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The rise of sample multiplexing in quantitative proteomics for the dissection of complex phenotypic comparisons has been advanced by the development of ever more sensitive and robust instrumentation. Here, we evaluated the utility of the Orbitrap Eclipse Tribrid mass spectrometer (advanced quadrupole filter, optimized FTMS scan overhead) and new instrument control software features (Precursor Fit filtering, TurboTMT and Real-time Peptide Search filtering). Multidimensional comparisons of these novel features increased total peptide identifications by 20% for SPS-MS(3) methods and 14% for HRMS(2) methods. Importantly Real-time Peptide Search filtering enabled a ∼2× throughput improvement for quantification. Across the board, these sensitivity increases were attained without sacrificing quantitative accuracy. New hardware and software features enable more efficient characterization in pursuit of comparative whole proteome insights.

High-field asymmetric waveform ion mobility spectrometry (FAIMS) has gained popularity in the proteomics field for its capability to improve mass spectrometry sensitivity and to decrease peptide co-fragmentation. The recent implementation of FAIMS on Tribrid Orbitrap instruments enhanced proteome coverage and increased the precision of quantitative measurements. However, the FAIMS interface has not been available on older generation Orbitrap mass spectrometers such as the Q-Exactive. Here, we report the integration of the FAIMS Pro device with embedded electrical and gas connections to a Q-Exactive HF mass spectrometer. Proteomic experiments performed on HeLa tryptic digests with the modified mass spectrometer improved signal to noise and reduced interfering ions, resulting in an increase of 42% in peptide identification. FAIMS was also combined with segmented ion fractionation where 100 m/z windows were obtained in turn to further increase the depth of proteome analysis by reducing the proportion of chimeric MS/MS spectra from 50 to 27%. We also demonstrate the application of FAIMS to improve quantitative measurements when using isobaric peptide labeling. FAIMS experiments performed on a two-proteome model revealed that FAIMS Pro provided a 65% improvement in quantification accuracy compared to conventional LC-MS/MS experiments.

Multiplexed, isobaric tagging methods are powerful techniques to increase throughput, precision, and accuracy in quantitative proteomics. The dynamic range and accuracy of quantitation, however, can be limited by coisolation of tag-containing peptides that release reporter ions and conflate quantitative measurements across precursors. Methods to alleviate these effects often lead to the loss of protein and peptide identifications through online or offline filtering of interference containing spectra. To alleviate this effect, high-Field Asymmetric-waveform Ion Mobility Spectroscopy (FAIMS) has been proposed as a method to reduce precursor coisolation and improve the accuracy and dynamic range of multiplex quantitation. Here we tested the use of FAIMS to improve quantitative accuracy using previously established TMT-based interference standards (triple-knockout [TKO] and Human-Yeast Proteomics Resource [HYPER]). We observed that FAIMS robustly improved the quantitative accuracy of both high-resolution MS(2) (HRMS(2)) and synchronous precursor selection MS(3) (SPS-MS(3))-based methods without sacrificing protein identifications. We further optimized and characterized the main factors that enable robust use of FAIMS for multiplexed quantitation. We highlight these factors and provide method recommendations to take advantage of FAIMS technology to improve isobaric-tag-quantification moving forward.

The depth of proteomic analyses is often limited by the overwhelming proportion of confounding background ions that compromise the identification and quantification of low abundance peptides. To alleviate these limitations, we present a new high field asymmetric waveform ion mobility spectrometry (FAIMS) interface that can be coupled to the Orbitrap Tribrid mass spectrometers. The interface provides several advantages over previous generations of FAIMS devices, including ease of operation, robustness, and high ion transmission. Replicate LC-FAIMS-MS/MS analyses (n = 100) of HEK293 protein digests showed stable ion current over extended time periods with uniform peptide identification on more than 10,000 distinct peptides. For complex tryptic digest analyses, the coupling of FAIMS to LC-MS/MS enabled a 30% gain in unique peptide identification compared with non-FAIMS experiments. Improvement in sensitivity facilitated the identification of low abundance peptides, and extended the limit of detection by almost an order of magnitude. The reduction in chimeric MS/MS spectra using FAIMS also improved the precision and the number of quantifiable peptides when using isobaric labeling with tandem mass tag (TMT) 10-plex reagent. We compared quantitative proteomic measurements for LC-MS/MS analyses performed using synchronous precursor selection (SPS) and LC-FAIMS-MS/MS to profile the temporal changes in protein abundance of HEK293 cells following heat shock for periods up to 9 h. FAIMS provided 2.5-fold increase in the number of quantifiable peptides compared with non-FAIMS experiments (30,848 peptides from 2,646 proteins for FAIMS versus 12,400 peptides from 1,229 proteins with SPS). Altogether, the enhancement in ion transmission and duty cycle of the new FAIMS interface extended the depth and comprehensiveness of proteomic analyses and improved the precision of quantitative measurements.

