Mass Spectrometry Proteomics Data Research Articles

Understanding bacterial pathogen diversity: A proteogenomic analysis and use of an array of genome assemblies to identify novel virulence factors of the honey bee bacterial pathogen Paenibacillus larvae.

Mass spectrometry proteomics data are typically evaluated against publicly available annotated sequences, but the proteogenomics approach is a useful alternative. A single genome is commonly utilized in custom proteomic and proteogenomic data analysis. We pose the question of whether utilizing numerous different genome assemblies in a search database would be beneficial. We reanalyzed raw data from the exoprotein fraction of four reference Enterobacterial Repetitive Intergenic Consensus (ERIC) I-IV genotypes of the honey bee bacterial pathogen Paenibacillus larvae and evaluated them against three reference databases (from NCBI-protein, RefSeq, and UniProt) together with an array of protein sequences generated by six-frame direct translation of 15 genome assemblies from GenBank. The wide search yielded 453 protein hits/groups, which UpSet analysis categorized into 50 groups based on the success of protein identification by the 18 database components. Nine hits that were not identified by a unique peptide were not considered for marker selection, which discarded the only protein that was not identified by the reference databases. We propose that the variability in successful identifications between genome assemblies is useful for marker mining. The results suggest that various strains of P. larvae can exhibit specific traits that set them apart from the established genotypes ERIC I-V.

Comparative proteomic analysis of the ovarian fluid and eggs of Siberian sturgeon

BackgroundSturgeon species are living fossils that exhibit unique reproductive characteristics, and elucidation of the molecular processes governing the formation and quality of sturgeon eggs is crucial. However, comprehensive data on the protein composition of sturgeon ovarian fluid (OF) and eggs and their functional significance are lacking. To address this knowledge gap, the aim of the present study was to conduct a comprehensive comparative proteomic analysis of Siberian sturgeon OF and eggs using liquid chromatography–mass spectrometry (LC–MS/MS).ResultsA total of 617 proteins were identified in OF, and 565 proteins were identified in eggs. A total of 772 proteins showed differential abundance. Among the differentially abundant proteins, 365 were more abundant in OFs, while 407 were more abundant in eggs. We identified 339 proteins unique to OFs and 287 proteins specific to eggs, and further investigated the top 10 most abundant proteins in each. The functional annotation of the OF proteins highlighted their predominant association with immune system processes, including the complement and coagulation cascade, neutrophil and leukocyte-mediated immunity, cholesterol metabolism, and regulation of the actin cytoskeleton. Analysis of egg proteins revealed enrichment in metabolic pathways, such as oxidative phosphorylation and fatty acid metabolism, and protein ubiquitination and translation. OF-specific proteins included extracellular matrix and secretory vesicles, and eggs were enriched in proteins localized to mitochondria and ribosome components.ConclusionsThis study presents the first comprehensive characterization of the protein composition of sturgeon OF and eggs and elucidates their distinct functional roles. These findings advance our understanding of sturgeon reproduction, OF-egg signaling and the origin of OF proteins. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium with the dataset identifier PXD044168 to ensure accessibility for further research.

Comparative Proteomics Identified EXOSC1 as a Target Protein of Anticancer Peptide LVTX-8 in Nasopharyngeal Carcinoma Cells.

Nasopharyngeal carcinoma (NPC) is a prevalent malignancy that usually occurs among the nose and throat. Due to mild initial symptoms, most patients are diagnosed in the late stage, and the recurrence rate of tumors is high, resulting in many deaths every year. Traditional radiotherapy and chemotherapy are prone to causing drug resistance and significant side effects. Therefore, searching for new bioactive drugs including anticancer peptides is necessary and urgent. LVTX-8 is a peptide toxin synthesized from the cDNA library of the spider Lycosa vittata, which is consisting of 25 amino acids. In this study, a series of in vitro cell experiments such as cell toxicity, colony formation, and cell migration assays were performed to exam the anticancer activity of LVTX-8 in NPC cells (5-8F and CNE-2). The results suggested that LVTX-8 significantly inhibited cell proliferation and migration of NPC cells. To find the potential molecular targets for the anticancer capability of LVTX-8, high-throughput proteomic and bioinformatics analysis were conducted on NPC cells. The results identified EXOSC1 as a potential target protein with significantly differential expression levels under LVTX-8+/LVTX-8- conditions. The results in this research indicate that spider peptide toxin LVTX-8 exhibits significant anticancer activity in NPC, and EXOSC1 may serve as a target protein for its anticancer activity. These findings provide a reference for the development of new therapeutic drugs for NPC and offer new ideas for the discovery of biomarkers related to NPC diagnosis. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (https://proteomecentral.proteomexchange.org) via the iProX partner repository with the data set identifier PXD050542.

