kDa were electrosprayed into the instrument using a nanoelectrospray chip. Resolving power of 60,000 was ample for isotope resolution of all protein charge states. We achieved absolute mass accuracies for intact proteins between 0.92 and 2.8 ppm using the "lock mass" mode of operation. Fifty femtomole of cytochrome c applied to the chip resulted in spectra with excellent signal-to-noise ratio and only low attomole sample consumption. Different protein charge states were dissociated in the LTQ, and the sensitivity of the orbitrap allowed routine, high resolution, and high mass accuracy fragment detection. This resulted in unambiguous charge state determination of fragment ions and identification of unmodified and modified proteins by database searching. Protein fragments were further isolated and fragmented in the LTQ followed by analysis of MS(3) fragments in the orbitrap, localizing modifications to part of the sequence and helping to identify the protein with these small peptide-like fragments. Given the ready availability and ease of operation of the LTQ-Orbitrap, it may have significant impact on top-down proteomics.     

Liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometric characterization of protein kinase C phosphorylation

A vented column, capillary liquid chromatography (LC) microelectrospray ionization (ESI) Fourier transform ion cyclotron resonance (FT-ICR (9.4 T)) mass spectrometry (MS) approach to phosphopeptide identification is described. A dual-ESI source capable of rapid (approximately 200 ms) switching between two independently controlled ESI emitters was constructed. The dual-ESI source, combined with external ion accumulation in a linear octopole ion trap, allowed for internal calibration of every mass spectrum during LC. LC ESI FT-ICR positive-ion MS of protein kinase C (PKC) revealed four previously unidentified phosphorylated peptides (one within PKC(alpha), one within PKC(delta), and two within PKC(zeta)). Internal calibration improved the mass accuracy for LC MS spectra from an absolute mean (47 peptide ions) of 11.5 ppm to 1.5 ppm. Five additional (out of eight known) activating sites of PKC phosphorylation, not detected in positive-ion experiments, were observed by subsequent negative-ion direct infusion nanoelectrospray. Extension of the method to enable infrared multiphoton dissociation of all ions in the ICR cell prior to every other mass measurement revealed the diagnostic neutral loss of H3PO4 from phosphorylated peptide ions. The combination of accurate-mass MS and MS/MS offers a powerful new tool for identifying the presence and site(s) of phosphorylation in peptides, without the need for additional wet chemical derivatization.     

Postexperiment monoisotopic mass filtering and refinement (PE-MMR) of tandem mass spectrometric data increases accuracy of peptide identification in LC/MS/MS

Methods for treating MS/MS data to achieve accurate peptide identification are currently the subject of much research activity. In this study we describe a new method for filtering MS/MS data and refining precursor masses that provides highly accurate analyses of massive sets of proteomics data. This method, coined "postexperiment monoisotopic mass filtering and refinement" (PE-MMR), consists of several data processing steps: 1) generation of lists of all monoisotopic masses observed in a whole LC/MS experiment, 2) clusterization of monoisotopic masses of a peptide into unique mass classes (UMCs) based on their masses and LC elution times, 3) matching the precursor masses of the MS/MS data to a representative mass of a UMC, and 4) filtration of the MS/MS data based on the presence of corresponding monoisotopic masses and refinement of the precursor ion masses by the UMC mass. PE-MMR increases the throughput of proteomics data analysis, by efficiently removing "garbage" MS/MS data prior to database searching, and improves the mass measurement accuracies (i.e. 0.05 +/- 1.49 ppm for yeast data (from 4.46 +/- 2.81 ppm) and 0.03 +/- 3.41 ppm for glycopeptide data (from 4.8 +/- 7.4 ppm)) for an increased number of identified peptides. In proteomics analyses of glycopeptide-enriched samples, PE-MMR processing greatly reduces the degree of false glycopeptide identification by correctly assigning the monoisotopic masses for the precursor ions prior to database searching. By applying this technique to analyses of proteome samples of varying complexities, we demonstrate herein that PE-MMR is an effective and accurate method for treating massive sets of proteomics data.     

