Proteomic analyses identify major vault protein as a prognostic biomarker for fatal prostate cancer.

The demographic shift toward an older population will increase the number of prostate cancer cases. A challenge in the treatment of prostate cancer is to avoid undertreatment of patients at high risk of progression following curative treatment. These men can benefit from early salvage treatment. An explorative cohort consisting of tissue from 16 patients who underwent radical prostatectomy, and were either alive or had died from prostate cancer within 10 years postsurgery, was analyzed by mass spectrometry analysis. Following proteomic and bioinformatic analyses, major vault protein (MVP) was identified as a putative prognostic biomarker. A publicly available tissue proteomics dataset and a retrospective cohort of 368 prostate cancer patients were used for validation. The prognostic value of the MVP was verified by scoring immunohistochemical staining of a tissue microarray. High level of MVP was associated with more than 4-fold higher risk for death from prostate cancer (hazard ratio = 4.41, 95% confidence interval: 1.45-13.38; P = 0.009) in a Cox proportional hazard models, adjusted for Cancer of the Prostate Risk Assessments Post-surgical (CAPRA-S) score and perineural invasion. Decision curve analyses suggested an improved standardized net benefit, ranging from 0.06 to 0.18, of adding MVP onto CAPRA-S score. This observation was confirmed by receiver operator characteristics curve analyses for the CAPRA-S score versus CAPRA-S and MVP score (area under the curve: 0.58 versus 0.73). From these analyses, one can infer that MVP levels in combination with CAPRA-S score might add onto established risk parameters to identify patients with lethal prostate cancer.

A high-throughput pipeline for validation of antibodies.

Western blotting (WB) is widely used to test antibody specificity, but the assay has low throughput and precision. Here we used preparative gel electrophoresis to develop a capture format for WB. Fractions with soluble, size-separated proteins facilitated parallel readout with antibody arrays, shotgun mass spectrometry (MS) and immunoprecipitation followed by MS (IP-MS). This pipeline provided the means for large-scale implementation of antibody validation concepts proposed by an international working group on antibody validation (IWGAV).

Proteomic and Metabolomic Analysis of Azospirillum brasilensentrC Mutant under High and Low Nitrogen Conditions.

Azospirillum brasilense is a diazotrophic microorganism capable of associating with roots of important grasses and cereals, promoting plant growth and increasing crop yields. Nitrogen levels and the Ntr regulatory system control the nitrogen metabolism in A. brasilense. This system comprises the nitrogen regulatory proteins GlnD, which is capable of adding uridylyl groups to the PII proteins, GlnB (PII-1) and GlnZ (PII-2), under limiting nitrogen levels. Under such conditions, the histidine kinase NtrB (nitrogen regulatory protein B) cannot interact with GlnB and phosphorylate NtrC (nitrogen regulatory protein C). The phosphorylated form of NtrC acts as a transcriptional activator of genes involved in the metabolism of alternative nitrogen sources. Considering the key role of NtrC in nitrogen metabolism in A. brasilense, in this work we evaluated the proteomic and metabolomic profiles of the wild-type FP2 strain and its mutant ntrC grown under high and low nitrogen. Analysis of the integrated data identifies novel NtrC targets, including proteins involved in the response against oxidative stress (i.e., glutathione S-transferase and hydroperoxide resistance protein), underlining the importance of NtrC to bacterial survival under oxidative stress conditions.

The SysteMHC Atlas project.

Mass spectrometry (MS)-based immunopeptidomics investigates the repertoire of peptides presented at the cell surface by major histocompatibility complex (MHC) molecules. The broad clinical relevance of MHC-associated peptides, e.g. in precision medicine, provides a strong rationale for the large-scale generation of immunopeptidomic datasets and recent developments in MS-based peptide analysis technologies now support the generation of the required data. Importantly, the availability of diverse immunopeptidomic datasets has resulted in an increasing need to standardize, store and exchange this type of data to enable better collaborations among researchers, to advance the field more efficiently and to establish quality measures required for the meaningful comparison of datasets. Here we present the SysteMHC Atlas (https://systemhcatlas.org), a public database that aims at collecting, organizing, sharing, visualizing and exploring immunopeptidomic data generated by MS. The Atlas includes raw mass spectrometer output files collected from several laboratories around the globe, a catalog of context-specific datasets of MHC class I and class II peptides, standardized MHC allele-specific peptide spectral libraries consisting of consensus spectra calculated from repeat measurements of the same peptide sequence, and links to other proteomics and immunology databases. The SysteMHC Atlas project was created and will be further expanded using a uniform and open computational pipeline that controls the quality of peptide identifications and peptide annotations. Thus, the SysteMHC Atlas disseminates quality controlled immunopeptidomic information to the public domain and serves as a community resource toward the generation of a high-quality comprehensive map of the human immunopeptidome and the support of consistent measurement of immunopeptidomic sample cohorts.