Analysis of Tandem Mass Spectrometry Data with CONGA: Combining Open and Narrow Searches with Group-Wise Analysis.

Searching for tandem mass spectrometry proteomics data against a database is a well-established method for assigning peptide sequences to observed spectra but typically cannot identify peptides harboring unexpected post-translational modifications (PTMs). Open modification searching aims to address this problem by allowing a spectrum to match a peptide even if the spectrum's precursor mass differs from the peptide mass. However, expanding the search space in this way can lead to a loss of statistical power to detect peptides. We therefore developed a method, called CONGA (combining open and narrow searches with group-wise analysis), that takes into account results from both types of searches─a traditional "narrow window" search and an open modification search─while carrying out rigorous false discovery rate control. The result is an algorithm that provides the best of both worlds: the ability to detect unexpected PTMs without a concomitant loss of power to detect unmodified peptides.

In-Depth Proteome Coverage of In Vitro-Cultured Treponema pallidum and Quantitative Comparison Analyses with In Vivo-Grown Treponemes.

Previous mass spectrometry (MS)-based global proteomics studies have detected a combined total of 86% of all Treponema pallidum proteins under infection conditions (in vivo-grown T. pallidum). Recently, a method was developed for the long-term culture of T. pallidum under in vitro conditions (in vitro-cultured T. pallidum). Herein, we used our previously reported optimized MS-based proteomics approach to characterize the T. pallidum global protein expression profile under in vitro culture conditions. These analyses provided a proteome coverage of 94%, which extends the combined T. pallidum proteome coverage from the previously reported 86% to a new combined total of 95%. This study provides a more complete understanding of the protein repertoire of T. pallidum. Further, comparison of the in vitro-expressed proteome with the previously determined in vivo-expressed proteome identifies only a few proteomic changes between the two growth conditions, reinforcing the suitability of in vitro-cultured T. pallidum as an alternative to rabbit-based treponemal growth. The MS proteomics data have been deposited in the MassIVE repository with the data set identifier MSV000093603 (ProteomeXchange identifier PXD047625).

Differential CpG methylation at Nnat in the early establishment of beta cell heterogeneity

Aims/hypothesisBeta cells within the pancreatic islet represent a heterogenous population wherein individual sub-groups of cells make distinct contributions to the overall control of insulin secretion. These include a subpopulation of highly connected ‘hub’ cells, important for the propagation of intercellular Ca2+ waves. Functional subpopulations have also been demonstrated in human beta cells, with an altered subtype distribution apparent in type 2 diabetes. At present, the molecular mechanisms through which beta cell hierarchy is established are poorly understood. Changes at the level of the epigenome provide one such possibility, which we explore here by focusing on the imprinted gene Nnat (encoding neuronatin [NNAT]), which is required for normal insulin synthesis and secretion.MethodsSingle-cell RNA-seq datasets were examined using Seurat 4.0 and ClusterProfiler running under R. Transgenic mice expressing enhanced GFP under the control of the Nnat enhancer/promoter regions were generated for FACS of beta cells and downstream analysis of CpG methylation by bisulphite sequencing and RNA-seq, respectively. Animals deleted for the de novo methyltransferase DNA methyltransferase 3 alpha (DNMT3A) from the pancreatic progenitor stage were used to explore control of promoter methylation. Proteomics was performed using affinity purification mass spectrometry and Ca2+ dynamics explored by rapid confocal imaging of Cal-520 AM and Cal-590 AM. Insulin secretion was measured using homogeneous time-resolved fluorescence imaging.ResultsNnat mRNA was differentially expressed in a discrete beta cell population in a developmental stage- and DNA methylation (DNMT3A)-dependent manner. Thus, pseudo-time analysis of embryonic datasets demonstrated the early establishment of Nnat-positive and -negative subpopulations during embryogenesis. NNAT expression is also restricted to a subset of beta cells across the human islet that is maintained throughout adult life. NNAT+ beta cells also displayed a discrete transcriptome at adult stages, representing a subpopulation specialised for insulin production, and were diminished in db/db mice. ‘Hub’ cells were less abundant in the NNAT+ population, consistent with epigenetic control of this functional specialisation.Conclusions/interpretationThese findings demonstrate that differential DNA methylation at Nnat represents a novel means through which beta cell heterogeneity is established during development. We therefore hypothesise that changes in methylation at this locus may contribute to a loss of beta cell hierarchy and connectivity, potentially contributing to defective insulin secretion in some forms of diabetes.Data availabilityThe mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD048465.Graphical

