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Tandem mass spectrometry is commonly used to identify peptides (and thereby proteins) that are present in complex mixtures. Peptide identification from tandem mass spectra is partially automated, but still requires human curation to resolve “borderline” peptide-spectrum matches (PSMs). SILVER is web-based software that assists manual curation of tandem mass spectra, using a recently developed intensity-based machine-learning approach to scoring PSMs, Elias et al. . In this method, a large training set of peptide, fragment, and peak-intensity properties for both matched and mismatched PSMs was used to develop a score measuring consistency between each predicted fragment ion of a candidate peptide and its corresponding observed spectral peak intensity. The SILVER interface provides a visual representation of match quality between each candidate fragment ion and the observed spectrum, thereby expediting manual curation of tandem mass spectra. SILVER is available online at http://llama.med.harvard.edu/Software.html. [Copyright &y& Elsevier]

Consistently collecting high-quality liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) data is a time-consuming hurdle for untargeted workflows. Analytical controls such as internal and biological standards are commonly included in high-throughput workflows, helping researchers recognize low-integrity specimens regardless of their biological source. However, evaluating these standards as data are collected has remained a considerable bottleneck─in both person-hours and accuracy. Here we present Rapid QC-MS, an automated, interactive dashboard for assessing LC-MS/MS data quality. Minutes after a new data file is written, a browser-viewable dashboard is updated with quality control results spanning multiple performance dimensions such as instrument sensitivity, in-run retention time shifts, and mass accuracy drift. Rapid QC-MS provides interactive visualizations that help users recognize acute deviations in these performance metrics, as well as gradual drifts over periods of hours, days, months, or years. Rapid QC-MS is open-source, simple to install, and highly configurable. By integrating open-source Python libraries and widely used MS analysis software, it can adapt to any LC-MS/MS workflow. Rapid QC-MS runs locally and offers optional remote quality control by syncing with Google Drive. Furthermore, Rapid QC-MS can operate in a semiautonomous fashion, alerting users to specimens with potentially poor analytical integrity via frequently used messaging applications. Initially developed for integration with Thermo Orbitrap workflows, Rapid QC-MS offers a fast, straightforward approach to help users collect high-quality untargeted LC-MS/MS data by eliminating many of the most time-consuming steps in manual data curation. Download for free: https://github.com/czbiohub-sf/Rapid-QC-MS.

The ubiquitin-proteasome system (UPS) is a potential pathway for therapeutic intervention for pathogens such as Plasmodium, the causative agent of malaria. However, due to the essential nature of this proteolytic pathway, proteasome inhibitors must avoid inhibition of the host enzyme complex to prevent toxic side effects. The Plasmodium proteasome is poorly characterized, making rational design of inhibitors that induce selective parasite killing difficult. In this study, we developed a chemical probe that labels all catalytic sites of the Plasmodium proteasome. Using this probe, we identified several subunit selective small molecule inhibitors of the parasite enzyme complex. Treatment with an inhibitor that is specific for the β5 subunit during blood stage schizogony led to a dramatic decrease in parasite replication while short-term inhibition of the β2 subunit did not affect viability. Interestingly, coinhibition of both the β2 and β5 catalytic subunits resulted in enhanced parasite killing at all stages of the blood stage life cycle and reduced parasite levels in vivo to barely detectable levels. Parasite killing was achieved with overall low host toxicity, something that has not been possible with existing proteasome inhibitors. Our results highlight differences in the subunit dependency of the parasite and human proteasome, thus providing a strategy for development of potent antimalarial drugs with overall low host toxicity.

Recently, mass spectrometry has been employed in many studies to provide unbiased, reproducible, and quantitative protein abundance information on a proteome-wide scale. However, how instruments' limited dynamic ranges impact the accuracy of such measurements has remained largely unexplored, especially in the context of complex mixtures. Here, we examined the distribution of peptide signal versus background noise (S/N) and its correlation with quantitative accuracy. With the use of metabolically labeled Jurkat cell lysate, over half of all confidently identified peptides had S/N ratios less than 10 when examined using both hybrid linear ion trap-Fourier transform ion cyclotron resonance and Orbitrap mass spectrometers. Quantification accuracy was also highly correlated with S/N. We developed a mass precision algorithm that significantly reduced measurement variance at low S/N beyond the use of highly accurate mass information alone and expanded it into a new software suite, Vista. We also evaluated the interplay between mass measurement accuracy and S/N; finding a balance between both parameters produced the greatest identification and quantification rates. Finally, we demonstrate that S/N can be a useful surrogate for relative abundance ratios when only a single species is detected.

