Regulatory network analysis of Epstein-Barr virus identifies functional modules and hub genes involved in infectious mononucleosis

© 2017, Springer-Verlag Wien.Epstein-Barr virus (EBV) is the most common cause of infectious mononucleosis (IM) and establishes lifetime infection associated with a variety of cancers and autoimmune diseases. The aim of this study was to develop an integrative gene regulatory network (GRN) approach and overlying gene expression data to identify the representative subnetworks for IM and EBV latent infection (LI). After identifying differentially expressed genes (DEGs) in both IM and LI gene expression profiles, functional annotations were applied using gene ontology (GO) and BiNGO tools, and construction of GRNs, topological analysis and identification of modules were carried out using several plugins of Cytoscape. In parallel, a human-EBV GRN was generated using the Hu-Vir database for further analyses. Our analysis revealed that the majority of DEGs in both IM and LI were involved in cell-cycle and DNA repair processes. However, these genes showed a significant negative correlation in the IM and LI states. Furthermore, cyclin-dependent kinase 2 (CDK2) – a hub gene with the highest centrality score – appeared to be the key player in cell cycle regulation in IM disease. The most significant functional modules in the IM and LI states were involved in the regulation of the cell cycle and apoptosis, respectively. Human-EBV network analysis revealed several direct targets of EBV proteins during IM disease. Our study provides an important first report on the response to IM/LI EBV infection in humans. An important aspect of our data was the upregulation of genes associated with cell cycle progression and proliferation

Integrated analysis of gene expression profiles reveals deregulation of the immune response genes during different phases of chronic hepatitis B infection

© 2017, Kowsar Corp.Background: The natural history of chronic hepatitis B (CHB) infection is divided into different phases including immune tolerance (IT), immune clearance (or immune active [IA]), inactive carrier (IC), and reactivation. Despite utilizing high-throughput data, the distinct immunological mechanisms of these phases have been insufficiently investigated. Objectives: The aim of the present study was to determine candidate disease-associated genes and significantly altered biological processes for each phase of CHB infection. Methods: The gene expression profiles of 83 CHB patients (22 IT, 50 IA, and 11 IC phases) were obtained from gene expression omnibus (GEO dataset: GSE65359) and analyzed by bioinformatics tools. Several plugins of Cytoscape software were used to construct protein-protein interaction (PPI) networks and measure their topological properties. Subsequently, functional annotation and signaling pathway enrichment were carried out using the database for annotation, visualization and integrated discovery (DAVID) and Kyoto encyclopedia of genes and genomes (KEGG). Results: 449 and 452 deregulated genes were identified in IT-IA and IA-IC patients, respectively. Gene ontology and KEGG pathway analyses showed that several immune response-associated genes and signaling pathways (i.e. cytokine-cytokine receptor interaction, chemokine signaling pathway and T cell receptor signalling pathway) were upregulated in the IA phase, but downregulated in the IC phase. The LCK (encoding a tyrosine kinase) was determined as the most important hub gene of both constructed PPI networks. Furthermore, other immune response-associated genes such as CXCR3, VCAN, MYC, and STAT1 were found to be the important hub genes in clinical phases of CHB. Conclusions: The immune response-related pathways were found to be up and downregulated in the immune clearance phase and inactive carrier phase of CHB, respectively. The LCK hub gene might help the pathogenesis of different phases of CHB and serve as a therapeutic target for the treatment of hepatitis B virus

A network analysis of the Internet Disorder Scale–Short Form (IDS9-SF): a large-scale cross-cultural study in Iran, Pakistan, and Bangladesh

