The nucleolus is involved in regulating several aspects of stress responses and cell cycle arrest through the tumor suppressor p53. Under normal conditions, p53 is a short-lived protein that is present in cells at a barely detectable level. Upon exposure of cells to various forms of exogenous stress, such as DNA damage, there is a stabilization of p53 which is then responsible for an ensuing cascade of events. To further investigate the effect of p53 activation, we used a MS-based proteomics method to provide an unbiased, quantitative and high-throughput approach for measuring the subcellular distribution of the proteome that is dependent on p53. The spatial proteomics method analyses a whole cell extract created by recombining differentially labeled subcellular fractions derived from cells in which proteins have been mass labeled with heavy isotopes [Boisvert, F.-M., Lam, Y. W., Lamont, D., Lamond, A. I., Mol. Cell. Proteomics 2010, 9, 457-470]. This was used here to measure the relative distribution between cytoplasm, nucleus and nucleolus of around 2000 proteins in HCT116 cells that are either expressing wild-type p53 or null for p53. Spatial proteomics also facilitates a proteome-wide comparison of changes in protein localization in response to a wide range of physiological and experimental perturbations. We used this method to study differences in protein localization in HCT116 cells either with or without p53, and studied the differences in cellular response to DNA damage following treatment of HCT116 cells with etoposide in both p53 wild-type and null genetic backgrounds.

Global protein expression profiling can potentially uncover perturbations associated with common forms of heart disease. We have used shotgun MS/MS to monitor the state of biological systems in cardiac tissue correlating with disease onset, cardiac insufficiency and progression to heart failure in a time-course mouse model of dilated cardiomyopathy. However, interpreting the functional significance of the hundreds of differentially expressed proteins has been challenging. Here, we utilize improved enrichment statistical methods and an extensive collection of functionally related gene sets, gaining a more comprehensive understanding of the progressive alterations associated with functional decline in dilated cardiomyopathy. We visualize the enrichment results as an Enrichment Map, where significant gene sets are grouped based on annotation similarity. This approach vastly simplifies the interpretation of the large number of enriched gene sets found. For pathways of specific interest, such as Apoptosis and the MAPK (mitogen-activated protein kinase) cascade, we performed a more detailed analysis of the underlying signaling network, including experimental validation of expression patterns.

Mycobacterium tuberculosis is a highly infectious pathogen that is still responsible for millions of deaths annually. Effectively treating this disease typically requires a course of antibiotics, most of which were developed decades ago. These drugs are, however, not effective against persistent tubercle bacilli and the emergence of drug-resistant stains threatens to make many of them obsolete. The identification of new drug targets, allowing the development of new potential drugs, is therefore imperative. Both proteomics and structural biology have important roles to play in this process, the former as a means of identifying promising drug targets and the latter allowing understanding of protein function and protein-drug interactions at atomic resolution. The determination of M. tuberculosis protein structures has been a goal of the scientific community for the last decade, who have aimed to supply a large amount of structural data that can be used in structure-based approaches for drug discovery and design. Only since the genome sequence of M. tuberculosis has been available has the determination of large numbers of tuberculosis protein structures been possible. Currently, the molecular structures of 8.5% of all the pathogen's protein-encoding ORFs have been determined. In this review, we look at the progress made in determining the M. tuberculosis structural proteome and the impact this has had on the development of potential new drugs, as well as the discovery of the function of crucial mycobaterial proteins.

Recent advances in proteomics have been combined with traditional methods for isolation of nucleoli from mammalian and plant cells. This approach has confirmed the growing body of data showing a wide role for the nucleolus in eukaryotic cell biology beyond ribosome generation into many areas of cell function from regulation of the cell cycle, modulation of the cell stress response to innate immune responses. This has been reflected in the growing body of evidence that viruses specifically target the nucleolus by sequestering cellular nucleolar proteins or by targeting viral proteins to the nucleolus in order to maximise viral replication. This review covers those key areas and looks at the latest approaches using high-throughput quantitative proteomics of the nucleolus in virus infected cells to gain an insight into the role of this fascinating compartment in viral infection.

