Search Tool For The Retrieval Of Interacting Genes/Proteins Research Articles

Nasal Lavage Fluid Proteomics Reveals Potential Biomarkers of Asthma Associated with Disease Control.

Little research has explored the proteomic characteristics of nasal lavage fluid from asthmatic patients. This study aims to investigate whether differentially expressed proteins (DEPs) in nasal lavage fluid can serve as a biomarker to differentiate asthma patients from healthy controls (HCs) and to discern between individuals with well controlled and poorly controlled asthma. We enrolled patients with allergic rhinitis (AR), asthma, or both conditions, and HCs in this study. We recorded patients' demographic and medical history data and administered asthma quality of life questionnaire (AQLQ) and asthma control questionnaire (ACQ). Nasal fluid samples were collected, followed by protein measurements, and proteomic analysis utilizing the data-independent acquisition (DIA) method. Twenty-four with asthma, 27 with combined asthma+ AR, 25 with AR, and 12 HCs were enrolled. Four proteins, superoxide dismutase 2 (SOD2), serpin B7 (SERPINB7), kallikrein-13 (KLK13), and bleomycin hydrolase (BLMH) were significantly upregulated in nasal lavage fluid samples of asthma without AR, compared to HCs (Fold change ≥2.0, false-discovery rate [FDR] <0.05). Conversely, 56 proteins including secretoglobin family 2A member 1 (SCGB2A1) were significantly downregulated (fold change ≥2.0, FDR <0.05). Furthermore, 96.49% of DEPs including peptidase inhibitor 3 (PI3) and C-X-C motif chemokine 17 (CXCL17) were upregulated in poorly controlled asthma patients without AR relative those with well- or partly controlled asthma (fold change ≥1.5, FDR <0.05). Search tool for the retrieval of interacting genes/proteins (STRING) analysis showed that PI3, with 18 connections, may be pivotal in asthma control. The study revealed significant alteration in the nasal lavage proteome in asthma without AR patients. Moreover, our results indicated a potential association between the expression of proteome in the upper airway and the level of asthma control. Specifically, PI3 appears to be a key role in the regulation of asthma without AR.

Identification of Critical Genes Differentiating Stable and Unstable Atherosclerotic Plaques: A Bioinformatic and Computational Analysis.

Identification of biomarkers to distinguish between stable and unstable plaque formation would be very useful to predict plaque vulnerability. We downloaded microarray profiles of gene set enrichment (GSE) accession numbers including GSE71226 and GSE20680 (group A: containing healthy vs stable plaque samples) and GSE62646 and GSE34822 (group B: containing stable vs unstable plaque samples) from Gene expression omnibus (GEO) database. Differentially expressed genes were compared in both data sets of each group. Ten and 12 key genes were screened in groups A and B, respectively. Gene Ontology (GO) enrichment was applied by the plugin "BiNGO" (Biological networks gene ontology tool) of the Cytoscape. The key genes were mostly enriched in the biological process of positive regulation of the cellular process. The protein-protein interaction and co-expression network were analyzed by the STRING (search tool for the retrieval of interacting genes/proteins) and GeneMANIA (gene multiple association network integration algorithm) plugin of Cytoscape, respectively, which showed that Epidermal growth factor (EGF), Heparin-binding EGF like growth factor (HBEGF), and Matrix metalloproteinase 9 (MMP9) were at the core of the network. Further validation of key genes using two datasets showed that Phosphodiesterase 5A (PDE5A) and Protein S (PROS1) were decreased in unstable plaques, while Suppressor of cytokine signaling (SOCS3), HBEGF, and Leukocyte immunoglobulin-like receptor B4 (LILRB4) were increased. The present study used several datasets to identify key genes associated with stable and unstable atherosclerotic plaque.

Cyclin B1: A potential prognostic and immunological biomarker in pan-cancer.

