Cytoscape Platform Research Articles

Acute myocardial infarction leads to distinct sex differences in the coding transcriptome of human monocytes with a potential impact in disease aetiopathology

Abstract Background Immune responses are intricately linked to human disease, not only during pathogenic infections but also in sterile injury events such as in cardiovascular disease. Atherosclerosis is the main driver leading to coronary artery disease (CAD) and subsequent development of acute myocardial infarction (AMI) and heart failure. The vital role of monocytes in the pathophysiology of atherosclerosis is well established. In the onset of AMI, monocytes act as first responders, both in the inflammatory and tissue repair phases. It is now apparent that sex-specific differences in the inflammatory responses leading to AMI impact the severity and outcome of patients. Yet, the immune responses during AMI have been under-investigated in women, often under-represented in clinical studies, and more research in this topic is required. Purpose Identification of sex-specific differences in the coding transcriptome of monocytes subpopulations in the onset of AMI compared to matched healthy subjects and CAD patients. Methods We isolated monocytes from male and female AMI patients, CAD patients and healthy controls. FACS sorting of monocytes (CD14 and CD16) resulted into classical, intermediate, and non-classical subpopulations. We performed ribosomal depletion and bulk Illumina RNA sequencing for each monocyte subpopulation. Differentially expressed genes (DEG) were calculated using specific R packages. Pathway enrichment analysis was performed with Gene set enrichment analysis (GSEA). Other computational tools were used to determine enrichment of genes linked to GWAS identified in cardiovascular diseases or to infer pathway responsive genes upon perturbation (Progeny). Network comparison and visualization were performed using Cytoscape platform. Results Whereas observing a clear overlap of most pathways such as homeostasis, regulation of signalling cascades and inflammatory response, we also identified other pathways contrasting strongly between both sexes. In fact, TGF beta/ SMAD signalling, wound healing and epithelial to mesenchymal transition are increased in female cells. On the contrast the more pro-inflammatory BMP/SMAD signalling is increased in male cells accompanied by decreased respiratory electron transport and translation. Additionally, when comparing our data to signatures identified in trauma patients, we observe clear mapping of our gene sets, which are upregulated in AMI, with the first 3 trauma associated signatures, whereas one of the signatures associated to homeostasis associates clearly with our CAD data as well as the healthy subjects. Conclusions Human monocytes display a specific coding transcriptome and certain pathways are differentially expressed in AMI and differ greatly between male and female cohorts. Interestingly, our DEG map closely to trauma associated signatures, highlighting potential similarities in disease aetiopathology between trauma and AMI patients.

Therapeutic mechanism of Convolvulus pluricaulis against Alzheimer's disease: Network pharmacology and molecular dynamics approach

Alzheimer disease (AD) is a type of dementia most prevalent in the elderly. A perennial herb, Convolvulus pluricaulis Choisy (C. pluricaulis) is used as a traditional folk medicine to treat AD and other neurodegenerative diseases, but the mechanism of action for its treatment has not been determined. This study attempts to clarify the mechanism of AD by investigating the phytochemical constituents of C. pluricaulis and their effect on it. In order to screen the active components of C. pluricaulis, values of oral bioavailability (OB) ≥ 30 % and Drug Like (DL) ≥ 0.18 was used. STRING and the Cytoscape platform have been used to construct an interactive network of targets and compounds. The network has been analyzed by Cytohubba, whereas GO functionality, KEGG pathways and metabolic pathway enrichment were performed using SRplot. The efficient targets were identified via Maximal Clique Centrality (MCC) and Degree using CytoHubba. The possible correlation between amyloid β-protein (Aβ), Tau pathology and identified efficient targets was determined via Alzdata database, and finally the core targets were analyzed. Molecular docking analysis and molecular dynamics (MD) simulation was further used in order to determine the binding affinity between the active ingredients and the core targets. Through a network pharmacological approach, we identified key genes in cytoscape. C. pluricaulis targets 30 signaling pathways and diseases associated with AD. Based on the overall results of the present study, it was found that all 4 bioactive compounds were identified to target GSK3β, and protein-ligand complex was shown to be stable for 100 ns in a molecular dynamics simulation and exhibited relativistic conformational dynamics on the trajectory. Thus, the present study suggests that modulating GSK3β with natural compounds is an attractive approach in treating AD and other neurodegenerative diseases after required validation.

Integrating network pharmacology and bioinformatics to explore the mechanism of Xiaojian Zhongtang in treating major depressive disorder: An observational study.