The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML-based format, capable of representing data about two-dimensional features from LC-MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java-based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer. The mzqLibrary contains routines for mapping (peptide) identifications on quantified features, inference of protein (group)-level quantification values from peptide-level values, normalisation and basic statistics for differential expression. These routines can be accessed via the command line, via a Java programming interface access or a basic graphical user interface. The mzqLibrary also contains several file format converters, including import converters (to mzQuantML) from OpenMS, Progenesis LC-MS and MaxQuant, and exporters (from mzQuantML) to other standards or useful formats (mzTab, HTML, csv). The mzqViewer contains in-built routines for viewing the tables of data (about features, peptides or proteins), and connects to the R statistical library for more advanced plotting options. The mzqLibrary and mzqViewer packages are available from https://code.google.com/p/mzq-lib/.

According to the Arg/N-end rule pathway, proteins with basic N-termini are targeted for degradation by the Arabidopsis thaliana E3 ligase, PROTEOLYSIS6 (PRT6). Proteins can also become PRT6 substrates following post-translational arginylation by arginyltransferases ATE1 and 2. Here, we undertook a quantitative proteomics study of Arg/N-end rule mutants, ate1/2 and prt6, to investigate the impact of this pathway on the root proteome. Tandem mass tag labelling identified a small number of proteins with increased abundance in the mutants, some of which represent downstream targets of transcription factors known to be N-end rule substrates. Isolation of N-terminal peptides using terminal amine isotope labelling of samples (TAILS) combined with triple dimethyl labelling identified 1465 unique N-termini. Stabilising residues were over-represented among the free neo-N-termini, but destabilising residues were not markedly enriched in N-end rule mutants. The majority of free neo-N-termini were revealed following cleavage of organellar targeting signals, thus compartmentation may account in part for the presence of destabilising residues in the wild-type N-terminome. Our data suggest that PRT6 does not have a marked impact on the global proteome of Arabidopsis roots and is likely involved in the controlled degradation of relatively few regulatory proteins. All MS data have been deposited in the ProteomeXchange with identifier PXD001719 (http://proteomecentral.proteomexchange.org/dataset/PXD001719).

Lipid body (LB) is recognized as the cellular carbon and energy storage organelle in many organisms. LBs have been observed in the marine haptophyte alga Tisochrysis lutea that produces special lipids such as long-chain (C37 -C40) ketones (alkenones) with 2-4 trans-type double bonds. In this study, we succeeded in developing a modified method to isolate LB from T. lutea. Purity of isolated LBs was confirmed by the absence of chlorophyll auto-fluorescence and no contamination of the most abundant cellular protein ribulose-1,5-bisphosphate carboxylase/oxygenase. As alkenones predominated in the LB by GC-MS analysis, the LB can be more appropriately named as "alkenone body (AB)." Extracted AB-containing proteins were analyzed by the combination of 1DE (SDS-PAGE) and MS/MS for confident protein identification and annotated using BLAST tools at National Center for Biotechnology Information. Totally 514 proteins were identified at the maximum. The homology search identified three major proteins, V-ATPase, a hypothetical protein EMIHUDRAFT_465517 found in other alkenone-producing haptophytes, and a lipid raft-associated SPFH domain-containing protein. Our data suggest that AB of T. lutera is surrounded by a lipid membrane originating from either the ER or the ER-derived four layer-envelopes chloroplast and function as the storage site of alkenones and alkenes.

The study of protein conformation by solution-phase hydrogen/deuterium exchange (HDX) coupled to MS is well documented. This involves monitoring the exchange of backbone amide protons with deuterium and provides details concerning the protein's tertiary structure. However, undesired back-exchange during post-HDX analyses can be difficult to control. Here, gas-phase HDX-MS, during which labile hydrogens on amino acid side chains are exchanged in sub-millisecond time scales, has been employed to probe changes within protein structures. Addition of the solvent 2,2,2-trifluoroethanol to a protein in solution can affect the structure of the protein, resulting in an increase in secondary and/or tertiary structure which is detected using circular dichroism. Using a Synapt G2-S ESI-mass spectrometer modified to allow deuterated ammonia into the transfer ion guide (situated between the ion mobility cell and the TOF analyser), gas-phase HDX-MS is shown to reflect minor structural changes experienced by the proteins β-lactoglobulin and ubiquitin, as observed by the reduction in the level of deuterium incorporation. Additionally, the use of gas-phase HDX-MS to distinguish between co-populated proteins conformers within a solution is demonstrated with the disordered protein calmodulin; the gas-phase HDX-MS results correspond directly with complementary data obtained by use of ion mobility spectrometry-MS.