Cyclin B1 (CCNB1) encodes a regulatory protein essential for the regulation of cell mitosis, particularly in controlling the G2/M transition phase of the cell cycle. Current research has implicated CCNB1 in the progression of various types of cancer, including gastric cancer, breast cancer, and non-small cell lung cancer. In this study, we conducted a pan-cancer analysis of CCNB1 to investigate its prognostic significance and immunological aspects. Our comprehensive investigation covered a wide range of analyses, including gene expression, promoter methylation, genetic alterations, immune infiltration, immune regulators, and enrichment studies. We utilized multiple databases and tools for this purpose, such as The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) project, the Human Protein Atlas (HPA), the University of Alabama at Birmingham CANcer data analysis Portal (UALCAN), the Gene Expression Profiling Interactive Analysis (GEPIA), the DNA Methylation Interactive Visualization Database (DNMIVD), the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Sangerbox, and cBioPortal. Data analyses were executed using GraphPad Prism software, R software, and various online tools. Our findings demonstrated a significant increase in CCNB1 expression across 28 cancer types. Elevated CCNB1 expression correlated with decreased overall survival (OS) in 11 cancer types and disease-free survival (DFS) in 12 cancer types. Additionally, DNA promoter methylation levels were significantly decreased in 14 cancer types. Furthermore, the study verified a significant association between CCNB1 expression and immune infiltration, immune modulators, microsatellite instability (MSI), and tumor mutational burden (TMB). Enrichment analysis indicated that CCNB1 is involved in multiple cellular pathways. Collectively, our results suggested that CCNB1 has the potential to serve as a valuable prognostic biomarker and may be a promising target for immunotherapy in various cancer types.

Identification of key genes and molecular mechanisms of chronic urticaria based on bioinformatics.

Chronic urticaria (CU) is characterized by persistent skin hives, redness, and itching, enhanced by immune dysregulation and inflammation. Our main objective is identifying key genes and molecular mechanisms of chronic urticaria based on bioinformatics. We used the Gene Expression Omnibus (GEO) database and retrieved two GEO datasets, GSE57178 and GSE72540. The raw data were extracted, pre-processed, and analyzed using the GEO2R tool to identify the differentially expressed genes (DEGs). The samples were divided into two groups: healthy samples and CU samples. We defined cut-off values of log2 fold change ≥1 and p<.05. Analyses were performed in the Kyoto Encyclopaedia of Genes and Genomes (KEGG), theDatabasefor Annotation, Visualization and Integrated Discovery (DAVID), Metascape, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and CIBERSOFT databases. We obtained 1613 differentially expressed genes. There were 114 overlapping genes in both datasets, out of which 102 genes were up-regulated while 12 were down-regulated. The biological processes included activation of myeloid leukocytes, response to inflammations, and response to organic substances. Moreover, the KEGG pathways of CU were enriched in the Nuclear Factor-Kappa B (NF-kB) signaling pathway, Tumor Necrosis Factor (TNF) signaling pathway, and Janus kinase/signal transducers and activators of transcription (JAK-STAT) signaling pathway. We identified 27 hub genes that were implicated in the pathogenesis of CU, such as interleukin-6 (IL-6), Prostaglandin-endoperoxide synthase 2 (PTGS2), and intercellular adhesion molecule-1 (ICAM1). The complex interplay between immune responses, inflammatory pathways, cytokine networks, and specific genes enhances CU. Understanding these mechanisms paves the way for potential interventions to mitigate symptoms and improve the quality of life of CU patients.

The possibility of Polygonum cuspidatum Against Osteoarthritis Based on Network Pharmacology and Molecular Docking.

Polygonum cuspidatum（PC）, a widely used Chinese herbal medicine (CHM), plays an important role in treating various diseases including osteoarthritis (OA). Yet, the multicomponent and multitarget characteristics of PC make deciphering the pharmacological mechanisms difficult. The purpose of this study is to identify the core molecular mechanisms of PC against OA. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was used to search the active ingredients of PC. GeneCards was then screened to establish relevant databases for OA. A visual interactive network diagram of the relationship between the active ingredient, action target, and disease was built using Uniprot. Finally, we used STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) database to explain the interaction network of proteins and to further analyze the relationships between related proteins. PC was screened for nine potentially effective active compounds that can be used to treat OA: 6,8-Dihydroxy-7-methoxyxanthone, rhein, physovenine, beta-sitosterol, picralinal, quercetin, luteolin, catechin, and resveratrol. Using GeneCards database and TCMSP database, we obtained 149 OA-related genes after taken the intersection of OA and PC targets. Moreover, eight core target proteins were calculated by CytoNCA plugin, which is used for network centrality analysis. The enrichment analysis of the common target genes shared by PC and OA unraveled the main biological processes, such as responses to lipopolysaccharide, chemical stress, and reactive oxygen species. Previous research has been demonstrated that signaling pathways related to apoptosis, inflammation, and cartilage protection are involved with those core target genes we found, like TNF and PI3K-Akt signaling pathways. The outcome of the molecular docking experiments illustrates that some PC's active components, including luteolin, resveratrol, and 6,8-Dihydroxy-7-methoxyxanthone, share strong molecular docking as well as binding ability with the core common target protein. The results bring that PC similarly has the potential to treat OA. The main purpose of this study is to screen the active ingredients and most important target molecules of PC in treating OA. This was achieved using bioinformatic tools and databases to investigate molecular docking technology. The findings provide a theoretical foundation and potential new treatment plan for OA using PC.

