Molecular & Cellular Proteomics最新文献

Antibody fragment crystallizable region (Fc) glycosylation critically modulates immune signaling, yet characterization of glycosylation beyond the immunoglobulin G (IgG) isotype remains limited. Here, we present the first site-specific glycoprofiling of immunoglobulin A (IgA) and immunoglobulin M (IgM) in elderly individuals with tuberculosis (TB), a population particularly susceptible to disease reactivation. Using dual-enzyme digestion and targeted LC-MS/MS analysis, we quantified Fc glycosylation of IgG, IgA, and IgM in plasma from 20 patients with active TB (ATB), 18 with latent TB infection (LTBI), and 20 controls. Consistent with previous studies, IgG1 and IgG2 in ATB displayed reduced galactosylation and elevated fucosylation compared with LTBI. Extending the analysis to other isotypes, we identified analogous alterations in IgA and IgM. ATB samples showed reduced digalactosylation and increased monogalactosylation at IgA1/2-N144/131, indicating a shift toward agalactosylation. In IgM, decreased galactosylation at N171, N332, and N395, increased agalactosylation at N563, and increased fucosylation and sialylation at N71 were observed in ATB relative to LTBI and controls. Integrating 18 significantly altered glycosylation traits across all three Ig isotypes revealed coordinated humoral remodeling associated with active disease. Collectively, these findings indicate that IgA and IgM, like IgG, undergo infection-associated proinflammatory glycan remodeling, underscoring their overlooked roles in antibody-mediated immune modulation and providing a broader framework for understanding humoral responses in aging and chronic infection.

Essential tremor (ET) stands as one of the most prevalent movement disorders originating from cerebellar dysfunction. However, effective treatment remains limited, largely due to a poor understanding of its molecular pathology. The harmaline-induced tremor in mice is a well-established model for ET research, though its mechanisms remain unclear. This study aimed to get insight into the molecular intricacies underlying cerebellar dysfunction in this model. Combining LC-MS/MS and RNA-Seq approach, we delved into the cerebellar alterations in harmaline-induced tremor in mouse. Multi-omics profiling identified 5194 correlated coding molecules, among which 19 were significantly dysregulated. Further KEGG enrichment analysis identified cerebellar serotonin transporter (SERT) as the key molecule in harmaline-induced tremor. We validated the upregulation of SERT in the cerebellar cortex following harmaline induction, particularly within Purkinje cells, and demonstrated that pharmacological inhibition or genetical knockdown of SERT significantly attenuated tremor severity and neuronal hyperexcitability. Further mechanistic studies revealed that harmaline-induced SERT upregulation leads to depleted serotonin levels in the cerebellum, contributing to tremor pathogenesis. In general, our study unveils crucial insights that could pave the way for molecular target identification and effective therapeutic interventions for ET.

The involvement of the oral microbiome (OM) in the pathophysiology of Alzheimer's disease and vascular dementia has been recognized epidemiologically, but the molecular mechanisms remain elusive. In this study, we uncovered the presence of OM-derived proteins (OMdPs) in brain extracellular vesicles (bEVs) from post-mortem Alzheimer's disease and vascular dementia subjects using unbiased metaproteomics. OMdP circulation in blood EVs was also confirmed in an independent cohort. Our findings also reveal that specific OMdPs are present in bEVs, with their levels varying with disease progression. Peptidome-wide correlation analyses further explored their exchange dynamics and composition within bEVs. In addition, we validated the ability of OM-derived EVs to cross the blood-brain barrier using a blood-brain barrier-on-a-chip model, confirming a potential route for bacterial-derived molecules to reach the central nervous system. Bioinformatics-driven interaction analyses indicated that OMdPs engage with key neuropathological proteins, including amyloid-beta and tau, suggesting a novel mechanism linking dysbiotic OM to dementia. These results provide new insights into the role of the OM in neurodegeneration and highlight OMdPs as potential biomarkers and therapeutic targets.

