Protein-protein Interaction Analysis Research Articles

Identification of Circulating Proteins Associated With Blood Pressure.

Circulating proteins in blood are involved in various physiological processes, but their contributions to blood pressure regulation remain partially understood. In traditional observational studies, identifying circulating proteins causally associated with blood pressure is challenging because of potentially unmeasured confounding and possible reverse causality. Two-sample Mendelian randomization analyses were conducted to estimate the causal effects of 2270 circulating proteins (data sourced from 8 genome-wide association studies) on diastolic blood pressure, systolic blood pressure, and pulse pressure. Colocalization analyses were then used to investigate whether the circulating proteins and blood pressure traits shared causal genetic variants. To further verify the findings, we subsequently performed Steiger filtering analyses, annotation of protein-altering variants, assessment of overlap between protein quantitative trait loci and expression quantitative trait loci, protein-protein interaction and functional enrichment analyses, and drug target evaluation. To provide more potential biomarkers, we further evaluated the epidemiological associations of 2923 circulating proteins with blood pressure and hypertension by cross-sectional and longitudinal analyses using individual data in the UK Biobank. Mendelian randomization and colocalization analyses identified 121 circulating proteins with putative causal effects on at least 1 blood pressure trait. Many of the identified proteins are enriched in the pathways relevant to blood pressure regulation, and a majority of these proteins are either known drug targets or druggable candidates. This study has uncovered numerous circulating proteins potentially causally associated with blood pressure, providing insights into the regulatory mechanisms of blood pressure and potential therapeutic targets to facilitate blood pressure management.

Network Pharmacology Studies on the Molecular Mechanism of Hashimoto's Thyroiditis Treated with Shutiao Qiji Decoction.

In recent years, the number of patients with Hashimoto's thyroiditis has been increasing, and traditional Chinese medicine ingredients and combinations have been applied to treat Hashimoto's thyroiditis to increase efficacy and reduce side effects during the treatment process. Shutiao Qiji Decoction is one of the Chinese traditional medicine prescriptions, which is commonly used to treat cancer, tumor, etc. It is also used for thyroid-related diseases in the clinic. Hashimoto's thyroiditis is an autoimmune disease. In this study, the mechanism of Shutiao Qiji Decoction in treating Hashimoto's thyroiditis was studied through network pharmacology and molecular docking verification. Each Chinese medicine ingredient of Shutiao Qiji Decoction was retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. The related genes of HT were searched from the UniProt and GeneCards databases. Meanwhile, we used Cytoscape to construct the protein-protein interaction (PPI) visual network analysis, and used the search tool to search the database of Interacting Genes (STRING) to build a PPI network. These key proteins were enriched and analyzed by molecular docking validation, Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Hashimoto's thyroiditis disease model was established in SD rats, and SQD was administered by gavage after the successful establishment of the model. After 6 weeks of continuous administration of the drug by gavage, tissue samples were collected and the thyroid and spleen tissues were visualized by HE staining to verify the therapeutic effect. The results showed that there were 287 TCM active ingredients, 1920 HT-related disease targets, and 176 drug and disease targets in SQD. Through PPI analysis, GP analysis, and KEGG analysis of the common targets of drugs and diseases, we found their pathways of action to be mainly cancer action pathway, PI3K-AKT signaling pathway, and T-cell action pathway. The active ingredients of the drugs in SQD, malvidin, stigmasterol, porin-5-en-3bta-ol, and chrysanthemum stigmasterol, were docked with the related target proteins, MAPK, GSK3β, TSHR, and NOTCH molecules. The best binding energies obtained from docking were mairin with TSHR, stigmasterol with TSHR, poriferast-5-en-3beta-ol with MAPK, and chryseriol with GSK3β, with binding energies of -6.84 kcal/mol, -6.53 kcal/mol, -5.03 kcal/mol, and -5.05 kcal/mol, respectively. HE staining sections of rat thyroid and spleen tissues showed that SQD had a therapeutic effect on Hashimoto's thyroiditis and restored its immune function. It is verified by molecular docking results that Shutiao Qiji Decoction has a potential therapeutic effect on Hashimoto's thyroiditis in the MAPK/TSHR/NOTCH signal pathway, and that the main components, mairin, stigmasterol, poriferast-5-en-3beta-ol, and chryseriol play a role in it. SQD has been shown to have a good therapeutic effect on Hashimoto's thyroiditis.

