Mass Spectrometry-Based Proteomics Reveal Alcohol Dehydrogenase 1B as a Blood Biomarker Candidate to Monitor Acetaminophen-Induced Liver Injury.

Acute liver injury (ALI) is a severe disorder resulting from excessive hepatocyte cell death, and frequently caused by acetaminophen intoxication. Clinical management of ALI progression is hampered by the dearth of blood biomarkers available. In this study, a bioinformatics workflow was developed to screen omics databases and identify potential biomarkers for hepatocyte cell death. Then, discovery proteomics was harnessed to select from among these candidates those that were specifically detected in the blood of acetaminophen-induced ALI patients. Among these candidates, the isoenzyme alcohol dehydrogenase 1B (ADH1B) was massively leaked into the blood. To evaluate ADH1B, we developed a targeted proteomics assay and quantified ADH1B in serum samples collected at different times from 17 patients admitted for acetaminophen-induced ALI. Serum ADH1B concentrations increased markedly during the acute phase of the disease, and dropped to undetectable levels during recovery. In contrast to alanine aminotransferase activity, the rapid drop in circulating ADH1B concentrations was followed by an improvement in the international normalized ratio (INR) within 10-48 h, and was associated with favorable outcomes. In conclusion, the combination of omics data exploration and proteomics revealed ADH1B as a new blood biomarker candidate that could be useful for the monitoring of acetaminophen-induced ALI.

LymphoAtlas: a dynamic and integrated phosphoproteomic resource of TCR signaling in primary T cells reveals ITSN2 as a regulator of effector functions.

T-cell receptor (TCR) ligation-mediated protein phosphorylation regulates the activation, cellular responses, and fates of T cells. Here, we used time-resolved high-resolution phosphoproteomics to identify, quantify, and characterize the phosphorylation dynamics of thousands of phosphorylation sites in primary T cells during the first 10 min after TCR stimulation. Bioinformatic analysis of the data revealed a coherent orchestration of biological processes underlying T-cell activation. In particular, functional modules associated with cytoskeletal remodeling, transcription, translation, and metabolic processes were mobilized within seconds after TCR engagement. Among proteins whose phosphorylation was regulated by TCR stimulation, we demonstrated, using a fast-track gene inactivation approach in primary lymphocytes, that the ITSN2 adaptor protein regulated T-cell effector functions. This resource, called LymphoAtlas, represents an integrated pipeline to further decipher the organization of the signaling network encoding T-cell activation. LymphoAtlas is accessible to the community at: https://bmm-lab.github.io/LymphoAtlas.

Proline: an efficient and user-friendly software suite for large-scale proteomics.

MOTIVATION: The proteomics field requires the production and publication of reliable mass spectrometry-based identification and quantification results. Although many tools or algorithms exist, very few consider the importance of combining, in a unique software environment, efficient processing algorithms and a data management system to process and curate hundreds of datasets associated with a single proteomics study. RESULTS: Here, we present Proline, a robust software suite for analysis of MS-based proteomics data, which collects, processes and allows visualization and publication of proteomics datasets. We illustrate its ease of use for various steps in the validation and quantification workflow, its data curation capabilities and its computational efficiency. The DDA label-free quantification workflow efficiency was assessed by comparing results obtained with Proline to those obtained with a widely used software using a spiked-in sample. This assessment demonstrated Proline's ability to provide high quantification accuracy in a user-friendly interface for datasets of any size. AVAILABILITY AND IMPLEMENTATION: Proline is available for Windows and Linux under CECILL open-source license. It can be deployed in client-server mode or in standalone mode at http://proline.profiproteomics.fr/#downloads. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Introducing plasma/serum glycodepletion for the targeted proteomics analysis of cytolysis biomarkers.

