scholarly journals Evidence of a dysregulated vitamin D endocrine system in SARS-CoV-2 infected patient’s lung cells

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bijesh George ◽  
Revikumar Amjesh ◽  
Aswathy Mary Paul ◽  
T. R. Santhoshkumar ◽  
Madhavan Radhakrishna Pillai ◽  
...  
Keyword(s):  
Vitamin D ◽  
Endocrine System ◽  
Interaction Network ◽  
Lavage Fluid ◽  
Differentially Expressed ◽  
Cytokine Signaling ◽  
Lung Cells ◽  
Protein Protein Interaction ◽  
The Status ◽  
Infected Cells

AbstractAlthough a defective vitamin D endocrine system has been widely suspected to be associated in SARS-CoV-2 pathobiology, the status of the vitamin D endocrine system and vitamin D-modulated genes in lung cells of patients infected with SARS-CoV-2 remains unknown. To understand the significance of the vitamin D endocrine system in SARS-CoV-2 pathobiology, computational approaches were applied to transcriptomic datasets from bronchoalveolar lavage fluid (BALF) cells of such patients or healthy individuals. Levels of vitamin D receptor, retinoid X receptor, and CYP27A1 in BALF cells of patients infected with SARS-CoV-2 were found to be reduced. Additionally, 107 differentially expressed, predominantly downregulated genes, as potentially modulated by vitamin D endocrine system, were identified in transcriptomic datasets from patient’s cells. Further analysis of differentially expressed genes provided eight novel genes with a conserved motif with vitamin D-responsive elements, implying the role of both direct and indirect mechanisms of gene expression by the dysregulated vitamin D endocrine system in SARS-CoV-2-infected cells. Protein–protein interaction network of differentially expressed vitamin D-modulated genes were enriched in the immune system, NF-κB/cytokine signaling, and cell cycle regulation as top predicted pathways that might be affected in the cells of such patients. In brief, the results presented here povide computational evidence to implicate a dysregulated vitamin D endocrine system in the pathobiology of SARS-CoV-2 infection.

scholarly journals Evidence of a dysregulated Vitamin D pathway in SARS-CoV-2 infected patient’s lung cells

2020 ◽  
Author(s):  
Bijesh George ◽  
Ravikumar Amjesh ◽  
Aswathy Mary Paul ◽  
Madhavan Radhakrishna Pillai ◽  
Rakesh Kumar
Keyword(s):  
Vitamin D ◽  
Bronchoalveolar Lavage Fluid ◽  
Lavage Fluid ◽  
Differentially Expressed ◽  
Cytokine Signaling ◽  
Lung Cells ◽  
The Status ◽  
Infected Cells ◽  
Cycle Regulation

AbstractAlthough a defective vitamin D pathway has been widely suspected to be associated in SARS-CoV-2 pathobiology, the status of the vitamin D pathway and vitamin D-modulated genes in lung cells of patients infected with SARS-CoV-2 remains unknown. To understand the significance of the vitamin D pathway in SARS-CoV-2 pathobiology, computational approaches were applied to transcriptomic datasets from bronchoalveolar lavage fluid (BALF) cells of such patients or healthy individuals. Levels of vitamin D receptor, retinoid X receptor, and CYP27A1 in BALF cells of patients infected with SARS-CoV-2 were found to be reduced. Additionally, 107 differentially expressed, predominantly downregulated genes modulated by vitamin D were identified in transcriptomic datasets from patient’s cells. Further analysis of differentially expressed genes provided eight novel genes with a conserved motif with vitamin D-responsive elements, implying the role of both direct and indirect mechanisms of gene expression by the dysregulated vitamin D pathway in SARS-CoV-2-infected cells. Network analysis of differentially expressed vitamin D-modulated genes identified pathways in the immune system, NF-κB/cytokine signaling, and cell cycle regulation as top predicted pathways that might be affected in the cells of such patients. In brief, the results provided computational evidence to implicate a dysregulated vitamin D pathway in the pathobiology of SARS-CoV-2 infection.