Epithelial-mesenchymal transition (EMT) is a key biological process in physiological and pathological conditions, spanning development, wound healing, and cancer. Vimentin, a key cytoskeletal intermediate filament (IF) protein, is an established intracellular determinant of EMT. Recently, extracellular vimentin has also emerged with important functions, and we demonstrated that vimentin from fibroblast-derived extracellular vesicles (EVs) promotes wound healing. Building on these findings, we explored whether extracellular vimentin regulates EMT. We employed fibroblast-derived EVs to assess their EMT-driving capacity. Using coculture models and EV treatments from WT and vimentin-KO fibroblasts, we observed that fibroblasts induce an EMT phenotype in epithelial cells, marked by elevated mesenchymal markers and reduced epithelial markers. EVs from vimentin-deficient fibroblasts showed a decreased EMT-inducing capacity and failed to stimulate cell cover closure, underscoring vimentin's critical role in orchestrating these processes. Coculturing epithelial cells with WT fibroblasts mirrored these outcomes, while vimentin-deficient fibroblasts produced similarly poor EMT induction. Proteomic profiling revealed that WT EVs contained an enriched set of EMT-associated proteins, including those involved in cytoskeletal organization, cell adhesion, and EMT-regulating signaling pathways. Notably, these proteins, such as fibronectin and N-cadherin, were significantly diminished in vimentin-deficient EVs. Moreover, we identified over 600 additional proteins uniquely present in WT-derived EVs, with enrichment in key biological processes like wound healing and cell migration. These findings demonstrate that vimentin-positive EVs drive EMT by transmitting a specific protein cargo that supports EMT-related cellular changes. The vimentin-positive EV proteome will help understand EMT mechanisms and develop targeted therapies for pathological conditions related to abnormal EMT.

Biophysical proteomics assays allow for proteome-wide, label-free monitoring of ligand-induced changes in protein structure and stability, offering insights into protein-ligand interactions and modulation of biophysical properties of cellular proteins. These assays exploit the principle that compound-induced alterations in structure or stability of proteins can be detected through changes in their susceptibility to denaturation. Here, we introduce solvent proteome profiling in cells (SPICE), which employs solvent-based denaturation of proteins under otherwise physiological conditions in intact cells. We characterized solvent-induced denaturation of proteins inside cells as distinct from that in cell extracts and validated SPICE by detecting known drug-target interactions for multiple compound classes. Our results indicate that SPICE, unlike experiments in cell extracts, also detects secondary compound-induced effects such as target profiles of drug metabolites, modulation of protein-protein interactions, and downstream signaling events. We further demonstrate complementarity of SPICE and cellular thermal shift assay, which both robustly detect the designated targets of well-characterized drugs and individually provide biologically meaningful and interpretable results. Finally, we show that SPICE can detect covalent drug-targets, compound-induced target-destabilization and stabilization of degrader drug targets despite their concurrent degradation.

Protein truncation is a common modification that can alter protein localization, interaction, activity, and function. Top-down proteomics targets the identification of all molecular forms in which a protein can exist (termed "proteoforms") and is thus well-suited for termini analysis. To examine the properties, origin, and consistency of truncated proteoforms, we performed a meta-analysis of 50 top-down proteomics datasets published over the past decade, covering 140,000 proteoforms derived from 14,500 proteins across various species. On average across all datasets, approximately 71% of proteoforms were truncated, with the vast majority not yet being documented in protein databases. Our analysis was able to distinguish between artificial truncations (e.g., sample preparation effects on labile peptide bonds) and endogenous truncations, enabling the identification of novel signal peptides and truncations between structured domains. This study highlights the importance of a common yet understudied mechanism for generating protein diversity and provides a valuable resource for future studies, targeting truncated proteoform functions or aiming to reduce artefacts in proteomics sample preparation.

Missing values are a major challenge in the analysis of mass spectrometry proteomics data. Missing values hinder reproducibility, decrease statistical power for identifying differentially abundant proteins, and make it challenging to analyze low-abundance proteins. We present Lupine, a deep learning-based method for imputing, or estimating, missing values in quantitative proteomics data. Lupine is, to our knowledge, the first imputation method that is designed to learn jointly from many datasets, and we provide evidence that this approach leads to more accurate predictions. We validated Lupine by applying it to tandem mass tag data from >1000 cancer patient samples spanning 10 cancer types from the Clinical Proteomics Tumor Atlas Consortium. Lupine outperforms the state of the art for proteomics imputation, uniquely identifies differentially abundant proteins and Gene Ontology terms, and learns a meaningful representation of proteins and patient samples. Lupine is implemented as an open-source Python package.