The Internet Disorder Scale–Short Form (IDS9-SF) is a validated instrument assessing internet disorder which modified the internet gaming disorder criteria proposed in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). However, the relationships between the nine items in the IDS9-SF are rarely investigated. The present study used network analysis to investigate the features of the IDS9-SF among three populations in Bangladesh, Iran, and Pakistan. Data were collected (N = 1901; 957 [50.3%] females; 666 [35.0%] Pakistani, 533 [28.1%] Bangladesh, and 702 [36.9%] Iranians) using an online survey platform (e.g., Google Forms). All the participants completed the IDS9-SF. The central-stability-coefficients of the nine IDS9-SF items were 0.71, 0.89, 0.96, 0.98, 0.98, 1.00, 0.67, 0.79, and 0.91, respectively. The node centrality was stable and interpretable in the network. The Network Comparison Test (NCT) showed that the network structure had no significant differences among Pakistani, Bangladeshi, and Iranian participants (p-values = 0.172 to 0.371). Researchers may also use the IDS9-SF to estimate underlying internet addiction for their target participants and further explore and investigate the phenomenon related to internet addiction. Li Li, Mohammed A. Mamun, Firoj Al-Mamun, Irfan Ullah, Ismail Hosen, Syed Ahsan Zia, Ali Poorebrahim, Morteza Pourgholami, Chung-Ying Lin, Halley M. Pontes, Mark D. Griffiths & Amir H. Pakpou

Topological analysis of regulatory networks reveals functionally key genes and miRNAs involved in the differentiation of mesenchymal stem cells

Background: The details of molecular mechanisms underlying the differentiation of Mesenchymal Stem Cells (MSCs) into specific lineages are not well understood. Objectives: We aimed to construct the interactome network and topology analysis of bone marrow mesenchymal stem cell of CAGE data. Applying the enrichment results, we wanted to introduce the common genes and hub-microRNA and hub-genes of these giant network. Materials and Methods: In this study, we constructed gene regulatory networks for each non-mesenchymal cell lineage according to their gene expression profiles obtained from FANTOM5 database. The putative interactions of TF-gene and protein-protein were determined using TRED, STRING, HPRD and GeneMANIA servers. In parallel, a regulatory network including corresponding miRNAs and total differentially expressed genes (DEGs) was constructed for each cell lineage. Results: The results indicated that analysis of networks’ topology can significantly distinguish the hub regulatory genes and miRNAs involved in the differentiation of MSCs. The functional annotation of identified hub genes and miRNAs revealed that several signal transduction pathways i.e. AKT, WNT and TGFβ and cell proliferation related pathways play a pivotal role in the regulation of MSCs differentiation. We also classified cell lineages into two groups based on their predicted miRNA profiles. Conclusions: In conclusion, we found a number of hub genes and miRNAs which seem to have key regulatory functions during differentiation of MSCs. Our results also introduce a number of new regulatory genes and miRNAs which can be considered as the new candidates for genetic manipulation of MSCs in vitro

Regulatory network analysis of Epstein-Barr virus identifies functional modules and hub genes involved in infectious mononucleosis

© 2017 Springer-Verlag WienEpstein-Barr virus (EBV) is the most common cause of infectious mononucleosis (IM) and establishes lifetime infection associated with a variety of cancers and autoimmune diseases. The aim of this study was to develop an integrative gene regulatory network (GRN) approach and overlying gene expression data to identify the representative subnetworks for IM and EBV latent infection (LI). After identifying differentially expressed genes (DEGs) in both IM and LI gene expression profiles, functional annotations were applied using gene ontology (GO) and BiNGO tools, and construction of GRNs, topological analysis and identification of modules were carried out using several plugins of Cytoscape. In parallel, a human-EBV GRN was generated using the Hu-Vir database for further analyses. Our analysis revealed that the majority of DEGs in both IM and LI were involved in cell-cycle and DNA repair processes. However, these genes showed a significant negative correlation in the IM and LI states. Furthermore, cyclin-dependent kinase 2 (CDK2) – a hub gene with the highest centrality score – appeared to be the key player in cell cycle regulation in IM disease. The most significant functional modules in the IM and LI states were involved in the regulation of the cell cycle and apoptosis, respectively. Human-EBV network analysis revealed several direct targets of EBV proteins during IM disease. Our study provides an important first report on the response to IM/LI EBV infection in humans. An important aspect of our data was the upregulation of genes associated with cell cycle progression and proliferation

Integrated analysis of gene expression profiles reveals deregulation of the immune response genes during different phases of chronic hepatitis B infection

