Proteomes最新文献

Sarcopenia is linked to the decline in muscle mass, strength and function during aging. It affects the quality and life expectancy and can lead to dependence. The biological process underlying sarcopenia is unclear, but the proteins myostatin and follistatin are involved in the balance between muscle breakdown and synthesis. While myostatin promotes muscle breakdown, follistatin promotes muscle growth, but several works have shown an inconsistent association of these proteins with aging-related parameters in serum of older people. We aimed to know the evolution of these putative sarcopenia biomarkers along muscle aging in an in vitro model. We created and phenotyped a longitudinal murine model (C2C12 cells). Then, we analyzed the protein and genetic expression of myostatin and follistatin as well as the signaling pathway regulators mTOR and RPS6KB1. Myostatin and RPS6KB1 showed a similar tendency in both protein and genetic expression with aging (basal-up-down). Follistatin, on the other hand, shows the opposite tendency (basal-down-up). Regarding mTOR, the tendencies differ when analyzing proteins (basal-up-down) or genes (basal-down-down). Our work demonstrates a U-shape tendency for myostatin and follistatin and for the signaling pathway regulators. These results could be of the utmost importance when designing further research on seeking molecular biomarkers and/or targets for sarcopenia.

Proteogenomics integrates genomic and proteomic data to elucidate cellular processes by identifying variant peptides, including single amino acid variants (SAAVs). In this study, we assessed the capability of data-independent acquisition mass spectrometry (DIA-MS) to identify SAAV peptides in HeLa cells using various search engine pipelines. We developed a customised sequence database (DB) incorporating SAAV sequences from the HeLa genome and conducted searches using DIA-NN, Spectronaut, and Fragpipe-MSFragger. Our evaluation focused on identifying true positive SAAV peptides and false positives through entrapment DBs. This study revealed that DIA-MS provides reproducible and comprehensive coverage of the proteome, identifying a substantial proportion of SAAV peptides. Notably, the DIA-MS searches maintained consistent identification of SAAV peptides despite varying sizes of the entrapment DB. A comparative analysis showed that Fragpipe-MSFragger (FP-DIA) demonstrated the most conservative and effective performance, exhibiting the lowest false discovery match ratio (FDMR). Additionally, integrating DIA and data-dependent acquisition (DDA) MS data search outputs enhanced SAAV peptide identification, with a lower false discovery rate (FDR) observed in DDA searches. The validation using stable isotope dilution and parallel reaction monitoring (SID-PRM) confirmed the SAAV peptides identified by DIA-MS and DDA-MS searches, highlighting the reliability of our approach. Our findings underscore the effectiveness of DIA-MS in proteogenomic workflows for identifying SAAV peptides, offering insights into optimising search engine pipelines and DB construction for accurate proteomics analysis. These methodologies advance the understanding of proteome variability, contributing to cancer research and the identification of novel proteoform therapeutic targets.

Non-healing diabetic foot ulcers (DFUs) not only significantly increase morbidity and mortality but also cost a lot and drain healthcare resources. Persistent inflammation, decreased angiogenesis, and altered extracellular matrix remodeling contribute to delayed healing or non-healing. Recent studies suggest an increasing trend of DFUs in diabetes patients, and non-healing DFYs increase the incidence of amputation. Despite the current treatment with offloading, dressing, antibiotics use, and oxygen therapy, the risk of amputation persists. Thus, there is a need to understand the molecular and cellular factors regulating healing in DFUs. The ongoing research based on proteomics and transcriptomics has predicted multiple potential targets, but there is no definitive therapy to enhance healing in chronic DFUs. Increased or decreased expression of various proteins encoded by genes, whose expression transcriptionally and post-transcriptionally is regulated by transcription factors (TFs) and microRNAs (miRs), regulates DFU healing. For this study, RNA sequencing was conducted on 20 DFU samples of ulcer tissue and non-ulcerated nearby healthy tissues. The IPA analysis revealed various activated and inhibited transcription factors and microRNAs. Further network analysis revealed interactions between the TFs and miRs and the molecular targets of these TFs and miRs. The analysis revealed 30 differentially expressed transcription factors (21 activated and 9 inhibited), two translational regulators (RPSA and EIF4G2), and seven miRs, including mir-486, mir-324, mir-23, mir-186, mir-210, mir-199, and mir-338 in upstream regulators (p < 0.05), while causal network analysis (p < 0.05) revealed 28 differentially expressed TFs (19 activated and 9 inhibited), two translational regulators (RPSA and EIF4G2), and five miRs including mir-155, mir-486, mir-324, mir-210, and mir-1225. The protein-protein interaction analysis revealed the interaction of various novel proteins with the proteins involved in regulating DFU pathogenesis and healing. The results of this study highlight many activated and inhibited novel TFs and miRs not reported in the literature so far, as well as the targeted molecules. Since proteins are the functional units during biological processes, alteration of gene expression may result in different proteoforms and protein species, making the wound microenvironment a complex protein interaction (proteome complexity). Thus, investigating the effects of these TFs and miRs on protein expression using proteomics and combining these results with transcriptomics will help advance research on DFU healing and delineate potential therapeutic strategies.