RXRα/MR signaling promotes diabetic kidney disease by facilitating renal tubular epithelial cells senescence and metabolic reprogramming

Cell senescence and metabolic reprogramming are significant features of diabetic kidney disease (DKD). However, the underlying mechanisms between cell senescence and metabolic reprogramming are poorly defined. Here, we report that retinoid X receptor α (RXRα), a key nuclear receptor transcription factor, regulates cell senescence and metabolic reprogramming in DKD. Through high-throughput sequencing, bioinformatic analysis and experimental validation, we confirmed the critical role of RXRα in promoting cell senescence and metabolic dysregulation in renal tubular epithelial cells (RTECs) induced by lipid overload. In vivo, in situ injection of AAV9-shRxra into the kidney reduced proteinuria, RTECs senescence and insulin resistance in DKD mice. In vitro, knockdown of RXRα markedly improved G2/M phase arrest and suppressed the expression of senescence-associated secretory phenotypes (SASPs). Protein-protein interaction (PPI) analysis and unbiased bioinformatics were employed to identify the direct interactions between RXRα and the mineralocorticoid receptor (MR), which were subsequently validated through coimmunoprecipitation. Gene network analysis revealed the collaborative regulatory role of RXRα and MR in RTECs senescence. In an accelerated aging mouse model, treatment with a MR antagonist has been shown to inhibite the RXRα/MR signaling, improve RTECs senescence, and reduce interstitial fibrosis and lipid deposition in the kidneys. These findings indicate that inhibition of RXRα/MR signaling could alleviate cell senescence during metabolic disorders. Thus, our study revealed that RXRα/MR signaling serves as a critical regulatory factor mediating the crosstalk between cell senescence and metabolic reprogramming, shedding light on a novel mechanism for targeting cell senescence and metabolic dysregulation in DKD.

Identification of biological pathways and putative candidate genes for residual feed intake in a tropically adapted beef cattle breed by plasma proteome analysis

This study identified potential biomarkers for feed efficiency by blood plasma proteome analysis of a tropically adapted beef cattle breed. Two experimental groups were selected based on residual feed intake (RFI). The proteome was investigated by LC-MS/MS in a data-dependent acquisition mode. After quality control, 123 differentially abundant proteins (DAPs) were identified between the two experimental groups. Among DAPs with the highest absolute log-fold change values, the PRDM2, KRT5, UGGT1, DENND5B, B2M, SLC44A2, SLC7A2, PTPRC, and FETUB were highlighted as potential biomarkers because of their functions that may contribute to RFI. Furthermore, functional enrichment analysis revealed several biological processes, molecular functions and pathways that contributes to RFI, such as cell signaling, cellular responses to stimuli, immune system, calcium, hormones, metabolism and functions of proteins, lipids and carbohydrates. Protein-protein interaction analysis identified 32 and 11 DAPs as important nodes based on their interactions in the high- and low-RFI groups, respectively. This study represents the first comprehensive profiling of the blood plasma proteome of a tropically adapted beef cattle breed and provides valuable insights into the potential roles of these DAPs in key biological processes and pathways, contributing to our understanding of the mechanisms underlying feed efficiency in tropically adapted beef cattle. SignificanceLC-MS/MS analysis was performed to investigate changes in the blood plasma proteome associated with residual feed intake (RFI) in a tropically adapted beef cattle breed (Bos taurus taurus). Some putative biomarkers were identified to distinguish the high-RFI to low-RFI animals, based on their log-fold change value or on their protein-protein interaction network, which provide helpful sources in developing novel selection strategies for breeding programs. Our findings also revealed valuable insights into the metabolic pathways and biological processes that contribute to RFI in beef cattle, such as those closely linked to cell signaling, cellular responses to stimuli, immune system, calcium, hormones, metabolism and functions of proteins, lipids and carbohydrates.

The Therapeutic Mechanisms of Shenyan Oral Liquid I Against Chronic Kidney Disease Based on Network Pharmacology and Experimental Validation.

Chronic Kidney Disease (CKD) leads to structural and functional abnormalities of the kidneys and seriously jeopardizes human health. Shenyan Oral Liquid (SOLI), a Chinese medicinal preparation, has been reported to protect podocytes in patients with chronic kidney disease (CKD). The objective of this study is to investigate the mechanism of action of the Chinese medicinal preparation Senyan Oral Liquid (SOLI) in the treatment of CKD by protecting podocytes through network pharmacology technology and experimental validation. Compounds of SOLI and targets of CKD disease were collected and screened. The SOLI network of bioactive compounds targeting CKD and the protein-protein interaction (PPI) network were constructed using Cytoscape software and the STRING online database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the R software Cluster Profiler package. Molecular docking was performed using Autodock software to verify the binding ability of bioactive compounds and target genes. Subsequently, the potential mechanism of SOLI on CKD predicted by network pharmacological analysis was experimentally studied and verified in an adriamycin-induced nephropathy rat model. A total of 81 targets of SOLI components acting on CKD were identified. The results of the PPI analysis clarified that five key target genes (TNF, AKT1, IL6, VEGFA, and TP53) play a critical role in the treatment of CKD by SOLI. The GO analysis and KEGG enrichment analysis indicated that SOLI acts through multiple pathways, including the PI3K/AKT signaling pathway against CKD. Molecular docking showed that the main compounds of SOLI and five key genes had strong binding affinity. In a rat model of adriamycin-induced nephropathy, SOLI significantly ameliorated disease symptoms and improved renal histopathology. Mechanistic studies showed that SOLI upregulated the expression level of Nephrin, inhibited the PI3K/AKT pathway in renal tissues, and ultimately suppressed the activation of autophagy-related proteins in CKD. SOLI exerted a renoprotective effect by regulating the Nephrin-PI3K/AKT autophagy signaling pathway, and these findings provide new ideas for the development of SOLI-based therapeutic approaches for CKD.

