Data-independent tandem mass spectrometry isolates and fragments all of the molecular species within a given mass-to-charge window, regardless of whether a precursor ion was detected within the window. For shotgun proteomics on complex protein mixtures, data-independent MS/MS offers certain advantages over the traditional data-dependent MS/MS: identification of low-abundance peptides with insignificant precursor peaks; more direct relative quantification, free of biases caused by competing precursors and dynamic exclusion; and faster throughput due to simultaneous fragmentation of multiple peptides. However, data-independent MS/MS, especially on low-resolution ion-trap instruments, strains standard peptide identification programs, because of less precise knowledge of the peptide precursor mass and large numbers of spectra composed of two or more peptides. Here we describe a computer program called DeMux that deconvolves mixture spectra and improves the peptide identification rate by ~25%. We compare the number of identifications made by data-independent and data-dependent MS/MS at the peptide and protein levels: conventional data-dependent MS/MS makes a greater number of identifications but is less reproducible from run to run.

We report the implementation of front-end higher energy collision induced dissociation (fHCD) on a bench-top dual pressure linear ion trap. Software and hardware modifications were employed, described in detail vide-infra, to allow isolated ions to undergo collisions with ambient gas molecules in an intermediate multipole (q00) of the instrument. Results comparing the performance of fHCD and resonance excitation collision induced dissociation (RE-CID) in terms of injection time, total number of scans, efficiency, mass measurement accuracy (MMA), unique peptide identifications, and spectral quality of labile modified peptides are presented. fHCD is approximately 23% as efficient as RE-CID and, depending on the search algorithm, it identifies 6.6% more or 15% less peptides (q<0.01) from a soluble whole-cell lysate (Caenorhabditis elegans) than RE-CID using Mascot or Sequest search algorithms, respectively. fHCD offers a clear advantage for the analysis of phosphorylated and glycosylated (O-GlcNAc) peptides as the average cross-correlation score (XCorr) for spectra using fHCD was statistically greater (p<0.05) than for spectra collected using RE-CID.

Filter aided sample preparation (FASP) and a new sample preparation method using a modified commercial SDS removal spin column are quantitatively compared in terms of their performance for shotgun proteomic experiments in three complex proteomic samples: a Saccharomyces cerevisiae lysate (insoluble fraction), a Caenorhabditis elegans lysate (soluble fraction), and a human embryonic kidney cell line (HEK293T). The characteristics and total number of peptides and proteins identified are compared between the two procedures. The SDS spin column procedure affords a conservative 4-fold improvement in throughput, is more reproducible, less expensive (i.e., requires less materials), and identifies between 30–107% more peptides at a q≤0.01, than the FASP procedure. The peptides identified by SDS spin column are more hydrophobic than species identified by the FASP procedure as indicated by the distribution of GRAVY scores. Ultimately, these improvements correlate to as great as a 50% increase in protein identifications with 2 or more peptides.

Aims

We investigate the role of mitochondrial oxidative stress in mitochondrial proteome remodelling using mouse models of heart failure induced by pressure overload.

Methods and results

We demonstrate that mice overexpressing catalase targeted to mitochondria (mCAT) attenuate pressure overload-induced heart failure. An improved method of label-free unbiased analysis of the mitochondrial proteome was applied to the mouse model of heart failure induced by transverse aortic constriction (TAC). A total of 425 mitochondrial proteins were compared between wild-type and mCAT mice receiving TAC or sham surgery. The changes in the mitochondrial proteome in heart failure included decreased abundance of proteins involved in fatty acid metabolism, an increased abundance of proteins in glycolysis, apoptosis, mitochondrial unfolded protein response and proteolysis, transcription and translational control, and developmental processes as well as responses to stimuli. Overexpression of mCAT better preserved proteins involved in fatty acid metabolism and attenuated the increases in apoptotic and proteolytic enzymes. Interestingly, gene ontology analysis also showed that monosaccharide metabolic processes and protein folding/proteolysis were only overrepresented in mCAT but not in wild-type mice in response to TAC.