In this article, we provide a comprehensive study of the content of the Universal Protein Resource (UniProt) protein data sets for human and mouse. The tryptic search spaces of the UniProtKB (UniProt knowledgebase) complete proteome sets were compared with other data sets from UniProtKB and with the corresponding International Protein Index, reference sequence, Ensembl, and UniRef100 (where UniRef is UniProt reference clusters) organism-specific data sets. All protein forms annotated in UniProtKB (both the canonical sequences and isoforms) were evaluated in this study. In addition, natural and disease-associated amino acid variants annotated in UniProtKB were included in the evaluation. The peptide unicity was also evaluated for each data set. Furthermore, the peptide information in the UniProtKB data sets was also compared against the available peptide-level identifications in the main MS-based proteomics repositories. Identifying the peptides observed in these repositories is an important resource of information for protein databases as they provide supporting evidence for the existence of otherwise predicted proteins. Likewise, the repositories could use the information available in UniProtKB to direct reprocessing efforts on specific sets of peptides/proteins of interest. In summary, we provide comprehensive information about the different organism-specific sequence data sets available from UniProt, together with the pros and cons for each, in terms of search space for MS-based bottom-up proteomics workflows. The aim of the analysis is to provide a clear view of the tryptic search space of UniProt and other protein databases to enable scientists to select those most appropriate for their purposes.

The in-depth analysis of complex proteome samples requires fractionation of the sample into subsamples prior to LC-MS/MS in shotgun proteomics experiments. We have established a 3D workflow for shotgun proteomics that relies on protein separation by 1D PAGE, gel fractionation, trypsin digestion, and peptide separation by in-gel IEF, prior to RP-HPLC-MS/MS. Our results show that applying peptide IEF can significantly increase the number of proteins identified from PAGE subfractionation. This method delivers deeper proteome coverage and provides a large degree of flexibility in experimentally approaching highly complex mixtures by still relying on protein separation according to molecular weight in the first dimension.

Cancer is a class of diseases characterized by abnormal cell growth and one of the major reasons for human deaths. Proteins are involved in the molecular mechanisms leading to cancer, furthermore they are affected by anti-cancer drugs, and protein biomarkers can be used to diagnose certain cancer types. Therefore, it is important to explore the proteomics background of cancer. In this report, we developed the Cancer Proteomics database to re-interrogate published proteome studies investigating cancer. The database is divided in three sections related to cancer processes, cancer types, and anti-cancer drugs. Currently, the Cancer Proteomics database contains 9778 entries of 4118 proteins extracted from 143 scientific articles covering all three sections: cell death (cancer process), prostate cancer (cancer type) and platinum-based anti-cancer drugs including carboplatin, cisplatin, and oxaliplatin (anti-cancer drugs). The detailed information extracted from the literature includes basic information about the articles (e.g., PubMed ID, authors, journal name, publication year), information about the samples (type, study/reference, prognosis factor), and the proteomics workflow (Subcellular fractionation, protein, and peptide separation, mass spectrometry, quantification). Useful annotations such as hyperlinks to UniProt and PubMed were included. In addition, many filtering options were established as well as export functions. The database is freely available at http://cancerproteomics.uio.no.

Drugs targeting MDM2's hydrophobic pocket activate p53. However, these agents act allosterically and have agonist effects on MDM2's protein interaction landscape. Dominant p53-independent MDM2-drug responsive-binding proteins have not been stratified. We used as a variable the differential expression of MDM2 protein as a function of cell density to identify Nutlin-3 responsive MDM2-binding proteins that are perturbed independent of cell density using SWATH-MS. Dihydrolipoamide dehydrogenase, the E3 subunit of the mitochondrial pyruvate dehydrogenase complex, was one of two Nutlin-3 perturbed proteins identified fours hour posttreatment at two cell densities. Immunoblotting confirmed that dihydrolipoamide dehydrogenase was induced by Nutlin-3. Depletion of MDM2 using siRNA also elevated dihydrolipoamide dehydrogenase in Nutlin-3 treated cells. Mitotracker confirmed that Nutlin-3 inhibits mitochondrial activity. Enrichment of mitochondria using TOM22+ immunobeads and TMT labeling defined key changes in the mitochondrial proteome after Nutlin-3 treatment. Proximity ligation identified rearrangements of cellular protein-protein complexes in situ. In response to Nutlin-3, a reduction of dihydrolipoamide dehydrogenase/dihydrolipoamide acetyltransferase protein complexes highlighted a disruption of the pyruvate dehydrogenase complex. This coincides with an increase in MDM2/dihydrolipoamide dehydrogenase complexes in the nucleus that was further enhanced by the nuclear export inhibitor Leptomycin B. The data suggest one therapeutic impact of MDM2 drugs might be on the early perturbation of specific protein-protein interactions within the mitochondria. This methodology forms a blueprint for biomarker discovery that can identify rearrangements of MDM2 protein-protein complexes in drug-treated cells.

