Elucidating the interaction of CF airway epithelial cells and rhinovirus: Using the host-pathogen relationship to identify future therapeutic strategies

© 2018 Ling, Garratt, Lassmann, Stick. Chronic lung disease remains the primary cause of mortality in cystic fibrosis (CF). Growing evidence suggests respiratory viral infections are often more severe in CF compared to healthy peers and contributes to pulmonary exacerbations (PEx) and deterioration of lung function. Rhinovirus is the most prevalent respiratory virus detected, particularly during exacerbations in children with CF < 5 years old. However, even though rhinoviral infections are likely to be one of the factors initiating the onset of CF lung disease, there is no effective targeted treatment. A better understanding of the innate immune responses by CF airway epithelial cells, the primary site of infection for viruses, is needed to identify why viral infections are more severe in CF. The aim of this review is to present the clinical impact of virus infection in both young children and adults with CF, focusing on rhinovirus infection. Previous in vitro and in vivo investigations looking at the mechanisms behind virus infection will also be summarized. The review will finish on the potential of transcriptomics to elucidate the host-pathogen responses by CF airway cells to viral infection and identify novel therapeutic targets

Identification of common key genes and pathways between type 1 diabetes and multiple sclerosis using transcriptome and interactome analysis

Purpose: Type 1 diabetes (T1D) and multiple sclerosis (MS) are classified as T cell-mediated autoimmune diseases. Although convergent evidence proposed common genetic architecture for autoimmune diseases, it remains a challenge to identify them. This study aimed to determine common gene signature and pathways in T1D and MS via systems biology approach. Methods: Gene expression profiles of peripheral blood mononuclear cells (PBMCs) and pancreatic-β cells in T1D as well as PBMCs and cerebrospinal fluid (CSF) in MS were analyzed in our previous published data, and differential expressed genes were integrated with protein�protein interactions data to construct Query�Query PPI (QQPPI) networks. In this study, QQPPI networks were further analyzed to investigate more central genes, functional modules and complexes shared in T1D and MS progression. Lastly, the interaction of common genes with drugs was also explored. Results: Several cytokines such as IL-23A, IL-32, IL-34, and IL-37 tend to be differentially expressed in both diseases. In addition, PSMA1, MYC, SRPK1, YBX1, HNRNPM, NF-κB2, IKBKE, RAC1, FN1, ARRB2, ESR1, HSP90AB1, and PPP1CA were common high central genes in QQPPI networks corresponding to each disease. Proteasome, spliceosome, immune responses, apoptosis, cellular communication/signaling transduction mechanism, interaction with environment, and activity of intercellular mediators were shared biological processes in T1D and MS. Finally, azathioprine, melatonin, resveratrol, and geldanamycin identified as prioritized drugs for the treatment of patients with T1D and MS. Conclusions: This study represented novel key genes and pathways shared between T1D and MS, which may facilitate the identification of potential therapeutic targets in these diseases. © 2020, Springer Science+Business Media, LLC, part of Springer Nature

Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets

Assessment of Post-Radiation Time Effect on Gene Expression Profiles of Saccharomyces cerevisiae Samples After Appling a UV Laser: Effect of UV Laser on Saccharomyces cerevisiae Gene Expression

Introduction: Widespread application of lasers in different fields of medicine implies more investigations into the molecular mechanism of laser effects on the human body. Network analysis of the dysregulated genes of Saccharomyces cerevisiae samples are irradiated by a UV laser and harvested 30 minutes after radiation compared with a 15-minute group is the aim of this research.Methods: The significantly dysregulated genes interacted via the STRING database, and the central nodes were determined by “Networkanalyzer” application of Cytoscape software. The critical genes and the related biological terms were identified via action map analysis and gene ontology assessment.Results: The gene expression profiles of the samples with 30-minute post-radiation time were different from the samples with 15 minutes of post-radiation time. 9 potent central genes, 50% of which were similar to the nodes of the 15-minute group, were identified. The terms “positive regulation of telomere maintenance” were targeted in the two sample groups.Conclusion: In spite of large alterations in the gene expression profiles of the samples, the results indicated that the main affected biological term for the 15-minute and 30-minute groups was similar. DOI:10.34172/jlms.2021.91

EGR1 Is a Critical Gene in Response of Human Keratinocyte to Blue Light Radiation: EGR1 Is a Critical Gene in Response to Blue Light Radiation

Introduction: Investigating the molecular mechanism of cellular response to light radiation has attracted many researchers’ attention. In the present study, the critically affected gene by 1-hour blue light radiation in human keratinocytes was investigated via network analysis.Methods: Gene expression profiles of human keratinocytes exposed to 1-hour blue light radiation plus controls were extracted from Gene Expression Omnibus (GEO). The significantly dysregulated genes plus 100 first neighbors were investigated by Cytoscape software and its applications. The central nodes of the network based on four centrality parameters were determined and discussed.Results: Among 6 significant dysregulated genes, 4 individuals were recognized by the STRING database. The network was constructed by using the 4 queried genes and 100 first neighbors. EGR1, STAT1, and ISG15 were identified as central nodes; however, the prominent role of EGR1 was highlighted.Conclusion: EGR1 appeared as a critically affected gene after blue light irradiation. It seems that this upregulated gene is responsible for protecting human keratinocytes against stress and cancer. Therefore, the application of blue light may be accompanied by antistress effects in the human body. DOI: 10.34172/jlms.2021.83