We describe ProteomeTools, a project building molecular and digital tools from the human proteome to facilitate biomedical research. Here we report the generation and multimodal liquid chromatography-tandem mass spectrometry analysis of >330,000 synthetic tryptic peptides representing essentially all canonical human gene products, and we exemplify the utility of these data in several applications. The resource (available at http://www.proteometools.org) will be extended to >1 million peptides, and all data will be shared with the community via ProteomicsDB and ProteomeXchange.

Multiplexed quantitative analyses of complex proteomes enable deep biological insight. While a multitude of workflows have been developed for multiplexed analyses, the most quantitatively accurate method (SPS-MS3) suffers from long acquisition duty cycles. We built a new, real-time database search (RTS) platform, Orbiter, to combat the SPS-MS3 method’s longer duty cycles. RTS with Orbiter enables the elimination of SPS-MS3 scans if no peptide matches to a given spectrum. With Orbiter’s online proteomic analytical pipeline, which includes RTS and false discovery rate analysis, it was possible to process a single spectrum database search in less than 10 milliseconds. The result is a fast, functional means to identify peptide spectral matches using Comet, filter these matches, and more efficiently quantify proteins of interest. Importantly, the use of Comet for peptide spectral matching allowed for a fully featured search, including analysis of post-translational modifications, with well-known and extensively validated scoring. These data could then be used to trigger subsequent scans in an adaptive and flexible manner. In this work we tested the utility of this adaptive data acquisition platform to improve the efficiency and accuracy of multiplexed quantitative experiments. We found that RTS enabled a 2-fold increase in mass spectrometric data acquisition efficiency. Orbiter’s RTS was able to quantify more than 8000 proteins across 10 proteomes in half the time of an SPS-MS3 analysis (18 hours for RTS, 36 hours for SPS-MS3).

We describe a new method to accomplish multiplexed, absolute protein quantification in a targeted fashion. The approach draws upon the recently developed neutron encoding (NeuCode) metabolic labeling strategy and parallel reaction monitoring (PRM). Since PRM scanning relies upon high-resolution tandem mass spectra for targeted protein quantification, incorporation of multiple NeuCode labeled peptides permits high levels of multiplexing that can be accessed from high-resolution tandem mass spectra. Here we demonstrate this approach in cultured cells by monitoring a viral infection and the corresponding viral protein production over many infection time points in a single experiment. In this context the NeuCode PRM combination affords up to 30 channels of quantitative information in a single MS experiment.

Intact protein sequencing by tandem mass spectrometry (MS/MS), known as top-down protein sequencing, relies on efficient gas-phase fragmentation at multiple experimental conditions to achieve extensive amino acid sequence coverage. We developed the "topdownr" R-package for automated construction of multi-modal (i.e. involving CID, HCD, ETD, ETciD, EThcD and UVPD) MS/MS fragmentation methods on an orbitrap instrument platform and systematic analysis of the resultant spectra. We used topdownr to generate and analyze thousands of MS/MS spectra for five intact proteins of 10 - 30kDa. We achieved 90-100% coverage for the proteins tested and derived guiding principles for efficient sequencing of intact proteins. The data analysis workflow and statistical models of topdownr software and multi-modal MS/MS experiments provide a framework for optimizing MS/MS sequencing for any intact protein. Refined topdownr software will be suited for comprehensive characterization of protein pharmaceuticals and eventually also for de novo sequencing and detailed characterization of intact proteins.