A major class of clinical biomarkers is constituted of intracellular proteins which are leaking into the blood following ischemia, exposure to toxic xenobiotics or mechanical aggression. Their ectopic presence in plasma/serum is an indicator of tissue damage and raises a warning signal. These proteins, referred to as cytolysis biomarkers, are generally of cytoplasmic origin and as such, are devoid of glycosylation. In contrast, most plasma/serum proteins originate from the hepatic secretory pathway and are heavily glycosylated (at the exception of albumin). Recent advances in targeted proteomics have supported the parallelized evaluation of new blood biomarkers. However, these analytical methods must be combined with prefractionation strategies that reduce the complexity of plasma/serum matrix. In this article, we present the glycodepletion method, which reverses the hydrazide-based glycocapture concept to remove plasma/serum glycoproteins from plasma/serum matrix and facilitates the detection of cytolysis biomarkers. Glycodepletion was integrated to a targeted proteomics pipeline to evaluate 4 liver cytolysis biomarker candidates in the context of acetaminophen-induced acute hepatitis.

Large-Scale SRM Screen of Urothelial Bladder Cancer Candidate Biomarkers in Urine.

Urothelial bladder cancer is a condition associated with high recurrence and substantial morbidity and mortality. Noninvasive urinary tests that would detect bladder cancer and tumor recurrence are required to significantly improve patient care. Over the past decade, numerous bladder cancer candidate biomarkers have been identified in the context of extensive proteomics or transcriptomics studies. To translate these findings in clinically useful biomarkers, the systematic evaluation of these candidates remains the bottleneck. Such evaluation involves large-scale quantitative LC-SRM (liquid chromatography-selected reaction monitoring) measurements, targeting hundreds of signature peptides by monitoring thousands of transitions in a single analysis. The design of highly multiplexed SRM analyses is driven by several factors: throughput, robustness, selectivity and sensitivity. Because of the complexity of the samples to be analyzed, some measurements (transitions) can be interfered by coeluting isobaric species resulting in biased or inconsistent estimated peptide/protein levels. Thus the assessment of the quality of SRM data is critical to allow flagging these inconsistent data. We describe an efficient and robust method to process large SRM data sets, including the processing of the raw data, the detection of low-quality measurements, the normalization of the signals for each protein, and the estimation of protein levels. Using this methodology, a variety of proteins previously associated with bladder cancer have been assessed through the analysis of urine samples from a large cohort of cancer patients and corresponding controls in an effort to establish a priority list of most promising candidates to guide subsequent clinical validation studies.

Multiplex and accurate quantification of acute kidney injury biomarker candidates in urine using Protein Standard Absolute Quantification (PSAQ) and targeted proteomics.

There is a need for multiplex, specific and quantitative methods to speed-up the development of acute kidney injury biomarkers and allow a more specific diagnosis. Targeted proteomic analysis combined with stable isotope dilution has recently emerged as a powerful option for the parallelized evaluation of candidate biomarkers. This article presents the development of a targeted proteomic assay to quantify 4 acute kidney injury biomarker candidates in urine samples. The proteins included in the assessed panel consisted of myo-inositol oxygenase (MIOX), phosphoenolpyruvate carboxykinase 1 (PCK1), neutrophil gelatinase-associated lipocalin (NGAL) and liver fatty acid-binding protein (L-FABP). The proteomic assay combined an antibody-free sample preparation and a liquid chromatography-selected reaction monitoring (LC-SRM) analysis pipeline. For accurate quantification of the selected candidates, we used PSAQ (Protein Standard Absolute Quantification) standards which are isotopically labeled versions of the target proteins. When added directly to the biological samples, these standards improve detection specificity and quantification accuracy. The multiplexed assay developed for the 4 biomarker candidates showed excellent analytical performance, in line with the recommendations of health authorities. Tests on urine from two small patient cohorts and a group of healthy donors confirmed the relevance of NGAL and L-FABP as biomarkers for AKI diagnosis. The assay is readily adaptable to other biomarker candidates and should be very useful for the simultaneous and accurate quantification of multiple biomarkers.

Looking for Missing Proteins in the Proteome of Human Spermatozoa: An Update.

