Journal of Proteome Research最新文献

Sperm capacitation is a critical process for fertilization. This work aims to analyze the effect in vitro capacitation had on the proteome and mitochondrial parameters of bull spermatozoa. Viability, mitochondrial membrane potential (MMP), and reactive oxygen species (mROS) were assessed by flow cytometry in noncapacitated (NC) and in vitro capacitated (IVC) sperm. Proteome was evaluated using SWATH-MS. In vitro capacitation significantly induced a decrease in sperm viability, a high MMP, and an increase in mROS production. Within the group of living spermatozoa, the capacitation significantly induced a decrease in healthy mitochondrial spermatozoa, as well as an increase in mROS production, without affecting the MMP intensity. A total number of 72 differentially abundant proteins were found of which 63 were over-represented in the NC sperm group and 9 in the IVC sperm group. It was observed that many proteins associated with the sperm membrane and acrosome were lost during the capacitation process. For the IVC sperm, the functional enrichment was found in proteins related to the oxidative phosphorylation process. Our results indicate that the capacitation process induces a significant loss of seminal plasma-derived membrane proteins and a significant increase in proteins related with the oxidative phosphorylation (OXPHOS) pathway. Data are available via ProteomeXchange with identifiers PXD056424 and PXD042286.

Recurrent ulcerative colitis (UC) seriously affects the quality of life of patients. Melatonin affects the alteration of the gut microbiota and can effectively relieve inflammation-associated diseases. In the present study, we determined that melatonin effectively alleviated intestinal inflammation and delayed weight loss in mice. Analysis of ileocecal contents in mice via 16S-rRNA and GC-MS revealed that melatonin could elevate the diversity of the gut microbiota and the abundance of short-chain fatty acids producing bacteria and promote the secretion of butyrate. Subsequently, butyrate negatively regulates the NLRP3-mediated inflammatory signaling pathway to inhibit the secretion of proinflammatory mediators such as caspase-1 and IL-1β to restrict the further development of intestinal inflammation. The NLRP3 expression increased, and the GPR109A expression was reduced significantly in the intestinal tissues of active UC patients, which was also closely related to clinical indicators CRP and ESR closely. However, disrupting the gut microbiota with broad-spectrum antibiotics (ABX) blocks melatonin's role in reducing intestinal inflammation. Collectively, we indicate that melatonin arrests UC in mice by modulating the microbiome and the NLRP3/caspase-1 inflammatory signaling pathways to skew macrophage polarization, which may have potential implications in the development of new approaches to treat acute UC.

Chronic inflammatory and immune dysregulation are critical drivers of the development and progression of chronic obstructive pulmonary disease (COPD). Posttranslational modifications, such as glycosylation of Immunoglobulin G (IgG), are crucial in modulating systemic inflammatory homeostasis. This study aims to profile plasma IgG glycopeptides (IgGPs) in COPD patients to uncover new insights into their pathogenesis and to identify novel biomarkers. An integrated platform that combines Fe₃O₄@PDA@DETA nanospheres enrichment with high-resolution mass spectrometry measurement was employed to analyze plasma IgG N-glycopeptides from 90 COPD patients, 45 clinically defined early COPD (CECOPD) patients, and 90 healthy individuals. To explore the underlying mechanism of COPD progression, correlations between IgG N-glycoforms and clinical parameters were assessed. Disease-specific IgGPs were identified in both the ECOPD and COPD cohorts. Notably, it was the IgG glycopattern, rather than the IgG levels themselves, that underwent changes as the disease progressed. In early COPD patients, there was a decrease in bisection, accompanied by an increase in site-specific afucosylated galactosylation and fucosylation of IgG, indicating an anti-inflammatory state. Conversely, in COPD patients, an increase in inflammation was observed, which was characterized by reduced galactosylation and sialylation. Interestingly, a subset of healthy controls displayed IgGP patterns similar to those of early COPD, possibly reflecting the impact of smoking and the associated immune responses. We finally identified 6 anti-inflammatory and 2 pro-inflammatory IgGPs as ECOPD-specific IgGP indicators. Collectively, these findings suggest that plasma IgG glycosylation holds great potential as a biomarker for early COPD diagnosis, providing valuable insights into the immune system changes during disease progression. The raw data files are publicly accessible via the ProteomeXchange Consortium with the identifier PXD056374.