Trade-off between high sensitivity and increased potential for false positive peptide sequence matches using a two-dimensional linear ion trap for tandem mass spectrometry-based proteomics

Two-dimensional linear ion trap mass spectrometers are rapidly becoming the new workhorse instruments for shotgun proteomic analysis of complex peptide mixtures. The objective of this study was to compare the potential for false positive peptide sequence matches between a two-dimensional ion trap instrument and a traditional, three-dimensional ion trap instrument. Through the comparative analysis of a complex protein sample, we found that in order to minimize false positive sequence matches, sequence match scoring criteria must be more stringent for data from the two-dimensional ion trap compared to the three-dimensional ion trap data. Given this increased potential for false positives, we also investigated two potential filtering strategies to reduce the false positive matches for data derived from the two-dimensional ion trap, including trypsin enzyme cleavage filtering, and the addition of peptide physicochemical information as a constraint, specifically peptide isoelectric point. The results described here provide a cautionary tale to researchers, demonstrating the need for careful analysis of MS/MS data from this new class of ion trap instruments, as well as the effectiveness of trypsin enzyme cleavage filtering and peptide pI information in maximizing high confidence protein identifications from this powerful proteomic instrumentation.     

Identification of tryptic peptides from large databases using multiplexed tandem mass spectrometry: simulations and experimental results

Multiplexed tandem mass spectrometry (MS/MS) has recently been demonstrated as a means to increase the throughput of peptide identification in liquid chromatography (LC) MS/MS experiments. In this approach, a set of parent species is dissociated simultaneously and measured in a single spectrum (in the same manner that a single parent ion is conventionally studied), providing a gain in sensitivity and throughput proportional to the number of species that can be simultaneously addressed. In the present work, simulations performed using the Caenorhabditis elegans predicted proteins database show that multiplexed MS/MS data allow the identification of tryptic peptides from mixtures of up to ten peptides from a single dataset with only three "y" or "b" fragments per peptide and a mass accuracy of 2.5 to 5 ppm. At this level of database and data complexity, 98% of the 500 peptides considered in the simulation were correctly identified. This compares favorably with the rates obtained for classical MS/MS at more modest mass measurement accuracy. LC multiplexed Fourier transform-ion cyclotron resonance MS/MS data obtained from a 66 kDa protein (bovine serum albumin) tryptic digest sample are presented to illustrate the approach, and confirm that peptides can be effectively identified from the C. elegans database to which the protein sequence had been appended.     

MyriMatch: highly accurate tandem mass spectral peptide identification by multivariate hypergeometric analysis

Shotgun proteomics experiments are dependent upon database search engines to identify peptides from tandem mass spectra. Many of these algorithms score potential identifications by evaluating the number of fragment ions matched between each peptide sequence and an observed spectrum. These systems, however, generally do not distinguish between matching an intense peak and matching a minor peak. We have developed a statistical model to score peptide matches that is based upon the multivariate hypergeometric distribution. This scorer, part of the "MyriMatch" database search engine, places greater emphasis on matching intense peaks. The probability that the best match for each spectrum has occurred by random chance can be employed to separate correct matches from random ones. We evaluated this software on data sets from three different laboratories employing three different ion trap instruments. Employing a novel system for testing discrimination, we demonstrate that stratifying peaks into multiple intensity classes improves the discrimination of scoring. We compare MyriMatch results to those of Sequest and X!Tandem, revealing that it is capable of higher discrimination than either of these algorithms. When minimal peak filtering is employed, performance plummets for a scoring model that does not stratify matched peaks by intensity. On the other hand, we find that MyriMatch discrimination improves as more peaks are retained in each spectrum. MyriMatch also scales well to tandem mass spectra from high-resolution mass analyzers. These findings may indicate limitations for existing database search scorers that count matched peaks without differentiating them by intensity. This software and source code is available under Mozilla Public License at this URL: http://www.mc.vanderbilt.edu/msrc/bioinformatics/.     