Conclusion

This is the first study to demonstrate that scavenging mitochondrial reactive oxygen species (ROS) by mCAT not only attenuates most of the mitochondrial proteome changes in heart failure, but also induces a subset of unique alterations. These changes represent processes that are adaptive to the increased work and metabolic requirements of pressure overload, but which are normally inhibited by overproduction of mitochondrial ROS.

There are ongoing events where aircraft engine lubricant containing tricresyl phosphates (TCPs) contaminates aircraft cabins. Some individuals have experienced tremors or other neurological symptoms that may last for many months following exposures. Mass spectrometric (MS) protocols are being developed to determine the percentage of “biomarker proteins” that are modified by such exposures, specifically on active site serines. Both plasma butyrylcholinesterase (BChE) and red cell acylpeptide hydrolase (APH) are readily inhibited by 2-(o-cresyl)-4H-1:3:2:benzodioxaphosphoran-2-one (CBDP) or phenyl saligenin cyclic phosphate (PSP) and have the potential to provide information about the level of exposure of an individual. We have developed immunomagnetic bead-based single-step purification protocols for both BChE and APH and have characterized the active site serine adducts of BChE by MS.

We report a method for high-throughput, cost-efficient empirical discovery of optimal proteotypic peptides and fragment ions for targeted proteomics applications using in vitro-synthesized proteins. We demonstrate the approach using human transcription factors – which are typically difficult, low-abundance – targets with an overall success rate of 98%. We show further that targeted proteomic assays developed using our approach facilitate robust in vivo quantification of human transcription factors.

High field asymmetric waveform ion mobility spectrometry (FAIMS) has been used increasingly in recent years as an additional method of ion separation and selection prior to mass spectrometry. The FAIMS electrodes are relatively simple to design and fabricate for laboratories wishing to implement their own FAIMS designs. However, construction of the electronics apparatus needed to produce the required high magnitude asymmetric electric field oscillating at a frequency of several hundred kilohertz is not trivial. Here we present an entirely custom-built electronics setup capable of supplying the required waveforms and voltages. The apparatus is relatively simple and inexpensive to implement. We also present data acquired on this system demonstrating the use of FAIMS as a gas phase ion filter interface to an ion trap mass spectrometer.

High-throughput proteomics experiments involving tandem mass spectrometry produce large volumes of complex data that require sophisticated computational analyses. As such, the field offers many challenges for computational biologists. In this article, we briefly introduce some of the core computational and statistical problems in the field and then describe a variety of outstanding problems that readers of PLoS Computational Biology might be able to help solve.

Proteomics experiments based on Selected Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) are being used to target large numbers of protein candidates in complex mixtures. At present, instrument parameters are often optimized for each peptide, a time and resource intensive process. Large SRM experiments are greatly facilitated by having the ability to predict MS instrument parameters that work well with the broad diversity of peptides they target. For this reason, we investigated the impact of using simple linear equations to predict the collision energy (CE) on peptide signal intensity and compared it with the empirical optimization of the CE for each peptide and transition individually. Using optimized linear equations, the difference between predicted and empirically derived CE values was found to be an average gain of only 7.8% of total peak area. We also found that existing commonly used linear equations fall short of their potential, and should be recalculated for each charge state and when introducing new instrument platforms. We provide a fully automated pipeline for calculating these equations and individually optimizing CE of each transition on SRM instruments from Agilent, Applied Biosystems, Thermo-Scientific and Waters in the open source Skyline software tool (http://proteome.gs.washington.edu/software/skyline).