Integrin adhesion receptors mediate cell-cell and cell-extracellular matrix interactions, which control cell morphology and migration, differentiation, and tissue integrity. Integrins recruit multimolecular adhesion complexes to their cytoplasmic domains, which provide structural and mechanosensitive signaling connections between the extracellular and intracellular milieux. The different functions of specific integrin heterodimers, such as α4β1 and α5β1, have been attributed to distinct signal transduction mechanisms that are initiated by selective recruitment of adhesion complex components to integrin cytoplasmic tails. Here, we report the isolation of ligand-induced adhesion complexes associated with wild-type α4β1 integrin, an activated α4β1 variant in the absence of the α cytoplasmic domain (X4C0), and a chimeric α4β1 variant with α5 leg and cytoplasmic domains (α4Pα5L), and the cataloguing of their proteomes by MS. Using hierarchical clustering and interaction network analyses, we detail the differential recruitment of proteins and highlight enrichment patterns of proteins to distinct adhesion complexes. We identify previously unreported components of integrin adhesion complexes and observe receptor-specific enrichment of molecules with previously reported links to cell migration and cell signaling processes. Furthermore, we demonstrate colocalization of MYO18A with active integrin in migrating cells. These datasets provide a resource for future studies of integrin receptor-specific signaling events.

To identify host factors involved in Salmonella replication, SILAC-based quantitative proteomics was used to investigate the interactions of Salmonella typhimurium with the secretory pathway in human epithelial cells. Protein profiles of Golgi-enriched fractions isolated from S. typhimurium-infected cells were compared with those of mock-infected cells, revealing significant depletion or enrichment of 105 proteins. Proteins annotated to play a role in membrane traffic were overrepresented among the depleted proteins whereas proteins annotated to the cytoskeleton showed a diverse behavior with some proteins being enriched, others being depleted from the Golgi fraction upon Salmonella infection. To study the functional relevance of identified proteins in the Salmonella infection cycle, small interfering RNA (siRNA) experiments were performed. siRNA-mediated depletion of a selection of affected proteins identified five host factors involved in Salmonella infection. Depletion of peroxiredoxin-6 (PRDX6), isoform β-4c of integrin β-4 (ITGB4), isoform 1 of protein lap2 (erbin interacting protein; ERBB2IP), stomatin (STOM) or TBC domain containing protein 10b (TBC1D10B) resulted in increased Salmonella replication. Surprisingly, in addition to the effect on Salmonella replication, depletion of STOM or ITGB4 resulted in a dispersal of intracellular Salmonella microcolonies. It can be concluded that by using SILAC-based quantitative proteomics we were able to identify novel host cell proteins involved in the complex interplay between Salmonella and epithelial cells.

The International Protein Index (IPI) database has been one of the most widely used protein databases in MS proteomics approaches. Recently, the closure of IPI in September 2011 was announced. Its recommended replacement is the new UniProt Knowledgebase (UniProtKB) "complete proteome" sets, launched in May 2011. Here, we analyze the consequences of IPI's discontinuation for human and mouse data, and the effect of its substitution with UniProtKB on two levels: (i) data already produced and (ii) newly performed experiments. To estimate the effect on existing data, we investigated how well IPI identifiers map to UniProtKB accessions. We found that 21% of human and 10% of mouse identifiers do not map to UniProtKB and would thus be "lost." To investigate the impact on new experiments, we compared the theoretical search space (i.e. the tryptic peptides) of both resources and found that it is decreased by 14.0% for human and 8.9% for mouse data through IPI's closure. An analysis on the experimental evidence for these "lost" peptides showed that the vast majority has not been identified in experiments available in the major proteomics repositories. It thus seems likely that the search space provided by UniProtKB is of higher quality than the one currently provided by IPI.