The Chromosome-Centric Human Proteome Project (C-HPP) aims to identify "missing" proteins in the neXtProt knowledgebase. We present an in-depth proteomics analysis of the human sperm proteome to identify testis-enriched missing proteins. Using protein extraction procedures and LC-MS/MS analysis, we detected 235 proteins (PE2-PE4) for which no previous evidence of protein expression was annotated. Through LC-MS/MS and LC-PRM analysis, data mining, and immunohistochemistry, we confirmed the expression of 206 missing proteins (PE2-PE4) in line with current HPP guidelines (version 2.0). Parallel reaction monitoring acquisition and sythetic heavy labeled peptides targeted 36 ≪one-hit wonder≫ candidates selected based on prior peptide spectrum match assessment. 24 were validated with additional predicted and specifically targeted peptides. Evidence was found for 16 more missing proteins using immunohistochemistry on human testis sections. The expression pattern for some of these proteins was specific to the testis, and they could possibly be valuable markers with fertility assessment applications. Strong evidence was also found of four "uncertain" proteins (PE5); their status should be re-examined. We show how using a range of sample preparation techniques combined with MS-based analysis, expert knowledge, and complementary antibody-based techniques can produce data of interest to the community. All MS/MS data are available via ProteomeXchange under identifier PXD003947. In addition to contributing to the C-HPP, we hope these data will stimulate continued exploration of the sperm proteome.

Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods.

This data article describes a controlled, spiked proteomic dataset for which the "ground truth" of variant proteins is known. It is based on the LC-MS analysis of samples composed of a fixed background of yeast lysate and different spiked amounts of the UPS1 mixture of 48 recombinant proteins. It can be used to objectively evaluate bioinformatic pipelines for label-free quantitative analysis, and their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. More specifically, it can be useful for tuning software tools parameters, but also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. The raw MS files can be downloaded from ProteomeXchange with identifier PXD001819. Starting from some raw files of this dataset, we also provide here some processed data obtained through various bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, to exemplify the use of such data in the context of software benchmarking, as discussed in details in the accompanying manuscript [1]. The experimental design used here for data processing takes advantage of the different spike levels introduced in the samples composing the dataset, and processed data are merged in a single file to facilitate the evaluation and illustration of software tools results for the detection of variant proteins with different absolute expression levels and fold change values.

Benchmarking quantitative label-free LC-MS data processing workflows using a complex spiked proteomic standard dataset.

Proteomic workflows based on nanoLC-MS/MS data-dependent-acquisition analysis have progressed tremendously in recent years. High-resolution and fast sequencing instruments have enabled the use of label-free quantitative methods, based either on spectral counting or on MS signal analysis, which appear as an attractive way to analyze differential protein expression in complex biological samples. However, the computational processing of the data for label-free quantification still remains a challenge. Here, we used a proteomic standard composed of an equimolar mixture of 48 human proteins (Sigma UPS1) spiked at different concentrations into a background of yeast cell lysate to benchmark several label-free quantitative workflows, involving different software packages developed in recent years. This experimental design allowed to finely assess their performances in terms of sensitivity and false discovery rate, by measuring the number of true and false-positive (respectively UPS1 or yeast background proteins found as differential). The spiked standard dataset has been deposited to the ProteomeXchange repository with the identifier PXD001819 and can be used to benchmark other label-free workflows, adjust software parameter settings, improve algorithms for extraction of the quantitative metrics from raw MS data, or evaluate downstream statistical methods. BIOLOGICAL SIGNIFICANCE: Bioinformatic pipelines for label-free quantitative analysis must be objectively evaluated in their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. This can be done through the use of complex spiked samples, for which the "ground truth" of variant proteins is known, allowing a statistical evaluation of the performances of the data processing workflow. We provide here such a controlled standard dataset and used it to evaluate the performances of several label-free bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, for detection of variant proteins with different absolute expression levels and fold change values. The dataset presented here can be useful for tuning software tool parameters, and also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods.

Computational and Mass-Spectrometry-Based Workflow for the Discovery and Validation of Missing Human Proteins: Application to Chromosomes 2 and 14.