Skeletal muscle wasting is a critical clinical problem associated with several diseases that significantly impair patient outcomes due to the progressive loss of muscle mass and function. This study explores the potential of 3-hydroxybutyrate (3-HB) as a therapeutic agent to counteract muscle atrophy by promoting the proliferation and differentiation of C2C12 myoblasts. Using nuclear magnetic resonance (NMR)-based metabolomics analysis, we uncover the underlying mechanisms by which 3-HB exerts its effects. Our findings demonstrate that 3-HB exerts its effects through two distinct mechanisms: as a metabolic substrate and as a signaling molecule. As a metabolic substrate, 3-HB enhances myoblast energy efficiency by stimulating the expression of G protein-coupled receptor 109a (GPR109a), which subsequently upregulates the 3-HB transporters MCT1 and CD147, the utilization enzyme OXCT1, and phosphorylated AMPK, thereby increasing ATP production. As a signaling molecule, 3-HB activates GPR109a, promoting calcium influx, improving calcium homeostasis, and increasing the expression of Ca²⁺-related proteins such as CAMKK2. This signaling cascade activates calcineurin (CaN), facilitating NFAT translocation to the nucleus and gene expression that drives myoblast proliferation and differentiation. By elucidating the dual regulatory roles of 3-HB in energy metabolism and cellular signaling, this study not only advances our understanding of muscle physiology but also highlights the potential of 3-HB as a novel therapeutic approach for the prevention or treatment of skeletal muscle atrophy.

Single-cell analysis is an active area of research in many fields of biology. Measurements at single-cell resolution allow researchers to study diverse populations without losing biologically meaningful information to sample averages. Many technologies have been used to study single cells, including mass spectrometry-based single-cell proteomics (SCP). SCP has seen a lot of growth over the past couple of years through improvements in data acquisition and analysis, leading to greater proteomic depth. Because method development has been the main focus in SCP, biological applications have been sprinkled in only as proof-of-concept. However, SCP methods now provide significant coverage of the proteome and have been implemented in many laboratories. Thus, a primary question to address in our community is whether the current state of technology is ready for widespread adoption for biological inquiry. In this Perspective, we examine the potential for SCP in three thematic areas of biological investigation: cell annotation, developmental trajectories, and spatial mapping. We identify that the primary limitation of SCP is sample throughput. As proteome depth has been the primary target for method development to date, we advocate for a change in focus to facilitate measuring tens of thousands of single-cell proteomes to enable biological applications beyond proof-of-concept.

Recent advancements in single-cell (sc) resolution analyses, particularly in sc transcriptomics and sc proteomics, have revolutionized our ability to probe and understand cellular heterogeneity. The study of metabolism through small molecules, metabolomics, provides an additional level of information otherwise unattainable by transcriptomics or proteomics by shedding light on the metabolic pathways that translate gene expression into functional outcomes. Metabolic heterogeneity, critical in health and disease, impacts developmental outcomes, disease progression, and treatment responses. However, dedicated approaches probing the sc metabolome have not reached the maturity of other sc omics technologies. Over the past decade, innovations in sc metabolomics have addressed some of the practical limitations, including cell isolation, signal sensitivity, and throughput. To fully exploit their potential in biological research, however, remaining challenges must be thoroughly addressed. Additionally, integrating sc metabolomics with orthogonal sc techniques will be required to validate relevant results and gain systems-level understanding. This perspective offers a broad-stroke overview of recent mass spectrometry (MS)-based sc metabolomics advancements, focusing on ongoing challenges from a biologist's viewpoint, aimed at addressing pertinent and innovative biological questions. Additionally, we emphasize the use of orthogonal approaches and showcase biological systems that these sophisticated methodologies are apt to explore.

Liquid chromatography-tandem mass spectrometry employing data-dependent acquisition (DDA) is a mature, widely used proteomics technique routinely applied to proteome profiling, protein-protein interaction studies, biomarker discovery, and protein modification analysis. Numerous tools exist for searching DDA data and myriad file formats are output as results. While some search and post processing tools include data visualization features to aid biological interpretation, they are often limited or tied to specific software pipelines. This restricts the accessibility, sharing and interpretation of data, and hinders comparison of results between different software pipelines. We developed Limelight, an easy-to-use, open-source, freely available tool that provides data sharing, analysis and visualization and is not tied to any specific software pipeline. Limelight is a data visualization tool specifically designed to provide access to the whole "data stack", from raw and annotated scan data to peptide-spectrum matches, quality control, peptides, proteins, and modifications. Limelight is designed from the ground up for sharing and collaboration and to support data from any DDA workflow. We provide tools to import data from many widely used open-mass and closed-mass search software workflows. Limelight helps maximize the utility of data by providing an easy-to-use interface for finding and interpreting data, all using the native scores from respective workflows.