Mass spectrometry (MS)-based quantification of highly homologous proteins in complex samples has proven difficult due to subtle sequence variations and the wide dynamic range of protein isoforms present. Herein, we report the use of reductive dimethylation on intact proteins to quantitatively compare protein isoform expression in the nucleus and cytoplasm of mesenchymal stem cells (MSC) and normal stroma. By coupling fixed-charge MS/MS scanning, high-resolution UPLC FT-MS data-dependent acquisition and MASCOT-based data mining, hydrogen/deuterium-labeled dimethyl-lysine peptides were simultaneously captured allowing the accurate comparison of 123 protein isoforms in parallel LC MS/MS runs. Thirty-four isoforms were identified that had expression levels specific to MSC. Where possible, proteomic analyses were verified by Western blotting and were demonstrated to be divergent from the level of gene transcription detected for certain proteins. Our analysis provides a protein isoform signature specific to MSC and demonstrates the suitability of dimethyl-lysine labeling on intact proteins for quantifying highly homologous proteins on a proteome-wide scale.

The in-gel digestion of proteins for analysis by liquid chromatograph mass spectrometry has been used since the early 1990s. Although several improvements have contributed to increasing the quality of the data obtained, many recent publications still use sub-optimal approaches. Updates of the in-gel digestion protocol has been presented in the study. It has been shown that alternative reducing, alkylating agent reactions, and tryptic digestion buffers increase peptide and protein identification and reduce incubation times. The results indicate that a simultaneous and short, high temperature reduction and alkylation reaction using Tris(2-carboxyethyl)phosphine hydrochloride and chloroacetamide with a subsequent gel wash improve protein identification and sequence coverage, and diminish peptide side reactions. Additionally, use of 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid buffer allows a significant reduction in the digestion time improving trypsin performance and increasing the peptide recovery. The updates of the in-gel digestion protocol described here are efficient and offer flexibility to be incorporated in any proteomic laboratory.

The mentioning of gene names in the body of the scientific literature 1901-2017 and their fractional counting is used as a proxy to assess the level of biological function discovery. A literature score of one has been defined as full publication equivalent (FPE), the amount of literature necessary to achieve one publication solely dedicated to a gene. It has been found that less than 5000 human genes have each at least 100 FPEs in the available literature corpus. This group of elite genes (4817 protein-coding genes, 119 non-coding RNAs) attracts the overwhelming majority of the scientific literature about genes. Yet, thousands of proteins have never been mentioned at all, ≈2000 further proteins have not even one FPE of literature and, for ≈4600 additional proteins, the FPE count is below 10. The protein function discovery rate measured as numbers of proteins first mentioned or crossing a threshold of accumulated FPEs in a given year has grown until 2000 but is in decline thereafter. This drop is partially offset by function discoveries for non-coding RNAs. The full human genome sequencing does not boost the function discovery rate. Since 2000, the fastest growing group in the literature is that with at least 500 FPEs per gene.

A challenge in developing personalized cancer immunotherapies is the prediction of putative cancer-specific antigens. Currently, predictive algorithms are used to infer binding of peptides to human leukocyte antigen (HLA) heterodimers to aid in the selection of putative epitope targets. One drawback of current epitope prediction algorithms is that they are trained on datasets containing biochemical HLA-peptide binding data that may not completely capture the rules associated with endogenous processing and presentation. The field of MS has made great improvements in instrumentation speed and sensitivity, chromatographic resolution, and proteogenomic database search strategies to facilitate the identification of HLA-ligands from a variety of cell types and tumor tissues. As such, these advances have enabled MS profiling of HLA-binding peptides to be a tractable, orthogonal approach to lower throughput biochemical assays for generating comprehensive datasets to train epitope prediction algorithms. In this review, we will highlight the progress made in the field of HLA-ligand profiling enabled by MS and its impact on current and future epitope prediction strategies.

The number of small proteins (SPs) encoded in the Escherichia coli genome is unknown, as current bioinformatics and biochemical techniques make short gene and small protein identification challenging. One method of small protein identification involves adding an epitope tag to the 3' end of a short open reading frame (sORF) on the chromosome, with synthesis confirmed by immunoblot assays. In this study, this strategy was used to identify new E. coli small proteins, tagging 80 sORFs in the E. coli genome, and assayed for protein synthesis. The selected sORFs represent diverse sequence characteristics, including degrees of sORF conservation, predicted transmembrane domains, sORF direction with respect to flanking genes, ribosome binding site (RBS) prediction, and ribosome profiling results. Of 80 sORFs, 36 resulted in encoded synthesized proteins-a 45% success rate. Modeling of detected versus non-detected small proteins analysis showed predictions based on RBS prediction, transcription data, and ribosome profiling had statistically-significant correlation with protein synthesis; however, there was no correlation between current sORF annotation and protein synthesis. These results suggest substantial numbers of small proteins remain undiscovered in E. coli, and existing bioinformatics techniques must continue to improve to facilitate identification.