scholarly journals Neutrophil Involvement in Covid-19

2020 ◽  
Author(s):  
Athanasios Didangelos
Keyword(s):  
Interaction Network ◽  
Lavage Fluid ◽  
Lung Epithelial Cells ◽  
Organ Injury ◽  
Rna Seq ◽  
Protein Protein Interaction ◽  
Associated Proteins ◽  
Infected Cells ◽  
Neutrophil Response

Covid-19 is often related to hyperinflammation that drives lung or multi-organ injury. The immunopathological mechanisms that cause excessive inflammation following SARS-Cov-2 infection are under investigation while different approaches to limit hyperinflammation in affected patients are being proposed. Here, a computational protein-protein interaction network approach was used on recently available data to identify possible Covid-19 inflammatory mechanisms and bioactive genes. First, network analysis of putative SARS-Cov-2 cellular receptors and their directly associated proteins, led to the mining of a robust neutrophil response signature and multiple relevant inflammatory genes. Second, analysis of RNA-seq datasets of lung epithelial cells infected with SARS-Cov-2 revealed that infected cells specifically expressed neutrophil-attracting chemokines, further supporting the likely role of neutrophils in Covid-19 inflammation. Third, analysis of RNA-seq datasets of bronchoalveolar lavage fluid from Covid-19 patients, identified neutrophil-specific genes and chemokines. Different immunoregulatory and neutrophil-relevant molecules mined here such as, TNFR, IL8, CXCR1, CXCR2, ADAM10, GPR84, MME-neprilysin, ANPEP and LAP3 are druggable and might be therapeutic targets in efforts to limit SARS-Cov-2 inflammation in severe clinical cases. The role of neutrophils in Covid-19 needs to be studied further.

Bioinformatics Analysis Reveals Functions of MicroRNAs in Rice Under the Drought Stress

2021 ◽  
Vol 15 (8) ◽  
pp. 927-936 ◽  
Author(s):  
Yan Peng ◽  
Yuewu Liu ◽  
Xinbo Chen
Keyword(s):  
Drought Stress ◽  
Target Genes ◽  
Hot Spot ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Promising Tool ◽  
Differentially Expressed Mirnas ◽  
Aba Biosynthesis

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Method: In this study, we integrated miRNAs and genes transcriptome data of rice under the drought stress. Some bioinformatics methods were used to reveal the functions of miRNAs in rice under drought stress. These methods included target genes identification, differentially expressed miRNAs screening, enrichment analysis of DEGs, network constructions for miRNA-target and target-target proteins interaction. Results: (1) A total of 229 miRNAs with differential expression in rice under the drought stress, corresponding to 73 rice miRNAs families, were identified. (2) 1035 differentially expressed genes (DEGs) were identified, which included 357 up-regulated genes, 542 down-regulated genes and 136 up/down-regulated genes. (3) The network of regulatory relationships between 73 rice miRNAs families and 1035 DEGs was constructed. (4) 25 UP_KEYWORDS terms of DEGs, 125 GO terms and 7 pathways were obtained. (5) The protein-protein interaction network of 1035 DEGs was constructed. Conclusion: (1) MiRNA-regulated targets in rice might mainly involve in a series of basic biological processes and pathways under drought conditions. (2) MiRNAs in rice might play critical roles in Lignin degradation and ABA biosynthesis. (3) MiRNAs in rice might play an important role in drought signal perceiving and transduction.

Extracting Biological Significant Subnetworks from Protein-Protein Interactions Induced by Differentially Expressed Genes of HIV-1 Vpr Variants

2015 ◽  
Vol 4 (4) ◽  
pp. 35-51 ◽  
Author(s):  
Bandana Barman ◽  
Anirban Mukhopadhyay
Keyword(s):  
Differentially Expressed Genes ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Differentially Expressed ◽  
Wild Type ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Hiv 1