A data analysis framework for combining multiple batches increases the power of isobaric proteomics experiments.

We present a framework for the analysis of multiplexed mass spectrometry proteomics data that reduces estimation error when combining multiple isobaric batches. Variations in the number and quality of observations have long complicated the analysis of isobaric proteomics data. Here we show that the power to detect statistical associations is substantially improved by utilizing models that directly account for known sources of variation in the number and quality of observations that occur across batches.In a multibatch benchmarking experiment, our open-source software (msTrawler) increases the power to detect changes, especially in the range of less than twofold changes, while simultaneously increasing quantitative proteome coverage by utilizing more low-signal observations. Further analyses of previously published multiplexed datasets of 4 and 23 batches highlight both increased power and the ability to navigate complex missing data patterns without relying on unverifiable imputations or discarding reliable measurements.

Temporal Profiling of Host Proteome against Different M. tuberculosis Strains Reveals Delayed Epigenetic Orchestration.

Apart from being preventable and treatable, tuberculosis is the deadliest bacterial disease afflicting humankind owing to its ability to evade host defence responses, many of which are controlled by epigenetic mechanisms. Here, we report the temporal dynamics of the proteome of macrophage-like host cells after infecting them for 6, 18, 30, and 42 h with two laboratory strains (H37Ra and H37Rv) and two clinical strains (BND433 and JAL2287) of Mycobacterium tuberculosis (MTB). Using SWATH-MS, the proteins characterized at the onset of infection broadly represented oxidative stress and cell cytoskeleton processes. Intermediary and later stages of infection are accompanied by a reshaping of the combination of proteins implicated in histone stability, gene expression, and protein trafficking. This study provides strain-specific and time-specific variations in the proteome of the host, which might further the development of host-directed therapeutics and diagnostic tools against the pathogen. Also, our findings accentuate the importance of proteomic tools in delineating the complex recalibration of the host defence enabled as an effect of MTB infection. To the best of our knowledge, this is the first comprehensive proteomic account of the host response to avirulent and virulent strains of MTB at different time periods of the life span of macrophage-like cells. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium via the PRIDE repository with the dataset identifier PXD022352.

Data-independent acquisition proteomics of cerebrospinal fluid implicates endoplasmic reticulum and inflammatory mechanisms in amyotrophic lateral sclerosis.