Unique scanning capabilities of a new hybrid linear ion trap mass spectrometer (Q TRAP) used for high sensitivity proteomics applications

The unique scanning capabilities of a hybrid linear ion trap (Q TRAP) mass spectrometer are described with an emphasis on proteomics applications. The combination of the very selective triple quadrupole based tandem mass spectrometry (MS/MS) scans with the very sensitive ion trap product ion scans allows rapid identification of peptides at low concentrations derived from post-translationally modified proteins on chromatographic time scales. The Q TRAP instrument also offers the opportunity to conduct a variety of ion processing steps prior to performing a mass scan. For example, the enhancement of the multiple-charge ion contents of the ion trap can be performed resulting in a survey mass spectrum dominated by double- and triple-charge peptides. This facilitates the identification of relevant biological species in both separated and unseparated peptide mixtures for further MS/MS experiments.     

Charge state estimation for tandem mass spectrometry proteomics

High-throughput protein analysis by tandem mass spectrometry produces anywhere from thousands to millions of spectra that are being used for peptide and protein identifications. Though each spectrum corresponds only to one charged peptide (ion) state, repetitive database searches of multiple charge states are typically conducted since the resolution of many common mass spectrometers is not sufficient to determine the charge state. The resulting database searches are both error-prone and time-consuming. We describe a straightforward, accurate approach on charge state estimation (CHASTE). CHASTE relies on fragment ion peak distributions, and by using reliable logistic regression models, combines different measurements to improve its accuracy. CHASTE's performance has been validated on data sets, comprised of known peptide dissociation spectra, obtained by replicate analyses of our earlier developed protein standard mixture using ion trap mass spectrometers at different laboratories. CHASTE was able to reduce number of needed database searches by at least 60% and the number of redundant searches by at least 90% virtually without any informational loss. This greatly alleviates one of the major bottlenecks in high throughput peptide and protein identifications. Thresholds and parameter estimates can be tailored to specific analysis situations, pipelines, and instrumentations. CHASTE was implemented in Java GUI-based and command-line-based interfaces.     

iTRAQ reagent-based quantitative proteomic analysis on a linear ion trap mass spectrometer

For proteomic analysis using tandem mass spectrometry, linear ion trap instruments provide unsurpassed sensitivity but unreliably detect low mass peptide fragments, precluding their use with iTRAQ reagent-labeled samples. Although the popular LTQ linear ion trap supports analyzing iTRAQ reagent-labeled peptides via pulsed Q dissociation, PQD, its effectiveness remains questionable. Using a standard mixture, we found careful tuning of relative collision energy necessary for fragmenting iTRAQ reagent-labeled peptides, and increasing microscan acquisition and repeat count improves quantification but identifies somewhat fewer peptides. We developed software to calculate abundance ratios via summing reporter ion intensities across spectra matching to each protein, thereby providing maximized accuracy. Testing found that results closely corresponded between analysis using optimized LTQ-PQD settings plus our software and using a Qstar instrument. Thus, we demonstrate the effectiveness of LTQ-PQD analyzing iTRAQ reagent-labeled peptides, and provide guidelines for successful quantitative proteomic studies.     

Systematic characterization of high mass accuracy influence on false discovery and probability scoring in peptide mass fingerprinting

Whereas the bearing of mass measurement error on protein identification is sometimes underestimated, uncertainty in observed peptide masses unavoidably translates to ambiguity in subsequent protein identifications. Although ongoing instrumental advances continue to make high accuracy mass spectrometry (MS) increasingly accessible, many proteomics experiments are still conducted with rather large mass error tolerances. In addition, the ranking schemes of most protein identification algorithms do not include a meaningful incorporation of mass measurement error. This article provides a critical evaluation of mass error tolerance as it pertains to false positive peptide and protein associations resulting from peptide mass fingerprint (PMF) database searching. High accuracy, high resolution PMFs of several model proteins were obtained using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FTICR-MS). Varying levels of mass accuracy were simulated by systematically modulating the mass error tolerance of the PMF query and monitoring the effect on figures of merit indicating the PMF quality. Importantly, the benefits of decreased mass error tolerance are not manifest in Mowse scores when operating at tolerances in the low parts-per-million range but become apparent with the consideration of additional metrics that are often overlooked. Furthermore, the outcomes of these experiments support the concept that false discovery is closely tied to mass measurement error in PMF analysis. Clear establishment of this relation demonstrates the need for mass error-aware protein identification routines and argues for a more prominent contribution of high accuracy mass measurement to proteomic science.     