Proteomic analysis illustrates the potential involvement of dysregulated ribosome-related pathways and disrupted metabolism during retinoic acid-induced cleft palate development

Recent studies have unveiled disrupted metabolism in the progression of cleft palate (CP), a congenital anomaly characterized by defective fusion of facial structures. Nonetheless, the precise composition of this disrupted metabolism remains elusive, prompting us to identify these components and elucidate primary metabolic irregularities contributing to CP pathogenesis. We established a murine CP model by retinoic acid (RA) treatment and analyzed control and RA-treated embryonic palatal tissues by LC-MS-based proteomic approach. We identified 220 significantly upregulated and 224 significantly downregulated proteins. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that these differentially expressed proteins (DEPs) were involved in translation, ribosome assembly, mitochondrial function, mRNA binding, as well as key metabolic pathways like oxidative phosphorylation (OXPHOS), glycolysis/gluconeogenesis, and amino acid biosynthesis. These findings suggest that dysregulated ribosome-related pathways and disrupted metabolism play a critical role in CP development. Protein-protein interaction analysis using the STRING database revealed a tightly connected network of DEPs. Furthermore, we identified the top 10 hub proteins in CP using the Cytohubba plugin in Cytoscape. These hub proteins, including RPL8, RPS11, ALB, PA2G4, RPL23, RPS6, CCT7, EGFR, HSPD1, and RPS28, are potentially key regulators of CP pathogenesis. In conclusion, our comprehensive proteomic analysis provides insights into the molecular alterations associated with RA-induced CP in Kun Ming mice. These findings suggest potential therapeutic targets and pathways to understand and prevent congenital craniofacial anomalies.

CRHBP, a novel multiple cancer biomarker connected with better prognosis and anti-tumorigenicity

BackgroundThe corticotropin-releasing hormone-binding protein (CRHBP) plays a crucial role in regulating corticotropin release. Little is known about the role of CRHBP, a major regulator of neuroendocrine, autonomic, and stress adaptation, in tumors. In this study, we aimed to investigate the clinical and molecular landscapes of CRHBP in various types of tumors.MethodsWe investigated the role of CRHBP in different types of tumors using publicly available databases and performed a comparative expression analysis of CRHBP-related genes in pan-cancer prognosis using methylation profiling, tumor-infiltrating immune cell expression analysis, gene enrichment analysis, and protein-protein interaction analysis, identified common pathways, and in vitro evaluation.ResultsWe evaluated CRHBP expression across tumor and corresponding normal tissues using the data from The Cancer Genome Atlas and the Genotype-Tissue Expression database. CRHBP was downregulated in most tumors and was identified as an important factor for predicting the prognosis of patients with cancer. Intracellular metabolic pathways and hormone-related processes were involved in the functional mechanisms of CRHBP. Mechanistically, the downregulation of CRHBP was attributed to the upregulation of four miRNAs in most tumors, and CRHBP expression was related to tumor-infiltrating immune cells in tumors. Overexpression of CRHBP significantly inhibited cell proliferation of LUAD, LIHC, and KIRC cell lines, while inhibition of cell mobility was found only in KIRC and HCC cells.ConclusionsThis study provides a comprehensive summary of the systemic role of CRHBP expression in various types of tumors, highlighting the prognostic importance and clinical significance of tumors. Furthermore, CRHBP decreases cell proliferation and mobility in cancer cell lines associated with OS and DFS, further research is needed to understand the underlying mechanisms and explore clinical applications.

Unveiling the role of melatonin-related gene CSNK1D in osteoclastogenesis and its implications for osteoporosis treatment.