In the framework of the C-HPP, our Franco-Swiss consortium has adopted chromosomes 2 and 14, coding for a total of 382 missing proteins (proteins for which evidence is lacking at protein level). Over the last 4 years, the French proteomics infrastructure has collected high-quality data sets from 40 human samples, including a series of rarely studied cell lines, tissue types, and sample preparations. Here we described a step-by-step strategy based on the use of bioinformatics screening and subsequent mass spectrometry (MS)-based validation to identify what were up to now missing proteins in these data sets. Screening database search results (85,326 dat files) identified 58 of the missing proteins (36 on chromosome 2 and 22 on chromosome 14) by 83 unique peptides following the latest release of neXtProt (2014-09-19). PSMs corresponding to these peptides were thoroughly examined by applying two different MS-based criteria: peptide-level false discovery rate calculation and expert PSM quality assessment. Synthetic peptides were then produced and used to generate reference MS/MS spectra. A spectral similarity score was then calculated for each pair of reference-endogenous spectra and used as a third criterion for missing protein validation. Finally, LC-SRM assays were developed to target proteotypic peptides from four of the missing proteins detected in tissue/cell samples, which were still available and for which sample preparation could be reproduced. These LC-SRM assays unambiguously detected the endogenous unique peptide for three of the proteins. For two of these, identification was confirmed by additional proteotypic peptides. We concluded that of the initial set of 58 proteins detected by the bioinformatics screen, the consecutive MS-based validation criteria led to propose the identification of 13 of these proteins (8 on chromosome 2 and 5 on chromosome 14) that passed at least two of the three MS-based criteria. Thus, a rigorous step-by-step approach combining bioinformatics screening and MS-based validation assays is particularly suitable to obtain protein-level evidence for proteins previously considered as missing. All MS/MS data have been deposited in ProteomeXchange under identifier PXD002131.

Urine sample preparation and fractionation for global proteome profiling by LC-MS.

Urine has garnered tremendous interest over the past decade as a potential source of protein biomarkers for various pathologies. However, due to its low protein concentration and the presence of interfering compounds, urine constitutes a challenging analyte in proteomics. In the context of a project aimed at the discovery and evaluation of new candidate biomarkers of bladder cancer in urine, our laboratory has implemented and evaluated an array of preparation techniques for urinary proteome analysis. We present here the protocol that, in our hands, yielded the best overall proteome coverage with the lowest analytical effort. It begins with protein precipitation using trichloroacetic acid, in solution digestion and RP-C18 cartridge desalting of the resulting peptides mixture, and is followed by peptide fractionation by gel-free isoelectric focusing, and nano-LC-MS/MS for database compilation.

DIGESTIF: a universal quality standard for the control of bottom-up proteomics experiments.

In bottom-up mass spectrometry-based proteomics analyses, variability at any step of the process, particularly during sample proteolysis, directly affects the sensitivity, accuracy, and precision of peptide detection and quantification. Currently, no generic internal standards are available to control the quality of sample processing steps. This makes it difficult to assess the comparability of MS proteomic data obtained under different experimental conditions. Here, we describe the design, synthesis, and validation of a universal protein standard, called DIGESTIF, that can be added to any biological sample. The DIGESTIF standard consists of a soluble recombinant protein scaffold to which a set of 11 artificial peptides (iRT peptides) with good ionization properties has been incorporated. In the protein scaffold, the amino acids flanking iRT peptide cleavage sites were selected either to favor or hinder protease cleavage. After sample processing, the retention time and relative intensity pattern of the released iRT peptides can be used to assess the quality of sample workup, the extent of digestion, and the performance of the LC-MS system. Thus, DIGESTIF can be used to standardize a broad spectrum of applications, ranging from simple replicate measurements to large-scale biomarker screening in biomedical applications.

Computational modeling of the main signaling pathways involved in mast cell activation.

A global and rigorous understanding of the signaling pathways and cross-regulatory processes involved in mast cell activation requires the integration of published information with novel functional datasets into a comprehensive computational model. Based on an exhaustive curation of the existing literature and using the software CellDesigner, we have built and annotated a comprehensive molecular map for the FcεRI signaling network. This map can be used to visualize and interpret high-throughput expression data. Furthermore, leaning on this map and using the logical modeling software GINsim, we have derived a qualitative dynamical model, which recapitulates the most salient features of mast cell activation. The resulting logical model can be used to explore the dynamical properties of the system and its responses to different stimuli, in normal or mutant conditions.

Mass spectrometry-based workflow for accurate quantification of Escherichia coli enzymes: how proteomics can play a key role in metabolic engineering.