While unbiased proteomics of human cerebrospinal fluid (CSF) has been used successfully to identify biomarkers of amyotrophic lateral sclerosis (ALS), high-abundance proteins mask the presence of lower abundance proteins that may have diagnostic and prognostic value. However, developments in mass spectrometry (MS) proteomic data acquisition methods offer improved protein depth. In this study, MS with library-free data-independent acquisition (DIA) was used to compare the CSF proteome of people with ALS (n = 40), healthy (n = 15) and disease (n = 8) controls. Quantified protein groups were subsequently correlated with clinical variables. Univariate analysis identified 7 proteins, all significantly upregulated in ALS versus healthy controls, and 9 with altered abundance in ALS versus disease controls (FDR < 0.1). Elevated chitotriosidase-1 (CHIT1) was common to both comparisons and was proportional to ALS disability progression rate (Pearson r = 0.41, FDR-adjusted p = 0.035) but not overall survival. Ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1; upregulated in ALS versus healthy controls) was proportional to disability progression rate (Pearson r = 0.53, FDR-adjusted p = 0.003) and survival (Kaplan Meier log-rank p = 0.013) but not independently in multivariate proportional hazards models. Weighted correlation network analysis was used to identify functionally relevant modules of proteins. One module, enriched for inflammatory functions, was associated with age at symptom onset (Pearson r = 0.58, FDR-adjusted p = 0.005) and survival (Hazard Ratio = 1.78, FDR = 0.065), and a second module, enriched for endoplasmic reticulum proteins, was negatively correlated with disability progression rate (r = -0.42, FDR-adjusted p = 0.109). DIA acquisition methodology therefore strengthened the biomarker candidacy of CHIT1 and UCHL1 in ALS, while additionally highlighted inflammatory and endoplasmic reticulum proteins as novel sources of prognostic biomarkers.

In-depth proteome analysis of brain tissue from Ewsr1 knockout mouse by multiplexed isobaric tandem mass tag labeling

EWS RNA binding protein 1 (EWSR1) is a multifunctional protein whose epigenetic signatures contribute to the pathogenesis of various human diseases, such as neurodegenerative disorders, skin development, and tumorigenic processes. However, the specific cellular functions and physiological characteristics of EWSR1 remain unclear. In this study, we used quantitative mass spectrometry-based proteomics with tandem mass tag labeling to investigate the global proteome changes in brain tissue in Ewsr1 knockout and wild-type mice. From 9115 identified proteins, we selected 118 differentially expressed proteins, which is common to three quantitative data processing strategies including only protein level normalizations and spectrum-protein level normalization. Bioinformatics analysis of these common differentially expressed proteins revealed that proteins up-regulated in Ewsr1 knockout mouse are mostly related to the positive regulation of bone remodeling and inflammatory response. The down-regulated proteins were associated with the regulation of neurotransmitter levels or amino acid metabolic processes. Collectively, these findings provide insight into the physiological function and pathogenesis of EWSR1 on protein level. Better understanding of EWSR1 and its protein interactions will advance the field of clinical research into neuronal disorders. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD026994.

MS Annika 2.0 Identifies Cross-Linked Peptides in MS2-MS3-Based Workflows at High Sensitivity and Specificity.

Cross-linking mass spectrometry has become a powerful tool for the identification of protein-protein interactions and for gaining insight into the structures of proteins. We previously published MS Annika, a cross-linking search engine which can accurately identify cross-linked peptides in MS2 spectra from a variety of different MS-cleavable cross-linkers. In this publication, we present MS Annika 2.0, an updated version implementing a new search algorithm that, in addition to MS2 level, only supports the processing of data from MS2-MS3-based approaches for the identification of peptides from MS3 spectra, and introduces a novel scoring function for peptides identified across multiple MS stages. Detected cross-links are validated by estimating the false discovery rate (FDR) using a target-decoy approach. We evaluated the MS3-search-capabilities of MS Annika 2.0 on five different datasets covering a variety of experimental approaches and compared it to XlinkX and MaXLinker, two other cross-linking search engines. We show that MS Annika detects up to 4 times more true unique cross-links while simultaneously yielding less false positive hits and therefore a more accurate FDR estimation than the other two search engines. All mass spectrometry proteomics data along with result files have been deposited to the ProteomeXchange consortium via the PRIDE partner repository with the dataset identifier PXD041955.

Proteogenomic data and resources for pan-cancer analysis.

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

Deep Proteomics Network and Machine Learning Analysis of Human Cerebrospinal Fluid in Japanese Encephalitis Virus Infection.