Liquid chromatography (LC) prefractionation is often implemented to increase proteomic coverage; however, while effective, this approach is laborious, requires considerable sample amount, and can be cumbersome. We describe how interfacing a recently described high-field asymmetric waveform ion mobility spectrometry (FAIMS) device between a nanoelectrospray ionization (nanoESI) emitter and an Orbitrap hybrid mass spectrometer (MS) enables the collection of single-shot proteomic data with comparable depth to that of conventional two-dimensional LC approaches. This next generation FAIMS device incorporates improved ion sampling at the ESI-FAIMS interface, increased electric field strength, and a helium-free ion transport gas. With fast internal compensation voltage (CV) stepping (25 ms/transition), multiple unique gas-phase fractions may be analyzed simultaneously over the course of an MS analysis. We have comprehensively demonstrated how this device performs for bottom-up proteomics experiments as well as characterized the effects of peptide charge state, mass loading, analysis time, and additional variables. We also offer recommendations for the number of CVs and which CVs to use for different lengths of experiments. Internal CV stepping experiments increase protein identifications from a single-shot experiment to >8000, from over 100 000 peptide identifications in as little as 5 h. In single-shot 4 h label-free quantitation (LFQ) experiments of a human cell line, we quantified 7818 proteins with FAIMS using intra-analysis CV switching compared to 6809 without FAIMS. Single-shot FAIMS results also compare favorably with LC fractionation experiments. A 6 h single-shot FAIMS experiment generates 8007 protein identifications, while four fractions analyzed for 1.5 h each produce 7776 protein identifications.

Gas chromatography-mass spectrometry (GC/MS) has long been considered one of the premiere analytical tools for small molecule analysis. Recently, a number of GC/MS systems equipped with high-resolution mass analyzers have been introduced. These systems provide analysts with a new dimension of information – accurate mass measurement to the third or fourth decimal place; however, existing data processing tools do not capitalize on this information. Beyond that, GC/MS spectral reference libraries, which have been curated over the last several decades, contain almost exclusively unit resolution MS spectra making integration of accurate mass data dubious. Here we present an informatic approach, called High-Resolution Filtering (HRF), which bridges this gap. During HRF, high-resolution mass spectra are assigned putative identifications through traditional spectral matching at unit resolution. Once candidate identities have been assigned, all unique combinations of atoms from these candidate precursors are generated and matched to m/z peaks using narrow mass tolerances. The total amount of measured signal that is annotated is used as a metric of plausibility for the presumed identification. Here we demonstrate that the HRF approach is both feasible and highly specific towards correct identifications.

Recent advances in chromatography and mass spectrometry (MS) have made rapid and deep proteomic profiling possible. To maximize the performance of the recently produced Orbitrap hybrid mass spectrometer, we have developed a protocol that combines improved sample preparation (including optimized cellular lysis by extensive bead beating) and chromatographic conditions (specifically, 30-cm capillary columns packed with 1.7-μm bridged ethylene hybrid material) and the manufacture of a column heater (to accommodate flow rates of 350–375 nl/min) that increases the number of proteins identified across a single liquid chromatography–tandem MS (LC-MS/MS) separation, thereby reducing the need for extensive sample fractionation. This strategy allowed the identification of up to 4,002 proteins (at a 1% false discovery rate (FDR)) in yeast (Saccharomyces cerevisiae strain BY4741) over 70 min of LC-MS/MS analysis. Quintuplicate analysis of technical replicates reveals 83% overlap at the protein level, thus demonstrating the reproducibility of this procedure. This protocol, which includes cell lysis, overnight tryptic digestion, sample analysis and database searching, takes ~24 h to complete. Aspects of this protocol, including chromatographic separation and instrument parameters, can be adapted for the optimal analysis of other organisms.

We have developed a multiplexed quantitative analysis method for carboxylic acids by liquid chromatography high resolution mass spectrometry. The method employs neutron encoded (NeuCode) methylamine labels ((13)C or (15)N enriched) that are affixed to carboxylic acid functional groups to enable duplex quantitation via mass defect measurement. This work presents the first application of NeuCode quantitation to small molecules. We have applied this technique to detect adulteration of olive oil by quantitative analysis of fatty acid methyl amide derivatives, and the quantitative accuracy of the NeuCode analysis was validated by GC/MS. Currently, the method enables duplex quantitation and is expandable to at least 6-plex analysis.