Major depressive disorder (MDD) is a common mental illness. The traditional Chinese medicine compound Xiaojian Zhongtang (XJZT) has a good therapeutic effect on MDD, but the specific mechanism is not clear. The aim of this study is to explore the molecular mechanism of XJZT in the treatment of MDD through network pharmacology and bioinformatics. The traditional Chinese medicine system pharmacology database was used to screen the chemical components and targets of XJZT, while the online Mendelian inheritance in man, DisGeNET, Genecards, and therapeutic target database databases were used to collect MDD targets and identify the intersection targets of XJZT and MDD. A "drugs-components-targets" network was constructed using the Cytoscape platform, and the STRING was used for protein-protein interaction analysis of intersecting targets. Gene Ontology and Kyoto encyclopedia of genes and genomes analysis of intersecting targets was performed using the DAVID database. Obtain serum and brain transcriptome datasets of MDD from the gene expression omnibus database, and perform differentially expressed genes, weighted gene co-expression network analysis, gene set enrichment analysis, and receiver operating characteristic analysis. A total of 127 chemical components and 767 targets were obtained from XJZT, among which quercetin, kaempferol, and maltose are the core chemical components, and 1728 MDD targets were screened out, with 77 intersecting targets between XJZT and MDD. These targets mainly involve AGE-RAGE signaling pathway in diabetic complexes, epidermal growth factor receptor tyrosine kinase inhibitor resistance, and HIF-1 signaling pathway, and these core targets have strong binding activity with core components. In addition, 1166 differentially expressed genes were identified in the MDD serum transcriptome dataset, and weighted gene co-expression network analysis identified the most relevant gene modules (1269 genes), among which RAC-alpha serine/threonine-protein kinase (AKT1), D(4) dopamine receptor (DRD4), and kynurenine 3-monooxygenase (KMO) were target genes for the treatment of MDD with XJZT, these 3 genes are mainly related to the ubiquitin-mediated proteolysis, arachidonic acid (AA) metabolism, and Huntington disease pathways, and the expression of AKT1, DRD4, and KMO was also found in the MDD brain transcriptome dataset, which is significantly correlated with the occurrence of MDD. We have identified 3 key targets for XJZT treatment of MDD, including AKT1, KMO, and DRD4, and they can be regulated by the key components of XJZT, including quercetin, maltose, and kaempferol. This provides valuable insights for the early clinical diagnosis and development of therapeutic drugs for MDD.

Bioinformatics-based screening and analysis of the key genes involved in the influence of antiangiogenesis on myeloid-derived suppressor cells and their effects on the immune microenvironment.

This study aimed to screen differentially expressed genes (DEGs) involved in the influence of antiangiogenic therapy on myeloid-derived suppressor cell (MDSC) infiltration and investigate their mechanisms of action. Data on DEGs after the action of antiangiogenic drugs in a pan-cancer context were obtained from the Gene Expression Omnibus (GEO) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the clusterProfiler package in R software. Single-sample gene set enrichment analysis was performed using the gene set variation analysis package to evaluate the levels of immune cells and the activity of immune-related pathways. The relationships of DEGs with the infiltration levels of MDSCs and specific immune cell subpopulations were investigated via gene module analysis. The top 10 key genes were subsequently obtained from PPI network analysis using the cytoHubba plugin of the Cytoscape platform. When the DEGs of the four datasets were intersected, a DEG in the intersection of three datasets and 12 DEGs in the intersection of two datasets were upregulated, and 28 DEGs in the intersection of two datasets were downregulated. GO and KEGG pathway enrichment analyses revealed that the DEGs were associated with multiple important signaling pathways closely related to tumor onset and development, including cell differentiation, cell proliferation, the cell cycle, and immune responses. Most downregulated genes in lung adenocarcinoma (LUAD) were positively correlated with MDSC expression. Only MGP was negatively correlated; the correlation between CACNG6 and MDSC expression was statistically insignificant. In lung squamous cell carcinoma (LUSC), the relationships of PMEPA1, PCDH7, NEURL1B, and CACNG6 with MDSC expression were statistically insignificant; MGP was negatively correlated with MDSC expression. The top 10 key genes with the highest degree scores obtained using the cytoHubba plugin of Cytoscape were AURKB, RRM2, BUB1, NUSAP1, PRC1, TOP2A, NCAPH, CENPA, KIF2C, and CCNA2. Most of these genes were upregulated in LUAD and associated with immune cell infiltration and prognosis in tumors. An analysis of the relationships between DEGs and infiltration by other specific immune cells revealed the presence of consistent patterns in the downregulated genes, which exhibited positive correlations with the levels of Th2 cells, γδ T cells, and CD56dim NK cells, and negative correlations with other infiltrating immune cells. Antiangiogenic therapy may regulate MDSC infiltration through multiple important signaling pathways closely associated with tumor onset and development, such as cell differentiation, cell proliferation, the cell cycle, and immune responses. Antiangiogenic drugs may exert effects by affecting various types of infiltrating cells associated with immune suppression.