Identification of protein interaction network is very important to find the cell signaling pathway for a particular disease. The authors have found the differentially expressed genes between two sample groups of HIV-1. Samples are wild type HIV-1 Vpr and HIV-1 mutant Vpr. They did statistical t-test and found false discovery rate (FDR) to identify the genes increased in expression (up-regulated) or decreased in expression (down-regulated). In the test, the authors have computed q-values of test to identify minimum FDR which occurs. As a result they found 172 differentially expressed genes between their sample wild type HIV-1 Vpr and HIV-1 mutant Vpr, R80A. They found 68 up-regulated genes and 104 down-regulated genes. From the 172 differentially expressed genes the authors found protein-protein interaction network with string-db and then clustered (subnetworks) the PPI networks with cytoscape3.0. Lastly, the authors studied significance of subnetworks with performing gene ontology and also studied the KEGG pathway of those subnetworks.

Uncovering potential lncRNAs and nearby mRNAs in systemic lupus erythematosus from the Gene Expression Omnibus dataset

Epigenomics ◽  
2019 ◽  
Vol 11 (16) ◽  
pp. 1795-1809 ◽  
Author(s):  
Haiyu Cao ◽  
Dong Li ◽  
Huixiu Lu ◽  
Jing Sun ◽  
Haibin Li
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Noncoding Rnas ◽  
Interaction Network ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Systemic Lupus ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

Aim: The aim of this study was to find potential differentially expressed long noncoding RNAs (lncRNAs) and mRNAs in systemic lupus erythematosus. Materials & methods: Differentially expressed lncRNAs and mRNAs were obtained in the Gene Expression Omnibus dataset. Functional annotation of differentially expressed mRNAs was performed, followed by protein–protein interaction network analysis. Then, the interaction network of lncRNA-nearby targeted mRNA was built. Results: Several interaction pairs of lncRNA-nearby targeted mRNA including NRIR-RSAD2, RP11-153M7.5-TLR2, RP4-758J18.2-CCNL2, RP11-69E11.4-PABPC4 and RP11-496I9.1-IRF7/ HRAS/ PHRF1 were identified. Measles and MAPK were significantly enriched signaling pathways of differentially expressed mRNAs. Conclusion: Our study identified several differentially expressed lncRNAs and mRNAs. And their interactions may play a crucial role in the process of systemic lupus erythematosus.

scholarly journals Hub Genes Related to the Pathogenesis and Progression of Colorectal Cancer and Adenoma by Integrative Bioinformatics Approaches

2021 ◽  
Author(s):  
Yuxuan HUANG ◽  
Ge CUI
Keyword(s):  
Colorectal Cancer ◽  
Cell Cycle ◽  
Differentially Expressed Genes ◽  
Protein Interaction ◽  
Biological Networks ◽  
Interaction Network ◽  
Differentially Expressed ◽  
Venn Diagram ◽  
Hub Genes ◽  
Protein Protein Interaction

Abstract Aims: To utilize the bioinformatics to analyze the differentially expressed genes (DEGs), interaction proteins, perform gene enrichment analysis, protein-protein interaction network (PPI) and map the hub genes between colorectal cancer(CRC) and colorectal adenocarcinomas(CA).Methods: We analyzed a microarray dataset (GSE32323 and GSE4183) from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in tumor tissues and non-cancerous tissues were identified using the dplyr and Venn diagram packages of the R Studio software. Functional annotation of the DEGs was performed using the Gene Ontology (GO) website. Pathway enrichment (KEGG) used the WebGestalt to analyze the data and R Studio to generate the graph. We constructed a protein–protein interaction (PPI) network of DEGs using STRING and Cytoscape software was used for visualization. Survival analysis of the hub genes and was performed using the online platform GEPIA to determine the prognostic value of the expression of hub genes in cell lines from CRC patients. The expression of molecules with prognostic values was validated on the UALCAN database. The expression of hub genes was examined using the Human Protein Atlas. Results: Applying the GEO2R analysis and R studio, we identified a total of 471 upregulated and 278 downregulated DEGs. By using the online database WebGestalt, we identified the most relevant biological networks involving DEGs with statistically significant differences in expression were mainly associated with biological processes involved in the cell proliferation, cell cycle transition, cell homeostasis and indicated the role of each DEGs in cell cycle regulation pathways. We found 10 hub genes with prognostic values were overexpressed in the CRC and CA samples.Conclusion: we found out ten hub genes and three core genes closely associated with the pathogenesis and prognosis of CRC and CA, which is of great significance for colorectal tumor early detection and prognosis evaluation.