Osteoporosis (OP) is a prevalent bone disease characterized by reduced bone density and quality, increasing fragility and fracture risk. Osteoclast (OC) activity and circadian rhythm play a role in the pathogenesis of OP. Melatonin is a circadian regulator that affects bone metabolism, but its molecular mechanism has not been studied in detail. This study aimed to identify the relationship between melatonin-related genes and OP through bioinformatics methods and to verify it experimentally.We analysed microarray data from the GSE35959 dataset, identifying differentially expressed genes in OP patients. Circadian rhythm-related genes and melatonin-related genes intersect with these differentially expressed genes, highlighting that CSNK1D is a central gene. Functional enrichment, correlation and protein-protein interaction analyses were conducted. Experimental validation involved in vitro differentiation assays using RAW264.7 cells and in vivo studies with an ovariectomy-induced rat model of OP to evaluate the role of CSNK1D in osteoclastogenesis to verify its effect on OP. Differential expression analysis revealed 272 significant genes, with CSNK1D identified as central to the circadian rhythm and to melatonin and OP interplay. Functional analyses showed involvement of CSNK1D in OC differentiation and inflammatory pathways. in vitro experiments confirmed CSNK1D upregulation during OC differentiation, and small interfering RNA-mediated knockdown reduced OC marker expression and TRAP+ cell formation. in vivo, CSNK1D expression is associated with bone loss in OP rats. Melatonin-related CSNK1D promotes OC differentiation and promotes the development of OP. These findings suggest CSNK1D as a potential therapeutic target for OP, offering insights into new treatment strategies integrating circadian rhythm regulation.

SKA1/2/3 is a prognostic and predictive biomarker in esophageal adenocarcinoma and squamous cell carcinoma

BackgroundEsophageal carcinoma (ESCA) ranks among the most prevalent malignant tumors globally. Despite significant advancements in treatment options and improved patient outcomes, the 5-year survival rate remains unsatisfactory. The spindle and kinetochore associated complex subunit 1/2/3 (SKA1/2/3) attached to the kinetochore (KT) in the metaphase of mitosis are implicated in the occurrence and development of various tumors. However, the expression patterns, diagnostic significance and prognostic implications of SKA1/2/3 in ESCA have not been comprehensively determined.MethodsTCGA, UALCAN, Kaplan-Meier Plotter, and TIMER databases were leveraged to dissect the expression patterns, prognostic implications and diagnostic value of SKA1/2/3 in ESCA patients, as well as to investigate the potential regulatory mechanism of SKA1/2/3 in the onset and progression of ESCA.ResultsIn ESCA, SKA1/2/3 exhibited substantial expression, with higher levels relating significantly with clinicopathological features and patient prognosis. Enrichment analysis of genes co-expressed with SKA1/2/3 highlighted their involvement in the cell cycle, DNA replication and p53 signaling pathway. Protein-protein interaction (PPI) analysis identified ten hub genes that were not only markedly upregulated but also portended a poor prognosis in ESCA. Additionally, immune infiltration assays uncovered a significant link between SKA1/2/3 expression and the immune cell infiltration within ESCA. Silencing of SKA1/2/3 significantly suppresses cell proliferation and migration, while concurrently promoting apoptosis in ESCA cells.ConclusionsSKA1/2/3 may serve as promising biomarkers for the prognosis and diagnosis of ESCA, which holds promise as a novel therapeutic target for the disease.

Mechanism of atorvastatin in treating hepatocellular carcinoma: a study based on network pharmacology, molecular docking, and bioinformatics analysis.

Hepatocellular carcinoma (HCC) is a tumor with high morbidity and mortality. Current research suggests that statins may aid in its prevention and treatment, while studies on the associated mechanisms remain limited. Therefore, we aim to reveal the mechanism of atorvastatin treatment for HCC by using network pharmacology and bioinformatics methods. The databases SwissTargetPrediction, PharmMapper, and DrugBank were utilized to obtain targets of atorvastatin, while GSE169289, GSE135631, and GSE207435 were used to identify differentially expressed genes (DEGs) for HCC. The overlap between the two groups was used to identify atorvastatin's target for treating HCC. Following protein-protein interaction (PPI) analysis, hub genes were identified using Cytoscape software and LASSO analysis. The hub genes were further validated using data from The Cancer Genome Atlas (TCGA) and The Human Protein Atlas (HPA) databases. To evaluate the clinical significance of the hub genes, Kaplan-Meier (KM) survival analysis and Cox analysis were conducted. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were performed to investigate potential mechanisms. Finally, molecular docking analysis was performed to validate the interaction between atorvastatin and the hub genes. A total of 1948 DEGs of HCC and 380 targets of atorvastatin were identified, respectively. After taking the intersection, 79 genes were identified as potential targets of atorvastatin for HCC treatment. After multiple screening methods, CYP2C9 was ultimately identified as the hub gene. Analysis of data from TCGA and HPA databases showed reduced expression of CYP2C9 in HCC tissues. KM and Cox analysis showed a favorable prognosis for HCC patients with high CYP2C9 expression. KEGG and GSEA indicated that metabolism of xenobiotics by cytochrome P450, and PPAR signaling pathway could be the potential mechanisms for atorvastatin in treating HCC. Molecular docking analysis revealed that atorvastatin binds to CYP2C9 with a binding energy of - 8.837, indicating highly stable binding. CYP2C9 is associated with the prognosis of HCC patients and could serve as a potential target for atorvastatin treatment in HCC.