A mass spectrometry (MS) method is described here that can reproducibly identify hundreds of peptides across multiple experiments. The method uses intelligent data acquisition to precisely target peptides while simultaneously identifying thousands of other, nontargeted peptides in a single nano-LC–MS/MS experiment. We introduce an online peptide elution order alignment algorithm that targets peptides based on their relative elution order, eliminating the need for retention-time-based scheduling. We have applied this method to target 500 mouse peptides across six technical replicate nano-LC–MS/MS experiments and were able to identify 440 of these in all six, compared with only 256 peptides using data-dependent acquisition (DDA). A total of 3757 other peptides were also identified within the same experiment, illustrating that this hybrid method does not eliminate the novel discovery advantages of DDA. The method was also tested on a set of mice in biological quadruplicate and increased the number of identified target peptides in all four mice by over 80% (826 vs 459) compared with the standard DDA method. We envision real-time data analysis as a powerful tool to improve the quality and reproducibility of proteomic data sets.

We describe the comprehensive analysis of the yeast proteome in just over one hour of optimized analysis. We achieve this expedited proteome characterization with improved sample preparation, chromatographic separations, and by using a new Orbitrap hybrid mass spectrometer equipped with a mass filter, a collision cell, a high-field Orbitrap analyzer, and, finally, a dual cell linear ion trap analyzer (Q-OT-qIT, Orbitrap Fusion). This system offers high MS(2) acquisition speed of 20 Hz and detects up to 19 peptide sequences within a single second of operation. Over a 1.3 h chromatographic method, the Q-OT-qIT hybrid collected an average of 13,447 MS(1) and 80,460 MS(2) scans (per run) to produce 43,400 (x) peptide spectral matches and 34,255 (x) peptides with unique amino acid sequences (1% false discovery rate (FDR)). On average, each one hour analysis achieved detection of 3,977 proteins (1% FDR). We conclude that further improvements in mass spectrometer scan rate could render comprehensive analysis of the human proteome within a few hours.

We describe a novel amine-reactive chemical label that exploits differential neutron-binding energy between (13)C and (15)N isotopes. These neutron-encoded (NeuCode) chemical labels enable up to 12-plex MS1-based protein quantification. Each structurally identical, but isotopically unique, tag is encoded with a 12.6-mDa mass difference-relative to its nearest neighbor-so that peptides bearing these NeuCode signatures do not increase spectral complexity and are detected only upon analysis with very high mass-resolving powers. We demonstrate that the method provides quantitative performance that is comparable to both metabolic labeling and isobaric tagging while combining the benefits of both strategies. Finally, we employ the tags to characterize the proteome of Saccharomyces cerevisiae during the diauxic shift, a metabolic transition from fermentation to aerobic respiration.

Metabolic labeling of cells using heavy amino acids is most commonly used for relative quantitation; however, partner mass shifts also detail the number of heavy amino acids contained within the precursor species. Here, we use a recently developed metabolic labeling technique, NeuCode (neutron encoding) stable isotope labeling with amino acids in cell culture (SILAC), which produces precursor partners spaced ~40 mDa apart to enable amino acid counting. We implement large scale counting of amino acids through a program, "Amino Acid Counter", which determines the most likely combination of amino acids within a precursor based on NeuCode SILAC partner spacing and filters candidate peptide sequences during a database search using this information. Counting the number of lysine residues for precursors selected for MS/MS decreases the median number of candidate sequences from 44 to 14 as compared to an accurate mass search alone (20 ppm). Furthermore, the ability to co-isolate and fragment NeuCode SILAC partners enables counting of lysines in product ions, and when the information is used, the median number of candidates is reduced to 7. We then demonstrate counting leucine in addition to lysine results in a 6-fold decrease in search space, 43 to 7, when compared to an accurate mass search. We use this scheme to analyze a nanoLC-MS/MS experiment and demonstrate that accurate mass plus lysine and leucine counting reduces the number of candidate sequences to one for ~20% of all precursors selected, demonstrating an ability to identify precursors without MS/MS analysis.

SummaryMitochondria are dynamic organelles that play a central role in a diverse array of metabolic processes. Elucidating mitochondrial adaptations to changing metabolic demands and the pathogenic alterations that underlie metabolic disorders represent principal challenges in cell biology. Here, we performed multiplexed quantitative mass spectrometry-based proteomics to chart the remodeling of the mouse liver mitochondrial proteome and phosphoproteome during both acute and chronic physiological transformations in more than 50 mice. Our analyses reveal that reversible phosphorylation is widespread in mitochondria, and is a key mechanism for regulating ketogenesis during the onset of obesity and type 2 diabetes. Specifically, we have demonstrated that phosphorylation of a conserved serine on Hmgcs2 (S456) significantly enhances its catalytic activity in response to increased ketogenic demand. Collectively, our work describes the plasticity of this organelle at high resolution and provides a framework for investigating the roles of proteome restructuring and reversible phosphorylation in mitochondrial adaptation.

