Proteomics最新文献

Posttranslational modifications (PTMs) are of significant interest in molecular biomedicine due to their crucial role in signal transduction across various cellular and organismal processes. Characterizing PTMs, distinguishing between functional and inert modifications, quantifying their occupancies, and understanding PTM crosstalk are challenging tasks in any biosystem. Studying each PTM often requires a specific, labor-intensive experimental design. Here, we present a PTM-centric proteome informatic pipeline for predicting relevant PTMs in mass spectrometry-based proteomics data without prior information. Once predicted, these in silico identified PTMs can be incorporated into a refined database search and compared to measured data. As a practical application, we demonstrate how this pipeline can be used to study glycoproteomics in oral squamous cell carcinoma based on the proteome profile of primary tumors. Subsequently, we experimentally identified cellular proteins that are differentially expressed in cells treated with multikinase inhibitors dasatinib and staurosporine using mass spectrometry-based proteomics. Computational enrichment analysis was then employed to determine the potential PTMs of differentially expressed proteins induced by both drugs. Finally, we conducted an additional round of database search with the predicted PTMs. Our pipeline successfully analyzed the enriched PTMs, and detected proteins not identified in the initial search. Our findings support the effectiveness of PTM-centric searching of MS data in proteomics based on computational enrichment analysis, and we propose integrating this approach into future proteomics search engines.

Although capillary electrophoresis coupled to mass spectrometry (CE-MS) holds promise for urinary peptide profiling, only a limited number of studies have used CE-MS to study plasma peptides. Here we describe the establishment of a workflow, including sample preparation, CE-MS analysis, data processing and normalization optimized for the analysis of plasma peptides. Using 291 plasma samples from 136 patients with end stage kidney failure (including pre- and post-dialysis samples) and 20 patients with chronic kidney disease, we identified and quantified the abundance of 3920 unique plasma peptides. The repeatability and intermediate precision of the analysis were high (with a coefficient of variation of 5% on average for all peptides). Six hundred sixty-one out of 3920 peptides were sequenced by CE-MS/MS. These peptide fragments belonged to 135 parent proteins. Using the pipeline, we identified 169 sequenced plasma peptides with different plasma abundance pre- and post-dialysis. These peptides combined in a support vector machine (SVM) classifier successfully discriminated between pre- and post-dialysis samples in a blinded validation cohort of 45 dialysis patients. Enriched peptides post-dialyses were for the major part associated to inflammation and the coagulation contact systems that may serve as signatures for optimizing dialysis materials. In conclusion, this high-throughput strategy focuses on the plasma peptidome, an understudied component of the plasma, as a promising area for further exploration. Due to their close proximity to the vascular bed, plasma peptides hold significant potential to serve as reliable biomarkers for systemic complications associated with kidney disease.

Protein N-glycosylation influences protein folding, stability, and trafficking, and has prominent functions in cell-cell adhesion and recognition. For the parasite Toxoplasma gondii, N-glycosylation of proteins is crucial for initial adhesion to host cells, parasite motility, and consequently, its ability to invade host cells. However, the glycoproteome of T. gondii remains largely unknown. In this study, we used the α-mannose-specific Burkholderia cenocepacia lectin A (BC2L-A) to enrich glycopeptides from T. gondii tachyzoites and analysed them by tandem mass spectrometry. The data enable the identification of over 100 N-glycoproteins with the glycosylation site(s) and the composition of the N-glycans at each site. T. gondii glycoproteins include known virulence factors, vaccine candidates as well as numerous uncharacterised proteins. These data provide ground knowledge to deepen our understanding of the role of glycoproteins in invasion and assist the rational design of vaccines.