In silico Prediction and Analysis of Autophagy Related Gene-5 Interacting Proteins and their Physicochemical Features

Autophagy related gene-5 (ATG5) acts as a marker for autophagosome formation and initiation of autophagy flux. For performing these functions, ATG5 may interacts with several proteins. Hence, this study aims to identify ATG5 interacting proteins and their regulatory features using in silico approaches. Briefly, Search Tool for the retrieval of interacting genes/proteins (STRING) database predicted thirty-four ATG5 interacting proteins.

Unraveling the Molecular Complexity of Adenoid Cystic Carcinoma (ACC): A Comprehensive Exploration of Hub Genes, Protein-Protein Interaction (PPI) Networks, microRNA (miRNA) Involvement, and Drug-Gene Interactions (DGIs).

Background Adenoid cystic carcinoma (ACC) poses clinical challenges with its unique histology and potential for perineural invasion, recurrence, and distant metastases. Recent genomic advancements have unveiled key genetic alterations in ACC, offering insights into its pathogenesis. Aim This study aims to unravel the intricate molecular landscape of ACC through a comprehensive analysis of gene expression patterns. By integrating data from multiple microarray datasets, the study explores differentially expressed genes (DEGs), their functional enrichment, protein-protein interactions (PPI), hub genes, microRNA (miRNA) involvement, transcription factors, and potential drug-gene interactions. Methods Three microarray datasets (GSE88804, GSE153002, and GSE36820) related to ACC were selected from theGene Expression Omnibus (GEO) repository. DEGs were identified using GEO2R and further analyzed for commonalities and differences. Functional enrichment analysis, including Gene Set Enrichment Analysis (GSEA), provided insights into biological processes, cellular components, molecular functions, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with ACC. PPI networks and hub genes were identified using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) (STRING Consortium, Lausanne,Switzerland) database and Cytoscape (Cytoscape Consortium, California, United States). The study also explored miRNAs, transcription factors, and potential drug-gene interactions. Results The integrated analysis revealed 339 common upregulated and 643 downregulated DEGs in ACC. Functional and pathway enrichment analyses unveiled the involvement of these genes in critical cellular processes, signaling cascades, and pathways. The PPI network, comprising 904 nodes and 4139 edges, highlighted the complexity of interactions. Hub genes, including KIF11, BUB1, and DLGAP5, were identified, shedding light on their pivotal roles in cell cycle regulation. The study also identified miRNAs (e.g., hsa-mir-7-5p and hsa-mir-138-5p) and transcription factors (e.g., E2F1 and TP53) associated with ACC. Drug-gene interactions have identified potential therapeutic options, including amsacrine and rucaparib. Conclusions The ACCgene expression highlights a nuanced molecular landscape, identifying pivotal hub genes such as KIF11 and CDK1 as potential therapeutic targets for ACC, given their roles in cell cycle progression. The dysregulation of microRNAs and transcription factors adds complexity to ACC's molecular profile. Exploration of drug-gene interactions reveals promising therapeutic strategies, involving FDA-approved drugs such as amsacrine and rucaparib, providing avenues for personalized interventions.

A comprehensive analysis of the prognostic and immunological role of ANK3 in pan-cancer.

Cancer is a common cause of death around the world. Immunotherapy plays a significant role in cancer treatment but still has limitations. The ankyrin-3 (ANK3) gene has been shown to have a variety of biological roles and has also been shown to be closely linked to individual cancers. We systematically investigated the role of ANK3 in pan-cancer, particularly in relation to immunity. We collected data from a number of databases, including the The University of ALabama at Birmingham CANcer data analysis Portal (UALCAN), tumor-immune system interactions (TISIDB), cBioPortal, Tumor Immune Estimation Resource (TIMER), Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), BioGRID, and SangerBox databases. R (version 3.6.3) was used for the statistical analysis and data visualization. The expression of ANK3 in tumors and its effects on patient prognosis, immune infiltration, neoantigens, the microenvironment, immune checkpoints (ICs), the tumor mutation burden, microsatellite instability (MSI), methylation, mismatch repair (MMR) genes, and cancer-associated fibroblasts were investigated. A gene set enrichment analysis (GSEA) was also conducted. The ANK3 gene was differentially expressed at the messenger RNA (mRNA) and protein levels in various human tumors. The prognosis of patients with different types of malignancies was correlated with the level of ANK3 expression. The immunological microenvironment was also linked to ANK3 expression, especially in colon adenocarcinoma (COAD), kidney renal clear cell carcinoma (KIRC), and liver hepatocellular carcinoma (LIHC). ANK3 was also associated with ICs, immune neoantigens, MSI, the tumor mutation load, MMR genes, and DNA methylation. Finally, we found the key pathway related to the ANK3 gene through the enrichment analysis. ANK3 could serve as a new biomarker specific to prognosis and immunotherapy in various cancers. Our findings could contribute to the development of novel strategies for treating malignancies.

