ADP-ribosylome analysis reveals homogeneous DNA-damage-induced serine ADP-ribosylation across wild-type and BRCA-mutant breast cancer cell lines.

ADP-ribosylation (ADPr) signaling plays a crucial role in DNA damage response. Inhibitors against the main enzyme catalyzing ADPr after DNA damage, poly(ADP-ribose) polymerase 1 (PARP1), are used to treat patients with breast cancer harboring BRCA1/2 mutations. However, resistance to PARP inhibitors (PARPi) is a major obstacle in treating patients. To understand the role of ADPr in PARPi sensitivity, we use liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze ADPr in six breast cancer cell lines exhibiting different PARPi sensitivities. We identify 1,632 sites on 777 proteins across all cell lines, primarily on serine residues, with site-specific overlap of targeted residues across DNA-damage-related proteins across all cell lines, demonstrating high conservation of serine ADPr-signaling networks upon DNA damage. Furthermore, we observe site-specific differences in ADPr intensities in PARPi-sensitive BRCA mutants and unique ADPr sites in PARPi-resistant BRCA-mutant HCC1937 cells, which have low poly(ADP-ribose) glycohydrolase (PARG) levels and longer ADPr chains on PARP1.

Imputation of label-free quantitative mass spectrometry-based proteomics data using self-supervised deep learning.

Imputation techniques provide means to replace missing measurements with a value and are used in almost all downstream analysis of mass spectrometry (MS) based proteomics data using label-free quantification (LFQ). Here we demonstrate how collaborative filtering, denoising autoencoders, and variational autoencoders can impute missing values in the context of LFQ at different levels. We applied our method, proteomics imputation modeling mass spectrometry (PIMMS), to an alcohol-related liver disease (ALD) cohort with blood plasma proteomics data available for 358 individuals. Removing 20 percent of the intensities we were able to recover 15 out of 17 significant abundant protein groups using PIMMS-VAE imputations. When analyzing the full dataset we identified 30 additional proteins (+13.2%) that were significantly differentially abundant across disease stages compared to no imputation and found that some of these were predictive of ALD progression in machine learning models. We, therefore, suggest the use of deep learning approaches for imputing missing values in MS-based proteomics on larger datasets and provide workflows for these.

The C-type lectin DCIR contributes to the immune response and pathogenesis of colorectal cancer.

Development and progression of malignancies are accompanied and influenced by alterations in the surrounding immune microenvironment. Understanding the cellular and molecular interactions between immune cells and cancer cells has not only provided important fundamental insights into the disease, but has also led to the development of new immunotherapies. The C-type lectin Dendritic Cell ImmunoReceptor (DCIR) is primarily expressed by myeloid cells and is an important regulator of immune homeostasis, as demonstrated in various autoimmune, infectious and inflammatory contexts. Yet, the impact of DCIR on cancer development remains largely unknown. Analysis of available transcriptomic data of colorectal cancer (CRC) patients revealed that high DCIR gene expression is associated with improved patients' survival, immunologically "hot" tumors and high immunologic constant of rejection, thus arguing for a protective and immunoregulatory role of DCIR in CRC. In line with these correlative data, we found that deficiency of DCIR1, the murine homologue of human DCIR, leads to the development of significantly larger tumors in an orthotopic murine model of CRC. This phenotype is accompanied by an altered phenotype of tumor-associated macrophages (TAMs) and a reduction in the percentage of activated effector CD4+ and CD8+ T cells in CRC tumors of DCIR1-deficient mice. Overall, our results show that DCIR promotes antitumor immunity in CRC, making it an attractive target for the future development of immunotherapies to fight the second deadliest cancer in the world.

Encystation and Stress Responses under the Control of Ubiquitin-like Proteins in Pathogenic Amoebae.

Amoebae found in aquatic and terrestrial environments encompass various pathogenic species, including the parasite Entamoeba histolytica and the free-living Acanthamoeba castellanii. Both microorganisms pose significant threats to public health, capable of inducing life-threatening effects on humans. These amoebae exist in two cellular forms: trophozoites and cysts. The trophozoite stage is the form used for growth and reproduction while the cyst stage is the resistant and disseminating form. Cysts occur after cellular metabolism slowdown due to nutritional deprivation or the appearance of environmental conditions unfavourable to the amoebae's growth and division. The initiation of encystation is accompanied by the activation of stress responses, and scarce data indicate that encystation shares factors and mechanisms identified in stress responses occurring in trophozoites exposed to toxic compounds derived from human immune defence. Although some "omics" analyses have explored how amoebae respond to diverse stresses, these studies remain limited and rarely report post-translational modifications that would provide knowledge on the molecular mechanisms underlying amoebae-specific stress responses. In this review, we discuss ubiquitin-like proteins associated with encystation and cell survival during oxidative damage. We aim to shed light on the signalling pathways involved in amoebic defence mechanisms, with a focus on their potential clinical implications against pathogenic amoebae, addressing the pressing need for effective therapies.