Genome-Wide Analysis in the Study of the Fetal Growth Restriction Pathogenetics

Fetal growth restriction is a complication of pregnancy that defined as the inability of the fetus to realize its genetically determined growth potential. Despite the high social and medical significance of this problem the exact pathogenesis of fetal growth restriction is not known by now. Therefore, the analysis of the molecular genetics mechanisms of this pathology within the framework of approaches using modern high-performance technologies of next generation sequencing is of undoubted interest. In this review we focused on the analysis of data obtained in studies of the fetal growth restriction genetics component. The authors of these researches used next generation sequencing technologies and carried out whole transcriptome profiling. The results of the genes expression genome-wide analysis in placental tissue allow us to identify 1430 differentially expressed genes between fetal growth restriction and normal pregnancy, of which only 1% were found in at least two studies. These differentially expressed genes are involved in the Wnt/β-catenin signaling pathway that plays an important role in cell migration, neural pattern formation and organogenesis during embryonic development. Common genes are associated with both obstetric and gynecological diseases, as well as with various somatic conditions from the groups of neurodegenerative, cardiovascular diseases and mental disorders, which probably reflects their involvement in the development of postnatal consequences of fetal growth restriction. The results of our work don‘t point only to potential molecular mechanisms and key genes underlying fetal growth restriction, but also indicate the important role of gene-gene communications in this pathology implementation: about 30% of all identified differentially expressed genes products interact with each other within the same gene network. In general, genome-wide RNA sequencing combined with the analysis of protein-protein interactions represents a promising direction in research on the development and functioning of the placenta, as well as the identification of placental insufficiency diseases genetics mechanisms, including fetal growth restriction.

Deciphering the prognostic landscape of triple-negative breast cancer: A focus on immune-related hub genes and therapeutic implications.

Triple-negative breast cancer (TNBC), known for its hostile nature and limited treatment modalities, has spurred researchers to explore novel approaches for enhancing clinical outcomes. Here, the study aimed to analyze transcriptomics data to identify immune-related hub genes associated with TNBC that might serve as prognostic biomarkers. Initially, we determined genes that were differentially expressed between TNBC and normal tissues by integrating microarray and RNA sequencing data. Then, through protein-protein interaction and module analysis, we identified five putative hub genes: AURKA, CCNB1, CDCA8, GAPDH, and TOP2A. Subsequently, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that the hub genes were primarily involved in the progesterone-mediated oocyte maturation signaling pathway and oocyte meiosis. Additionally, we observed that these five hub genes were significantly elevated at both protein and mRNA levels in TNBC tissues and contributed to worse survival. Furthermore, the expression of these hub genes exhibited a strong positive association with immune-invading cells such as CD8 T cells, CD4 T cells, and dendritic cells. The analysis of the regulatory network revealed three transcription factors (YBX-1, E2F1, and E2F3) and three posttranscriptional regulators (hsa-mir-25-3p, hsa-mir-92a-3p, and hsa-let-7b-5p) of hub genes. Finally, we explored potential drug candidates for the hub genes using Drug-Gene Interaction Database and discovered that there are no FDA-approved drugs for CCNB1 and CDCA8, highlighting a promising area for future research. Taken together, our results will be of immense importance in addressing the intricacies of TNBC.

Pharmacoproteomics reveals energy metabolism pathways as therapeutic targets of ivermectin in ovarian cancer toward 3P medical approaches.