Japanese encephalitis virus is a leading cause of neurological infection in the Asia-Pacific region with no means of detection in more remote areas. We aimed to test the hypothesis of a Japanese encephalitis (JE) protein signature in human cerebrospinal fluid (CSF) that could be harnessed in a rapid diagnostic test (RDT), contribute to understanding the host response and predict outcome during infection. Liquid chromatography and tandem mass spectrometry (LC-MS/MS), using extensive offline fractionation and tandem mass tag labeling (TMT), enabled comparison of the deep CSF proteome in JE vs other confirmed neurological infections (non-JE). Verification was performed using data-independent acquisition (DIA) LC-MS/MS. 5,070 proteins were identified, including 4,805 human proteins and 265 pathogen proteins. Feature selection and predictive modeling using TMT analysis of 147 patient samples enabled the development of a nine-protein JE diagnostic signature. This was tested using DIA analysis of an independent group of 16 patient samples, demonstrating 82% accuracy. Ultimately, validation in a larger group of patients and different locations could help refine the list to 2-3 proteins for an RDT. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD034789 and 10.6019/PXD034789.

Deep Proteogenomics of a Photosynthetic Cyanobacterium.

Cyanobacteria, the evolutionary ancestors of plant chloroplasts, contribute substantially to the Earth's biogeochemical cycles and are of great interest for a sustainable economy. Knowledge of protein expression is the key to understanding cyanobacterial metabolism; however, proteome studies in cyanobacteria are limited and cover only a fraction of the theoretical proteome. Here, we performed a comprehensive proteogenomic analysis of the model cyanobacterium Synechocystis sp. PCC 6803 to characterize the expressed (phospho)proteome, re-annotate known and discover novel open reading frames (ORFs). By mapping extensive shotgun mass spectrometry proteomics data onto a six-frame translation of the Synechocystis genome, we refined the genomic annotation of 64 ORFs, including eight completely novel ORFs. Our study presents the largest reported (phospho)proteome dataset for a unicellular cyanobacterium, covering the expression of about 80% of the theoretical proteome under various cultivation conditions, such as nitrogen or carbon limitation. We report 568 phosphorylated S/T/Y sites that are present on numerous regulatory proteins, including the transcriptional regulators cyAbrB1 and cyAbrB2. We also catalogue the proteins that have never been detected under laboratory conditions and found that a large portion of them is plasmid-encoded. This dataset will serve as a resource, providing dedicated information on growth condition-dependent protein expression and phosphorylation.

The phosphoproteome of choroid plexus epithelial cells following infection with Neisseria meningitidis.

The Gram-negative bacterium Neisseria meningitidis, which causes meningitis in humans, has been demonstrated to manipulate or alter host signalling pathways during infection of the central nervous system (CNS). However, these complex signalling networks are not completely understood. We investigate the phosphoproteome of an in vitro model of the blood-cerebrospinal fluid barrier (BCSFB) based on human epithelial choroid plexus (CP) papilloma (HIBCPP) cells during infection with the N. meningitidis serogroup B strain MC58 in presence and absence of the bacterial capsule. Interestingly, our data demonstrates a stronger impact on the phosphoproteome of the cells by the capsule-deficient mutant of MC58. Using enrichment analyses, potential pathways, molecular processes, biological processes, cellular components and kinases were determined to be regulated as a consequence of N. meningitidis infection of the BCSFB. Our data highlight a variety of protein regulations that are altered during infection of CP epithelial cells with N. meningitidis, with the regulation of several pathways and molecular events only being detected after infection with the capsule-deficient mutant. Mass spectrometry proteomics data are available via ProteomeXchange with identifier PXD038560.

Elevated inorganic carbon and salinity enhances photosynthesis and ATP synthesis in picoalga Picocystis salinarum as revealed by label free quantitative proteomics.