A Study of Dual Function and Expression Pattern of Klf4 between Two Different Processes of Differentiation and Maintenance of Pluripotency in Spermatogonial Stem Cells

Krüppel-like factor 4 (Klf4) is a transcription factor involved in proliferation, self-renewal, differentiation, apoptosis, and somatic cell reprogramming; thus, it has a critical role in accurate spermatogenesis. In this study, we examine the different protein localizations of Klf4 in the mouse testis and in two populations of spermatogonial stem cells (SSCs), including differentiated and undifferentiated cell types. We show that in contrast to its function during spermatogenesis in the adult testis, in vitro Klf4 is a factor in maintaining stemness in different SSC populations. Furthermore, we suggest that its functions could be age-dependent. Bioinformatics analysis in the Cytoscape platform was conducted to highlight pathways and networks of Klf4 interactions. Our results support the different functions of Klf4 dependent on the age and differentiation state of SSCs.

Identification of ubiquitination-related hub genes in chronic myeloid leukemia cell by bioinformatics analysis.

Purpose: Chronic myeloid leukemia stem cells (CML-LSCs) are posited as the primary instigators of resistance to tyrosine kinase inhibitors (TKIs) and recurrence of CML. Ubiquitination, a post-translational modification, has been implicated in the worsening process of CML. A more detailed understanding of their crosstalk needs further investigation. Our research aims to explore the potential ubiquitination-related genes in CML-LSC using bioinformatics analysis that might be the target for the eradication of LSCs. Methods: The ubiquitination modification-related differentially expressed genes (UUC-DEGs) between normal hematopoietic stem cells (HSCs) and LSCs were obtained from GSE47927 and iUUCD database. Subsequently, the hub UUC-DEGs were identified through protein-protein interaction (PPI) network analysis utilizing the STRING database and the MCODE plug-in within the Cytoscape platform. The upstream regulation network of the hub UUC-DEGs was studied by hTFtarget, PROMO, miRDB and miRWalk databases respectively. Then the correlation between the hub UUC-DEGs and the immune cells was analyzed by the CIBERSORT algorithm and "ggcorrplot" package. Finally, we validated the function of hub UUC-DEGs in CML animal models, CML cell lines and CD34+ cells of the GSE24739 dataset. Results: There is a strong association between the 4 hub UUC genes (AURKA, Fancd2, Cdc20 and Uhrf1) of LSCs and the infiltration of CD4+/CD8+ T cells, NK cells and monocytes. 8 TFs and 23 miRNAs potentially targeted these 4 hub genes were constructed. Among these hub genes, Fancd2, Cdc20 and Uhrf1 were found to be highly expressed in CML-LSC, which knocking down resulted in significant inhibition of CML cell proliferation. Conclusions: From the perspective of bioinformatics analysis, UHRF1 and CDC20 were identified as the novel key ubiquitination-related genes in CML-LSCs and the pathogenesis of CML.

Network pharmacology and molecular docking reveal potential mechanism of esculetin in the treatment of ulcerative colitis.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease of the colonic mucosa. Esculetin is a type of natural coumarin that has many pharmacological activities such as antioxidant, anticancer, anti-inflammatory, etc. A previous study showed that esculetin improved intestinal inflammation and reduced serum proinflammatory cytokines in UC. The present study aimed to utilize network pharmacology and molecular docking to explore the potential mechanism of esculetin against UC. The potential gene targets of esculetin were predicted through SwissTargetPrediction and Super-PRED web servers. UC-related genes were obtained from DisGeNet, OMIM, and GeneCards databases. The overlap between gene targets of esculetin and UC-related genes were identified as the potential targets of esculetin against UC. The interaction between these overlapping genes was analyzed by the STRING database and the core genes were identified by Cytoscape platform. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of the core genes were then performed. And the results of these analyses were further confirmed through molecular docking. A total of 50 overlapping genes were identified as the potential action targets of esculetin against UC. Among them, 10 genes (AKT1, STAT1, CCND1, SRC, PTGS2, EGFR, NFKB1, ESR1, MMP9, SERPINE1) were finally identified as the core genes. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis results showed that the top signaling pathway associated with the core genes of esculetin against UC was the prolactin (PRL) signaling pathway. Molecular docking results showed that esculetin has a strong binding affinity to the core genes, as well as PRL and prolactin receptor. This study suggests that esculetin may have a crucial impact on UC through the PRL signaling pathway and provides insights into the potential mechanism of esculetin in the treatment of UC, which may shed light on the mechanism and treatment of UC.