Extracellular proteins are supposed to play crucial roles in the formation and structure of biofilms and aggregates. However, often little is known about these proteins, in particular for microbial communities. Here, we use two advanced metaproteomic approaches to study the extracellular proteome in a granular Candidatus Accumulibacter enrichment as a proxy for microbial communities that form solid microbial granules, such as those used in biological wastewater treatment. Limited proteolysis of whole granules and metaproteome isolation from the culture's supernatant successfully classified over 50% of the identified protein biomass to be secreted. Moreover, structural and sequence-based classification identified 387 proteins, corresponding to over 50% of the secreted protein biomass, with characteristics that could aid the formation of aggregates, including filamentous, beta-barrel containing, and cell surface proteins. While various of these aggregate-forming proteins originated from Ca. Accumulibacter, some proteins associated with other taxa. This suggests that not only a range of different proteins but also multiple organisms contribute to granular biofilm formation. Therefore, the obtained extracellular metaproteome data from the granular Ca. Accumulibacter enrichment provides a resource for exploring proteins that potentially support the formation and stability of granular biofilms, whereas the demonstrated approaches can be applied to explore biofilms of microbial communities in general.

Mass spectrometry (MS) is widely used in proteomics research in recent years. In practice, MS is often coupled with liquid chromatography or gas chromatography to analyze complex mixtures. Retention time (RT) is a critical feature that distinguishes different components in mixtures. And RT alignment is one of the crucial methods for correlating identical components across different samples. This review provides a broad perspective of RT alignment methods and tools used in proteomics and metabolomics. Firstly, we categorize these methods and tools into four types based on the information they employ, and introduce them, respectively. Subsequently, we present the application of RT alignment in proteomics. We have emphasized that the identification-free strategy might be a potential application of RT alignment. Finally, we summarize the limitations of current methods and discuss the future direction of RT alignment.

Glycosylation, a major posttranslational modification (PTM), is often dysregulated in cancer due to altered glycosyltransferase activity. Studies have shown specific changes in glycan structures associated with epithelial-mesenchymal transition (EMT) in cancer cells. However, the specific mechanism by which glycosyltransferases contribute to EMT remains unclear. In this study, we used bronchoalveolar lavage fluid (BALF) from lung adenocarcinoma (LUAD) patients to comparatively characterize glycopatterns and identify dysregulated glycosyltransferases in LUAD. We found a significant reduction in N-glycans containing the bisecting GlcNAc structure and confirmed by Western blot that N-acetylglucosaminyltransferase-III (MGAT3) is downregulated in LUAD. We observed a notable downregulation of both messenger RNA (mRNA) and protein expression of Forkhead box protein A2 (FOXA2) in early-stage LUAD, with FOXA2 loss emerging as an EMT promoter. Interestingly, cellular EMT models demonstrated that FOXA2 deficiency decreased MGAT3 expression during TGF-β1-driven EMT, leading to reduced levels of bisecting-GlcNAc N-glycans in LUAD cells. Our findings unveil a novel mechanism underlying the downregulation of MGAT3 and bisecting GlcNAc N-glycan expression during EMT, a process crucial for tumor metastasis.

Developing methodological approaches for discovering novel pathways is a key challenge in the life science research. Biological pathways are regulated-in higher eukaryotes-by a vast diversity of linear peptide motifs that mediate combinatorial specificity in signal transduction pathways. The E3 ubiquitin ligase component (MDM2) is such a protein that interacts with target proteins containing linear motifs such as p53. Drug leads, such as Nutlin-3, that bind to the MDM2 hydrophobic pocket mimic p53 and can release p53 from MDM2 control and this can lead to cell death. However, these drug leads act allosterically, having agonist effects on MDM2's functions and there are other proteins whose steady state levels can be altered by Nutlin-3. As cell density can alter the proliferation state of cell populations, we examined the impact of Nutlin-3 on levels of newly synthesized proteins using pulse-SILAC mass spectrometry. The data demonstrate that at differing cell densities or population-wide proliferation rates, different newly synthesized proteins dominate the proteome landscape in a Nutlin-3 dependent manner. These data further confirm that the cell state in a population of cells can in turn impact on the MDM2 signalling landscape. This methodology forms a blueprint for biomarker discovery using clinical samples that can detect changes in the synthesis rate of proteins in cell populations treated with specific agents. Broader implications highlight tools that can be used to study allosteric regulation of protein-drug combinations.