Saline soda lakes are of immense ecological value as they niche some of the most exclusive haloalkaliphilic communities dominated by bacterial and archaeal domains, with few eukaryotic algal representatives. A handful reports describe Picocystis as a key primary producer with great production rates in extremely saline alkaline habitats. An extremely haloalkaliphilic picoalgal strain, Picocystis salinarum SLJS6 isolated from hypersaline soda lake Sambhar, Rajasthan, India, grew robustly in an enriched soda lake medium containing mainly Na2CO3, 50 g/l; NaHCO3, 50 g/l, NaCl, 50 g/l (salinity ≈150‰) at pH 10. To elucidate the molecular basis of such adaptation to high inorganic carbon and NaCl concentrations, a high-throughput label-free quantitation based quantitative proteomics approach was applied. Out of the total 383 proteins identified in treated samples, 225 were differentially abundant proteins (DAPs), of which 150 were statistically significant (p < 0.05) including 70 upregulated and 64 downregulated proteins after 3 days of growth in highly saline-alkaline medium. Most DAPs were involved in photosynthesis, oxidative phosphorylation, glucose metabolism and ribosomal structural components envisaging that photosynthesis and ATP synthesis were central to the salinity-alkalinity response. Key components of photosynthetic machinery like photosystem reaction centres, adenosine triphosphate (ATP) synthase ATP, Rubisco, Fructose-1,6-bisphosphatase, Fructose-bisphosphate aldolase were highly upregulated. Enzymes peptidylprolyl isomerases (PPIase), important for correct protein folding showed remarkable marked-up regulation along with other chaperon proteins indicating their role in osmotic adaptation. Enhanced photosynthetic activity exhibited by P. salinarum in highly saline-alkaline condition is noteworthy as photosynthesis is suppressed under hyperosmotic conditions in most photosynthetic organisms. The study provided the first insights into the proteome of extremophilic alga P. salinarum exhibiting extraordinary osmotic adaptation and proliferation in polyextreme conditions prevailing in saline sodic ecosystems, potentially unraveling the basis of resilience in this not so known organism and paves the way for a promising future candidate for biotechnological applications and model organism for deciphering the molecular mechanisms of osmotic adaptation. The mass spectrometry proteomics data is available at the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD037170.

Comprehensive proteomic characterization and functional annotation of Siberian sturgeon seminal plasma proteins

Siberian sturgeon (Acipenser baerii) is considered the most valuable species in aquaculture. The uniqueness of sturgeon reproduction implicates the need for studying semen composition at the protein level. Seminal plasma supports and protects the viability, motility and fertilizing capacity of spermatozoa by creating the optimal environment for storage and might be a rich source of biomarkers of reproductive physiology and/or disorders in male fishes. To our knowledge, there are no reports on the in-depth characterization of sturgeon seminal plasma proteins. The present study is the first to describe the in-depth proteomic characterization of Siberian sturgeon seminal plasma using two complementary proteomic approaches: gel-based (2DE and 2D blue native (BN)/SDS–PAGE) and gel-free (LC–MS/MS). LC–MS/MS allowed the identification of 657 proteins and 339 protein spots were identified after 2DE (almost 60% were present in various proteoforms). Combining the two proteomic strategies, we identified 665 proteins with high confidence (false positive rate below 1%), producing the largest catalogue of proteins from sturgeon seminal plasma to date. For the first time, we demonstrated interactions between seminal plasma proteins; four multiprotein complexes (MC1-MC4) were identified after 2D BN/SDS–PAGE, including (MC1) serotransferrin-2 (TF) and fish-egg lectin (FEL); (MC2) serum albumin 2 (ALB) and retinol-binding protein 4 (RBP4); (MC3) ALB and TF; and (MC4) apolipoprotein A-I (APOA1), riboflavin-binding protein (RfBP) and myoglobin (MB). BN/SDS–PAGE also revealed that immunoglobulin and TF formed homomultimeric (dimer, trimer, tetramer and pentamer) complexes in seminal plasma. ALB, TF, beta-Ala-His dipeptidase (CNDP1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), IGH, APOA1, hemopexin (HPX), type-4 ice-structuring protein (AFP4), FEL, RfBP, ovochymase 2 (OVCH2) and glycogen phosphorylase, liver form-like (PYGL) were selected as major seminal plasma proteins. The functional analysis of the identified proteins indicated their involvement mainly in immune system processes and response to stimulus, metabolism, vesicle-mediated transport, proteolysis, and cadherin binding involved in cell–cell adhesion. Moreover, 69 proteins were associated with reproductive processes, including spermatogenesis, fertilization, acrosomal reaction and sperm motility. Comparative proteomic analysis of sturgeon seminal plasma showed common proteins between fish and humans and 172 proteins specific for sturgeons, which may reflect the specificity of sturgeon reproduction. To conclude, this integrative proteomic view offers a deeper insight into the physiological function of seminal plasma and processes occurring in the sturgeon reproductive tract. The availability of a catalogue of sturgeon seminal plasma proteins opens the way to future research into development of new biomarkers and possible application in the improvement of methods of controlled reproduction. The mass spectrometry proteomics data have been deposited into ProteomeXchange with the identifier PXD035351.