Exploring the Common Gene Signatures Between Myocardial Infarction-Reperfusion Injury and the Gut Microbiome Using Bioinformatics

Background: This bioinformatics report attempts to explore the cross-talk genes, transcription factors (TFs), and pathways related to myocardial ischemia-reperfusion injury (MIRI) as well as the gut microbiome. Method: The datasets GSE61592 (three MIRI and three sham samples) and GSE160516 (twelve MIRI and four sham samples) were selected in the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) identification (p < 0.05 and |log FC (fold change)| ≥1) together with functional annotation (p < 0.05) was implemented. The Cytoscape platform established the protein-protein interaction (PPI) network. Genes associated with gut microbiome disorder were extracted based on the DisGeNET database, and those associated with MIRI were overlapped. The Recursive Feature Elimination (RFE) algorithm was adopted for selecting features, and cross-talk genes were predicted by the Support Vector Machine (SVM) models. A network encompassing cross-talk genes along with the TFs was thereby established. Result: The MIRI datasets comprised 138 shared DEGs, with 101 showing up-regulation whereas 37 showing down-regulation. Notably, the PPI interwork for MIRI contained 2517 edges along with 1818 nodes. By using RFE and SVM methods, six feature genes with the highest prediction were identified: B2m, VCAM-1, PDIA4, Ptgds, Mlxipl, and ACADS. Among these genes, B2m and PDIA4 were most highly expressed in MIRI and the gut microbiome disorder. Conclusion: B2m and PDIA4 were identified to be significantly correlated with candidate cross-talk genes of MIRI with gut microbiome disorder, implying a similarity between MIRI and Gut microbiome disorder (GMD). These genes can serve as an experimental research basis for future studies.

Bioinformatics-based screening of key genes for transformation of tyrosine kinase inhibitor-resistant lung adenocarcinoma to small cell lung cancer.

Lung adenocarcinoma (LUAD) is a common type of lung cancer. Cancer in a small number of patients with EGFR mutations will transform from LUAD to small cell lung cancer (SCLC) during epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) therapiesr. The purpose of the present study was to identify the core genes related to the transformation of LUAD into SCLC and to explore the associated molecular mechanisms. GSE29016, GSE1037, GSE6044 and GSE40275 mRNA microarray datasets from Gene Expression Omnibus (GEO) were analyzed to obtain differentially expressed genes (DEGs) between LUAD and SCLC tissues, and the results were used for network analysis of protein-protein interactions (PPIs). After identifying the hub gene by STRING and Cytoscape platform, we explored the relationship between hub genes and the occurrence and development of SCLC. Finally, the obtained hub genes were validated in treated LUAD cells. A total of 41 DEGs were obtained, four hub genes (EZH2, NUSAP1, TTK and UBE2C) were identified, and related prognostic information was obtained. The coexpressed genes of the hub gene set were further screened, and the analysis identified many genes related to the cell cycle. Subsequently, LUAD cell models with TP53 and RB1 inactivation and overexpression of ASCL1 were constructed, and then the expression of hub genes was detected, the results showed that the four hub genes were all elevated in the established cell model. EZH2, NUSAP1, TTK and UBE2C may affect the transformation of LUAD to SCLC and represent new candidate molecular markers for the occurrence and development of SCLC.

Gene Ontology Analysis Highlights Biological Processes Influencing Responsiveness to Biological Therapy in Psoriasis.

Psoriasis is a chronic, immune-mediated and inflammatory skin disease. Although various biological drugs are available for psoriasis treatment, some patients have poor responses or do not respond to treatment. The aim of the present study was to highlight the molecular mechanism of responsiveness to current biological drugs for psoriasis treatment. To this end, we reviewed previously published articles that reported genes associated with treatment response to biological drugs in psoriasis, and gene ontology analysis was subsequently performed using the Cytoscape platform. Herein, we revealed a statistically significant association between NF-kappaB signaling (p value = 3.37 × 10-9), regulation of granulocyte macrophage colony-stimulating factor production (p value = 6.20 × 10-6), glial cell proliferation (p value = 2.41 × 10-5) and treatment response in psoriatic patients. To the best of our knowledge, we are the first to directly associate glial cells with treatment response. Taken together, our study revealed gene ontology (GO) terms, some of which were previously shown to be implicated in the molecular pathway of psoriasis, as novel GO terms involved in responsiveness in psoriatic disease patients.

Insight from sirtuins interactome: topological prominence and multifaceted roles of SIRT1 in modulating immunity, aging and cancer.