Characterization of the Small Intestinal Lesion in Celiac Disease by Label-Free Quantitative Mass Spectrometry.

Global characterization of tissue proteomes from small amounts of biopsy material has become feasible because of advances in mass spectrometry and bioinformatics tools. In celiac disease (CD), dietary gluten induces an immune response that is accompanied by pronounced remodeling of the small intestine. Removal of gluten from the diet abrogates the immune response, and the tissue architecture normalizes. In this study, differences in global protein expression of small intestinal biopsy specimens from CD patients were quantified by analyzing formalin-fixed, paraffin-embedded material using liquid chromatography-mass spectrometry and label-free protein quantitation. Protein expression was compared in biopsy specimens collected from the same patients before and after 1-year treatment with gluten-free diet (n = 10) or before and after 3-day gluten provocation (n = 4). Differential expression of proteins in particular from mature enterocytes, neutrophils, and plasma cells could distinguish untreated from treated CD mucosa, and Ig variable region IGHV5-51 expression was found to serve as a CD-specific marker of ongoing immune activation. In patients who had undergone gluten challenge, coordinated up-regulation of wound response proteins, including the CD autoantigen transglutaminase 2, was observed. Our study provides a global and unbiased assessment of antigen-driven changes in protein expression in the celiac intestinal mucosa.

Dynamics of the Escherichia coli proteome in response to nitrogen starvation and entry into the stationary phase.

Nitrogen is needed for the biosynthesis of biomolecules including proteins and nucleic acids. In the absence of fixed nitrogen prokaryotes such as E. coli immediately ceases growth. Ammonium is the preferred nitrogen source for E. coli supporting the fastest growth rates. Under conditions of ammonium limitation, E. coli can use alternative nitrogen sources to supply ammonium ions and this reprogramming is led by the induction of the NtrC regulon. Here we used label free proteomics to determine the dynamics of E. coli proteins expression in response to ammonium starvation in both the short (30min) and the longer (60min) starvation. Protein abundances and post-translational modifications confirmed that activation of the NtrC regulon acts as the first line of defense against nitrogen starvation. The ribosome inactivating protein Rmf was induced shortly after ammonium exhaustion and this was preceded by induction of other ribosome inactivating proteins such as Hpf and RaiA supporting the hypothesis that ribosome shut-down is a key process during nitrogen limitation stress. The proteomic data revealed that growth arrest due to nitrogen starvation correlates with the accumulation of proteins involved in DNA condensation, RNA and protein catabolism and ribosome hibernation. Collectively, these proteome adaptations will result in metabolic inactive cells which are likely to exhibit multidrug tolerance.

Label-free Proteomic Reveals that Cowpea Severe Mosaic Virus Transiently Suppresses the Host Leaf Protein Accumulation During the Compatible Interaction with Cowpea (Vigna unguiculata [L.] Walp.).

Viruses are important plant pathogens that threaten diverse crops worldwide. Diseases caused by Cowpea severe mosaic virus (CPSMV) have drawn attention because of the serious damages they cause to economically important crops including cowpea. This work was undertaken to quantify and identify the responsive proteins of a susceptible cowpea genotype infected with CPSMV, in comparison with mock-inoculated controls, using label-free quantitative proteomics and databanks, aiming at providing insights on the molecular basis of this compatible interaction. Cowpea leaves were mock- or CPSMV-inoculated and 2 and 6 days later proteins were extracted and analyzed. More than 3000 proteins were identified (data available via ProteomeXchange, identifier PXD005025) and 75 and 55 of them differentially accumulated in response to CPSMV, at 2 and 6 DAI, respectively. At 2 DAI, 76% of the proteins decreased in amount and 24% increased. However, at 6 DAI, 100% of the identified proteins increased. Thus, CPSMV transiently suppresses the synthesis of proteins involved particularly in the redox homeostasis, protein synthesis, defense, stress, RNA/DNA metabolism, signaling, and other functions, allowing viral invasion and spread in cowpea tissues.