The yeast ATPase Cdc48 (known as p97/VCP in human cells) plays an important role in the Ubiquitin Proteasome System. VCP is essential for cancer cell proliferation, and its dysregulation has been implicated in several neurodegenerative diseases. Cdc48 functions by extracting ubiquitylated proteins from membranes, protein complexes and chromatin by often facilitating their proteasomal degradation. Specific adaptors or cofactors, primarily belonging to the UBX domain-containing protein family (which has seven members in Saccharomyces cerevisiae) recruit Cdc48 to ubiquitylated proteins. Here, we employed sample multiplexing-based quantitative mass spectrometry to profile global protein abundance in p97 adaptor deletion strains, specifically comparing seven single deletion strains of UBX domain-containing proteins and the Cuz1 deletion strain, which belongs to the zinc finger AN1-type domain protein family. We observed that each strain showed unique sets of differentially abundant proteins compared to the wild type. Our analysis also revealed a role for Ubx3 in maintaining wild type levels of mitochondrial proteins. Overall, we identified ~1400 differentially abundant proteins in the absence of a specific Cdc48 adaptor. This unique dataset offers a valuable resource for studying the functions of these adaptors, aiming to achieve a better understanding of the cellular processes regulated by Cdc48 itself and to deepen our understanding of the Ubiquitin Proteasome System.

Current immunoassay techniques for analyzing clinically relevant parathyroid hormone (PTH) circulating fragments cannot distinguish microheterogeneity among structurally similar molecular species. This hinders the identification of molecular species and the capture of target analyte information. Since structural modifications are important in disease pathways, mass spectrometry can detect, identify, and quantify heterogeneous ligands captured by antibodies. We aimed to create a sensitive and selective multiple reaction monitoring-mass spectrometric immunoassay analysis (MRM-MSIA)-based method for detecting and quantifying PTH fragments or proteoforms for clinical research. Our study established MRM transitions using triple-quadrupole tandem mass spectrometry for the signature peptides of five PTH fragments. This method was validated according to FDA guidelines, employing the mass spectrometric immunoassay (MSIA) protocol to bolster detection selectivity and sensitivity. This validated approach was applied by analyzing samples from type 2 diabetes mellitus (T2DM) patients with and without vitamin D deficiency. We found serum PTH fragments associated with vitamin D deficiency in patients with and without T2DM. We developed and validated the MRM-MSIA technique specifically designed for the detection and quantification (amino acid (aa38-44), (aa45-51), and (aa65-75)) of these fragments associated with vitamin D deficiency and T2DM. This study is the first to accurately quantify plasma PTH fragments using MRM-MSIA, demonstrating its potential for clinical diagnostics.

Background: Diabetes, particularly type 2 diabetes (T2D), is linked with an increased risk of developing coronary heart disease (CHD). The present study aimed to evaluate potential circulating biomarkers of CHD by adopting a targeted proteomic approach based on proximity extension assays (PEA). Methods: The study was based on 30 patients with both T2D and CHD (group DC), 30 patients with T2D without CHD (group DN) and 29 patients without diabetes but with a diagnosis of CHD (group NC). Plasma samples were analyzed using PEA, with an Olink Target 96 cardiometabolic panel expressed as normalized protein expression (NPX) units. Results: Lysosomal Pro-X carboxypeptidase (PRCP), Liver carboxylesterase 1 (CES1), Complement C2 (C2), and Intercellular adhesion molecule 3 (ICAM3) were lower in the DC and NC groups compared with the DN groups. Lithostathine-1-alpha (REG1A) and Immunoglobulin lambda constant 2 (IGLC2) were found higher in the DC group compared to DN and NC groups. ROC analysis suggested a significant ability of the six proteins to distinguish among the three groups (whole model test p < 0.0001, AUC 0.83-0.88), with a satisfactory discriminating performance in terms of sensitivity (77-90%) and specificity (70-90%). A possible role of IGLC2, PRCP, and REG1A in indicating kidney impairment was found, with a sensitivity of 92% and specificity of 83%. Conclusions: The identified panel of six plasma proteins, using a targeted proteomic approach, provided evidence that these parameters could be considered in the chronic evolution of T2D and its complications.