Transcriptomic Analysis of Metastatic Colorectal Tumor with Low Mutational Burden

Objective: To identify potential drug targets for metastasis colorectal cancer (CRC) patients with low mutational burden by examining differences in immune-related gene expression. Methods: For this study, 623 samples were collected from The Cancer Genome Atlas (TCGA) database, comprising tumor mutational burden (TMB), RNA sequencing (RNA-Seq), and clinical data. Differential gene expression analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the identified genes were conducted using the R package. Additionally, a comparative analysis of immune infiltrating cell composition in metastatic and non-metastatic groups was performed. Hub genes, exhibiting high levels of interaction, were selected using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The Drug Gene Interaction Database (DGIdb) was then utilized to estimate drugs targeting the identified hub genes. Results: The transcriptome data of 326 colorectal cancer patients with low TMB were analyzed, comprising 58 patients with metastasis and 268 patients without metastasis. Among the differential expression in 1,111 genes for patients with metastasis compared to those without metastasis, 733 genes were upregulated, and 378 genes were downregulated. KEGG and GO enrichment analysis indicated significant differences in gene expression in CRC metastatic patients with low TMB compared to non-metastasis patients with low TMB. Enriched pathways included humoral immuneresponse, immunoglobulin production, and regulation of AMPA receptor activity. Two genes related to interleukin-12 were identified through secondary enrichment for immune-related genes. Analysis of tumor-infiltrating immune cell data revealed significant differences in memory-activated T cell CD4 and T cell CD8. Conclusions: This analysis of RNA sequencing data and immune-filtrating cell data revealed significant differences between metastatic colorectal cancer patients with low TMB and their non-metastatic counterparts. These distinctions suggest the possibility of identifying more effective drugs or therapies for metastatic colorectal cancer patients with low TMB.

Role of sleep in asthenospermia induced by di (2-ethyl-hexyl) phthalate.

Di (2-ethyl-hexyl) phthalate (DEHP) mainly enters the human body through the digestive tract, respiratory tract, and skin. At the same time, it has reproductive and developmental toxicity, neurotoxicity, and so on, which can cause the decrease of sperm motility. Asthenospermia is also known as low sperm motility, and the semen quality of men in some areas of China is declining year by year. Interestingly, previous studies have shown that sleep disorders can also lead to asthenospermia. However, the relationship between sleep, DEHP, and asthenospermia is still unclear. Analysis of the National Health and Nutrition Examination Survey (NHANES) population database showed that DEHP was associated with sleep disorders, and subsequent experiments in mice and Drosophila indicated that DEHP exposure had certain effects on sleep and asthenospermia. Furthermore, we analyzed the Comparative Toxicogenomics Database (CTD) to find out the common signaling pathway among the three: hypoxia-inducible factor 1(HIF-1). Then Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) was used to screen out the proteins that DEHP affected the HIF-1 pathway: glyceraldehyde-3-phosphate dehydrogenase (GAPDH), serine/threonine-protein kinase (AKT1), epidermal growth factor receptor (EGFR), and finally Western blot analysis was used to detect the expression levels of the three proteins. Compared with the control group, DEHP decreased the protein expression levels of GAPDH and AKT1 in the HIF-1 pathway, and caused sleep disorders and decreased sperm motility. This study provides preliminary evidence for exploring the mechanism among DEHP, sleep disorders, and asthenospermia.

A pancancer analysis of histone deacetylase 3 in human tumors.

Histone deacetylase 3 (HDAC3) is known to be an important role in various kinds of cancer, but its effect has not been examined on the pancancer level. Thus, a systematic pancancer analysis was conducted to explore its potential role in pancancer diagnosis, prognosis, and immune correlation research. We used a series of databases including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) Project, The University of Alabama at Birmingham Cancer data analysis portal (UALCAN), Tumor Immune Estimation Resource (TIMER), and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), among others, to analyze the relationship between the expression of HDAC3 and the diagnosis and prognosis of cancer, the tumor microenvironment (TME), immune infiltration, tumor mutational burden (TMB), microsatellite instability (MSI), mismatch repair (MMR) system using various bioinformatics methods. Downstream pathways of HDAC3 were identified by gene set enrichment analysis (GSEA). Furthermore, the protein expression of HDAC3 in tumor tissues and normal tissues of 17 patients with gliomas was analyzed via western blotting. The expression of HDAC3 changed in most types of tumors, which was closely related to most tumor diagnoses and negatively related to some patients' overall survival (OS) and recurrence-free survival (RFS). The pan-cancer analysis demonstrated that it was tightly correlated to DNA methylation and RNA methylation modifications and associated with TMB and MSI. The expression level of HDAC3 was positively correlated with many immune checkpoint molecules and regulators and positively associated with the infiltration levels of immune cells in the TME in most tumor types. Furthermore, enrichment analysis revealed that transcriptional misregulation in cancer and RNA splicing functions were involved in the functional mechanism of HDAC3-related genes. Experimental research showed that the protein expression of HDAC3 was elevated in tumor tissues of patients with glioma. Through our comprehensive bioinformatics analysis, we evaluated the role of HDAC3 in pancancer, and our findings suggest that it may be an indicator for some cancer diagnoses and influence immune balance.