HLA-DQ molecules as affinity matrix for identification of gluten T cell epitopes.

Even though MHC class II is a dominant susceptibility factor for many diseases, culprit T cell epitopes presented by disease-associated MHC molecules remain largely elusive. T cells of celiac disease lesions recognize cereal gluten epitopes presented by the disease-associated HLA molecules DQ2.5, DQ2.2, or DQ8. Employing celiac disease and complex gluten Ag digests as a model, we tested the feasibility of using DQ2.5 and DQ2.2 as an affinity matrix for identification of disease-relevant T cell epitopes. Known gluten T cell epitope peptides were enriched by DQ2.5, whereas a different set of peptides was enriched by DQ2.2. Of 86 DQ2.2-enriched peptides, four core sequences dominated. One of these core sequences is a previously known epitope and two others are novel epitopes. The study provides insight into the selection of gluten epitopes by DQ2.2. Furthermore, the approach presented is relevant for epitope identification in other MHC class II-associated disorders.

Mechanisms underlying AQP4 accumulation in astrocyte endfeet.

The brain-blood interface holds the key to our understanding of how cerebral blood flow is regulated and how water and solutes are exchanged between blood and brain. The highly specialized astrocytic membranes that enwrap brain microvessels are salient constituents of the brain-blood interface. These endfoot membranes contain a distinct set of molecules that is anchored to the subendothelial basal lamina forming an endfoot-basal lamina junctional complex. Here we explore the mechanisms underpinning the formation of this complex. By use of a tailor made model system we show that endothelial cells promote AQP4 accumulation by exerting an inductive effect through extracellular matrix components such as agrin, as well as through a direct mechanical interaction with the endfoot processes. Through the compounds they secrete, the endothelial cells also increase AQP4 expression. The present data suggest that the highly specialized gliovascular interface is established through inductive processes that include both chemical and mechanical factors. GLIA 2015;63:2073-2091.

Intrathecal BCR transcriptome in multiple sclerosis versus other neuroinflammation: Equally diverse and compartmentalized, but more mutated, biased and overlapping with the proteome.

The mechanisms driving the intrathecal synthesis of IgG in multiple sclerosis (MS) are unknown. We combined high-throughput sequencing of transcribed immunoglobulin heavy-chain variable (IGHV) genes and mass spectrometry to chart the diversity and compartmentalization of IgG-producing B cells in the cerebrospinal fluid (CSF) of MS patients and controls with other neuroinflammatory diseases. In both groups, a few clones dominated the intrathecal IGHV transcriptome. In most MS patients and some controls, dominant transcripts matched the CSF IgG. The IGHV transcripts in CSF of MS patients frequently carried IGHV4 genes and had more replacement mutations compared to controls. In both groups, dominant IGHV transcripts were identified within clusters of clonally related B cells that had identical or related IGHV transcripts in the blood. These findings suggest more pronounced affinity maturation, but an equal degree of diversity and compartmentalization of the intrathecal B-cell response in MS compared to other neuroinflammatory diseases.

Different binding motifs of the celiac disease-associated HLA molecules DQ2.5, DQ2.2, and DQ7.5 revealed by relative quantitative proteomics of endogenous peptide repertoires.