Higher-energy C-trap dissociation for peptide modification analysis

Peptide sequencing is the basis of mass spectrometry-driven proteomics. Here we show that in the linear ion trap-orbitrap mass spectrometer (LTQ Orbitrap) peptide ions can be efficiently fragmented by high-accuracy and full-mass-range tandem mass spectrometry (MS/MS) via higher-energy C-trap dissociation (HCD). Immonium ions generated via HCD pinpoint modifications such as phosphotyrosine with very high confidence. Additionally we show that an added octopole collision cell facilitates de novo sequencing.     

Intensity-based protein identification by machine learning from a library of tandem mass spectra

Tandem mass spectrometry (MS/MS) has emerged as a cornerstone of proteomics owing in part to robust spectral interpretation algorithms. Widely used algorithms do not fully exploit the intensity patterns present in mass spectra. Here, we demonstrate that intensity pattern modeling improves peptide and protein identification from MS/MS spectra. We modeled fragment ion intensities using a machine-learning approach that estimates the likelihood of observed intensities given peptide and fragment attributes. From 1,000,000 spectra, we chose 27,000 with high-quality, nonredundant matches as training data. Using the same 27,000 spectra, intensity was similarly modeled with mismatched peptides. We used these two probabilistic models to compute the relative likelihood of an observed spectrum given that a candidate peptide is matched or mismatched. We used a 'decoy' proteome approach to estimate incorrect match frequency, and demonstrated that an intensity-based method reduces peptide identification error by 50-96% without any loss in sensitivity.     

Identification of phosphorylation sites of proteins by high performance liquid chromatography-electrospray ionization-quadrupole ion trap mass spectrometry

The phosphorylation sites of two phosphorylated proteins, bovine β-casein and myelin basic protein (MBP), were identified by high performance liquid chromatography-electrospray ionization-quadrupole ion trap mass spectrometry (HPLC-ESI-QITMS). The tryptic digest of each protein was separated by HPLC, the molecular weight of each peptide was determined by ESI-QITMS on line, and MS/MS spectrum of each peptide was simultaneously obtained by the combination of collision-induced desorption (CID) technique and tandem mass spectrometry (MS/MS) of QITMS. The phosphorylated peptide was identified by looking into whether the difference between the observed and predicted molecular weights of a peptide is 80 u or its integral multiple. Then the phosphorylation site was identified through manual interpretation of the MS/MS spectrum of the phosphorylated peptide or automatic SEQUEST data base-searching.     

Identification of phosphorylation sites of proteins by high performance liquid chromatography-electrospray ionization-quadrupole ion trap mass spectrometry

The phosphorylation sites of two phosphorylated proteins, bovine β-casein and myelin basic protein (MBP), were identified by high performance liquid chromatography-electrospray ionization-quadrupole ion trap mass spectrometry (HPLC-ESI-QITMS). The tryptic digest of each protein was separated by HPLC, the molecular weight of each peptide was determined by ESI-QITMS on line, and MS/MS spectrum of each peptide was simultaneously obtained by the combination of collision-induced desorption (CID) technique and tandem mass spectrometry (MS/MS) of QITMS. The phosphorylated peptide was identified by looking into whether the difference between the observed and predicted molecular weights of a peptide is 80 u or its integral multiple. Then the phosphorylation site was identified through manual interpretation of the MS/MS spectrum of the phosphorylated peptide or automatic SEQUEST data base-searching.     

SALAMI (Spectrum ALignments using high Accuracy Mass and hIgh sensitivity data): how to make the best out of hybrid MS/MS data

We present a software algorithm that combines ion trap and orbitrap product ion spectra acquired in parallel. The hybrid product ion spectra identify more peptides than when using two separate searches for the orbitrap and LTQ data. The program extracts the high-accuracy mass data from the Orbitrap mass analyzer and combines it with the high-sensitivity data analyzed in the LTQ linear ion trap; the m/z values of the high-confidence fragment ions are corrected to orbitrap mass accuracies and the fragment ion intensities are amplified. This approach utilizes the parallel spectrum measurement capabilities of the LTQ-Orbitrap. We present our approach to handling this type of hybrid data, explain our alignment program, and discuss the advantages of the chosen methodology.