Metabolic engineering aims to design high performance microbial strains producing compounds of interest. This requires systems-level understanding; genome-scale models have therefore been developed to predict metabolic fluxes. However, multi-omics data including genomics, transcriptomics, fluxomics, and proteomics may be required to model the metabolism of potential cell factories. Recent technological advances to quantitative proteomics have made mass spectrometry-based quantitative assays an interesting alternative to more traditional immuno-affinity based approaches. This has improved specificity and multiplexing capabilities. In this study, we developed a quantification workflow to analyze enzymes involved in central metabolism in Escherichia coli (E. coli). This workflow combined full-length isotopically labeled standards with selected reaction monitoring analysis. First, full-length (15)N labeled standards were produced and calibrated to ensure accurate measurements. Liquid chromatography conditions were then optimized for reproducibility and multiplexing capabilities over a single 30-min liquid chromatography-MS analysis. This workflow was used to accurately quantify 22 enzymes involved in E. coli central metabolism in a wild-type reference strain and two derived strains, optimized for higher NADPH production. In combination with measurements of metabolic fluxes, proteomics data can be used to assess different levels of regulation, in particular enzyme abundance and catalytic rate. This provides information that can be used to design specific strains used in biotechnology. In addition, accurate measurement of absolute enzyme concentrations is key to the development of predictive kinetic models in the context of metabolic engineering.

Proteomic analysis of the SH2 domain-containing leukocyte protein of 76 kDa (SLP76) interactome in resting and activated primary mast cells [corrected].

We report the first proteomic analysis of the SLP76 interactome in resting and activated primary mouse mast cells. This was made possible by a novel genetic approach used for the first time here. It consists in generating knock-in mice that express signaling molecules bearing a C-terminal tag that has a high affinity for a streptavidin analog. Tagged molecules can be used as molecular baits to affinity-purify the molecular complex in which they are engaged, which can then be studied by mass spectrometry. We examined first SLP76 because, although this cytosolic adapter is critical for both T cell and mast cell activation, its role is well known in T cells but not in mast cells. Tagged SLP76 was expressed in physiological amounts and fully functional in mast cells. We unexpectedly found that SLP76 is exquisitely sensitive to mast cell granular proteases, that Zn(2+)-dependent metalloproteases are especially abundant in mast cells and that they were responsible for SLP76 degradation. Adding a Zn(2+) chelator fully protected SLP76 in mast cell lysates, thereby enabling an efficient affinity-purification of this adapter with its partners. Label-free quantitative mass spectrometry analysis of affinity-purified SLP76 interactomes uncovered both partners already described in T cells and novel partners seen in mast cells only. Noticeably, molecules inducibly recruited in both cell types primarily concur to activation signals, whereas molecules recruited in activated mast cells only are mostly associated with inhibition signals. The transmembrane adapter LAT2, and the serine/threonine kinase with an exchange factor activity Bcr were the most recruited molecules. Biochemical and functional validations established the unexpected finding that Bcr is recruited by SLP76 and positively regulates antigen-induced mast cell activation. Knock-in mice expressing tagged molecules with a normal tissue distribution and expression therefore provide potent novel tools to investigate signalosomes and to uncover novel signaling molecules in mast cells.

Identification of a novel BET bromodomain inhibitor-sensitive, gene regulatory circuit that controls Rituximab response and tumour growth in aggressive lymphoid cancers.

Immuno-chemotherapy elicit high response rates in B-cell non-Hodgkin lymphoma but heterogeneity in response duration is observed, with some patients achieving cure and others showing refractory disease or relapse. Using a transcriptome-powered targeted proteomics screen, we discovered a gene regulatory circuit involving the nuclear factor CYCLON which characterizes aggressive disease and resistance to the anti-CD20 monoclonal antibody, Rituximab, in high-risk B-cell lymphoma. CYCLON knockdown was found to inhibit the aggressivity of MYC-overexpressing tumours in mice and to modulate gene expression programs of biological relevance to lymphoma. Furthermore, CYCLON knockdown increased the sensitivity of human lymphoma B cells to Rituximab in vitro and in vivo. Strikingly, this effect could be mimicked by in vitro treatment of lymphoma B cells with a small molecule inhibitor for BET bromodomain proteins (JQ1). In summary, this work has identified CYCLON as a new MYC cooperating factor that autonomously drives aggressive tumour growth and Rituximab resistance in lymphoma. This resistance mechanism is amenable to next-generation epigenetic therapy by BET bromodomain inhibition, thereby providing a new combination therapy rationale for high-risk lymphoma.