Invasive candidiasis (IC) is a serious, life-threatening, and costly fungal infection if not diagnosed early and treated appropriately. However, this healthcare-associated mycosis caused by Candida spp. is difficult to diagnose because of its nonspecific clinical signs and symptoms, and the lack of early and accurate detection methods. IC is also difficult to treat due to its late diagnosis, the limited antifungal arsenal, and the rapid emergence and spread of (multi)drug-resistant Candida strains. Therefore, early and accurate innovative methods for species and resistance identification in IC (candidemia and deep-seated candidiasis) are urgently needed to initiate timely and appropriate antifungal therapy, and reduce its high morbidity, mortality, and health care costs in hospitalized patients (especially, severely immunocompromised or critically ill patients). The availability of the complete genome sequences of the most clinically relevant Candida species coupled with recent advances in high-throughput omics technologies have spurred an unprecedented era in the discovery and development of IC diagnostics at different levels of molecular complexity. Here, we review the contribution of current and emerging omics technologies, including genomics, transcriptomics, proteomics, peptidomics, metabolomics, lipidomics, glycomics, immunomics (immunoproteomics, immunopeptidomics, and immunoglycomics), imiomics (imaging-omics), and microbiomics (metagenomics, metatranscriptomics, metaproteomics, and metabonomics), to the process of biomarker development for early diagnosis, antifungal susceptibility, prognosis, follow-up, and therapeutic monitoring in IC. We highlight the potential of integrating multiple omic data (through integromics, multiomics, or panomics, together with systems biology and artificial intelligence) for the discovery of multidimensional biomarker signatures and computational algorithms for IC diagnosis. Finally, we discuss future challenges and prospects for their clinical implementation. These next-generation IC diagnostics promise to revolutionize medical practice by unraveling the complexity of biological systems at multiple levels. Furthermore, these could help clinicians make more precise and personalized clinical decisions through multiomics or panomics-based precision medicine approaches, rather than traditional one-size-fits-all approaches.

Loss of the tumor suppressor phosphatase and tensin homolog (PTEN) is frequently observed in various cancers and promotes tumorigenesis by activating the PI3K-AKT pathway. However, the effectiveness of therapies targeting this pathway is limited by complex signaling crosstalk and compensatory mechanisms. Here, we employed quantitative proteomic and phosphoproteomic analyses using MCF10A PTEN KO models to comprehensively map the signaling alterations induced by PTEN loss. Our analyses revealed that PTEN deficiency not only activates canonical PI3K-AKT signaling but also induces widespread changes in cytoskeleton organization, cell cycle regulation, and central carbon metabolism. PTEN loss also substantially elevates the activity of a variety of tyrosine kinases, including Src kinase and EphA2, a receptor tyrosine kinase implicated in cancer progression. Mechanistic studies demonstrated that Src activation, rather than the canonical AKT signaling pathway, drives the upregulation of the receptor tyrosine kinase EphA2. The activation of the noncanonical tyrosine kinase signaling renders AKT inhibition alone insufficient in PTEN-deficient cancers. Importantly, combined treatment with the Food and Drug Administration-approved AKT inhibitor capivasertib and the Src inhibitor dasatinib synergistically induced apoptosis and suppressed the tumor cell growth in various PTEN-deficient cell lines as well as in 3D cultures of endometrial cancer patient-derived xenograft models. Our study reveals that PTEN loss drives oncogenic signaling via dual activation of PI3K-AKT and tyrosine kinase pathways. Specifically, Src-mediated upregulation of EphA2 in PTEN-deficient cells highlights a therapeutic vulnerability that can be exploited by combined AKT and Src inhibition. This approach addresses the resistance associated with AKT inhibition alone and enhances therapeutic efficacy in PTEN-deficient cancers, supporting its potential application in targeted combination therapies.

The mechanism underlying asthenozoospermia in male infertility has been a prominent topic in reproductive medicine research. Human sperm function is modified by various protein post-translational modifications (PTMs). Among these, lactylation modification, a relatively novel PTM, has not been previously reported in the context of the male reproductive system. Comparative analyses between asthenozoospermic and normal sperm have revealed a significant down-regulation in the level of lysine lactylation (Kla) in proteins from asthenozoospermic sperm. Based on proteomic studies of protein Kla, 220 lactylated proteins were identified in sperm. Bioinformatics results showed that these lactylated proteins were highly enriched in the glycolytic pathway. Phosphoglycerate kinase 2 (PGK2), a key glycolytic enzyme and testis-specific protein, has been found to have 10 lactylated sites (K6, K11, K31, K41, K141, K192, K220, K272, K322, and K353). In asthenozoospermic sperm, both the lactylation level of PGK2 and its enzyme activity were reduced, while exogenous supplementation with PGK2 downstream products ameliorated sperm motility dysfunction. Mutation experiments at the K220 site confirmed that PGK2 (K220) lactylation affects glycolysis by regulating its enzyme activity. This study provides the first evidence of the regulatory role of proteins lactylation in sperm function.