Hunting for the elusive target antigen in gestational alloimmune liver disease (GALD).

The prevailing concept is that gestational alloimmune liver disease (GALD) is caused by maternal antibodies targeting a currently unknown antigen on the liver of the fetus. This leads to deposition of complement on the fetal hepatocytes and death of the fetal hepatocytes and extensive liver injury. In many cases, the newborn dies. In subsequent pregnancies early treatment of the woman with intravenous immunoglobulin can be instituted, and the prognosis for the fetus will be excellent. Without treatment the prognosis can be severe. Crucial improvements of diagnosis require identification of the target antigen. For this identification, this work was based on two hypotheses: 1. The GALD antigen is exclusively expressed in the fetal liver during normal fetal life in all pregnancies; 2. The GALD antigen is an alloantigen expressed in the fetal liver with the woman being homozygous for the minor allele and the father being, most frequently, homozygous for the major allele. We used three different experimental approaches to identify the liver target antigen of maternal antibodies from women who had given birth to a baby with the clinical GALD diagnosis: 1. Immunoprecipitation of antigens from either a human liver cell line or human fetal livers by immunoprecipitation with maternal antibodies followed by mass spectrometry analysis of captured antigens; 2. Construction of a cDNA expression library from human fetal liver mRNA and screening about 1.3 million recombinants in Escherichia coli using antibodies from mothers of babies diagnosed with GALD; 3. Exome/genome sequencing of DNA from 26 presumably unrelated women who had previously given birth to a child with GALD with husband controls and supplementary HLA typing. In conclusion, using the three experimental approaches we did not identify the GALD target antigen and the exome/genome sequencing results did not support the hypothesis that the GALD antigen is an alloantigen, but the results do not yield basis for excluding that the antigen is exclusively expressed during fetal life., which is the hypothesis we favor.

Recent advances in kinase signaling network profiling by mass spectrometry.

Mass spectrometry-based phosphoproteomics is currently the leading methodology for the study of global kinase signaling. The scientific community is continuously releasing technological improvements for sensitive and fast identification of phosphopeptides, and their accurate quantification. To interpret large-scale phosphoproteomics data, numerous bioinformatic resources are available that help understanding kinase network functional role in biological systems upon perturbation. Some of these resources are databases of phosphorylation sites, protein kinases and phosphatases; others are bioinformatic algorithms to infer kinase activity, predict phosphosite functional relevance and visualize kinase signaling networks. In this review, we present the latest experimental and bioinformatic tools to profile protein kinase signaling networks and provide examples of their application in biomedicine.

Identifying the genes impacted by cell proliferation in proteomics and transcriptomics studies.

Hypothesis-free high-throughput profiling allows relative quantification of thousands of proteins or transcripts across samples and thereby identification of differentially expressed genes. It is used in many biological contexts to characterize differences between cell lines and tissues, identify drug mode of action or drivers of drug resistance, among others. Changes in gene expression can also be due to confounding factors that were not accounted for in the experimental plan, such as change in cell proliferation. We combined the analysis of 1,076 and 1,040 cell lines in five proteomics and three transcriptomics data sets to identify 157 genes that correlate with cell proliferation rates. These include actors in DNA replication and mitosis, and genes periodically expressed during the cell cycle. This signature of cell proliferation is a valuable resource when analyzing high-throughput data showing changes in proliferation across conditions. We show how to use this resource to help in interpretation of in vitro drug screens and tumor samples. It informs on differences of cell proliferation rates between conditions where such information is not directly available. The signature genes also highlight which hits in a screen may be due to proliferation changes; this can either contribute to biological interpretation or help focus on experiment-specific regulation events otherwise buried in the statistical analysis.

Kinetic proofreading through the multi-step activation of the ZAP70 kinase underlies early T cell ligand discrimination.