Celiac disease is caused by intolerance to cereal gluten proteins, and HLA-DQ molecules are involved in the disease pathogenesis by presentation of gluten peptides to CD4(+) T cells. The α- or ß-chain sharing HLA molecules DQ2.5, DQ2.2, and DQ7.5 display different risks for the disease. It was recently demonstrated that T cells of DQ2.5 and DQ2.2 patients recognize distinct sets of gluten epitopes, suggesting that these two DQ2 variants select different peptides for display. To explore whether this is the case, we performed a comprehensive comparison of the endogenous self-peptides bound to HLA-DQ molecules of B-lymphoblastoid cell lines. Peptides were eluted from affinity-purified HLA molecules of nine cell lines and subjected to quadrupole orbitrap mass spectrometry and MaxQuant software analysis. Altogether, 12,712 endogenous peptides were identified at very different relative abundances. Hierarchical clustering of normalized quantitative data demonstrated significant differences in repertoires of peptides between the three DQ variant molecules. The neural network-based method, NNAlign, was used to identify peptide-binding motifs. The binding motifs of DQ2.5 and DQ7.5 concurred with previously established binding motifs. The binding motif of DQ2.2 was strikingly different from that of DQ2.5 with position P3 being a major anchor having a preference for threonine and serine. This is notable as three recently identified epitopes of gluten recognized by T cells of DQ2.2 celiac patients harbor serine at position P3. This study demonstrates that relative quantitative comparison of endogenous peptides sampled from our protein metabolism by HLA molecules provides clues to understand HLA association with disease.

Assessing the citrullinome in rheumatoid arthritis synovial fluid with and without enrichment of citrullinated peptides.

Protein citrullination is a posttranslational modification that has attracted increased attention, especially for its involvement in rheumatoid arthritis (RA). Here, we assess the citrullinome in RA synovial fluid by direct LC-MS/MS analysis and by the use of an enrichment strategy based on citrulline specific biotinylation. RA synovial fluid was depleted for abundant proteins, and total and depleted fractions were analyzed. Frequency of citrullinated peptides and their degree of citrullination could be determined for four known RA autoantigens, as well as a novel in vivo autocitrullination site of peptidylarginine deiminase 4. From the analysis of total and depleted synovial fluid after enrichment we could estimate the numbers of citrullinated peptides to be approximately 3600 and 2100, respectively. However, identification of these biotinylated peptides by MS/MS turned out to be very difficult due to fragmentation of the biotin moiety. By direct MS analysis of the total and depleted synovial fluid without enrichment, 119 and 157 citrullinated peptides were identified, respectively. This indicates that direct analysis allows identification of only a fraction of the citrullinated proteins present in synovial fluid and that specific enrichment is still needed for a comprehensive in-depth elucidation of the citrullinome.

Proteogenomic analysis of polymorphisms and gene annotation divergences in prokaryotes using a clustered mass spectrometry-friendly database.

Precise annotation of genes or open reading frames is still a difficult task that results in divergence even for data generated from the same genomic sequence. This has an impact in further proteomic studies, and also compromises the characterization of clinical isolates with many specific genetic variations that may not be represented in the selected database. We recently developed software called multistrain mass spectrometry prokaryotic database builder (MSMSpdbb) that can merge protein databases from several sources and be applied on any prokaryotic organism, in a proteomic-friendly approach. We generated a database for the Mycobacterium tuberculosis complex (using three strains of Mycobacterium bovis and five of M. tuberculosis), and analyzed data collected from two laboratory strains and two clinical isolates of M. tuberculosis. We identified 2561 proteins, of which 24 were present in M. tuberculosis H37Rv samples, but not annotated in the M. tuberculosis H37Rv genome. We were also able to identify 280 nonsynonymous single amino acid polymorphisms and confirm 367 translational start sites. As a proof of concept we applied the database to whole-genome DNA sequencing data of one of the clinical isolates, which allowed the validation of 116 predicted single amino acid polymorphisms and the annotation of 131 N-terminal start sites. Moreover we identified regions not present in the original M. tuberculosis H37Rv sequence, indicating strain divergence or errors in the reference sequence. In conclusion, we demonstrated the potential of using a merged database to better characterize laboratory or clinical bacterial strains.

Using a label-free proteomics method to identify differentially abundant proteins in closely related hypo- and hypervirulent clinical Mycobacterium tuberculosis Beijing isolates.