We have developed and implemented a sequence identification algorithm ( inSeq ) that processes tandem mass spectra in real-time using the mass spectrometer’s (MS) onboard processors. The inSeq algorithm relies on accurate mass tandem MS data for swift spectral matching with high accuracy. The instant spectral processing technology takes ∼16 ms to execute and provides information to enable autonomous, real-time decision making by the MS system. Using inSeq and its advanced decision tree logic, we demonstrate ( i ) real-time prediction of peptide elution windows en masse (∼3 min width, 3,000 targets), ( ii ) significant improvement of quantitative precision and accuracy (~3x boost in detected protein differences), and ( iii ) boosted rates of posttranslation modification site localization (90% agreement in real-time vs. offline localization rate and an approximate 25% gain in localized sites). The decision tree logic enabled by inSeq promises to circumvent problems with the conventional data-dependent acquisition paradigm and provides a direct route to streamlined and expedient targeted protein analysis.

Combining high-mass-accuracy mass spectrometry, isobaric tagging and software for multiplexed, large-scale protein quantification, we report deep proteomic coverage of four human embryonic stem cell and four induced pluripotent stem cell lines in biological triplicate. This 24-sample comparison resulted in a very large set of identified proteins and phosphorylation sites in pluripotent cells. The statistical analysis afforded by our approach revealed subtle but reproducible differences in protein expression and protein phosphorylation between embryonic stem cells and induced pluripotent cells. Merging these results with RNA-seq analysis data, we found functionally related differences across each tier of regulation. We also introduce the Stem Cell-Omics Repository (SCOR), a resource to collate and display quantitative information across multiple planes of measurement, including mRNA, protein and post-translational modifications.

Here we present the Coon OMSSA Proteomic Analysis Software Suite (COMPASS): a free and open-source software pipeline for high-throughput analysis of proteomics data, designed around the Open Mass Spectrometry Search Algorithm. We detail a synergistic set of tools for protein database generation, spectral reduction, peptide false discovery rate analysis, peptide quantitation via isobaric labeling, protein parsimony and protein false discovery rate analysis, and protein quantitation. We strive for maximum ease of use, utilizing graphical user interfaces and working with data files in the original instrument vendor format. Results are stored in plain text comma-separated value files, which are easy to view and manipulate with a text editor or spreadsheet program. We illustrate the operation and efficacy of COMPASS through the use of two LC-MS/MS data sets. The first is a data set of a highly annotated mixture of standard proteins and manually validated contaminants that exhibits the identification workflow. The second is a data set of yeast peptides, labeled with isobaric stable isotope tags and mixed in known ratios, to demonstrate the quantitative workflow. For these two data sets, COMPASS performs equivalently or better than the current de facto standard, the Trans-Proteomic Pipeline.

Single-molecule tracking algorithms and analyses that use particle trajectory information rely on the accurate determination of particle positions to produce a meaningful interpretation of molecular dynamics. However, artifacts arising from vibration can sometimes distort or entirely mask the processes being studied. Here we describe a straightforward implementation of the Lucas-Kanade stabilization algorithm that can remove the impact of instrument-related vibrations on molecular diffusion measurements after a data set has been collected. Using fluorescently derivatized αHL on supported lipid bilayers in conjunction with computer simulations of 2D diffusion, we report that post-hoc stabilization can be effective in removing both simple and complex noise sources. The effectiveness of vibration mitigation is a function of the relationship between the vibration amplitude and the magnitude of the diffusion constant. For diffusion constants in the range of typical membrane proteins (e.g., 10−9 to 10−...

We describe a synthesis strategy for the preparation of lysine isotopologues that differ in mass by as little as 6 mDa. We demonstrate that incorporation of these molecules into the proteomes of actively growing cells does not affect cellular proliferation, and we discuss how to use the embedded mass signatures (neutron encoding (NeuCode)) for multiplexed proteome quantification by means of high-resolution mass spectrometry. NeuCode SILAC amalgamates the quantitative accuracy of SILAC with the multiplexing of isobaric tags and, in doing so, offers up new opportunities for biological investigation. We applied NeuCode SILAC to examine the relationship between transcript and protein levels in yeast cells responding to environmental stress. Finally, we monitored the time-resolved responses of five signaling mutants in a single 18-plex experiment.