T cells recognize a few high-affinity antigens among a vast array of lower affinity antigens. According to the kinetic proofreading model, antigen discrimination properties could be explained by the gradual amplification of small differences in binding affinities as the signal is transduced downstream of the T cell receptor. Which early molecular events are affected by ligand affinity, and how, has not been fully resolved. Here, we used time-resolved high-throughput proteomic analyses to identify and quantify the phosphorylation events and protein-protein interactions encoding T cell ligand discrimination in antigen-experienced T cells. Although low-affinity ligands induced phosphorylation of the Cd3 chains of the T cell receptor and the interaction of Cd3 with the Zap70 kinase as strongly as high-affinity ligands, they failed to activate Zap70 to the same extent. As a result, formation of the signalosome of the Lat adaptor was severely impaired with low- compared with high-affinity ligands, whereas formation of the signalosome of the Cd6 receptor was affected only partially. Overall, this study provides a comprehensive map of molecular events associated with T cell ligand discrimination.

A time-resolved multi-omics atlas of Acanthamoeba castellanii encystment.

Encystment is a common stress response of most protists, including free-living amoebae. Cyst formation protects the amoebae from eradication and can increase virulence of the bacteria they harbor. Here, we mapped the global molecular changes that occur in the facultatively pathogenic amoeba Acanthamoeba castellanii during the early steps of the poorly understood process of encystment. By performing transcriptomic, proteomic, and phosphoproteomic experiments during encystment, we identified more than 150,000 previously undescribed transcripts and thousands of protein sequences absent from the reference genome. These results provide molecular details to the regulation of expected biological processes, such as cell proliferation shutdown, and reveal new insights such as a rapid phospho-regulation of sites involved in cytoskeleton remodeling and translation regulation. This work constitutes the first time-resolved molecular atlas of an encysting organism and a useful resource for further investigation of amoebae encystment to allow for a better control of pathogenic amoebae.

Phosphorylation of SHP2 at Tyr62 Enables Acquired Resistance to SHP2 Allosteric Inhibitors in FLT3-ITD-Driven AML.

The protein tyrosine phosphatase SHP2 is crucial for oncogenic transformation of acute myeloid leukemia (AML) cells expressing mutated receptor tyrosine kinases. SHP2 is required for full RAS-ERK activation to promote cell proliferation and survival programs. Allosteric SHP2 inhibitors act by stabilizing SHP2 in its autoinhibited conformation and are currently being tested in clinical trials for tumors with overactivation of the RAS/ERK pathway, alone and in various drug combinations. In this study, we established cells with acquired resistance to the allosteric SHP2 inhibitor SHP099 from two FLT3-ITD (internal tandem duplication)-positive AML cell lines. Label-free and isobaric labeling quantitative mass spectrometry-based phosphoproteomics of these resistant models demonstrated that AML cells can restore phosphorylated ERK (pERK) in the presence of SHP099, thus developing adaptive resistance. Mechanistically, SHP2 inhibition induced tyrosine phosphorylation and feedback-driven activation of the FLT3 receptor, which in turn phosphorylated SHP2 on tyrosine 62. This phosphorylation stabilized SHP2 in its open conformation, preventing SHP099 binding and conferring resistance. Combinatorial inhibition of SHP2 and MEK or FLT3 prevented pERK rebound and resistant cell growth. The same mechanism was observed in a FLT3-mutated B-cell acute lymphoblastic leukemia cell line and in the inv(16)/KitD816Y AML mouse model, but allosteric inhibition of Shp2 did not impair the clonogenic ability of normal bone marrow progenitors. Together, these results support the future use of SHP2 inhibitor combinations for clinical applications. SIGNIFICANCE: These findings suggest that combined inhibition of SHP2 and FLT3 effectively treat FLT3-ITD-positive AML, highlighting the need for development of more potent SHP2 inhibitors and combination therapies for clinical applications.

Multi-laboratory experiment PME11 for the standardization of phosphoproteome analysis.

Global analysis of protein phosphorylation by mass spectrometry proteomic techniques has emerged in the last decades as a powerful tool in biological and biomedical research. However, there are several factors that make the global study of the phosphoproteome more challenging than measuring non-modified proteins. The low stoichiometry of the phosphorylated species and the need to retrieve residue specific information require particular attention on sample preparation, data acquisition and processing to ensure reproducibility, qualitative and quantitative robustness and ample phosphoproteome coverage in phosphoproteomic workflows. Aiming to investigate the effect of different variables in the performance of proteome wide phosphoprotein analysis protocols, ProteoRed-ISCIII and EuPA launched the Proteomics Multicentric Experiment 11 (PME11). A reference sample consisting of a yeast protein extract spiked in with different amounts of a phosphomix standard (Sigma/Merck) was distributed to 31 laboratories around the globe. Thirty-six datasets from 23 laboratories were analyzed. Our results indicate the suitability of the PME11 reference sample to benchmark and optimize phosphoproteomics strategies, weighing the influence of different factors, as well as to rank intra and inter laboratory performance.

