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1.
Front Immunol ; 12: 789317, 2021.
Article in English | MEDLINE | ID: covidwho-1593957

ABSTRACT

Background: The recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches. Methods: RNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules. Results: Based on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19's main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis. Conclusion: This study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic.


Subject(s)
COVID-19/genetics , Gene Expression Profiling/methods , Signal Transduction/genetics , Transcription Factors/genetics , Transcriptome/genetics , COVID-19/epidemiology , COVID-19/virology , Cluster Analysis , Gene Ontology , Gene Regulatory Networks , Humans , Immunity/genetics , Models, Genetic , Pandemics , Protein Interaction Maps/genetics , SARS-CoV-2/physiology
2.
Front Immunol ; 12: 724936, 2021.
Article in English | MEDLINE | ID: covidwho-1592205

ABSTRACT

The COVID-19 pandemic has created an urgent situation throughout the globe. Therefore, it is necessary to identify the differentially expressed genes (DEGs) in COVID-19 patients to understand disease pathogenesis and the genetic factor(s) responsible for inter-individual variability. The DEGs will help understand the disease's potential underlying molecular mechanisms and genetic characteristics, including the regulatory genes associated with immune response elements and protective immunity. This study aimed to determine the DEGs in mild and severe COVID-19 patients versus healthy controls. The Agilent-085982 Arraystar human lncRNA V5 microarray GEO dataset (GSE164805 dataset) was used for this study. We used statistical tools to identify the DEGs. Our 15 human samples dataset was divided into three groups: mild, severe COVID-19 patients and healthy control volunteers. We compared our result with three other published gene expression studies of COVID-19 patients. Along with significant DEGs, we developed an interactome map, a protein-protein interaction (PPI) pattern, a cluster analysis of the PPI network, and pathway enrichment analysis. We also performed the same analyses with the top-ranked genes from the three other COVID-19 gene expression studies. We also identified differentially expressed lncRNA genes and constructed protein-coding DEG-lncRNA co-expression networks. We attempted to identify the regulatory genes related to immune response elements and protective immunity. We prioritized the most significant 29 protein-coding DEGs. Our analyses showed that several DEGs were involved in forming interactome maps, PPI networks, and cluster formation, similar to the results obtained using data from the protein-coding genes from other investigations. Interestingly we found six lncRNAs (TALAM1, DLEU2, and UICLM CASC18, SNHG20, and GNAS) involved in the protein-coding DEG-lncRNA network; which might be served as potential biomarkers for COVID-19 patients. We also identified three regulatory genes from our study and 44 regulatory genes from the other investigations related to immune response elements and protective immunity. We were able to map the regulatory genes associated with immune elements and identify the virogenomic responses involved in protective immunity against SARS-CoV-2 infection during COVID-19 development.


Subject(s)
COVID-19/genetics , Gene Expression Profiling/methods , Gene Expression Regulation , Immunity/genetics , Aged , COVID-19/epidemiology , COVID-19/immunology , Female , Gene Ontology , Gene Regulatory Networks , Humans , Male , Middle Aged , Pandemics/prevention & control , Protein Interaction Maps/genetics , SARS-CoV-2/immunology , SARS-CoV-2/physiology , Signal Transduction/genetics , Signal Transduction/immunology
3.
Cells ; 10(12)2021 12 10.
Article in English | MEDLINE | ID: covidwho-1572376

ABSTRACT

To assess the biology of the lethal endpoint in patients with SARS-CoV-2 infection, we compared the transcriptional response to the virus in patients who survived or died during severe COVID-19. We applied gene expression profiling to generate transcriptional signatures for peripheral blood mononuclear cells (PBMCs) from patients with SARS-CoV-2 infection at the time when they were placed in the Intensive Care Unit of the Pavlov First State Medical University of St. Petersburg (Russia). Three different bioinformatics approaches to RNA-seq analysis identified a downregulation of three common pathways in survivors compared with nonsurvivors among patients with severe COVID-19, namely, low-density lipoprotein (LDL) particle receptor activity (GO:0005041), important for maintaining cholesterol homeostasis, leukocyte differentiation (GO:0002521), and cargo receptor activity (GO:0038024). Specifically, PBMCs from surviving patients were characterized by reduced expression of PPARG, CD36, STAB1, ITGAV, and ANXA2. Taken together, our findings suggest that LDL particle receptor pathway activity in patients with COVID-19 infection is associated with poor disease prognosis.