EGLN1: A Biomarker of Poor Prognosis of Cervical Cancer and a Target of Treatment.

Objective: To conduct bioinformatics analysis on the prognostic effect, mechanism of action, and drug sensitivity of Egl-9 family hypoxia-inducible factor 1 (EGLN1) expression on cervical cancer. Methods: Bioinformatics were obtained from Gene Expression Profiling Interactive Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), and the human cancer metastasis database (HCMDB), and the effect of EGLN1 expression level on the prognosis of cervical cancer was comprehensively analyzed. The protein-protein interaction network was constructed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and the possible mechanism of EGLN1 affecting the prognosis of cervical cancer was discussed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In addition, Gene Set Cancer Analysis (GSCALite) was used to predict sensitive drugs online. Results: The higher the expression level of EGLN1, the shorter the tumor-free survival time and overall survival time of cervical cancer. The higher the stage of cervical cancer, the higher the expression level of EGLN1. The expression of EGLN1 affects the degree of immune infiltration, the variation of somatic copy number, and the level of N6-methyladenosine (m6A) modification in cervical cancer. COX regression model suggested that EGLN1 was an independent prognostic factor of cervical cancer. Conclusions: The high expression of EGLN1 in cervical cancer is an independent risk factor for the prognosis of cervical cancer, which affects the prognosis of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) through different signal pathways. It is expected to be used to predict the sensitive anticancer drugs for the treatment of cervical cancer.

Analysis of Germin-like protein genes family in Vitis vinifera (VvGLPs) using various in silico approaches.

Germin-like proteins (GLPs) play an important role against various stresses. Vitis vinifera L. genome contains 7 GLPs; many of them are functionally unexplored. However, the computational analysis may provide important new insight into their function. Currently, physicochemical properties, subcellular localization, domain architectures, 3D structures, N-glycosylation & phosphorylation sites, and phylogeney of the VvGLPs were investigated using the latest computational tools. Their functions were predicted using the Search tool for the retrieval of interacting genes/proteins (STRING) and Blast2Go servers. Most of the VvGLPs were extracellular (43%) in nature but also showed periplasmic (29%), plasma membrane (14%), and mitochondrial- or chloroplast-specific (14%) expression. The functional analysis predicted unique enzymatic activities for these proteins including terpene synthase, isoprenoid synthase, lipoxygenase, phosphate permease, receptor kinase, and hydrolases generally mediated by Mn+ cation. VvGLPs showed similarity in the overall structure, shape, and position of the cupin domain. Functionally, VvGLPs control and regulate the production of secondary metabolites to cope with various stresses. Phylogenetically VvGLP1, -3, -4, -5, and VvGLP7 showed greater similarity due to duplication while VvGLP2 and VvGLP6 revealed a distant relationship. Promoter analysis revealed the presence of diverse cis-regulatory elements among which CAAT box, MYB, MYC, unnamed-4 were common to all of them. The analysis will help to utilize VvGLPs and their promoters in future food programs by developing resistant cultivars against various biotic (Erysiphe necator and in Powdery Mildew etc.) and abiotic (Salt, drought, heat, dehydration, etc.) stresses.

Investigating D-Amino Acid Oxidase Expression and Interaction Network Analyses in Pathways Associated With Cellular Stress: Implications in the Biology of Aging.