Pandoraviruses: amoeba viruses with genomes up to 2.5 Mb reaching that of parasitic eukaryotes.

Ten years ago, the discovery of Mimivirus, a virus infecting Acanthamoeba, initiated a reappraisal of the upper limits of the viral world, both in terms of particle size (>0.7 micrometers) and genome complexity (>1000 genes), dimensions typical of parasitic bacteria. The diversity of these giant viruses (the Megaviridae) was assessed by sampling a variety of aquatic environments and their associated sediments worldwide. We report the isolation of two giant viruses, one off the coast of central Chile, the other from a freshwater pond near Melbourne (Australia), without morphological or genomic resemblance to any previously defined virus families. Their micrometer-sized ovoid particles contain DNA genomes of at least 2.5 and 1.9 megabases, respectively. These viruses are the first members of the proposed "Pandoravirus" genus, a term reflecting their lack of similarity with previously described microorganisms and the surprises expected from their future study.

A micro-silicon chip for in vivo cerebral imprint in monkey.

Access to cerebral tissue is essential to better understand the molecular mechanisms associated with neurodegenerative diseases. In this study, we present, for the first time, a new tool designed to obtain molecular and cellular cerebral imprints in the striatum of anesthetized monkeys. The imprint is obtained during a spatially controlled interaction of a chemically modified micro-silicon chip with the brain tissue. Scanning electron and immunofluorescence microscopies showed homogeneous capture of cerebral tissue. Nano-liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS) analysis of proteins harvested on the chip allowed the identification of 1158 different species of proteins. The gene expression profiles of mRNA extracted from the imprint tool showed great similarity to those obtained via the gold standard approach, which is based on post-mortem sections of the same nucleus. Functional analysis of the harvested molecules confirmed the spatially controlled capture of striatal proteins implicated in dopaminergic regulation. Finally, the behavioral monitoring and histological results establish the safety of obtaining repeated cerebral imprints in striatal regions. These results demonstrate the ability of our imprint tool to explore the molecular content of deep brain regions in vivo. They open the way to the molecular exploration of brain in animal models of neurological diseases and will provide complementary information to current data mainly restricted to post-mortem samples.

An extended proteome map of the lysosomal membrane reveals novel potential transporters.

Lysosomes are membrane-bound endocytic organelles that play a major role in degrading cell macromolecules and recycling their building blocks. A comprehensive knowledge of the lysosome function requires an extensive description of its content, an issue partially addressed by previous proteomic analyses. However, the proteins underlying many lysosomal membrane functions, including numerous membrane transporters, remain unidentified. We performed a comparative, semi-quantitative proteomic analysis of rat liver lysosome-enriched and lysosome-nonenriched membranes and used spectral counts to evaluate the relative abundance of proteins. Among a total of 2,385 identified proteins, 734 proteins were significantly enriched in the lysosomal fraction, including 207 proteins already known or predicted as endo-lysosomal and 94 proteins without any known or predicted subcellular localization. The remaining 433 proteins had been previously assigned to other subcellular compartments but may in fact reside on lysosomes either predominantly or as a secondary location. Many membrane-associated complexes implicated in diverse processes such as degradation, membrane trafficking, lysosome biogenesis, lysosome acidification, signaling, and nutrient sensing were enriched in the lysosomal fraction. They were identified to an unprecedented extent as most, if not all, of their subunits were found and retained by our screen. Numerous transporters were also identified, including 46 novel potentially lysosomal proteins. We expressed 12 candidates in HeLa cells and observed that most of them colocalized with the lysosomal marker LAMP1, thus confirming their lysosomal residency. This list of candidate lysosomal proteins substantially increases our knowledge of the lysosomal membrane and provides a basis for further characterization of lysosomal functions.