© 2017, Kowsar Corp.Background: The natural history of chronic hepatitis B (CHB) infection is divided into different phases including immune tolerance (IT), immune clearance (or immune active [IA]), inactive carrier (IC), and reactivation. Despite utilizing high-throughput data, the distinct immunological mechanisms of these phases have been insufficiently investigated. Objectives: The aim of the present study was to determine candidate disease-associated genes and significantly altered biological processes for each phase of CHB infection. Methods: The gene expression profiles of 83 CHB patients (22 IT, 50 IA, and 11 IC phases) were obtained from gene expression omnibus (GEO dataset: GSE65359) and analyzed by bioinformatics tools. Several plugins of Cytoscape software were used to construct protein-protein interaction (PPI) networks and measure their topological properties. Subsequently, functional annotation and signaling pathway enrichment were carried out using the database for annotation, visualization and integrated discovery (DAVID) and Kyoto encyclopedia of genes and genomes (KEGG). Results: 449 and 452 deregulated genes were identified in IT-IA and IA-IC patients, respectively. Gene ontology and KEGG pathway analyses showed that several immune response-associated genes and signaling pathways (i.e. cytokine-cytokine receptor interaction, chemokine signaling pathway and T cell receptor signalling pathway) were upregulated in the IA phase, but downregulated in the IC phase. The LCK (encoding a tyrosine kinase) was determined as the most important hub gene of both constructed PPI networks. Furthermore, other immune response-associated genes such as CXCR3, VCAN, MYC, and STAT1 were found to be the important hub genes in clinical phases of CHB. Conclusions: The immune response-related pathways were found to be up and downregulated in the immune clearance phase and inactive carrier phase of CHB, respectively. The LCK hub gene might help the pathogenesis of different phases of CHB and serve as a therapeutic target for the treatment of hepatitis B virus

Regulatory network analysis of Epstein-Barr virus identifies functional modules and hub genes involved in infectious mononucleosis

© 2017, Springer-Verlag Wien.Epstein-Barr virus (EBV) is the most common cause of infectious mononucleosis (IM) and establishes lifetime infection associated with a variety of cancers and autoimmune diseases. The aim of this study was to develop an integrative gene regulatory network (GRN) approach and overlying gene expression data to identify the representative subnetworks for IM and EBV latent infection (LI). After identifying differentially expressed genes (DEGs) in both IM and LI gene expression profiles, functional annotations were applied using gene ontology (GO) and BiNGO tools, and construction of GRNs, topological analysis and identification of modules were carried out using several plugins of Cytoscape. In parallel, a human-EBV GRN was generated using the Hu-Vir database for further analyses. Our analysis revealed that the majority of DEGs in both IM and LI were involved in cell-cycle and DNA repair processes. However, these genes showed a significant negative correlation in the IM and LI states. Furthermore, cyclin-dependent kinase 2 (CDK2) – a hub gene with the highest centrality score – appeared to be the key player in cell cycle regulation in IM disease. The most significant functional modules in the IM and LI states were involved in the regulation of the cell cycle and apoptosis, respectively. Human-EBV network analysis revealed several direct targets of EBV proteins during IM disease. Our study provides an important first report on the response to IM/LI EBV infection in humans. An important aspect of our data was the upregulation of genes associated with cell cycle progression and proliferation

Integrated analysis of gene expression profiles reveals deregulation of the immune response genes during different phases of chronic hepatitis B infection

© 2017, Kowsar Corp.Background: The natural history of chronic hepatitis B (CHB) infection is divided into different phases including immune tolerance (IT), immune clearance (or immune active [IA]), inactive carrier (IC), and reactivation. Despite utilizing high-throughput data, the distinct immunological mechanisms of these phases have been insufficiently investigated. Objectives: The aim of the present study was to determine candidate disease-associated genes and significantly altered biological processes for each phase of CHB infection. Methods: The gene expression profiles of 83 CHB patients (22 IT, 50 IA, and 11 IC phases) were obtained from gene expression omnibus (GEO dataset: GSE65359) and analyzed by bioinformatics tools. Several plugins of Cytoscape software were used to construct protein-protein interaction (PPI) networks and measure their topological properties. Subsequently, functional annotation and signaling pathway enrichment were carried out using the database for annotation, visualization and integrated discovery (DAVID) and Kyoto encyclopedia of genes and genomes (KEGG). Results: 449 and 452 deregulated genes were identified in IT-IA and IA-IC patients, respectively. Gene ontology and KEGG pathway analyses showed that several immune response-associated genes and signaling pathways (i.e. cytokine-cytokine receptor interaction, chemokine signaling pathway and T cell receptor signalling pathway) were upregulated in the IA phase, but downregulated in the IC phase. The LCK (encoding a tyrosine kinase) was determined as the most important hub gene of both constructed PPI networks. Furthermore, other immune response-associated genes such as CXCR3, VCAN, MYC, and STAT1 were found to be the important hub genes in clinical phases of CHB. Conclusions: The immune response-related pathways were found to be up and downregulated in the immune clearance phase and inactive carrier phase of CHB, respectively. The LCK hub gene might help the pathogenesis of different phases of CHB and serve as a therapeutic target for the treatment of hepatitis B virus