Comparative proteomic analysis reveals the different hepatotoxic mechanisms of human hepatocytes exposed to silver nanoparticles

Silver nanoparticles (AgNPs), which have been used extensively in consuming products and eventually released into the natural environment, have aroused concerns recently because of their potentially harmful effects on human beings following various routes of exposure. As the liver is one of the largest accumulation and deposition sites of circulatory AgNPs, it is important to evaluate the hepatotoxicity induced by AgNPs. However, the acting mechanisms of AgNPs-induced hepatotoxicity are still elusive to a great extent. Herein, we investigated the hepatotoxic effects of AgNPs using a comparative proteomics approach. First, we evaluated the cytotoxicity of different-sized AgNPs and found that the cancerous liver cells were generally more sensitive than the normal liver cells. Next, proteomics results suggested that HepG2 and L02 cells showed distinct adaptive responses upon AgNPs exposure. HepG2 cells respond to stresses by adapting energy metabolism, upregulating metallothionein expression and increasing the expression of antioxidants, while L02 cells protect themselves by increasing DNA repair and macro-autophagy. Besides, mitochondrial ROS has been identified as one of the causes of AgNPs-induced hepatotoxicity. Collectively, our results revealed that hepatic cancer cells and normal cells cope with AgNPs in notably different pathways, providing new insights into mechanisms underlying AgNPs-induced hepatotoxicity. Data availabilityThe mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (Deutsch et al. (2020)) via the PRIDE (Perez-Riverol et al. (2019)) partner repository with the dataset identifier PXD029511.

Naive Pluripotent and Trophoblastic Stem Cell Lines as a Model for Detecting Missing Proteins in the Context of the Chromosome-Centric Human Proteome Project.

The Chromosome-centric Human Proteome Project (C-HPP) aims at identifying the proteins as gene products encoded by the human genome, characterizing their isoforms and functions. The existence of products has now been confirmed for 93.2% of the genes at the protein level. The remaining mostly correspond to proteins of low abundance or difficult to access. Over the past years, we have significantly contributed to the identification of missing proteins in the human spermatozoa. We pursue our search in the reproductive sphere with a focus on early human embryonic development. Pluripotent cells, developing into the fetus, and trophoblast cells, giving rise to the placenta, emerge during the first weeks. This emergence is a focus of scientists working in the field of reproduction, placentation and regenerative medicine. Most knowledge has been harnessed by transcriptomic analysis. Interestingly, some genes are uniquely expressed in those cells, giving the opportunity to uncover new proteins that might play a crucial role in setting up the molecular events underlying early embryonic development. Here, we analyzed naive pluripotent and trophoblastic stem cells and discovered 4 new missing proteins, thus contributing to the C-HPP. The mass spectrometry proteomics data was deposited on ProteomeXchange under the data set identifier PXD035768.

The ProteomeXchange consortium at 10 years: 2023 update.

Mass spectrometry (MS) is by far the most used experimental approach in high-throughput proteomics. The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) was originally set up to standardize data submission and dissemination of public MS proteomics data. It is now 10 years since the initial data workflow was implemented. In this manuscript, we describe the main developments in PX since the previous update manuscript inNucleicAcids Researchwas published in 2020. The six members of the Consortium are PRIDE, PeptideAtlas (including PASSEL), MassIVE, jPOST, iProX and Panorama Public. We report the current data submission statistics, showcasing that the number of datasets submitted to PX resources has continued to increase every year. As of June 2022, more than 34 233 datasets had been submitted to PX resources, and from those, 20 062 (58.6%) just in the last three years. We also report the development of the Universal Spectrum Identifiers and the improvements in capturing the experimental metadata annotations. In parallel, we highlight that data re-use activities of public datasets continue to increase, enabling connections between PX resources and other popular bioinformatics resources, novel research and also new data resources. Finally, we summarise the current state-of-the-art in data management practices for sensitive human (clinical) proteomics data.