Ovarian cancer is the malignant tumor with the highest mortality rate in the female reproductive system, enormous socio-economic burden, and limited effective drug therapy. There is an urgent need to find novel effective drugs for ovarian cancer therapy. Our previous in vitro studies demonstrate that ivermectin effectively inhibits ovarian cancer cells and affects energy metabolism pathways. This study aims to clarify in vivo mechanisms and therapeutic targets of ivermectin in the treatment of ovarian cancer to establish predictive biomarkers, guide personalized treatments, and improve preventive strategies in the framework of 3P medicine. A TOV-21G tumor-bearing mouse model was constructed based on histopathological data and biochemical parameters. TMT-based proteomic analysis was performed on tumor tissues from the different treatment groups. All significantly differentially abundant proteins were characterized by hierarchical clustering, Gene Ontology (GO) enrichment analyses, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In addition, the data were integrated and analyzed with the proteomic data of clinical ovarian cancer tissues from our previous study and the proteomic data of ivermectin intervention in ovarian cancer cells to identify key regulators of ivermectin. Ivermectin (10mg/kg) had a significant anti-ovarian cancer effect in mice, with a tumor inhibitory rate of 61.5%. Molecular changes in tumor tissue of ivermectin-treated mice were established, and protein-protein interaction (PPI) analysis showed that the main differential pathway networks included the TCA cycle, propanoate metabolism, 2-0xocarboxyacid metabolism, and other pathways. Integrating our previous clinical ovarian cancer tissue and cell experimental data, this study found that ivermectin significantly interfered with the energy metabolic pathways of ovarian cancer, including glycolysis, TCA cycle, oxidative phosphorylation, and other related pathways. This study evaluated the anti-ovarian cancer effect in vitro and in vivo, and its specific regulatory effect on energy metabolism. The expressions of drug target molecules in the energy metabolism pathway of ovarian cancer will be used to guide the diagnosis and prevention of ovarian cancer. The significant efficacy of ivermectin will be applied to the treatment of ovarian cancer and personalized medication. This has guiding significance for the clinical diagnosis, treatment, personalized medication, and prognosis evaluation of ovarian cancer. The online version contains supplementary material available at 10.1007/s13167-024-00385-1.

ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics.

Mass spectrometry (MS) is a technique widely employed for the identification and characterization of proteins, with personalized medicine, systems biology, and biomedical applications. The application of MS-based proteomics advances our understanding of protein function, cellular signaling, and complex biological systems. MS data analysis is a critical process that includes identifying and quantifying proteins and peptides and then exploring their biological functions in downstream analysis. To address the complexities associated with MS data analysis, we developed ProtPipe to streamline and automate the processing and analysis of high-throughput proteomics and peptidomics datasets with DIA-NN preinstalled. The pipeline facilitates data quality control, sample filtering, and normalization, ensuring robust and reliable downstream analyses. ProtPipe provides downstream analyses, including protein and peptide differential abundance identification, pathway enrichment analysis, protein-protein interaction analysis, and Major histocompatibility complex (MHC) -peptide binding affinity analysis. ProtPipe generates annotated tables and visualizations by performing statistical postprocessing and calculating fold changes between predefined pairwise conditions in an experimental design. It is an open-source, well-documented tool available online at https://github.com/NIH-CARD/ProtPipe, with a user-friendly web interface.

Transcriptome combined with Mendelian randomization to screen key genes associated with mitochondrial and programmed cell death causally associated with diabetic retinopathy.

Mitochondrial dysfunction in the retina can induce apoptosis of retinal capillary cells, leading to diabetic retinopathy (DR). This study aimed to explore key genes related to programmed cell death (PCD) and mitochondria in DR via bioinformatic analysis. A differential analysis was performed to identify differentially expressed genes (DEGs) between DR and control samples using the GSE94019 dataset from the Gene Expression Omnibus (GEO) database. Pearson correlation analysis was then utilized to select genes linked to mitochondrial function and PCD (M-PCD). Candidate genes were identified by overlapping DR-DEGs and M-PCD genes, followed by functional annotation. Mendelian randomization (MR) analysis was employed to identify genes with causal relationships to DR. Key genes were identified through protein-protein interaction (PPI) analysis using six algorithms (DEgree, DMNC, EPC, MCC, Genes are BottleNeck, and MNC) within Cytoscape software. The expression patterns of these genes were validated using GSE94019 and GSE60436 datasets, as well as RT-qPCR. Enrichment analysis provided insights into the function and pathways of these key genes in DR. Differential immune cell profiles were determined via immune infiltration analysis, followed by exploring the relationships between immune cells, cytokines, and the identified genes. Correlations between key genes and apoptosis genes were also examined. In vivo experiments using RT-PCR, immunohistochemistry (IHC), and western blot analysis confirmed that MYC and SLC7A11 expression was significantly elevated in DR rat retinal tissues. From 658 candidate genes, 12 showed significant causal associations with DR. MYC and SLC7A11 were particularly notable, showing upregulated expression in DR samples and involvement in apoptosis and diabetes-related pathways. These genes were significantly associated with apoptotic genes and correlated positively with altered immune cell types and cytokines, suggesting a link between immune response and DR pathogenesis. In vivo findings confirmed that MYC and SLC7A11 expression was elevated in DR rat retinal tissues. Key genes (MYC and SLC7A11) associated with mitochondrial function and PCD in DR were identified, offering insights into DR's pathological mechanisms and potential targets for diagnostic and therapeutic strategies.