D-amino acid oxidase (DAO) is a flavoenzyme that metabolizes D-amino acids by oxidative deamination, producing hydrogen peroxide (H2O2) as a by-product. The generation of intracellular H2O2 may alter the redox-homeostasis mechanism of cells and increase the oxidative stress levels in tissues, associated with the pathogenesis of age-related diseases and organ decline. This study investigates the effect of DAO knockdown using clustered regularly interspaced short palindromic repeats (CRISPR) through an in silico approach on its protein-protein interactions (PPIs) and their potential roles in the process of aging. The target sequence and guide RNA of DAO were designed using the CCTop database, PPI analysis using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, Reactome biological pathway, protein docking using GalaxyTongDock database, and structure analysis. The translated target sequence of DAO lies between amino acids 43 to 50. The 10 proteins that were predicted to interact with DAO are involved in peroxisome pathways such as acyl-coenzyme A oxidase 1 (ACOX1), alanine-glyoxylate and serine-pyruvate aminotransferase (AGXT), catalase (CAT), carnitine O-acetyltransferase (CRAT), glyceronephosphate O-acyltransferase (GNPAT), hydroxyacid oxidase 1 (HAO1), hydroxyacid oxidase 2 (HAO2), trans-L-3-hydroxyproline dehydratase (L3HYPDH), polyamine oxidase (PAOX), and pipecolic acid and sarcosine oxidase (PIPOX). In summary, DAO mutation would most likely reduce activity with its interacting proteins that generate H2O2. However, DAO mutation may result in peroxisomal disorders, and thus, alternative techniques should be considered for an in vivo approach.

Alzheimer's Disease-Related Proteins Targeted by Secondary Metabolite Compounds from Streptomyces: A Scoping Review.

Alzheimer's disease (AD) is a neurodegenerative disease that is characterized as rapid and progressive cognitive decline affecting 26 million people worldwide. Although immunotherapies are ideal, its clinical safety and effectiveness are controversial, hence, treatments are still reliant on symptomatic medications. Concurrently, the Streptomyces genus has attracted attention given its pharmaceutically beneficial secondary metabolites to treat neurodegenerative diseases. To present secondary metabolites from Streptomyces sp. with regulatory effects on proteins and identified prospective target proteins for AD treatment. Research articles published between 2010 and 2021 were collected from five databases and 83 relevant research articles were identified. Post-screening, only 12 research articles on AD-related proteins were selected for further review. Bioinformatics analyses were performed through the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) network, PANTHER Go-Slim classification system (PANTHER17.0), and Kyoto Encyclopedia of Genes and Genomes (KEGG) Mapper. A total of 20 target proteins were identified from the 12 shortlisted articles. Amyloid-β, BACE1, Nrf-2, Beclin-1, and ATG5 were identified as the potential target proteins, given their role in initiating AD, mitigating neuroinflammation, and autophagy. Besides, 10 compounds from Streptomyces sp., including rapamycin, alborixin, enterocin, bonnevillamides D and E, caniferolide A, anhydroexfoliamycin, rhizolutin, streptocyclinone A and B, were identified to exhibit considerable regulatory effects on these target proteins. The review highlights several prospective target proteins that can be regulated through treatments with Streptomyces sp. compounds to prevent AD's early stages and progression. Further identification of Streptomyces sp. compounds with potential anti-AD properties is recommended.

The mechanisms underlying alcohol-induced decreased splenic size: A network meta-analysis study.

Organ weight change is widely accepted as a measure of toxicologic pathology. We and other groups have shown that excessive alcohol exposure leads to decreased spleen weight in rodents. This study explores the mechanisms underlying alcohol-induced splenic injury through a network meta-analysis. QIAGEN Ingenuity Pathway Analysis (IPA) and Mammalian Phenotype (MP) Ontology were used to identify alcohol-related molecules associated with the small spleen phenotype. Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and IPA bioinformatics tools were then used to analyze the biologic processes and enriched signaling pathways engaging these molecules. In addition, the "downstream effects analysis" algorithm was used to quantify alcohol's effects. IPA identified 623 molecules affected by alcohol and a Venn diagram revealed that 26 of these molecules overlapped with those associated with the MP Ontology of small spleen. The 26 molecules are TGFB1, CASP8, MTOR, ESR1, CXCR4, CAMK4, NFKBIA, DRD2, BCL2, FAS, PEBP1, TRAF2, ATM, IGHM, EDNRB, MDM2, GLRA1, PRF1, TLR7, IFNG, ALOX5, FOXO1, IL15, APOE, IKBKG, and RORA. Some of the 26 molecules were also associated with the MP Ontology of abnormal white pulp and red pulp morphology of the spleen, abnormal splenic cell ratio, decreased splenocyte number, abnormal spleen physiology, increased splenocyte apoptosis, and reduced splenocyte proliferation. STRING and IPA "Core Analysis" showed that these molecules were mainly involved in pathways related to cell apoptosis, proliferation, migration, and immune responses. IPA's "Molecular Activity Predictor" tool showed that concurrent effects of activation and inhibition of these molecules led to decreased spleen size by modulating apoptosis, proliferation, and migration of splenocytes. Our network meta-analysis revealed that excessive alcohol exposure can damage the spleen through a variety of molecular mechanisms, thereby affecting immune function and human health. We found that alcohol-mediated splenic atrophy is largely mediated by increased apoptosis signaling, migration of cells, and inhibition of splenocyte proliferation.