Although the genome of the Mycobacterium tuberculosis H37Rv laboratory strain has been available for over 10 years, it is only recently that genomic information from clinical isolates has been used to generate the hypothesis of virulence differences between different strains. In addition, the relationship between strains displaying differing virulence in an epidemiological setting and their behavior in animal models has received little attention. The potential causes for variation in virulence between strains, as determined by differential protein expression, have similarly been a neglected area of investigation. In this study, we used a label-free quantitative proteomics approach to estimate differences in protein abundance between two closely related Beijing genotypes that have been shown to be hyper- and hypovirulent on the basis of both epidemiological and mouse model studies. We were able to identify a total of 1668 proteins from both samples, and protein abundance calculations revealed that 48 proteins were over-represented in the hypovirulent isolate, whereas 53 were over-represented in the hypervirulent. Functional classification of these results shows that molecules of cell wall organization and DNA transcription regulatory proteins may have a critical influence in defining the level of virulence. The reduction in the presence of ESAT-6, other Esx-like proteins, and FbpD (MPT51) in the hypervirulent strain indicates that changes in the repertoire of highly immunogenic proteins can be a defensive process undertaken by the virulent cell. In addition, most of the previously well characterized gene targets related to virulence were found to be similarly expressed in our model. Our data support the use of proteomics as a complementary tool for genomic comparisons to understand the biology of M. tuberculosis virulence.

A proteomic view of mycobacteria.

Tuberculosis, the disease caused by Mycobacterium tuberculosis, remains a relevant public health issue. This is due mostly to the coepidemiology with HIV/AIDS, the appearance of multidrug-resistant strains globally, and failure of BCG (bacillus Calmette-Guerin) vaccination to confer complete protection. This bacterium was one of the first to have its genome sequenced, yet over a decade after the release of the genomic information, the characterization of its phylogenetic tree and of different strain variants inside this species revealed that much is still needed to be done for a full understanding of the M. tuberculosis genome and proteome. Current methods using LC-MS/MS and hybrid high-resolution mass spectrometers can identify 2400-2800 proteins of the 4000 predicted genes in M. tuberculosis. In this article, we review relevant details of this bacterium's pathology and immunology, describing articles where proteomics helped the community to tackle some of the organism biology, from understanding strain diversity, cellular structure composition, immunogenicity, and host-pathogen interactions. Finally, we will discuss the challenges yet to be fulfilled in order to better characterize M. tuberculosis by proteomics.

MSMSpdbb: providing protein databases of closely related organisms to improve proteomic characterization of prokaryotic microbes.

UNLABELLED: The Microbial Proteomic Resource (MPR) is a repository service that contains non-redundant protein databases of related bacterial strains, which were generated through an in-house developed software called Multi-Strain Mass Spectrometry Prokaryotic DataBase Builder (MSMSpdbb). MSMSpdbb merges and clusters protein sequences inferred from genomic sequences, and provide a protein list in FASTA format that covers for divergence in gene annotation, translational start site choice and presence of single nucleotide polymorphisms and other mutations. AVAILABILITY: MSMSpdbb was developed in C++ using the Qt libraries (Nokia) and licensed under the GNU General Public License version 2. MSMSpdbb is freely available, and its installation files, instructions for use and additional documentation can be found at the MPR web site http://org.uib.no/prokaryotedb/ can also be found at Proteomecommons.org (see Supplementary Methods for Hash number).

Comparison of membrane proteins of Mycobacterium tuberculosis H37Rv and H37Ra strains.

BACKGROUND: The potential causes for variation in virulence between distinct M. tuberculosis strains are still not fully known. However, differences in protein expression are probably an important factor. In this study we used a label-free quantitative proteomic approach to estimate differences in protein abundance between two closely related M. tuberculosis strains; the virulent H37Rv strain and its attenuated counterpart H37Ra. RESULTS: We were able to identify more than 1700 proteins from both strains. As expected, the majority of the identified proteins had similar relative abundance in the two strains. However, 29 membrane-associated proteins were observed with a 5 or more fold difference in their relative abundance in one strain compared to the other. Of note, 19 membrane- and lipo-proteins had higher abundance in H37Rv, while another 10 proteins had a higher abundance in H37Ra. Interestingly, the possible protein-export membrane protein SecF (Rv2586c), and three ABC-transporter proteins (Rv0933, Rv1273c and Rv1819c) were among the more abundant proteins in M. tuberculosis H37Rv. CONCLUSION: Our data suggests that the bacterial secretion system and the transmembrane transport system may be important determinants of the ability of distinct M. tuberculosis strains to cause disease.