Mass spectrometry-based discovery of bacterial immunopeptides presented by infected cells allows untargeted discovery of bacterial antigens that can serve as vaccine candidates. However, reliable identification of bacterial epitopes is challenged by their extremely low abundance. Here, we describe an optimized bioinformatic framework to enhance the confident identification of bacterial immunopeptides. Immunopeptidomics data of cell cultures infected with Listeria monocytogenes were searched by four different search engines, PEAKS, Comet, Sage and MSFragger, followed by data-driven rescoring with MS²Rescore. Compared with individual search engine results, this integrated workflow boosted immunopeptide identification by an average of 27% and led to the high-confidence detection of 18 additional bacterial peptides (+27%) matching 15 different Listeria proteins (+36%). Despite the strong agreement between the search engines, a small number of spectra (<1%) had ambiguous matches to multiple peptides and were excluded to ensure high-confidence identifications. Finally, we demonstrate our workflow with sensitive timsTOF SCP data acquisition and find that rescoring, now with inclusion of ion mobility features, identifies 76% more peptides compared to Q Exactive HF acquisition. Together, our results demonstrate how integration of multiple search engine results along with data-driven rescoring maximizes immunopeptide identification, boosting the detection of high-confidence bacterial epitopes for vaccine development.

Background: Colorectal carcinoma (CRC) is a leading cause of cancer-related deaths globally. Diagnostic biomarkers are essential for risk stratification and early detection, potentially enhancing patient survival. Our study aimed to explore the potential biomarkers of CRC at the protein and metabolic levels.

Methods: Blood serum from CRC patients and healthy controls was analyzed using metabolomic and proteomic techniques. A conjoint analysis was conducted, and samples were split into training and validation sets (7:3 ratio) to develop and evaluate a disease diagnosis classifier model. Immunohistochemistry (IHC) analyses were conducted to validate the results.

Results: We identified 631 differential metabolites and 61 differentially expressed proteins (DEPs) in CRC, involved in pathways such as arginine and proline metabolism, central carbon metabolism in cancer, and signaling pathways including TGF-β, mTOR, PI3K-Akt, and others. Key proteins (CILP2, SLC3A2, EXTL2, hydroxypyruvate isomerase (HYI), ENPEP, LRG1, CTSS, thyrotropin-releasing hormone-degrading ectoenzyme (TRHDE), SELE, and HSPA1A) showed significant expression differences between CRC patients and controls. IHC results showed that compared with the paracancerous tissues, the expression of CILP2, EXTL2, and HYI was significantly downregulated in the CRC tissues (P < 0.05). The classifier model, comprising l-arginine, Harden-Young ester, l-aspartic acid, oxoglutaric acid, l-proline, octopine, l-valine, and progesterone, achieved AUC values of 0.998 and 0.914 in training and validation data sets, respectively.

Conclusions: The identified metabolites and DEPs are promising CRC biomarkers. The developed classifier model based on eight metabolites demonstrates high accuracy for CRC assessment and diagnosis.

Hederagenin (Hed), a natural triterpenoid, exhibits antitumor potential in cervical cancer. The present study was designed to explore Hed's regulatory mechanisms on mitophagy in SiHa cervical cancer cells, employing tandem mass tag (TMT) proteomics and an advanced network association algorithm (NAA). Our findings revealed that Hed decreased SiHa cell viability, induced apoptosis, and altered mitochondrial membrane potential. Notably, Hed inhibited mitophagic flux under both normoxic and hypoxic conditions. Through TMT proteomics analysis and innovative NAA, we identified a close association between the HIF-1 signaling pathway and mitophagy. Network analysis further suggested that Hed acts on a target network centered on SRC, STAT3, AKT1, and HIF1A. Western blot analysis confirmed the expression and phosphorylation status of these targets in response to Hed. This study elucidates the molecular mechanisms underlying Hed's regulation of mitophagy in SiHa cells, offering novel insights and potential therapeutic targets for cervical cancer treatment.