The molecular mechanism of sepsis-induced diaphragm dysfunction.

No effective drugs for the treatment of sepsis-induced diaphragm dysfunction are currently available. Therefore, it is particularly important to clarify the molecular regulatory mechanism of this condition and subsequently implement effective treatment and prevention of sepsis-induced diaphragm dysfunction. A mouse model of diaphragm dysfunction was established via injection of lipopolysaccharide (LPS). An RNA-sequencing (RNA-seq) technique was used to detect the differentially expressed genes (DEGs) in the diaphragms of mice. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for functional analysis of DEGs. The protein-protein interaction network obtained from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website was imported into Cytoscape, the key molecular regulatory network was constructed with CytoNCA, the ClueGo plugin was further used to analyze the core regulatory pathways of key molecular, and finally, the iRegulon plugin was used to the identify key transcription factors. The genes upregulated after LPS treatment were involved in biological processes and pathways related to immune response; the genes downregulated after LPS treatment were mainly correlated with the muscle contraction. The expressions of several inflammation-related genes were upregulated after LPS treatment, of which tumor necrosis factor (Tnf), interleukin (Il)-1β, and Il-6 assumed a core regulatory role in the network; meanwhile, the downregulated key genes included Col1a1, Uqcrfs1, Sdhb, and ATP5a1, among others. These key regulatory factors participated in the activation of Toll-like receptor (TLR) signaling pathway, nuclear factor (NF)-κB signaling pathway, and TNF signaling pathway as well as the inhibition of oxidative phosphorylation pathway, cardiac muscle contraction pathway, and citrate cycle pathway. Finally, RelA, IRF1, and STAT3, were identified as the key regulators in the early stage of diaphragmatic inflammatory response. Sepsis-induced diaphragm dysfunction in mice is closely correlated with the activation of TLR signaling pathway, NF-κB signaling pathway, and TNF signaling pathway and the inhibition of oxidative phosphorylation pathway, cardiac muscle contraction pathway, and citrate cycle pathway. Our findings provide insight into the molecular mechanism of sepsis-induced diaphragm dysfunction in mice and provide a promising new strategy for targeted treatment of diaphragm dysfunction.

Function and prognosis analysis of nucleolus protein DCAF13 in breast cancer.

Breast cancer is one of the main causes of death among women. RNA binding proteins (RBPs) play a crucial role in the progression of breast cancer, with increasingly detailed understanding of RBP functional molecular mechanisms in breast cancer, the functional research of RBPs may help elucidate the potential mechanisms of tumor occurrence, development, invasion, metastasis and prognosis. DDB1- and CUL4-associated factor 13 (DCAF13) is an RBPs has been identified as a substrate receptor for the CUL4-DDB1 E3 ligase complex. Its expression is related to the prognosis of certain cancer. We tried to explore both co-expressed network and biological functions of DCAF13 in breast cancer. The Cancer Genome Atlas (TCGA) database was used to analyze the different expression of DCAF13 messenger RNA (mRNA) between normal breast tissue and breast carcinoma tissue, and the clinical data about 960 samples were downloaded from the cBio Cancer Genomics Portal (cBioPortal). The expression level of DCAF13, co-expression network, and survival were analyzed. Those with a fold change ≥1 and FDR <0.05 were considered to have statistical significance. Unsupervised clustering of differentially expressed RBPs was performed based on log2-transformed FPKM values using the "pheatmap" package in R. Genes with a Spearman score >0.55 were regarded as moderately co-expressed genes. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was used to construct a co-expression network. Meanwhile, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used to identify the biological process cluster and pathway cluster, respectively. Compared with normal breast tissue, DCAF13 mRNA expression was significantly increased in breast cancer tissue (P<0.01). The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to identify the functions of the co-expressed network. These genes were mainly enriched in mitosis, nuclear division, metabolic process, recombination, replication and repair of DNA, double-strand break repair, posttranscriptional regulation of gene expression, regulation of cell cycle, division and proliferation, regulation of protein stability and also participation in in regulation of poly(A) RNA binding, mRNA binding, tRNA binding, adenosine triphosphate (ATP) binding. KEGG pathway analysis revealed that the genes were mainly enriched in cell cycle, oocyte meiosis and oxidative phosphorylation. According to survival analysis, upregulation of DCAF13 mRNA was significant for overall survival (OS) (P=0.0163). DCAF13 is up-regulated in breast cancer, the OS of patients with DCAF13 up-regulation was obviously reduced. DCAF13 was used as a diagnostic marker and therapeutic target for breast cancer. By building a co-expression network of DCAF13 and conducting bioinformatics analysis, it is possible to find the biomarker to evaluate patient prognosis. This finding provides a new target in mechanism and cell research of breast cancer.