The relative quantification of protein expression levels in different cell samples through the utilization of stable isotope dilution has become a standard method in the field of proteomics. We describe here the development of a new reductively cleavable reagent which facilitates the relative quantification of thousands of proteins from only tens of micrograms of starting protein. The ligand features a novel disulfide moiety that links biotin and a thiol-reactive entity. The disulfide is stable to reductive conditions employed during sample labeling but is readily cleaved under mild conditions using tris-(2-carboxyethyl) phosphine (TCEP). This unique chemical property allows for the facile use of immobilized avidin in a manner equivalent to the use of conventional reversible-binding affinity resins. Target peptides are bound to avidin resin, washed rigorously, then cleaved directly from the resin, resulting in simplified sample handling procedures and reduced nonspecific interactions. Here we demonstrate the stability of the linker under two different reducing conditions and show how this "catch-and-release (CAR)" reagent can be used to quantitatively compare protein abundances from two distinct cellular lysates. Starting with only 40 microg protein from each sample, 1840 individual proteins were identified in a single experiment. Using in-house software for automated peak integration, 1620 of these proteins were quantified for differential expression.

Protein phosphorylation is essential for numerous cellular processes. Large-scale profiling of phosphoproteins continues to enhance the depth and speed at which we understand these processes. The development of effective phosphoprotein and peptide enrichment techniques and improvements to mass spectrometric instrumentation have intensified phosphoproteomic research in recent years, leading to unprecedented achievements. Here, we describe a large-scale phosphorylation analysis of alpha-factor-arrested yeast. Using a multidimensional separation strategy involving preparative SDS-PAGE for prefractionation, in-gel digestion with trypsin, and immobilized metal affinity chromatography (IMAC) enrichment of phosphopeptides, followed by LC-MS/MS analysis employing a hybrid LTQ-Orbitrap mass spectrometer, we were able to catalog a substantial portion of the phosphoproteins present in yeast whole-cell lysate. This analysis yielded the confident identification of 2288 nonredundant phosphorylation sites from 985 proteins. The ambiguity score (Ascore) algorithm was utilized to determine the certainty of site localization for the entire data set. In addition, the size of the data set permitted extraction of known and novel kinase motifs using the Motif-X algorithm. Finally, a large number of members of the pheromone signaling pathway were found as phosphoproteins and are discussed.

The primary goal of proteomics is to gain a better understanding of biological function at the protein expression level. As the field matures, numerous technologies are being developed to aid in the identification, quantification and characterization of protein expression and post-translational modifications on a near-global scale. Stable isotope labeling by amino acids in cell culture is one such technique that has shown broad biological applications. While we have recently shown the application of this technology to a model of metastatic prostate cancer, we now report a substantial improvement in quantitative analysis using a linear ion-trap Fourier transform ion cyclotron resonance mass spectrometer (LTQ FT) and novel quantification software. This resulted in the quantification of nearly 1400 proteins, a greater than 3-fold increase in comparison to our earlier study. This dramatic increase in proteome coverage can be attributed to (1) use of a double-labeling strategy, (2) greater sensitivity, speed and mass accuracy provided by the LTQ FT mass spectrometer, and (3) more robust quantification software. Finally, by using a concatenated target/decoy protein database for our peptide searches, we now report these data in the context of an estimated false-positive rate of one percent.

Highly complex protein mixtures can be directly analyzed after proteolysis by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). In this paper, we have utilized the combination of strong cation exchange (SCX) and reversed-phase (RP) chromatography to achieve two-dimensional separation prior to MS/MS. One milligram of whole yeast protein was proteolyzed and separated by SCX chromatography (2.1 mm i.d.) with fraction collection every minute during an 80-min elution. Eighty fractions were reduced in volume and then re-injected via an autosampler in an automated fashion using a vented-column (100 microm i.d.) approach for RP-LC-MS/MS analysis. More than 162,000 MS/MS spectra were collected with 26,815 matched to yeast peptides (7,537 unique peptides). A total of 1,504 yeast proteins were unambiguously identified in this single analysis. We present a comparison of this experiment with a previously published yeast proteome analysis by Yates and colleagues (Washburn, M. P.; Wolters, D.; Yates, J. R., III. Nat. Biotechnol. 2001, 19, 242-7). In addition, we report an in-depth analysis of the false-positive rates associated with peptide identification using the Sequest algorithm and a reversed yeast protein database. New criteria are proposed to decrease false-positives to less than 1% and to greatly reduce the need for manual interpretation while permitting more proteins to be identified.