The mammalian sirtuin family, consisting of SIRT1-SIRT7, plays a vital role in various biological processes, including cancer, diabetes, neurodegeneration, cardiovascular disease, cellular metabolism, and cellular homeostasis maintenance. Due to their involvement in these biological processes, modulating sirtuin activity seems promising to impact immune- and aging-related diseases, as well as cancer pathways. However, more understanding is required regarding the safety and efficacy of sirtuin-targeted therapies due to the complex regulatory mechanisms that govern their activity, particularly in the context of multiple targets. In this study, the interaction landscape of the sirtuin family was analyzed using a systems biology approach. A sirtuin protein-protein interaction network was built using the Cytoscape platform and analyzed using the NetworkAnalyzer and stringApp plugins. The result revealed the sirtuin family's association with numerous proteins that play diverse roles, suggesting a complex interplay between sirtuins and other proteins. Based on network topological and functional analysis, SIRT1 was identified as the most prominent among sirtuin family members, demonstrating that 25 of its protein partners are involved in cancer, 22 in innate immune response, and 29 in aging, with some being linked to a combination of two or more pathways. This study lays the foundation for the development of novel therapies that can target sirtuins with precision and efficacy. By illustrating the various interactions among the proteins in the sirtuin family, we have revealed the multifaceted roles of SIRT1 and provided a framework for their possible roles to be precisely understood, manipulated, and translated into therapeutics in the future.

Exploring the pharmacological mechanisms of Tripterygium wilfordii against diabetic kidney disease using network pharmacology and molecular docking

BackgroundTripterygium wilfordii (TW), when formulated in traditional Chinese medicine (TCM), can effectively treat diabetic kidney disease (DKD). However, the pharmacological mechanism associated with its success has not yet been elucidated. The current work adopted network pharmacology and molecular docking for exploring TW-related mechanisms in treating DKD. Methods: In the present work, the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was employed to obtain the effective components and candidate targets of TW. Additionally, this work utilized the UniProt protein database for screening and standardizing human-derived targets for effective components. The Cytoscape software was utilized to construct an effective component-target network for TW. Targets for DKD were acquired in the GEO, DisGeNET, GeneCards, and OMIM databases. Additionally, a Venn diagram was also plotted to select the possible targets of TW for treating DKD. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted to explore the TW-related mechanism underlying DKD treatment. This work also built a protein-protein interaction (PPI) network based on the Cytoscape and String platform. Then, molecular docking was conducted in order to assess the affinity of key proteins for related compounds. Results: In total, 29 active components and 134 targets of TW were acquired, including 63 shared targets, which were identified as candidate therapeutic targets. Some key targets and important pathways were included in the effect of TW in treating DKD. Genes with higher degrees, including TNF and AKT1, were identified as hub genes of TW against DKD. Molecular docking showed that TNF and AKT1 bind well to the main components in TW (kaempferol, beta-sitosterol, triptolide, nobiletin, and stigmasterol). ConclusionsTW primarily treats DKD by acting on two targets (AKT1 and TNF) via the five active ingredients kaempferol, beta-sitosterol, triptolide, nobiletin, and stigmasterol.

Exploring underlying mechanism of artesunate in treatment of acute myeloid leukemia using network pharmacology and molecular docking.

Acute myeloid leukemia (AML) is a highly heterogeneous hematological cancer. The current diagnosis and therapy model of AML has gradually shifted to personalization and accuracy. Artesunate, a member of the artemisinin family, has anti-tumor impacts on AML. This research uses network pharmacology and molecular docking to anticipate artesunate potential mechanisms of action in the therapy of AML. Screening the action targets of artesunate through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), PubChem, and Swiss Target Prediction databases; The databases of Online Mendelian Inheritance in Man (OMIM), Disgenet, GeneCards, and Drugbank were utilized to identify target genes of AML, and an effective target of artesunate for AML treatment was obtained through cross-analysis. Protein-protein interaction (PPI) networks are built on the Cytoscape platform. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the relevant targets using R software. Finally, using molecular docking technology and Pymol, we performed verification of the effects of active components and essential targets. Artesunate 30 effective targets for treating AML include CASP3, EGFR, MAPK1, and STAT3, four targeted genes that may have a crucial function in disease management. The virus infection-related pathway (HeptatisB (HBV), Human papillomavirus (HPV), Epstein-Barr virus (EBV) infection and etc.), FoxO, viral carcinogenesis, and proteoglycans in cancer signaling pathways have all been hypothesized to be involved in the action mechanism of GO, which is enriched in 2044 biological processes, 125 molecular functions, 209 cellular components, and 106 KEGG pathways. Molecular docking findingsrevealed that artesunate was critically important in the therapy of AML due to its high affinity for the four primary disease targets. Molecular docking with a low binding energy yields helpful information for developing medicines against AML. Consequently, artesunate may play a role in multi-targeted, multi-signaling pathways in treating AML, suggesting that artesunate may have therapeutic potential for AML.

