A nested mixture model for protein identification using mass spectrometry

Mass spectrometry provides a high-throughput way to identify proteins in biological samples. In a typical experiment, proteins in a sample are first broken into their constituent peptides. The resulting mixture of peptides is then subjected to mass spectrometry, which generates thousands of spectra, each characteristic of its generating peptide. Here we consider the problem of inferring, from these spectra, which proteins and peptides are present in the sample. We develop a statistical approach to the problem, based on a nested mixture model. In contrast to commonly used two-stage approaches, this model provides a one-stage solution that simultaneously identifies which proteins are present, and which peptides are correctly identified. In this way our model incorporates the evidence feedback between proteins and their constituent peptides. Using simulated data and a yeast data set, we compare and contrast our method with existing widely used approaches (PeptideProphet/ProteinProphet) and with a recently published new approach, HSM. For peptide identification, our single-stage approach yields consistently more accurate results. For protein identification the methods have similar accuracy in most settings, although we exhibit some scenarios in which the existing methods perform poorly.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS316 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Sampling the proteome by emerging single-molecule and mass-spectrometry methods

Mammalian cells have about 30,000-fold more protein molecules than mRNA molecules. This larger number of molecules and the associated larger dynamic range have major implications in the development of proteomics technologies. We examine these implications for both liquid chromatography-tandem mass spectrometry (LC-MS/MS) and single-molecule counting and provide estimates on how many molecules are routinely measured in proteomics experiments by LC-MS/MS. We review strategies that have been helpful for counting billions of protein molecules by LC-MS/MS and suggest that these strategies can benefit single-molecule methods, especially in mitigating the challenges of the wide dynamic range of the proteome. We also examine the theoretical possibilities for scaling up single-molecule and mass spectrometry proteomics approaches to quantifying the billions of protein molecules that make up the proteomes of our cells.Comment: Recorded presentation: https://youtu.be/w0IOgJrrvN

Quantitative Profiling of Ubiquitylated Proteins Reveals Proteasome Substrates and the Substrate Repertoire Influenced by the Rpn10 Receptor Pathway

The ubiquitin proteasome system (UPS) comprises hundreds of different conjugation/deconjugation enzymes and multiple receptors that recognize ubiquitylated proteins. A formidable challenge to deciphering the biology of ubiquitin is to map the networks of substrates and ligands for components of the UPS. Several different receptors guide ubiquitylated substrates to the proteasome, and neither the basis for specificity nor the relative contribution of each pathway is known. To address how broad of a role the ubiquitin receptor Rpn10 (S5a) plays in turnover of proteasome substrates, we implemented a method to perform quantitative analysis of ubiquitin conjugates affinity-purified from experimentally perturbed and reference cultures of Saccharomyces cerevisiae that were differentially labeled with 14N and 15N isotopes. Shotgun mass spectrometry coupled with relative quantification using metabolic labeling and statistical analysis based on q values revealed ubiquitylated proteins that increased or decreased in level in response to a particular treatment. We first identified over 225 candidate UPS substrates that accumulated as ubiquitin conjugates upon proteasome inhibition. To determine which of these proteins were influenced by Rpn10, we evaluated the ubiquitin conjugate proteomes in cells lacking either the entire Rpn10 (rpn10{Delta}) (or only its UIM (ubiquitin-interacting motif) polyubiquitin-binding domain (uim{Delta})). Twenty-seven percent of the UPS substrates accumulated as ubiquitylated species in rpn10{Delta} cells, whereas only one-fifth as many accumulated in uim{Delta} cells. These findings underscore a broad role for Rpn10 in turnover of ubiquitylated substrates but a relatively modest role for its ubiquitin-binding UIM domain. This approach illustrates the feasibility of systems-level quantitative analysis to map enzyme-substrate networks in the UPS

A Biofilm Matrix-Associated Protease Inhibitor Protects Pseudomonas Aeruginosa from Proteolytic Attack

Pseudomonas aeruginosa produces an extracellular biofilm matrix that consists of nucleic acids, exopolysaccharides, lipid vesicles, and proteins. In general, the protein component of the biofilm matrix is poorly defined and understudied relative to the other major matrix constituents. While matrix proteins have been suggested to provide many functions to the biofilm, only proteins that play a structural role have been characterized thus far. Here we identify proteins enriched in the matrix of P. aeruginosa biofilms. We then focused on a candidate matrix protein, the serine protease inhibitor ecotin (PA2755). This protein is able to inhibit neutrophil elastase, a bactericidal enzyme produced by the host immune system during P. aeruginosa biofilm infections. We show that ecotin binds to the key biofilm matrix exopolysaccharide Psl and that it can inhibit neutrophil elastase when associated with Psl. Finally, we show that ecotin protects both planktonic and biofilm P. aeruginosa cells from neutrophil elastase-mediated killing. This may represent a novel mechanism of protection for biofilms to increase their tolerance against the innate immune response. IMPORTANCE Proteins associated with the extracellular matrix of bacterial aggregates called biofilms have long been suggested to provide many important functions to the community. To date, however, only proteins that provide structural roles have been described, and few matrix-associated proteins have been identified. We developed a method to identify matrix proteins and characterized one. We show that this protein, when associated with the biofilm matrix, can inhibit a bactericidal enzyme produced by the immune system during infection and protect biofilm cells from death induced by the enzyme. This may represent a novel mechanism of protection for biofilms, further increasing their tolerance against the immune response. Together, our results are the first to show a nonstructural function for a confirmed matrix-interacting protein

Substrate Trapping Proteomics Reveals Targets of the βTrCP2/FBXW11 Ubiquitin Ligase

Defining the full complement of substrates for each ubiquitin ligase remains an important challenge. Improvements in mass spectrometry instrumentation and computation and in protein biochemistry methods have resulted in several new methods for ubiquitin ligase substrate identification. Here we used the parallel adapter capture (PAC) proteomics approach to study βTrCP2/FBXW11, a substrate adaptor for the SKP1–CUL1–F-box (SCF) E3 ubiquitin ligase complex. The processivity of the ubiquitylation reaction necessitates transient physical interactions between FBXW11 and its substrates, thus making biochemical purification of FBXW11-bound substrates difficult. Using the PAC-based approach, we inhibited the proteasome to “trap” ubiquitylated substrates on the SCFFBXW11E3 complex. Comparative mass spectrometry analysis of immunopurified FBXW11 protein complexes before and after proteasome inhibition revealed 21 known and 23 putatively novel substrates. In focused studies, we found that SCFFBXW11bound, polyubiquitylated, and destabilized RAPGEF2, a guanine nucleotide exchange factor that activates the small GTPase RAP1. High RAPGEF2 protein levels promoted cell-cell fusion and, consequently, multinucleation. Surprisingly, this occurred independently of the guanine nucleotide exchange factor (GEF) catalytic activity and of the presence of RAP1. Our data establish new functions for RAPGEF2 that may contribute to aneuploidy in cancer. More broadly, this report supports the continued use of substrate trapping proteomics to comprehensively define targets for E3 ubiquitin ligases. All proteomic data are available via ProteomeXchange with identifier PXD001062