scholarly journals Integrated analyses of long noncoding RNAs and mRNAs in the progression of breast cancer

2021 ◽  
Vol 49 (9) ◽  
pp. 030006052097313
Author(s):  
Jingyun Guo ◽  
Huining Lian ◽  
Minfeng Liu ◽  
Jianyu Dong ◽  
Zhaoze Guo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Noncoding Rna ◽  
Interaction Network ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Biological Regulation ◽  
Invasion And Migration ◽  
Protein Protein Interaction ◽  
Biological Adhesion ◽  
And Migration

Objective The objective was to explore the expression and potential functions of long noncoding RNA (lncRNA) and mRNAs in human breast cancer (BC). Methods Differentially expressed lncRNAs and mRNAs were identified and annotated in BC tissues by using the Agilent human lncRNA assay (Agilent Technologies, Santa Clara, CA, USA) and RNA sequencing. After identification of lncRNAs and mRNAs through quantitative reverse transcription polymerase chain reaction, we conducted a series of functional experiments to confirm the effects of knockdown of one lncRNA, TCONS_00029809, on the progression of BC. Results We discovered 238 lncRNAs and 200 mRNAs that were differentially expressed in BC tissues and para-carcinoma tissue. We showed that differentially expressed mRNAs were related to biological adhesion and biological regulation and mainly enriched in cytokine-cytokine receptor interaction, metabolic pathways, and PI3K-Akt signaling pathway. We created a protein–protein interaction network to analyze the proteins enriched in these pathways. We demonstrated that silencing of TCONS_00029809 remarkably inhibited proliferation, invasion, and migration of BC cells, and accelerated their apoptosis. Conclusions We identified a large number of differentially expressed lncRNAs and mRNAs, which provide data useful in understanding BC carcinogenesis. The lncRNA TCONS_00029809 may be involved in the development of BC.

scholarly journals Integrated analysis of the miRNA-mRNA network associated with LMP1 gene in nasopharyngeal carcinoma

2019 ◽  
Author(s):  
Yang Yang ◽  
Wen Liu ◽  
Yan Zhang ◽  
Shuo Wu ◽  
Bing Luo
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Expression Profiles ◽  
Interaction Network ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Protein Protein Interaction ◽  
Barr Virus ◽  
Lmp1 Gene ◽  
Epstein Barr

AbstractEpstein-Barr virus oncogenic latent membrane protein 1 (LMP1) has been known to play important roles in nasopharyngeal carcinoma (NPC). LMP1 gene also induced a variety of microRNAs (miRNAs) which bear pivotal roles in regulation of mRNAs expression. However, little was known about the global change of mRNAs and miRNAs induced by LMP1 gene in NPC. In our study, one NPC tissue microarray profile and two LMP1-associated microarray expression profiles data were downloaded from the Gene Expression Omnibus database. A protein-protein interaction network was constructed by using bioinformatics platform Gene-Cloud of Biotechnology Information (GCBI). 78 differentially expressed miRNAs and 3322 differentially expressed genes were identified in order to generate a macroscopic network between miRNAs and mRNAs associated with LMP1 gene. In addition, two significant models were generated to illustrate the expression tendency. Our study provided a way to reveal the interaction between miRNAs and mRNAs in LMP1 axis, bringing insights into the pathogenesis of NPC.

scholarly journals PCV2 Regulates Cellular Inflammatory Responses through Dysregulating Cellular miRNA-mRNA Networks