Whole-Exome Sequencing Indicated New Candidate Genes Associated with Unilateral Cryptorchidism in Pigs

Introduction: Cryptorchidism is a hereditary anomaly characterized by the incomplete descent of one or both testicles to the scrotum. One of the challenges of this anomaly is that the retained testicle maintains its endocrine function. As a consequence, cryptorchid animals produce hormone-tainted meat in comparison to castrated animals and are likely to be more aggressive. Cryptorchidism can lead to reduced animal welfare outcomes and cause economic losses. Identifying genetic markers for cryptorchidism is an essential step toward mitigating these negative outcomes and may facilitate genome manipulation to reduce the occurrence of cryptorchidism. Attempts to identify such markers have used genome-wide association studies. Using whole-exome sequencing, we aimed to identify single nucleotide polymorphisms (SNPs) in the coding regions of cryptorchid pigs and to characterize functional pathways concerning these SNPs. Methods: DNA was extracted and sequenced from 5 healthy and 5 cryptorchid animals from the Landrace breed, using the Illumina HiSeq 2500 platform. Data were pre-processed using the SeqyClean tool and further mapped against the swine reference genome (Sus scrofa 11.1) using BWA software. GATK was used to identify polymorphisms (SNPs and InDels), which were annotated using the VEP tool. Network prediction and gene ontology enrichment analysis were conducted using the Cytoscape platform, and STRING software was used for visualization. Results: A total of 63 SNPs were identified across the genes PIGB, CCPG1, COMMD9, LDLRAD3, TRIM44, MYLPF, SEPTIN, ZNF48, TIA1, FAIM2, KRT18, FBP1, FBP2, CTSL, DAPK1, DHX8, GPR179, DEPDC1B, ENSSSCG00000049573, ENSSSCG00000016384, ENSSSCG00000022657, ENSSSCG00000038825, and ENSSSCG00000001229. Using pathway enrichment analyses and network prospection, we have identified the following significant adjusted p value threshold of 0.001 involved with the biological function pathways of estrogen signaling, cytoskeleton organization, and the pentose phosphate pathway. Conclusion: Our data suggest the involvement of new SNPs and genes in developing cryptorchidism in pigs. However, further studies are needed to validate our results in a larger cohort population. Variations in the GPR179 gene, with implications at the protein level, may be associated with the appearance of this anomaly in the swine. Finally, we are showing that the estrogen signaling pathway may be involved in the pathophysiological mechanisms of this congenital anomaly as previously reported in GWAS.

Integration of Proteomic Data Obtained from the Saliva of Children with Caries through Bioinformatic Analysis

Background: Dental caries can affect the expression of salivary proteins. Proteomics allows us to analyze and identify many proteins in a single sample and experiment; bioinformatics is essential to analyze proteomic data. Objective: This research aims to identify and integrate the main differentially expressed proteins in the saliva of children with caries, infer their Gene Ontology and interactions, and identify regulatory factors. Materials and Methods: We extracted proteins from a bibliographic search in the Scopus and PubMed databases. We analyzed these proteins with the web application ShinyGO v0.76, ToppGene and NetworkAnalyst 3.0, and the Cytoscape platform. Results: In the literature search, we extracted 26 differentially expressed proteins. These proteins show enrichment in antioxidant activity, antimicrobial response, immune response, and vitamin and mineral metabolism. We found three transcription factors that regulate most of the genes of these proteins: TFDP1, SOX13, and BCL6. We also identified three microRNAs that highly restrict the expression of these proteins: hsa-mir-124-3p, hsa-mir-27a-3p, and hsa-mir-26b-5p. On the other hand, the main drugs associated with these proteins are potassium persulfate, aluminum, and cadmium. Conclusion: The differentially expressed proteins in the saliva of children with dental caries are involved in metabolic pathways related to folate, selenium, and vitamin B12 metabolism. In addition, some transcription factors (TFDP1, SOX13, and BCL6) miRNAs (hsa-mir-124-3p, hsa-mir-27a-3p, and hsa-mir-26b-5p) and chemical compounds (potassium persulfate, aluminum, and cadmium) can regulate the genes, mRNAs or proteins studied.

IFI44 is an immune evasion biomarker for SARS-CoV-2 and Staphylococcus aureus infection in patients with RA.