In recent years, avocados have gained worldwide popularity as a nutritive food. This trend is causing a rise in the production of this fruit, which is accompanied by several problems associated with monocultural practices. Despite massive economic gains, limited molecular and structural information has been generated about avocado ripening. In fact, limited studies have attempted to unravel the proteome complexity dynamics of avocado fruit. We therefore conducted a comparative proteomics study on avocado peel and pulp during the postharvest shelf life using tandem mass tag synchronous precursor selection triple-stage mass spectrometry. We identified 3161 and 1128 proteins in the peel and pulp, respectively. Peels exhibited major over-accumulation of proteins associated with water deprivation and oxidative stress, along with abscisic acid biosynthesis. Ethylene, jasmonic acid, phenylpropanoid, and flavonoid biosynthesis pathways were activated. Structurally, we observed the accumulation of lignin and a reduction in cuticular thickness, which coincides with the reduction in the levels of long-chain acyl-coenzyme A synthetase and a marginal increase in 10,16-dihydroxyhexadecanoic acid. Our study sheds light on the association of proteome modulation with the structural features of Hass avocado. Its detailed characterization will provide an alternative for better preservation during the postharvest period.

Muscle tissue is one of the most dynamic and plastic tissues of the mammalian body and covers different roles, such as force generation and metabolic control. Muscular proteomics provides an important opportunity to reveal the molecular mechanisms behind muscle pathophysiology. To ensure successful proteomic analysis, it is necessary to have an efficient and reproducible protein extraction method. This study aimed to evaluate the efficacy of two different extraction protocols of muscle samples for two-dimensional gel electrophoresis. In particular, mouse muscle proteins were extracted by an SDS-based buffer (Method A) and by a UREA/CHAPS/DTE/TRIS solution (Method B). The efficacies of the methods were assessed by performing an image analysis of the 2DE gels and by statistical and multivariate analyses. The 2DE gels in both preparations showed good resolution and good spot overlapping. Methods A and B produced 2DE gels with different means of total spots, higher for B. Image analysis showed different patterns of protein abundance between the protocols. The results showed that the two methods extract and solubilize proteins with different chemical-physical characteristics and different cellular localizations. These results attest the efficacy and reproducibility of both protein extraction methods, which can be parallelly applied for comprehensive proteomic profiling of muscle tissue.

Despite the advances in modern cancer therapy, malignant diseases are still a leading cause of morbidity and mortality worldwide. Conventional treatment methods frequently lead to side effects and drug resistance in patients, highlighting the need for novel therapeutic approaches. Recent findings have identified the existence of non-canonical micropeptides, an additional layer of the proteome complexity, also called the microproteome. These small peptides are a promising class of therapeutic agents with the potential to address the limitations of current cancer treatments. The microproteome is encoded by regions of the genome historically annotated as non-coding, and its existence has been revealed thanks to recent advances in proteomic and bioinformatic technology, which dramatically improved the understanding of proteome complexity. Micropeptides have been shown to be biologically active in several cancer types, indicating their therapeutic role. Furthermore, they are characterized by low toxicity and high target specificity, demonstrating their potential for the development of better tolerated drugs. In this review, we survey the current landscape of known micropeptides with a role in cancer progression or treatment, discuss their potential as anticancer agents, and describe the methodological challenges facing the proteome field of research.

High-throughput omics technologies have dramatically changed biological research, providing unprecedented insights into the complexity of living systems. This review presents a comprehensive examination of the current landscape of high-throughput omics pipelines, covering key technologies, data integration techniques and their diverse applications. It looks at advances in next-generation sequencing, mass spectrometry and microarray platforms and highlights their contribution to data volume and precision. In addition, this review looks at the critical role of bioinformatics tools and statistical methods in managing the large datasets generated by these technologies. By integrating multi-omics data, researchers can gain a holistic understanding of biological systems, leading to the identification of new biomarkers and therapeutic targets, particularly in complex diseases such as cancer. The review also looks at the integration of omics data into electronic health records (EHRs) and the potential for cloud computing and big data analytics to improve data storage, analysis and sharing. Despite significant advances, there are still challenges such as data complexity, technical limitations and ethical issues. Future directions include the development of more sophisticated computational tools and the application of advanced machine learning techniques, which are critical for addressing the complexity and heterogeneity of omics datasets. This review aims to serve as a valuable resource for researchers and practitioners, highlighting the transformative potential of high-throughput omics technologies in advancing personalized medicine and improving clinical outcomes.