Selected reaction monitoring (SRM) is a powerful tandem mass spectrometry method that can be used to monitor target peptides within a complex protein digest. The specificity and sensitivity of the approach, as well as its capability to multiplex the measurement of many analytes in parallel, has made it a technology of particular promise for hypothesis driven proteomics. An underappreciated step in the development of an assay to measure many peptides in parallel is the time and effort necessary to establish a usable assay. Here we report the use of shotgun proteomics data to expedite the selection of SRM transitions for target peptides of interest. The use of tandem mass spectrometry data acquired on an LTQ ion trap mass spectrometer can accurately predict which fragment ions will produce the greatest signal in an SRM assay using a triple quadrupole mass spectrometer. Furthermore, we present a scoring routine that can compare the targeted SRM chromatogram data with an MS/MS spectrum acquired by data-dependent acquisition and stored in a library. This scoring routine is invaluable in determining which signal in the chromatogram from a complex mixture best represents the target peptide. These algorithmic developments have been implemented in a software package that is available from the authors upon request.

Summary

Proper centromere function is critical to maintain genomic stability and to prevent aneuploidy, a hallmark of tumors and birth defects. A conserved feature of all eukaryotic centromeres is an essential histone H3 variant called CENP-A that requires a centromere targeting domain (CATD) for its localization. Although proteolysis prevents CENP-A from mislocalizing to euchromatin, regulatory factors have not been identified. Here, we identify an E3 ubiquitin ligase called Psh1 that leads to the degradation of Cse4, the budding yeast CENP-A homolog. Cse4 overexpression is toxic to psh1Δ cells and results in euchromatic localization. Strikingly, the Cse4 centromere targeting domain is a key regulator of its stability and helps Psh1 discriminate Cse4 from histone H3. Taken together, we propose that the CATD has a previously unknown role in maintaining the exclusive localization of Cse4 by preventing its mislocalization to euchromatin via Psh1-mediated degradation.

The identification of peptides by microcapillary liquid chromatography-tandem mass spectrometry (µLC-MS/MS) has become routine because of the development of fast scanning mass spectrometers, data-dependent acquisition, and database searching algorithms. However, many peptides within the detection limit of the mass spectrometer remain unidentified because of limitations in MS/MS sampling speed despite the dynamic range and peak capacity of the instrument. We have developed an automated approach that uses the mass spectra from high resolution µLC-MS data to define the molecular species present in the mixture and directs the acquisition of MS/MS spectra to precursors that were missed in prior analyses. This approach increases the coverage of the molecular species sampled by MS/MS and consequently the number of peptides and proteins identified during the acquisition of technical or biological replicates using a simple one-dimensional chromatographic separation. The combination of a unique workflow and custom software contribute to the improved identification of molecular features detected in proteomics experiments of complex protein mixtures.

Proteomics experiments on complex mixtures have benefited greatly from the advent of fast-scanning ion trap mass spectrometers. However, the complexity and dynamic range of mixtures analyzed using shotgun proteomics is still beyond what can be sampled by data-dependent acquisition. Furthermore, the total liquid chromatography-mass spectrometry (LC-MS) peak capacity is not sufficient to resolve the precursors within these mixtures, let alone acquire tandem mass spectra on all of them. Here we describe the application of a high-field asymmetric waveform ion mobility spectrometry (FAIMS) device as an interface to an ion trap mass spectrometer. The dynamic range and peak capacity of the nanoflow LC-FAIMS-MS analysis was assessed using a complex tryptic digest of S. cerevisiae proteins. By adding this relatively simple device to the front of the mass spectrometer, we obtain an increase in peak capacity >8 fold and an increase in dynamic range of >5 fold, without increasing the length of the LC-MS analysis. Thus, the addition of FAIMS to the front of a table top mass spectrometer can obtain the peak capacity of multidimensional protein identification technology (MudPIT) while increasing the throughput by a factor of 12.

