Proteomics最新文献

Cells are comprised of a broad spectrum of structures that compartmentalize biochemical and signaling mechanisms. These structures can be comprised of many biomolecules, but especially lipids, proteins, and nucleic acids. Techniques are limited to quantify or discover new subcellular structures. We explored whether a proteomics approach using chemical crosslinking followed by size-exclusion chromatography and mass spectrometry (SEC-MS) of whole cell lysates can address this challenge. Formaldehyde crosslinking was used to preserve the weak molecular interactions responsible for many protein and nucleic acid assemblies. In this study, we perform the first formaldehyde crosslinking-assisted SEC-MS in a bacterial system. We demonstrate that when expressed ectopically in E. coli, large structures of a known assembly protein, FUS, can be detected through SEC-MS. We then show that E. coli proteins are enriched in particles of large or medium size due to formaldehyde crosslinking, which is the first analysis by formaldehyde and SEC-MS for a bacterial system. Last, analysis identified previously characterized E. coli protein assemblies and condensates, as well as potentially novel associations of prokaryote metabolism with large subcellular bodies. We propose this unbiased method can be used to stimulate or supplement targeted methods for discovery of new cellular bodies in a wide range of cell types.

Cobalt is an essential micronutrient but becomes toxic at elevated concentrations, requiring microorganisms to balance acquisition and detoxification. Aeromonas hydrophila, an opportunistic aquatic pathogen, is often encountered in metal-contaminated aquatic environments; however, its adaptive responses to cobalt stress have not been systematically characterized. Here, we applied quantitative proteomics to characterize the global protein response of A. hydrophila under cobalt stress. A total of 2767 proteins were identified, of which 724 were differentially abundant. Enrichment analyses indicated that cobalt exposure was associated with alterations in energy metabolism, oxidative phosphorylation, and ribosome-related pathways. Gene set enrichment analysis suggested an overall upregulation of ribosome-associated functions, accompanied by down regulation of carbon metabolism and the tricarboxylic acid cycle. Protein-protein interaction network mapping identified 15 functional clusters, with core modules linked to oxidative phosphorylation, ABC transport, carbohydrate metabolism, and Fe-S cluster biogenesis. Ten hub proteins associated with respiratory and transport systems were identified based on network topology. Functional validation using seven deletion mutants indicated that genes encoding shikimate kinase, glutaminase, and arsenate reductase contribute to cobalt tolerance. Together, these findings provide a systems-level view of how A. hydrophila adapts to cobalt stress, reveal candidate factors mediating metal resistance, and suggest potential targets for antimicrobial development and bioremediation strategies.

Extracellular vesicles (EVs) are heterogeneous and play important roles in intercellular communication, contributing to physiological and pathological processes. Since few markers currently exist to differentiate subtypes of EVs, this study aimed to determine proteomic and lipidomic differences among four EV subpopulations. Large and small EVs (L-EVs and S-EVs) were isolated from human mast cells (HMC-1) and monocytes (THP-1) by differential ultracentrifugation and then further separated by density cushions into two different densities [low-density (LD) and high-density (HD)]. L-EVs were pelleted at 16,500 × g, and S-EVs were pelleted at 118,000 × g. LD EVs were collected at 1.079-1.146 g/mL, while HD EVs were collected at 1.146-1.185 g/mL. The morphology, size and yield of EVs were determined by TEM and western blot. The proteome and lipidome of the EV subpopulations were determined with mass spectrometry. A total of 5364 proteins were quantified, and L-EVs LD were enriched in mitochondrial proteins such as TIMM/TOMM and MICOS proteins, while L-EVs HD were enriched in cytoskeleton- and cytokinesis-associated proteins, such as KIF proteins. S-EVs LD were enriched in tetraspanins, ADAM10 and ESCRT machinery proteins, while S-EVs HD were enriched in proteins commonly viewed as contaminants, such as histones, complement factors and collagen. Proteins involved in membrane trafficking between the plasma membrane and organelles, such as adaptor protein complexes, the conserved oligomeric Golgi complex, the trafficking protein particle complex, sortin-nexins, TBC1 domain proteins and coatomer subunits, were expressed at similar levels across all EV subtypes. Furthermore, 107 lipids were quantified, and phosphatidylethanolamine (PE) was less abundant in L-EVs LD as compared to the other EV subtypes, while ceramides were enriched in L-EVs as compared to S-EVs.This study demonstrates that there is a core proteome and lipidome that is similar across all four EV subtypes, but importantly, it also shows that a portion of the proteome and lipidome differs in EV subpopulations separated based on size and density. We suggest that these could be important markers in future EV studies and that they may reflect a different biogenesis and EV function.