A proteomics sample metadata representation for multiomics integration and big data analysis.

The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.

The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS): an open community for bioinformatics training and research.

The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS; eubic-ms.org) was founded in 2014 to unite European computational mass spectrometry researchers and proteomics bioinformaticians working in academia and industry. EuBIC-MS maintains educational resources (proteomics-academy.org) and organises workshops at national and international conferences on proteomics and mass spectrometry. Furthermore, EuBIC-MS is actively involved in several community initiatives such as the Human Proteome Organization's Proteomics Standards Initiative (HUPO-PSI). Apart from these collaborations, EuBIC-MS has organised two Winter Schools and two Developers' Meetings that have contributed to the strengthening of the European mass spectrometry network and fostered international collaboration in this field, even beyond Europe. Moreover, EuBIC-MS is currently actively developing a community-driven standard dedicated to mass spectrometry data annotation (SDRF-Proteomics) that will facilitate data reuse and collaboration. This manuscript highlights what EuBIC-MS is, what it does, and what it already has achieved. A warm invitation is extended to new researchers at all career stages to join the EuBIC-MS community on its Slack channel (eubic.slack.com).

Conformational maps of human 20S proteasomes reveal PA28- and immuno-dependent inter-ring crosstalks.

Hydrogen-Deuterium eXchange coupled to Mass Spectrometry (HDX-MS) is now common practice in structural biology. However, it is most of the time applied to rather small oligomeric complexes. Here, we report on the use of HDX-MS to investigate conformational differences between the human standard 20S (std20S) and immuno 20S (i20s) proteasomes alone or in complex with PA28αß or PA28γ activators. Their solvent accessibility is analyzed through a dedicated bioinformatic pipeline including stringent statistical analysis and 3D visualization. These data confirm the existence of allosteric differences between the std20S and i20S at the surface of the α-ring triggered from inside the catalytic ß-ring. Additionally, binding of the PA28 regulators to the 20S proteasomes modify solvent accessibility due to conformational changes of the ß-rings. This work is not only a proof-of-concept that HDX-MS can be used to get structural insights on large multi-protein complexes in solution, it also demonstrates that the binding of the std20S or i20S subtype to any of its PA28 activator triggers allosteric changes that are specific to this 20S/PA28 pair.

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.

The protein kinase PknB negatively regulates biosynthesis and trafficking of mycolic acids in mycobacteria.

Mycobacterium tuberculosis is the causative agent of tuberculosis and remains one of the most widespread and deadliest bacterial pathogens in the world. A distinguishing feature of mycobacteria that sets them apart from other bacteria is the unique architecture of their cell wall, characterized by various species-specific lipids, most notably mycolic acids (MAs). Therefore, targeted inhibition of enzymes involved in MA biosynthesis, transport, and assembly has been extensively explored in drug discovery. Additionally, more recent evidence suggests that many enzymes in the MA biosynthesis pathway are regulated by kinase-mediated phosphorylation, thus opening additional drug-development opportunities. However, how phosphorylation regulates MA production remains unclear. Here, we used genetic strategies combined with lipidomics and phosphoproteomics approaches to investigate the role of protein phosphorylation in Mycobacterium The results of this analysis revealed that the Ser/Thr protein kinase PknB regulates the export of MAs and promotes the remodeling of the mycobacterial cell envelope. In particular, we identified the essential MmpL3 as a substrate negatively regulated by PknB. Taken together, our findings add to the understanding of how PknB activity affects the mycobacterial MA biosynthesis pathway and reveal the essential role of protein phosphorylation/dephosphorylation in governing lipid metabolism, paving the way for novel antimycobacterial strategies.

The final assembly of trehalose polyphleates takes place within the outer layer of the mycobacterial cell envelope.