The problem of identifying proteins from a shotgun proteomics experiment has not been definitively solved. Identifying the proteins in a sample requires ranking them, ideally with interpretable scores. In particular, “degenerate” peptides, which map to multiple proteins, have made such a ranking difficult to compute. The problem of computing posterior probabilities for the proteins, which can be interpreted as confidence in a protein’s presence, has been especially daunting. Previous approaches have either ignored the peptide degeneracy problem completely, addressed it by computing a heuristic set of proteins or heuristic posterior probabilities, or by estimating the posterior probabilities with sampling methods. We present a probabilistic model for protein identification in tandem mass spectrometry that recognizes peptide degeneracy. We then introduce graph-transforming algorithms that facilitate efficient computation of protein probabilities, even for large data sets. We evaluate our identification procedure on five different well-characterized data sets and demonstrate our ability to efficiently compute high-quality protein posteriors.

Electron-transfer dissociation (ETD) induces fragmentation along the peptide backbone by transferring an electron from a radical anion to a protonated peptide. In contrast with collision induced dissociation, side chains and modifications such as phosphorylation are left intact through the ETD process. Because the precursor charge state is an important input to MS/MS sequence database search tools, the ability to accurately determine the precursor charge is helpful for the identification process. Furthermore, because ETD can be applied to large, highly charged peptides, the need for accurate precursor charge state determination is magnified. Otherwise, each spectrum must be searched repeatedly using a large range of possible precursor charge states. To address this problem, we have developed an ETD charge state prediction tool based on support vector machine classifiers that is demonstrated to exhibit superior classification accuracy while minimizing the overall number of predicted charge states. The tool is freely available, open source, cross platform compatible, and demonstrated to perform well when compared with an existing charge state prediction tool. The program is available from http://code.google.com/p/etdz/.

Knowledge of protein structures and protein-protein interactions is essential for understanding of biological processes. Recent advances in protein crosslinking and mass spectrometry (MS) have shown significant potential to contribute to this area. Here we report a novel method to rapidly and accurately identify crosslinked peptides based on their unique isotope signature when digested in the presence of H218O. This method overcomes the need for specially synthesized crosslinkers and/or multiple MS runs required by other techniques. We validated our method by performing a ‘blind’ analysis of 5 proteins/complexes of known structure. Side chain repacking calculations using Rosetta show that 17 of our 20 positively identified crosslinks fit the published atomic structures. The remaining 3 crosslinks are likely due to protein aggregation. The accuracy and rapid throughput of our workflow will advance the use of protein crosslinking in structural biology.

The Purkinje cell degeneration (pcd) mouse is a recessive model of neurodegeneration, involving cerebellum and retina. Purkinje cell death in pcd is dramatic, as >99% of Purkinje neurons are lost in three weeks. Loss-of-function of Nna1 causes pcd, and Nna1 is a highly conserved zinc carboxypeptidase. To determine the basis of pcd, we implemented a two-pronged approach, combining characterization of loss-of-function phenotypes of the Drosophila Nna1 orthologue (NnaD) with proteomics analysis of pcd mice. Reduced NnaD function yielded larval lethality, with survivors displaying phenotypes that mirror disease in pcd. Quantitative proteomics revealed expression alterations for glycolytic and oxidative phosphorylation enzymes. Nna proteins localize to mitochondria, loss of NnaD / Nna1 produces mitochondrial abnormalities, and pcd mice display altered proteolytic processing of Nna1 interacting proteins. Our studies indicate that Nna1 loss-of-function results in altered bioenergetics and mitochondrial dysfunction, and suggest that pcd shares pathogenic features with neurodegenerative disorders such as Parkinson's disease.

Background

Seminal fluid plays an important role in successful fertilization, but knowledge of the full suite of proteins transferred from males to females during copulation is incomplete. The list of ejaculated proteins remains particularly scant in one of the best-studied mammalian systems, the house mouse (Mus domesticus), where artificial ejaculation techniques have proven inadequate. Here we investigate an alternative method for identifying ejaculated proteins, by isotopically labeling females with 15N and then mating them to unlabeled, vasectomized males. Proteins were then isolated from mated females and identified using mass spectrometry. In addition to gaining insights into possible functions and fates of ejaculated proteins, our study serves as proof of concept that isotopic labeling is a powerful means to study reproductive proteins.