Differentially Expressed Genes and Alternative Splicing Analysis Revealed the Difference in Virulence to American Eels (Anguilla rostrata) Infected by Edwardsiella anguillarum and Aeromonas hydrophila.

Edwardsiella anguillarum and Aeromonas hydrophila are two common bacterial pathogens affecting cultivated eels, and the differences in their virulence remain unclear. In this study, after two groups of American eels (Anguilla rostrata) were administered the LD50 dose of E. anguillarum and A. hydrophila, respectively, the histopathology of the liver, trunk kidney, and spleen, as well as transcriptomic RNA sequencing (RNA-seq) analysis of the spleen, was examined at three time points: pre-infection (Con group) and post-infection at 36h (Ea_36 group, Ah_36 group) and 60h (Ea_60 group, Ah_60 group). The results showed that the differences in pathological changes were characterized by severe hepatocyte edema at 36h post-infection (hpi) and hepatocyte atrophy at 60 hpi in the livers of eels infected by A. hydrophila, in contrast to the severe atrophy of glomeruli in the trunk kidneys and numerous bacterial nodules in the spleens of eels infected by E. anguillarum. The RNA-seq results revealed 906 and 77 typical differentially expressed genes (DEGs) in eels infected with E. anguillarum and A. hydrophila, respectively, compared to the control eels. The DEGs between the infected and control groups were predominantly annotated in GO terms related to binding, catalytic activity, membrane part, cell part, and cellular process, as well as in KEGG pathways associated with human diseases and organismal systems. The GO enrichment analysis showed 83 and 146 differential GO terms, along with 32 and 78 differential KEGG pathways in two comparisons of Ea_36 vs Con versus Ah_36 vs Con and Ea_60 vs Con versus Ah_60 vs Con, respectively. Furthermore, the analysis of differential alternative splicing genes (DASs) showed 1244 and 1341 DASs out of 12,907 and 12,833 AS genes, respectively, in the comparisons of Ea_36 vs Ah_36 and Ea_60 vs Ah_60. These DASs were enriched in two common KEGG pathways: "NOD-like receptor signaling pathway" and "necroptosis" which shared 11 hub DASs. Finally, analysis of protein-protein interactions revealed that 91 of 412 cross DASs between Ea_36 vs Ah_36 and Ea_60 vs Ah_60 potentially play an essential role in the difference in virulence of E. anguillarum and A. hydrophila in American eels, with 12 encoded proteins being particularly notable. Together, this study is the first to report a comparative pathogenicity and RNA-seq analysis of E. anguillarum and A. hydrophila in American eels, shedding new light on our understanding of the differences in virulence as revealed by pathological changes, DEGs, and DASs, contributing to more effective control strategies to prevent outbreaks of bacterial infections.

Exploring the Antiviral Potential of Artemisia annua Through JAK-STAT Pathway Targeting: A Network Pharmacology Approach.

Artemisia annua, a plant with antiviral potential, has shown promise against various viral infections, yet its mechanisms of action are not fully understood. This study explores A. annua's antiviral effects using network pharmacology and molecular docking, focusing on key active compounds and their interactions with viral protein targets, particularly within the JAK-STAT signaling pathway-a critical mediator of immune responses to viral infections. From the TCMSP database, we identified eight active compounds and 335 drug targets for A. annua, with 19 intersecting targets between A. annua compounds and viral proteins. A protein-protein interaction (PPI) network highlighted 10 key hub genes, analyzed further through Gene Ontology (GO) and KEGG pathways to understand their immune and antiviral roles. ADMET properties of the active compound Patuletin (MOL004112) were assessed, followed by 200 ns molecular dynamics simulations to examine its stability in complex with JAK2. PPI analysis identified JAK2, MAPK3, MAPK1, JAK1, PTPN1, HSPA8, TYK2, RAF1, MAPT, and HMOX1 as key hub genes, with JAK2 emerging as a critical regulator of immune and antiviral pathways. ADMET analysis confirmed Patuletin's favorable pharmacokinetic properties, and molecular dynamics simulations showed a stable Patuletin-JAK2 complex, with FEL analysis indicating minimal disruption to JAK2's intrinsic flexibility. These findings highlight JAK2 as a promising target in the antiviral activity of A. annua compounds, particularly Patuletin, supporting its potential as an antiviral agent and providing a foundation for further research on A. annua's therapeutic applications.

HC-HA/PTX3 from Human Amniotic Membrane Induced Differential Gene Expressions in DRG Neurons: Insights into the Modulation of Pain.