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic of severe coronavirus disease 2019 (COVID-19). Staphylococcus aureus is one of the most common pathogenic bacteria in humans, rheumatoid arthritis (RA) is among the most prevalent autoimmune conditions. RA is a significant risk factor for SARS-CoV-2 and S. aureus infections, although the mechanism of RA and SARS-CoV-2 infection in conjunction with S. aureus infection has not been elucidated. The purpose of this study is to investigate the biomarkers and disease targets between RA and SARS-CoV-2 and S. aureus infections using bioinformatics analysis, to search for the molecular mechanisms of SARS-CoV-2 and S. aureus immune escape and potential drug targets in the RA population, and to provide new directions for further analysis and targeted development of clinical treatments.MethodsThe RA dataset (GSE93272) and the S. aureus bacteremia (SAB) dataset (GSE33341) were used to obtain differentially expressed gene sets, respectively, and the common differentially expressed genes (DEGs) were determined through the intersection. Functional enrichment analysis utilizing GO, KEGG, and ClueGO methods. The PPI network was created utilizing the STRING database, and the top 10 hub genes were identified and further examined for functional enrichment using Metascape and GeneMANIA. The top 10 hub genes were intersected with the SARS-CoV-2 gene pool to identify five hub genes shared by RA, COVID-19, and SAB, and functional enrichment analysis was conducted using Metascape and GeneMANIA. Using the NetworkAnalyst platform, TF-hub gene and miRNA-hub gene networks were built for these five hub genes. The hub gene was verified utilizing GSE17755, GSE55235, and GSE13670, and its effectiveness was assessed utilizing ROC curves. CIBERSORT was applied to examine immune cell infiltration and the link between the hub gene and immune cells.ResultsA total of 199 DEGs were extracted from the GSE93272 and GSE33341 datasets. KEGG analysis of enrichment pathways were NLR signaling pathway, cell membrane DNA sensing pathway, oxidative phosphorylation, and viral infection. Positive/negative regulation of the immune system, regulation of the interferon-I (IFN-I; IFN-α/β) pathway, and associated pathways of the immunological response to viruses were enriched in GO and ClueGO analyses. PPI network and Cytoscape platform identified the top 10 hub genes: RSAD2, IFIT3, GBP1, RTP4, IFI44, OAS1, IFI44L, ISG15, HERC5, and IFIT5. The pathways are mainly enriched in response to viral and bacterial infection, IFN signaling, and 1,25-dihydroxy vitamin D3. IFI44, OAS1, IFI44L, ISG15, and HERC5 are the five hub genes shared by RA, COVID-19, and SAB. The pathways are primarily enriched for response to viral and bacterial infections. The TF-hub gene network and miRNA-hub gene network identified YY1 as a key TF and hsa-mir-1-3p and hsa-mir-146a-5p as two important miRNAs related to IFI44. IFI44 was identified as a hub gene by validating GSE17755, GSE55235, and GSE13670. Immune cell infiltration analysis showed a strong positive correlation between activated dendritic cells and IFI44 expression.ConclusionsIFI144 was discovered as a shared biomarker and disease target for RA, COVID-19, and SAB by this study. IFI44 negatively regulates the IFN signaling pathway to promote viral replication and bacterial proliferation and is an important molecular target for SARS-CoV-2 and S. aureus immune escape in RA. Dendritic cells play an important role in this process. 1,25-Dihydroxy vitamin D3 may be an important therapeutic agent in treating RA with SARS-CoV-2 and S. aureus infections.

Identification ofITPR1as a Hub Gene of Group 3 Medulloblastoma and Coregulated Genes with Potential Prognostic Values.

The Group 3 Medulloblastoma (Grp3-MB) is an aggressive molecular subtype with a high incidence of metastasis and deaths. In this study, were used an RNA sequencing data (RNA-Seq) from a Brazilian cohort of MBs to identify hub genes associated with the metastatic risk. Data validation were performed by using multiple large datasets from MBs (GSE85217, GSE37418, and EGAS00001001953). DESeq2 package in R software was used to identify the differentially expressed genes (DEGs) in our RNA-Seq data. The DEGs data were accessed to construct the modules/graphs of co-expression and to identify hub genes through Cytoscape platform. The coregulated genes were enriched by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and the protein-protein interaction (PPI) network was visualized by Cytoscape. The Kaplan-Meier plotter and ROC curves were used to validate the diagnostic and prognostic values of specific biomarkers identified through this model. We identified that inositol 1,4,5-trisphosphate receptor type 1 (ITPR1) as a downregulated hub gene, with a high diagnostic accuracy to Grp3-MBs and associated with tumor metastasis. In addition, we identified genes significantly correlated with ITPR1 that were associated with metastasis in Grp3-MB (ATP1A2, MTTL7A, and RGL1) and worst overall survival in MBs (ANTXR1 and RGL1). Our findings suggest that the ITPR1 hub gene is potentially involved in the metastatic process for Grp3-MB. Our data also provide evidence of targets that may serve as prognostic predictors and/or regulators for the metastatic process that maybe explored for further research of individualized therapy to Grp3-MBs.