Investigating the prognostic and predictive value of the type II cystatin genes in gastric cancer

BackgroundAccumulating evidence indicates that type II cystatin (CST) genes play a pivotal role in several tumor pathological processes, thereby affecting all stages of tumorigenesis and tumor development. However, the prognostic and predictive value of type II CST genes in GC has not yet been investigated.MethodsThe present study evaluated the expression and prognostic value of type II CST genes in GC by using The Cancer Genome Atlas (TCGA) database and the Kaplan–Meier plotter (KM plotter) online database. The type II CST genes related to the prognosis of GC were then screened out. We then validated the expression and prognostic value of these genes by immunohistochemistry. We also used Database for Annotation, Visualization, and Integrated Discovery (DAVID), Gene Multiple Association Network Integration Algorithm (GeneMANIA), Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), nomogram, genome-wide co-expression analysis, and other bioinformatics tools to analyze the value of type II CST genes in GC and the underlying mechanism.ResultsThe data from the TCGA database and the KM plotter online database showed that high expression of CST2 and CST4 was associated with the overall survival (OS) of patients with GC. The immunohistochemical expression analysis showed that patients with high expression of CST4 in GC tissues have a shorter OS than those with low expression of CST4 (HR = 1.85,95%CI: 1.13–3.03, P = 0.015). Multivariate Cox regression analysis confirmed that the high expression level of CST4 was an independent prognostic risk factor for OS.ConclusionsOur findings suggest that CST4 could serve as a tumor marker that affects the prognosis of GC and could be considered as a potential therapeutic target for GC.

Identification of key genes and validation of key gene aquaporin 1 on Wilms' tumor metastasis.

Wilms' tumor (WT) is one of the most common solid tumors in children with unsatisfactory prognosis, but few molecular prognostic markers have been discovered for it. Many genes are associated with the occurrence and prognosis of WT. This study aimed to explore the key genes and potential molecular mechanisms through bioinformatics and to verify the effects of aquaporin 1 (AQP1) on WT metastasis. Differentially expressed genes (DEGs) were generated from WT gene expression data sets from the Gene Expression Omnibus (GEO) database. Gene functional enrichment analysis was carried out with the Database for Annotation, Visualization and Integrated Discovery (DAVID). A protein-protein interaction network (PPI) was constructed and visualized by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and Cytoscape software. Minimal Common Oncology Data Elements (MCODE) was used to detect the important modules in the PPI network, and the important nodes (genes) in the PPI module were sorted by CytoHubba. RT-qPCR was performed to validate the expression of the key genes in WT. Wound healing and Transwell assays were used to detect the cell migration and invasion abilities of AQP1-overexpressing cells. Phalloidin-iFlour 488 was used to stain the cytoskeleton to observe how AQP1 overexpression affects cytoskeletal microfilament structure. A total of 73 co-expressed DEGs were chosen for further investigation. The importance of homeostasis and transmembrane transport of ions and water were highlighted by functional analysis. Gene regulatory network and PPI network were predicted. MCODE plug identified two important modules. Finally, top five key genes were identified using CytoHubba, including Renin (REN), nephrosis 2 (NPHS2), Solute Carrier Family 12 Member 3 (SLC12A3), Solute Carrier Family 12 Member 1 (SLC12A1) and AQP1. The five key genes were mainly enriched in cell volume and ion homeostasis. RT-qPCR confirmed the expression of the five key genes in WT. AQP1 was validated to be expressed at significantly lower levels in WT than in normal tissue. AQP1 overexpression significantly reduced the migratory and invasive capacity of Wit-49 cells, as evidenced by reducing the scratch healing rate and the number of perforated control cells by Wit-49 cells. AQP1 overexpression also reduced the expression of biomarkers of epithelial-mesenchymal transformation, decreased levels of vimentin and N-cadherin and increased expression of E-cadherin, resulting in decreased formation of conspicuous lamellipodial protrusions, characteristic of diminished WT cell invasion and migration. Our study reveals the key genes of WT. These key genes may provide novel insight for the mechanism and diagnosis of WT. AQP1 overexpression inhibited invasion, migration, EMT, and cytoskeletal rearrangement of WT cells, indicating that AQP1 plays a role in the pathogenesis of WT.