Trehalose polyphleates (TPP) are high-molecular-weight, surface-exposed glycolipids present in a broad range of nontuberculous mycobacteria. These compounds consist of a trehalose core bearing polyunsaturated fatty acyl substituents (called phleic acids) and a straight-chain fatty acid residue and share a common basic structure with trehalose-based glycolipids produced by Mycobacterium tuberculosis TPP production starts in the cytosol with the formation of a diacyltrehalose intermediate. An acyltransferase, called PE, subsequently catalyzes the transfer of phleic acids onto diacyltrehalose to form TPP, and an MmpL transporter promotes the export of TPP or its precursor across the plasma membrane. PE is predicted to be an anchored membrane protein, but its topological organization is unknown, raising questions about the subcellular localization of the final stage of TPP biosynthesis and the chemical nature of the substrates that are translocated by the MmpL transporter. Here, using genetic, biochemical, and proteomic approaches, we established that PE of Mycobacterium smegmatis is exported to the cell envelope following cleavage of its signal peptide and that this process is required for TPP biosynthesis, indicating that the last step of TPP formation occurs in the outer layers of the mycobacterial cell envelope. These results provide detailed insights into the molecular mechanisms controlling TPP formation and transport to the cell surface, enabling us to propose an updated model of the TPP biosynthetic pathway. Because the molecular mechanisms of glycolipid production are conserved among mycobacteria, these findings obtained with PE from M. smegmatis may offer clues to glycolipid formation in M. tuberculosis.

Comparing 22 Popular Phosphoproteomics Pipelines for Peptide Identification and Site Localization.

Phosphorylation-driven cell signaling governs most biological functions and is widely studied using mass-spectrometry-based phosphoproteomics. Identifying the peptides and localizing the phosphorylation sites within them from the raw data is challenging and can be performed by several algorithms that return scores that are not directly comparable. This increases the heterogeneity among published phosphoproteomics data sets and prevents their direct integration. Here we compare 22 pipelines implemented in the main software tools used for bottom-up phosphoproteomics analysis (MaxQuant, Proteome Discoverer, PeptideShaker). We test six search engines (Andromeda, Comet, Mascot, MS Amanda, SequestHT, and X!Tandem) in combination with several localization scoring algorithms (delta score, D-score, PTM-score, phosphoRS, and Ascore). We show that these follow very different score distributions, which can lead to different false localization rates for the same threshold. We provide a strategy to discriminate correctly from incorrectly localized phosphorylation sites in a consistent manner across the tested pipelines. The results presented here can help users choose the most appropriate pipeline and cutoffs for their phosphoproteomics analysis.

Top-Down and Intact Protein Mass Spectrometry Data Visualization for Proteoform Analysis Using VisioProt-MS.

The rise of intact protein analysis by mass spectrometry (MS) was accompanied by an increasing need for flexible tools allowing data visualization and analysis. These include inspection of the deconvoluted molecular weights of the proteoforms eluted alongside liquid chromatography (LC) through their representation in three-dimensional (3D) liquid chromatography coupled to mass spectrometry (LC-MS) maps (plots of deconvoluted molecular weights, retention times, and intensity of the MS signal). With this aim, we developed a free and open-source web application named VisioProt-MS (https://masstools.ipbs.fr/mstools/visioprot-ms/). VisioProt-MS is highly compatible with many algorithms and software developed by the community to integrate and deconvolute top-down and intact protein MS data. Its dynamic and user-friendly features greatly facilitate analysis through several graphical representations dedicated to MS and tandem mass spectrometry (MS/MS) analysis of proteoforms in complex samples. Here, we will illustrate the importance of LC-MS map visualization to optimize top-down acquisition/search parameters and analyze intact protein MS data. We will go through the main features of VisioProt-MS using the human proteasomal 20S core particle as a user-case.

HDX-Viewer: interactive 3D visualization of hydrogen-deuterium exchange data.

SUMMARY: With the advent of fully automated sample preparation robots for Hydrogen-Deuterium eXchange coupled to Mass Spectrometry (HDX-MS), this method has become paramount for ligand binding or epitope mapping screening, both in academic research and biopharmaceutical industries. However, bridging the gap between commercial HDX-MS software (for raw data interpretation) and molecular viewers (to map experiment results onto a 3D structure for biological interpretation) remains laborious and requires simple but sometimes limiting coding skills. We solved this bottleneck by developing HDX-Viewer, an open-source web-based application that facilitates and quickens HDX-MS data analysis. This user-friendly application automatically incorporates HDX-MS data from a custom template or commercial HDX-MS software in PDB files, and uploads them to an online 3D molecular viewer, thereby facilitating their visualization and biological interpretation. AVAILABILITY AND IMPLEMENTATION: The HDX-Viewer web application is released under the CeCILL (http://www.cecill.info) and GNU LGPL licenses and can be found at https://masstools.ipbs.fr/hdx-viewer. The source code is available at https://github.com/david-bouyssie/hdx-viewer.