Proteomics is strengthening research in biology and the diversification of the model organisms studied is very promising for fully understanding the complexity of biological principles. However, the lack of protein sequence databases for many species is a major bottleneck. Existing computational solutions are usually incomplete and/or only usable by bioinformaticians. We have built an open-source, user-friendly pipeline, called Brownotate, which allows anyone to generate protein sequence databases for any species as long as sequencing information is available. The pipeline can extract already existing protein sequences, but also automatically annotate any genome assembly or assemble and annotate any DNA sequence dataset. By testing the pipeline with numerous sequencing and assembly datasets covering a large part of the phylogenetic tree, we show that Brownotate generates fragmented but good quality assemblies and good quality annotations when compared to reference data. By comparing the use of protein databases generated by Brownotate or downloaded from NCBI to interpret proteomic data, we show very comparable results. The Brownotate pipeline is, therefore, an important new addition to the proteomics toolbox. The pipeline and its web interface are freely available at https://github.com/LSMBO/Brownotate and https://github.com/LSMBO/brownotate-app, respectively. SUMMARY: This study evaluated the performance of a newly developed pipeline, Brownotate, for the assembly and annotation of sequencing data for multiple species, from prokaryotes to eukaryotes. We compared their fragmentation level (assembly) and completeness based on evolutionary expectations of gene content, and we evaluated their overlap. Brownotate generated fragmented, slightly less complete assemblies. However, the overlap of proteins predicted was very good, despite an excess of predicted sequences of small size with Brownotate. In addition, the interpretation of proteomics data downloaded from PRIDE repository for 27 species was found to lead to very similar results regardless of the origin of the protein sequencing database used, whether it was generated by Brownotate or downloaded from NCBI. Brownotate, made available to the community, will, therefore, be a tool of choice to mitigate the lack of an appropriate protein sequence database for many species, and allow proteomists to analyse without delay samples from species for which only sequencing data are available.

Extracellular vesicles (EVs) are critical mediators of intercellular communication, and valuable sources of biomarkers for diagnostic and therapeutic applications. However, the complexity and heterogeneity of EVs present significant challenges for their proteomic characterization. Major challenges of EV samples include low yield, technical variability, and the need for sensitive and high throughput quantification approaches. In this study, we implement a tandem mass tag (TMT)-based MS workflow for comprehensive, quantitative proteomic profiling of isolated EVs. Through comparison with label-free quantitation (LFQ), we highlight the potential pitfalls and limitations of methodological choices in EV proteomic analyses. Our study integrates standard EV isolation with robust TMT labeling and high-resolution MS, providing insights into practical EV analysis. Utilizing this approach, we profiled EVs isolated from human fibroblasts treated with ionizing radiation. The TMT workflow uncovered an EV proteomic signature reflective of the cellular origins and potential functional roles of irradiated fibroblasts, compared to the LFQ workflow. Our case study underscores the potential of TMT-based MS to overcome common barriers in EV proteomics, facilitating new discoveries in EV biology and advancing their application in biomarker development and translational research.

We systematically reviewed published studies to assess reproducibility in miRNA expression profiles from extracellular vesicles (EVs) isolated from mouse serum. Our search specifically targeted mouse studies employing precipitation methods for EV isolation from blood and small RNA sequencing of EV-miRNAs in control groups. Out of 53 identified studies, approximately half lacked publicly available raw data, leaving four eligible studies containing sequencing data from a total of 11 mice. miRNA expression counts were standardized using z-scores for comparability. Within individual studies, miRNA profiles showed reasonable consistency; however, significant variability was observed across different studies. Principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and Spearman correlation consistently demonstrated study-specific clustering rather than biological similarity. Methodological discrepancies in EV isolation, RNA extraction protocols, and unreported confounders such as platelet contamination or blood-handling procedures likely contributed to this variability. Our findings emphasize substantial reproducibility challenges in EV-miRNA research across murine studies, highlighting an urgent need for standardized methodologies and transparent reporting to improve reliability of miRNA biomarker discovery and facilitate meta-analytic integration in preclinical research.

Protein S-palmitoylation, a reversible lipid modification, plays critical roles in regulating protein function and localization. However, its comprehensive role in the rapid reprogramming of macrophages during early immune responses remains incompletely understood. This study investigates the dynamics of the palmitoylome in immortalized bone marrow-derived macrophages (iBMDMs) during the initial phase of lipopolysaccharide (LPS) stimulation. Employing acyl-biotin exchange (ABE) proteomics coupled with a multi-protease digestion strategy (trypsin, AspN, chymotrypsin, or GluC), we significantly enhanced palmitoylation proteome coverage, identifying 2502 putative S-palmitoylated proteins (Log₂ fold change > 2, FDR < 0.05). Notably, this approach uncovered 527 proteins not previously associated with the mouse palmitoylome, including 185 candidates exclusively identified using non-tryptic proteases. In the context of immune cells, this study revealed 1378 proteins not previously reported, with 556 candidates identified exclusively via AspN, chymotrypsin, and/or GluC. Several of these novel candidates are established immune system components and phosphoproteins. Upon stimulation with 100 ng/mL LPS for 30 min, quantitative comparison revealed 648 differentially enriched proteins (308 predominantly detected in untreated, 340 predominantly detected in LPS-treated), indicating dynamic regulation via this posttranslational modification during early innate immune activation. Functional enrichment analysis linked these dynamically regulated proteins to critical pathways: LPS treatment enriched for immune signaling cascades and infection pathways, while untreated cells showed enrichment for metabolic and transport processes. This study provides a comprehensive resource of the macrophage palmitoylome and its dynamic remodeling, offering novel targets for investigating the regulation of macrophage function.