XlinkCyNET: A Cytoscape Application for Visualization of Protein Interaction Networks Based on Cross-Linking Mass Spectrometry Identifications.

Software tools that allow the visualization and analysis of protein interaction networks are essential for studies in systems biology. One of the most popular network visualization tools in biology is Cytoscape, which offers a great selection of plug-ins for the interpretation of network data. Chemical cross-linking coupled to mass spectrometry (XL-MS) is an increasingly important source for protein interaction data; however, to date, no Cytoscape tools are available to analyze XL-MS results. In light of the suitability of the Cytoscape platform and to expand its toolbox, here we introduce XlinkCyNET, an open-source Cytoscape Java plug-in for exploring large-scale XL-MS-based protein interaction networks. XlinkCyNET offers the rapid and easy visualization of intra- and interprotein cross-links in a rectangular-bar style as well as on the 3D structure, allowing the interrogation of protein interaction networks at the residue level. XlinkCyNET is freely available from the Cytoscape App Store (http://apps.cytoscape.org/apps/xlinkcynet) and at the Liu lab webpage (https://www.theliulab.com/software/xlinkcynet).

Weighted gene correlation network analysis reveals novel biomarkers associated with mesenchymal stromal cell differentiation in early phase.

Osteoporosis is a major public health problem that is associated with high morbidity and mortality, and its prevalence is increasing as the world’s population ages. Therefore, understanding the molecular basis of the disease is becoming a high priority. In this regard, studies have shown that an imbalance in adipogenic and osteogenic differentiation of bone marrow mesenchymal stem cells (MSCs) is associated with osteoporosis. In this study, we conducted a Weighted Gene Co-Expression Network Analysis to identify gene modules associated with the differentiation of bone marrow MSCs. Gene Ontology and Kyoto Encyclopedia of Genes and Genome enrichment analysis showed that the most significant module, the brown module, was enriched with genes involved in cell cycle regulation, which is in line with the initial results published using these data. In addition, the Cytoscape platform was used to identify important hub genes and lncRNAs correlated with the gene modules. Furthermore, differential gene expression analysis identified 157 and 40 genes that were upregulated and downregulated, respectively, after 3 h of MSCs differentiation. Interestingly, regulatory network analysis, and comparison of the differentially expressed genes with those in the brown module identified potential novel biomarker genes, including two transcription factors (ZNF740, FOS) and two hub genes (FOXQ1, SGK1), which were further validated for differential expression in another data set of differentiation of MSCs. Finally, Gene Set Enrichment Analysis suggested that the two most important candidate hub genes are involved in regulatory pathways, such as the JAK-STAT and RAS signaling pathways. In summary, we have revealed new molecular mechanisms of MSCs differentiation and identified novel genes that could be used as potential therapeutic targets for the treatment of osteoporosis.

Application of weighted gene co‑expression network analysis to explore the potential diagnostic biomarkers for colorectal cancer.

Colorectal cancer (CRC) is one of the most common malignant diseases in the world. Although mechanistic studies have been conducted on the pathogenesis of CRC, the molecular mechanism of CRC tumorigenesis remains unclear. In the present study, the weighted gene co-expression network analysis was performed for the Gene Expression Omnibus (GEO) dataset GSE87211, in order to analyze the key modules involved in the pathogenesis of CRC. Next, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on the key module genes to analyze the functional pathways involved. The hub genes were screened using the Cytoscape platform and verified by a second GEO dataset, GSE21510. Finally, 10 hub genes were identified in 2 key modules (the green and brown modules) as the genes most significantly associated with the tumorigenesis of CRC. The 5 hub genes from the green module included collagen type I α1 chain, collagen type XII α1 chain, collagen triple helix repeat containing 1, inhibin subunit βa (INHBA) and chromobox 2 (CBX2), while the 5 hub genes from the brown module included bestrophin 2 (BEST2), carbonic anhydrase 2, glucagon, solute carrier family 4 member 4 and gliomedin. The 2 key modules with the 10 hub genes identified may regulate the occurrence and development of CRC through the extracellular matrix pathway, PI3K-Akt and chemokine signaling pathways, thus providing a reference for understanding the complex mechanism of tumorigenesis in CRC. Of note, few studies have reported the pathogenesis of CRC with the 3 identified hub genes, INHBA, CBX2 and BEST2. Further investigation of the molecular mechanism of these genes in CRC is recommended.