Results

We identified 69 male-derived proteins from the female reproductive tract following copulation. More than a third of all spectra detected mapped to just seven genes known to be structurally important in the formation of the copulatory plug, a hard coagulum that forms shortly after mating. Seminal fluid is significantly enriched for proteins that function in protection from oxidative stress and endopeptidase inhibition. Females, on the other hand, produce endopeptidases in response to mating. The 69 ejaculated proteins evolve significantly more rapidly than other proteins that we previously identified directly from dissection of the male reproductive tract.

Conclusion

Our study attempts to comprehensively identify the proteins transferred from males to females during mating, expanding the application of isotopic labeling to mammalian reproductive genomics. This technique opens the way to the targeted monitoring of the fate of ejaculated proteins as they incubate in the female reproductive tract.

Advances in Fourier transform mass spectrometry have made the acquisition of high-resolution and accurate mass measurements routine on a chromatographic time-scale. Here we report an algorithm, Hardklör, for the rapid and robust analysis of high resolution mass spectra acquired in shotgun proteomics experiments. Our algorithm is demonstrated in the analysis of an Escherichia coli enriched membrane fraction. The mass spectrometry data of the respective peptides are acquired by micro-capillary HPLC on an LTQ-Orbitrap mass spectrometer with data-dependent acquisition of MS/MS spectra. Hardklör detects 211,272 total peptide isotope distributions over a two hour analysis (75 min gradient) in only a small fraction of the time required to acquire the data. From these data there are 13,665 distinct, chromatographically persistent peptide isotope distributions. Hardklör is also used to assess the quality of the product ion spectra and finds that more than 11.2% of the MS/MS spectra are composed of fragment ions from multiple different molecular species. Additionally, a method is reported that enzymatically labels N-linked glycosylation sites on proteins, creating a unique isotope signature that can be detected with Hardklör. Using the protein invertase, Hardklör identifies 18O-labeled peptide isotope distributions of four glycosylation sites. The speed and robustness of the algorithm create a versatile tool that can be used in many different areas of mass spectrometry data analysis.

Summary: Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools.

Availability: Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.

Contact: brendanx@u.washington.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

A major challenge for core facilities is determining quantitative protein differences across complex biological samples. Although there are numerous techniques in the literature for relative and absolute protein quantification, the majority is nonroutine and can be challenging to carry out effectively. There are few studies comparing these technologies in terms of their reproducibility, accuracy, and precision, and no studies to date deal with performance across multiple laboratories with varied levels of expertise. Here, we describe an Association of Biomolecular Resource Facilities (ABRF) Proteomics Research Group (PRG) study based on samples composed of a complex protein mixture into which 12 known proteins were added at varying but defined ratios. All of the proteins were present at the same concentration in each of three tubes that were provided. The primary goal of this study was to allow each laboratory to evaluate its capabilities and approaches with regard to: detection and identification of proteins spiked into samples that also contain complex mixtures of background proteins and determination of relative quantities of the spiked proteins. The results returned by 43 participants were compiled by the PRG, which also collected information about the strategies used to assess overall performance and as an aid to development of optimized protocols for the methodologies used. The most accurate results were generally reported by the most experienced laboratories. Among laboratories that used the same technique, values that were closer to the expected ratio were obtained by more experienced groups.