The ability to acquire highly accurate quantitative data is an increasingly important part of any proteomics experiment, whether shotgun or top-down approaches are used. We recently developed a quantitation strategy for peptides based on neutron encoding, or NeuCode SILAC, which uses closely spaced heavy isotope-labeled amino acids and high-resolution mass spectrometry to provide quantitative data. We reasoned that the strategy would also be applicable to intact proteins and could enable robust, multiplexed quantitation for top-down experiments. We used yeast lysate labeled with either (13)C6(15)N2-lysine or (2)H8-lysine, isotopologues of lysine that are spaced 36 mDa apart. Proteins having such close spacing cannot be distinguished during a medium resolution scan, but upon acquiring a high-resolution scan, the two forms of the protein with each amino acid are resolved and the quantitative information revealed. An additional benefit NeuCode SILAC provides for top down is that the spacing of the isotope peaks indicates the number of lysines present in the protein, information that aids in identification. We used NeuCode SILAC to quantify several hundred isotope distributions, manually identify and quantify proteins from 1:1, 3:1, and 5:1 mixed ratios, and demonstrate MS(2)-based quantitation using ETD.

Summary Calorie restriction (CR) extends life span in diverse species. Mitochondria play a key role in CR adaptation; however, the molecular details remain elusive. We developed and applied a quantitative mass spectrometry method to probe the liver mitochondrial acetyl-proteome during CR versus control diet in mice that were wild-type or lacked the protein deacetylase SIRT3. Quantification of 3,285 acetylation sites—2,193 from mitochondrial proteins—rendered a comprehensive atlas of the acetyl-proteome and enabled global site-specific, relative acetyl occupancy measurements between all four experimental conditions. Bioinformatic and biochemical analyses provided additional support for the effects of specific acetylation on mitochondrial protein function. Our results (1) reveal widespread reprogramming of mitochondrial protein acetylation in response to CR and SIRT3, (2) identify three biochemically distinct classes of acetylation sites, and (3) provide evidence that SIRT3 is a prominent regulator in CR adaptation by coordinately deacetylating proteins involved in diverse pathways of metabolism and mitochondrial maintenance.

We describe a protein quantification method called neutron encoding that exploits the subtle mass differences caused by nuclear binding energy variation in stable isotopes. These mass differences are synthetically encoded into amino acids and incorporated into yeast and mouse proteins via metabolic labeling. Mass spectrometry analysis with high mass resolution (>200,000) reveals the isotopologue-embedded peptide signals, permitting quantification. Neutron encoding will enable highly multiplexed proteome analysis with excellent dynamic range and accuracy.

Selected reaction monitoring on a triple quadrupole mass spectrometer is currently experiencing a renaissance within the proteomics community for its, as yet, unparalleled ability to characterize and quantify a set of proteins reproducibly, completely, and with high sensitivity. Given the immense benefit that high resolution and accurate mass instruments have brought to the discovery proteomics field, we wondered if highly accurate mass measurement capabilities could be leveraged to provide benefits in the targeted proteomics domain as well. Here, we propose a new targeted proteomics paradigm centered on the use of next generation, quadrupole-equipped high resolution and accurate mass instruments: parallel reaction monitoring (PRM). In PRM, the third quadrupole of a triple quadrupole is substituted with a high resolution and accurate mass mass analyzer to permit the parallel detection of all target product ions in one, concerted high resolution mass analysis. We detail the analytical performance of the PRM method, using a quadrupole-equipped bench-top Orbitrap MS, and draw a performance comparison to selected reaction monitoring in terms of run-to-run reproducibility, dynamic range, and measurement accuracy. In addition to requiring minimal upfront method development and facilitating automated data analysis, PRM yielded quantitative data over a wider dynamic range than selected reaction monitoring in the presence of a yeast background matrix because of PRM's high selectivity in the mass-to-charge domain. With achievable linearity over the quantifiable dynamic range found to be statistically equal between the two methods, our investigation suggests that PRM will be a promising new addition to the quantitative proteomics toolbox.