Viruses ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1055 ◽  
Author(s):  
Chang Li ◽  
Yumei Sun ◽  
Jing Li ◽  
Changsheng Jiang ◽  
Wei Zeng ◽  
...  
Keyword(s):  
Data Analysis ◽  
Inflammatory Responses ◽  
Interaction Network ◽  
Porcine Circovirus Type ◽  
Pcv2 Infection ◽  
Porcine Circovirus ◽  
Cytokine Signaling ◽  
Cellular Inflammatory Response ◽  
Infected Cells

Porcine circovirus type 2 (PCV2) is closely linked to postweaning multisystemic wasting syndrome (PMWS) and other PCV-associated diseases (PCVADs), which influence the global pig industry. MicroRNAs (miRNAs) are evolutionarily conserved classes of endogenous small non-coding RNA that regulate almost every cellular process. According to our previous transcription study, PCV2 infection causes up-regulation of genes related to inflammation. To reveal the function of miRNAs in PCV2 infection and PCV2-encoded miRNAs, next generation sequencing and data analysis was performed to explore miRNA expression in PCV2-infected cells and non-infected cells. Data analysis found some small RNAs matched the PCV2 genome but PCV2 does not express miRNAs in an in vitro infection (PK-15 cells). More than 297 known and 427 novel miRNAs were identified, of which 44 miRNAs were differently expressed (DE). The pathways of inflammation mediated by chemokine and cytokine signaling pathway (P00031), were more perturbed in PCV2-infected cells than in mock controls. DE miRNAs and DE mRNA interaction network clearly revealed that PCV2 regulates the cellular inflammatory response through dysregulating the cellular miRNA-mRNA network. MiRNA overexpression and down-expression results demonstrated that miRNA dysregulation could affect PCV2 infection-induced cellular inflammatory responses. Our study revealed that host miRNA can be dysregulated by PCV2 infection and play an important role in PCV2-modulated inflammation.

scholarly journals PIGNON: a protein–protein interaction-guided functional enrichment analysis for quantitative proteomics

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rachel Nadeau ◽  
Anastasiia Byvsheva ◽  
Mathieu Lavallée-Adam
Keyword(s):  
Breast Cancer ◽  
Protein Interaction ◽  
Quantitative Proteomics ◽  
Interaction Network ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Experimental Conditions ◽  
Cancer Subtypes ◽  
Functional Annotations ◽  
Protein Protein Interaction

Abstract Background Quantitative proteomics studies are often used to detect proteins that are differentially expressed across different experimental conditions. Functional enrichment analyses are then typically used to detect annotations, such as biological processes that are significantly enriched among such differentially expressed proteins to provide insights into the molecular impacts of the studied conditions. While common, this analytical pipeline often heavily relies on arbitrary thresholds of significance. However, a functional annotation may be dysregulated in a given experimental condition, while none, or very few of its proteins may be individually considered to be significantly differentially expressed. Such an annotation would therefore be missed by standard approaches. Results Herein, we propose a novel graph theory-based method, PIGNON, for the detection of differentially expressed functional annotations in different conditions. PIGNON does not assess the statistical significance of the differential expression of individual proteins, but rather maps protein differential expression levels onto a protein–protein interaction network and measures the clustering of proteins from a given functional annotation within the network. This process allows the detection of functional annotations for which the proteins are differentially expressed and grouped in the network. A Monte-Carlo sampling approach is used to assess the clustering significance of proteins in an expression-weighted network. When applied to a quantitative proteomics analysis of different molecular subtypes of breast cancer, PIGNON detects Gene Ontology terms that are both significantly clustered in a protein–protein interaction network and differentially expressed across different breast cancer subtypes. PIGNON identified functional annotations that are dysregulated and clustered within the network between the HER2+, triple negative and hormone receptor positive subtypes. We show that PIGNON’s results are complementary to those of state-of-the-art functional enrichment analyses and that it highlights functional annotations missed by standard approaches. Furthermore, PIGNON detects functional annotations that have been previously associated with specific breast cancer subtypes. Conclusion PIGNON provides an alternative to functional enrichment analyses and a more comprehensive characterization of quantitative datasets. Hence, it contributes to yielding a better understanding of dysregulated functions and processes in biological samples under different experimental conditions.

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