We describe a method to measure protein synthesis and catabolism in humans without prior purification and use the method to measure the turnover of surfactant protein-B (SP-B). SP-B, a lung-specific, hydrophobic protein essential for fetal-neonatal respiratory transition, is present in only picomolar quantities in tracheal aspirate samples and difficult to isolate for dynamic turnover studies using traditional in vivo tracer techniques. Using infusion of [5,5,5-2H3] leucine and a targeted proteomics method, we measured both the quantity and kinetics of SP-B tryptic peptides in tracheal aspirate samples of symptomatic newborn infants. The fractional synthetic rate (FSR) of SP-B measured using the most abundant proteolytic fragment, a 10 amino acid peptide from the carboxy-terminus of proSP-B (SPTGEWLPR), from the circulating leucine pool was 0.035±0.005 hr−1 and fractional catabolic rate was 0.044±0.003 hr−1. This technique permits high-throughput, sensitive measurement of turnover of low abundance proteins with minimal sample preparation.

In shotgun proteomics, the analysis of tandem mass spectrometry data from peptides can benefit greatly from high mass accuracy measurements. In this study we have evaluated two database search strategies which use high mass accuracy measurements of the peptide precursor ion. Our results indicate that peptide identifications are improved when spectra are searched with a wide mass tolerance window and precursor mass is used as a filter to discard incorrect matches. Database searches with a peptide dataset constrained to peptides within a narrow mass window resulted in fewer peptide identifications but a significantly faster database search time.

Identifying fertilization molecules is key to our understanding of reproductive biology, yet only a few examples of interacting sperm and egg proteins are known. One of the best characterized comes from the invertebrate archeogastropod abalone (Haliotis spp.), where sperm lysin mediates passage through the protective egg vitelline envelope (VE) by binding to the VE protein vitelline envelope receptor for lysin (VERL). Rapid adaptive divergence of abalone lysin and VERL are an example of positive selection on interacting fertilization proteins contributing to reproductive isolation. Previously, we characterized a subset of the abalone VE proteins that share a structural feature, the zona pellucida (ZP) domain, which is common to VERL and the egg envelopes of vertebrates. Here, we use additional expressed sequence tag sequencing and shotgun proteomics to characterize this family of proteins in the abalone egg VE. We expand 3-fold the number of known ZP domain proteins present within the VE (now 30 in total) and identify a paralog of VERL (vitelline envelope zona pellucida domain protein [VEZP] 14) that contains a putative lysin-binding motif. We find that, like VERL, the divergence of VEZP14 among abalone species is driven by positive selection on the lysin-binding motif alone and that these paralogous egg VE proteins bind a similar set of sperm proteins including a rapidly evolving 18-kDa paralog of lysin, which may mediate sperm–egg fusion. This work identifies an egg coat paralog of VERL under positive selection and the candidate sperm proteins with which it may interact during abalone fertilization.

Circulative transmission of viruses in the Luteoviridae, such as cereal yellow dwarf virus (CYDV), requires a series of precisely orchestrated interactions between virus, plant, and aphid proteins. Natural selection has favored these viruses to be retained in the phloem to facilitate acquisition and transmission by aphids. We show that treatment of infected oat tissue homogenate with sodium sulfite reduces transmission of the purified virus by aphids. Transmission electron microscopy data indicated no gross change in virion morphology due to treatments. However, treated virions were not acquired by aphids through the hindgut epithelial cells and were not transmitted when injected directly into the hemocoel. Analysis of virus preparations using nanoflow liquid chromatography coupled to tandem mass spectrometry revealed a number of host plant proteins co-purifying with viruses, some of which were lost following sodium sulfite treatment. Using targeted mass spectrometry, we show data suggesting that several of the virus-associated host plant proteins accumulated to higher levels in aphids that were fed on CYDV-infected plants compared to healthy plants. We propose two hypotheses to explain these observations, and these are not mutually exclusive: (a) that sodium sulfite treatment disrupts critical virion-host protein interactions required for aphid transmission, or (b) that host infection with CYDV modulates phloem protein expression in a way that is favorable for virus uptake by aphids. Importantly, the genes coding for the plant proteins associated with virus may be examined as targets in breeding cereal crops for new modes of virus resistance that disrupt phloem-virus or aphid-virus interactions.