Analysis of detergent-insoluble and whole cell lysate fractions of resting neutrophils using high-resolution mass spectrometry.

Neutrophilic granulocytes play a major role in the initiation and resolution of the inflammatory response, and demonstrate significant transcriptional and translational activity. Although much was known about neutrophils prior to the introduction of proteomics, the use of MS-based methodologies has provided an unprecedented tool to confirm and extend previous findings. In the present study, we performed a Gel-LC-MS/MS analysis of neutrophil detergent insoluble and whole cell lysate fractions of resting neutrophils. We achieved a set of identifications through the use of high-resolution mass spectrometry and validation of its data. We identified a total of 1249 proteins with a wide range of intensities from both detergent-insoluble and whole cell lysate fractions, allowing a mapping of proteins such as those involved in intracellular transport (Rab and Sec family proteins) and cell signaling (S100 proteins). These results represent the most comprehensive proteomic characterization of resting human neutrophils to date, and provide important information relevant for further studies of the immune system in health and disease. The methods applied here can be employed to help us understand how neutrophils respond to various physiologic and pathophysiologic conditions and could be extended to protein quantitation after cell activation.

Definition of novel cell envelope associated proteins in Triton X-114 extracts of Mycobacterium tuberculosis H37Rv.

BACKGROUND: Membrane- and membrane-associated proteins are important for the pathogenicity of bacteria. We have analysed the content of these proteins in virulent Mycobacterium tuberculosis H37Rv using Triton X-114 detergent-phase separation for extraction of lipophilic proteins, followed by their identification with high resolution mass spectrometry. RESULTS: In total, 1417 different proteins were identified. In silico analysis of the identified proteins revealed that 248 proteins had at least one predicted trans-membrane region. Also, 64 of the identified proteins were predicted lipoproteins, and 54 proteins were predicted as outer membrane proteins. Three-hundred-and-ninety-five of the observed proteins, including 91 integral membrane proteins were described for the first time. Comparison of abundance levels of the identified proteins was performed using the exponentially modified protein abundance index (emPAI) which takes into account the number of the observable peptides to the number of experimentally observed peptide ions for a given protein. The outcome showed that among the membrane-and membrane-associated proteins several proteins are present with high relative abundance. Further, a close examination of the lipoprotein LpqG (Rv3623) which is only detected in the membrane fractions of M. tuberculosis but not in M. bovis, revealed that the homologous gene in M. bovis lack the signal peptide and lipobox motif, suggesting impaired export to the membrane. CONCLUSIONS: Altogether, we have identified a substantial proportion of membrane- and membrane-associated proteins of M. tuberculosis H37Rv, compared the relative abundance of the identified proteins and also revealed subtle differences between the different members of the M. tuberculosis complex.

EpitoCore: Mining Conserved Epitope Vaccine Candidates in the Core Proteome of Multiple Bacteria Strains.

In reverse vaccinology approaches, complete proteomes of bacteria are submitted to multiple computational prediction steps in order to filter proteins that are possible vaccine candidates. Most available tools perform such analysis only in a single strain, or a very limited number of strains. But the vast amount of genomic data had shown that most bacteria contain pangenomes, i.e., their genomic information contains core, conserved genes, and random accessory genes specific to each strain. Therefore, in reverse vaccinology methods it is of the utmost importance to define core proteins and core epitopes. EpitoCore is a decision-tree pipeline developed to fulfill that need. It provides surfaceome prediction of proteins from related strains, defines core proteins within those, calculate their immunogenicity, predicts epitopes for a given set of MHC alleles defined by the user, and then reports if epitopes are located extracellularly and if they are conserved among the core homologs. Pipeline performance is illustrated by mining peptide vaccine candidates in Mycobacterium avium hominissuis strains. From a total proteome of ~4,800 proteins per strain, EpitoCore predicted 103 highly immunogenic core homologs located at cell surface, many of those related to virulence and drug resistance. Conserved epitopes identified among these homologs allows the users to define sets of peptides with potential to immunize the largest coverage of tested HLA alleles using peptide-based vaccines. Therefore, EpitoCore is able to provide automated identification of conserved epitopes in bacterial pangenomic datasets.