Integrated analysis of gene expression profiles reveals deregulation of the immune response genes during different phases of chronic hepatitis B infection

© 2017, Kowsar Corp.Background: The natural history of chronic hepatitis B (CHB) infection is divided into different phases including immune tolerance (IT), immune clearance (or immune active [IA]), inactive carrier (IC), and reactivation. Despite utilizing high-throughput data, the distinct immunological mechanisms of these phases have been insufficiently investigated. Objectives: The aim of the present study was to determine candidate disease-associated genes and significantly altered biological processes for each phase of CHB infection. Methods: The gene expression profiles of 83 CHB patients (22 IT, 50 IA, and 11 IC phases) were obtained from gene expression omnibus (GEO dataset: GSE65359) and analyzed by bioinformatics tools. Several plugins of Cytoscape software were used to construct protein-protein interaction (PPI) networks and measure their topological properties. Subsequently, functional annotation and signaling pathway enrichment were carried out using the database for annotation, visualization and integrated discovery (DAVID) and Kyoto encyclopedia of genes and genomes (KEGG). Results: 449 and 452 deregulated genes were identified in IT-IA and IA-IC patients, respectively. Gene ontology and KEGG pathway analyses showed that several immune response-associated genes and signaling pathways (i.e. cytokine-cytokine receptor interaction, chemokine signaling pathway and T cell receptor signalling pathway) were upregulated in the IA phase, but downregulated in the IC phase. The LCK (encoding a tyrosine kinase) was determined as the most important hub gene of both constructed PPI networks. Furthermore, other immune response-associated genes such as CXCR3, VCAN, MYC, and STAT1 were found to be the important hub genes in clinical phases of CHB. Conclusions: The immune response-related pathways were found to be up and downregulated in the immune clearance phase and inactive carrier phase of CHB, respectively. The LCK hub gene might help the pathogenesis of different phases of CHB and serve as a therapeutic target for the treatment of hepatitis B virus

Regulatory network analysis of Epstein-Barr virus identifies functional modules and hub genes involved in infectious mononucleosis

© 2017, Springer-Verlag Wien.Epstein-Barr virus (EBV) is the most common cause of infectious mononucleosis (IM) and establishes lifetime infection associated with a variety of cancers and autoimmune diseases. The aim of this study was to develop an integrative gene regulatory network (GRN) approach and overlying gene expression data to identify the representative subnetworks for IM and EBV latent infection (LI). After identifying differentially expressed genes (DEGs) in both IM and LI gene expression profiles, functional annotations were applied using gene ontology (GO) and BiNGO tools, and construction of GRNs, topological analysis and identification of modules were carried out using several plugins of Cytoscape. In parallel, a human-EBV GRN was generated using the Hu-Vir database for further analyses. Our analysis revealed that the majority of DEGs in both IM and LI were involved in cell-cycle and DNA repair processes. However, these genes showed a significant negative correlation in the IM and LI states. Furthermore, cyclin-dependent kinase 2 (CDK2) – a hub gene with the highest centrality score – appeared to be the key player in cell cycle regulation in IM disease. The most significant functional modules in the IM and LI states were involved in the regulation of the cell cycle and apoptosis, respectively. Human-EBV network analysis revealed several direct targets of EBV proteins during IM disease. Our study provides an important first report on the response to IM/LI EBV infection in humans. An important aspect of our data was the upregulation of genes associated with cell cycle progression and proliferation