Background: The biologics derived from human amniotic membranes (AMs) demonstrate potential pain-inhibitory effects in clinical settings. However, the molecular basis underlying this therapeutic effect remains elusive. HC-HA/PTX3 is a unique water-soluble regenerative matrix that is purified from human AMs. We examined whether HC-HA/PTX3 can modulate the gene networks and transcriptional signatures in the dorsal root ganglia (DRG) neurons transmitting peripheral sensory inputs to the spinal cord. Methods: We conducted bulk RNA-sequencing (RNA-seq) of mouse DRG neurons after treating them with HC-HA/PTX3 (15 µg/mL) for 10 min and 24 h in culture. Differential gene expression analysis was performed using the limma package, and Gene Ontology (GO) and protein-protein interaction (PPI) analyses were conducted to identify the networks of pain-related genes. Western blotting and in vitro calcium imaging were used to examine the protein levels and signaling of pro-opiomelanocortin (POMC) in DRG neurons. Results: Compared to the vehicle-treated group, 24 h treatment with HC-HA/PTX3 induced 2047 differentially expressed genes (DEGs), which were centered on the ATPase activity, receptor-ligand activity, and extracellular matrix pathways. Importantly, PPI analysis revealed that over 50 of these DEGs are closely related to pain and analgesia. Notably, HC-HA/PTX3 increased the expression and signaling pathway of POMC, which may affect opioid analgesia. Conclusions: HC-HA/PTX3 induced profound changes in the gene expression in DRG neurons, centered around various neurochemical mechanisms associated with pain modulation. Our findings suggest that HC-HA/PTX3 may be an important biological active component in human AMs that partly underlies its pain inhibitory effect, presenting a new strategy for pain treatment.

Exploring microbial diversity and functionality in Verdejo wine vinegar fermentation through LC-MS/MS analysis

The identification of microorganisms in vinegar production remains a challenge mainly, due to the difficulty of isolating and characterizing the microbiota involved. This implies that despite progress in understanding the composition and role of these microbial communities, there are still virtually unknown microorganisms in these environments. Metaproteomics reveals microbial diversity and behavior by analysis of proteins, offering precise insights into key moments and conditions in biological processes like acetification. This study consists of a thorough metaproteomic analysis during the elaboration of an innovative vinegar, Verdejo wine vinegar. Acetic acid fermentation occurred by submerged culture in an 8L automated Frings reactor operated in semi-continuous mode. LC-MS/MS identified 1626 proteins from 149 taxonomic groups, mainly Acetobacteraceae (1529), followed by yeast (47), lactic acid bacteria (29), and Archaea (21). Komagataeibacter (73.7%), Acetobacter (10.7%), Gluconacetobacter (1.7%), Novacetimonas (1.6%), and Gluconobacter (1.3%) were prevalent genera, with K. europaeus being the dominant species (56.7%). To our knowledge, this is the first metaproteomic approach to comprehensively address the study of so diverse microbial populations. GO Term analysis emphasized "heterocyclic compound binding" and "organic substance metabolic process", while analysis of protein-protein interactions identified key metabolic processes, such as amino acid biosynthesis, especially BCAAs, and crucial energetic pathways such as the TCA cycle. Stress response mechanisms, such as the dnaK-dnaJ-grpE and cl2p system, have been also highlighted. These analyses revealed the molecular and functional complexity of the acetification process, highlighting the critical importance of diverse metabolic routes in the adaptation of the microbiota members to the medium conditions. Overall, this study aims to characterize the microbiota driving Verdejo wine acetification and explore its composition, functions, and key metabolic processes.

Downregulation of miR-214 promotes dilated Cardiomyopathy Progression through PDE5A-Mediated cGMP regulation

Dilated cardiomyopathy (DCM) is a myocardial disorder resulting in a substantial decline in cardiac function and potentially leading to heart failure. This research combines bioinformatics analysis with empirical validation to explore the roles and mechanisms of miR-214 in DCM. Using the DEseq2 R package, a total of 125 differentially expressed circulating miRNAs (DE c-miRNAs) and 784 DE genes (DEGs) were identified. Cross-analysis between target genes of DE c-miRNAs and DEGs identified 124 common genes, and protein-protein interaction analysis of common genes identified 11 hub genes. Twelve DE c-miRNAs were further verified by quantifying their levels in the serum of DCM patients and healthy individuals. miR-214 levels were significantly decreased in serum from DCM patients, positively correlated with left ventricular ejection fraction and left ventricular fractional shortening. Further analysis showed that miR-214 directly targets and negatively regulates phosphodiesterase 5 A (PDE5A). Elevated PDE5A expression reduced cGMP levels; however, using sildenafil, a PDE5A inhibitor, reversed this effect, substantiating the regulatory mechanism of miR-214 on cGMP via PDE5A. These results provide new potential targets for the diagnosis and treatment of DCM.