Peptide sequencing by computational assignment of tandem mass spectra to a database of putative protein sequences provides an independent approach to confirming or refuting protein predictions based on large-scale DNA and RNA sequencing efforts. This use of mass spectrometrically-derived sequence data for testing and refining predicted gene models has been termed proteogenomics. We report herein the application of proteogenomic methodology to a database of 10.9 million tandem mass spectra collected over a period of two years from proteolytically generated peptides isolated from the model legume Medicago truncatula. These spectra were searched against a database of predicted M. truncatula protein sequences generated from public databases, in silico gene model predictions, and a whole-genome six-frame translation. This search identified 78,647 distinct peptide sequences, and a comparison with the publicly available proteome from the recently published M. truncatula genome supported translation of 9,843 existing gene models and identified 1,568 novel peptides suggesting corrections or additions to the current annotations. Each supporting and novel peptide was independently validated using mRNA-derived deep sequencing coverage and an overall correlation of 93% between the two data types was observed. We have additionally highlighted examples of several aspects of structural annotation for which tandem MS provides unique evidence not easily obtainable through typical DNA or RNA sequencing. Proteogenomic analysis is a valuable and unique source of information for the structural annotation of genomes and should be included in such efforts to ensure that the genome models used by biologists mirror as accurately as possible what is present in the cell.

Symbiotic associations between legumes and rhizobia usually commence with the perception of bacterial lipochitooligosaccharides, known as Nod factors (NF), which triggers rapid cellular and molecular responses in host plants. We report here deep untargeted tandem mass spectrometry-based measurements of rapid NF-induced changes in the phosphorylation status of 13,506 phosphosites in 7739 proteins from the model legume Medicago truncatula. To place these phosphorylation changes within a biological context, quantitative phosphoproteomic and RNA measurements in wild-type plants were compared with those observed in mutants, one defective in NF perception (nfp) and one defective in downstream signal transduction events (dmi3). Our study quantified the early phosphorylation and transcription dynamics that are specifically associated with NF-signaling, confirmed a dmi3-mediated feedback loop in the pathway, and suggested “cryptic” NF-signaling pathways, some of them being also involved in the response to symbiotic arbuscular mycorrhizal fungi.

We implemented negative electron-transfer dissociation (NETD) on a hybrid ion trap/Orbitrap mass spectrometer to conduct ion/ion reactions using peptide anions and radical reagent cations. In addition to sequence-informative ladders of a•- and x-type fragment ions, NETD generated intense neutral loss peaks corresponding to the entire or partial side-chain cleavage from amino acids constituting a given peptide. Thus, a critical step towards the characterization of this recently introduced fragmentation technique is a systematic study of synthetic peptides to identify common neutral losses and preferential fragmentation pathways. Examining 46 synthetic peptides with high mass accuracy and high resolution analysis permitted facile determination of the chemical composition of each neutral loss. We identified 19 unique neutral losses from 14 amino acids and three modified amino acids, and assessed the specificity and sensitivity of each neutral loss using a database of 1542 confidently identified peptides generated from NETD shotgun experiments employing high-pH separations and negative electrospray ionization. As residue-specific neutral losses indicate the presence of certain amino acids, we determined that many neutral losses have potential diagnostic utility. We envision this catalogue of neutral losses being incorporated into database search algorithms to improve peptide identification specificity and to further advance characterization of the acidic proteome.

Electron transfer dissociation (ETD) is an alternative peptide dissociation method developed in recent years. Compared with the traditional collision induced dissociation (CID) b and y ion formation, ETD generates c and z ions and the backbone cleavage is believed to be less selective. We have reported previously the application of a statistical data mining strategy, K-means clustering, to discover fragmentation patterns for CID, and here we report application of this approach to ETD spectra. We use ETD data sets from digestions with three different proteases. Data analysis shows that selective cleavages do exist for ETD, with the fragmentation patterns affected by protease, charge states, and amino acid residue compositions. It is also noticed that the c(n-1) ion, corresponding to loss of the C-terminal amino acid residue, is statistically strong regardless of the residue at the C-terminus of the peptide, which suggests that the peptide gas phase conformation plays an important role in the dissociation pathways. These patterns provide a basis for mechanism elucidation, spectral prediction, and improvement of ETD peptide identification algorithms.