Subject(s)
COVID-19/genetics , Down-Regulation/genetics , Gene Expression Profiling , Receptors, LDL/genetics , Aged , COVID-19/virology , Gene Ontology , Gene Regulatory Networks , Humans , Leukocytes, Mononuclear/metabolism , Male , Middle Aged , RNA-Seq , SARS-CoV-2/physiology
4.
BMC Med Genomics ; 14(1): 226, 2021 09 17.
Article in English | MEDLINE | ID: covidwho-1542114

ABSTRACT

BACKGROUND: Higher mortality of COVID-19 patients with lung disease is a formidable challenge for the health care system. Genetic association between COVID-19 and various lung disorders must be understood to comprehend the molecular basis of comorbidity and accelerate drug development. METHODS: Lungs tissue-specific neighborhood network of human targets of SARS-CoV-2 was constructed. This network was integrated with lung diseases to build a disease-gene and disease-disease association network. Network-based toolset was used to identify the overlapping disease modules and drug targets. The functional protein modules were identified using community detection algorithms and biological processes, and pathway enrichment analysis. RESULTS: In total, 141 lung diseases were linked to a neighborhood network of SARS-CoV-2 targets, and 59 lung diseases were found to be topologically overlapped with the COVID-19 module. Topological overlap with various lung disorders allows repurposing of drugs used for these disorders to hit the closely associated COVID-19 module. Further analysis showed that functional protein-protein interaction modules in the lungs, substantially hijacked by SARS-CoV-2, are connected to several lung disorders. FDA-approved targets in the hijacked protein modules were identified and that can be hit by exiting drugs to rescue these modules from virus possession. CONCLUSION: Lung diseases are clustered with COVID-19 in the same network vicinity, indicating the potential threat for patients with respiratory diseases after SARS-CoV-2 infection. Pathobiological similarities between lung diseases and COVID-19 and clinical evidence suggest that shared molecular features are the probable reason for comorbidity. Network-based drug repurposing approaches can be applied to improve the clinical conditions of COVID-19 patients.


Subject(s)
COVID-19/drug therapy , COVID-19/epidemiology , Drug Repositioning , Lung Diseases/epidemiology , Pandemics , SARS-CoV-2 , Algorithms , Antiviral Agents/therapeutic use , COVID-19/genetics , Comorbidity , Drug Discovery , Drug Repositioning/methods , Gene Regulatory Networks/drug effects , Host Microbial Interactions/drug effects , Host Microbial Interactions/genetics , Humans , Lung Diseases/drug therapy , Lung Diseases/genetics , Protein Interaction Maps/drug effects , Protein Interaction Maps/genetics , Systems Biology
5.
Sci Rep ; 11(1): 21872, 2021 11 08.
Article in English | MEDLINE | ID: covidwho-1506466

ABSTRACT

Severe acute respiratory syndrome (SARS) is a highly contagious viral respiratory illness. This illness is spurred on by a coronavirus known as SARS-associated coronavirus (SARS-CoV). SARS was first detected in Asia in late February 2003. The genome of this virus is very similar to the SARS-CoV-2. Therefore, the study of SARS-CoV disease and the identification of effective drugs to treat this disease can be new clues for the treatment of SARS-Cov-2. This study aimed to discover novel potential drugs for SARS-CoV disease in order to treating SARS-Cov-2 disease based on a novel systems biology approach. To this end, gene co-expression network analysis was applied. First, the gene co-expression network was reconstructed for 1441 genes, and then two gene modules were discovered as significant modules. Next, a list of miRNAs and transcription factors that target gene co-expression modules' genes were gathered from the valid databases, and two sub-networks formed of transcription factors and miRNAs were established. Afterward, the list of the drugs targeting obtained sub-networks' genes was retrieved from the DGIDb database, and two drug-gene and drug-TF interaction networks were reconstructed. Finally, after conducting different network analyses, we proposed five drugs, including FLUOROURACIL, CISPLATIN, SIROLIMUS, CYCLOPHOSPHAMIDE, and METHYLDOPA, as candidate drugs for SARS-CoV-2 coronavirus treatment. Moreover, ten miRNAs including miR-193b, miR-192, miR-215, miR-34a, miR-16, miR-16, miR-92a, miR-30a, miR-7, and miR-26b were found to be significant miRNAs in treating SARS-CoV-2 coronavirus.


Subject(s)
COVID-19/drug therapy , COVID-19/immunology , COVID-19/virology , Drug Repositioning , Gene Expression Profiling , Gene Expression Regulation, Viral , SARS-CoV-2 , Computational Biology , Gene Regulatory Networks , Genes, Viral , Genetic Techniques , Humans , MicroRNAs/metabolism , Oligonucleotide Array Sequence Analysis , Systems Biology , Transcription Factors
6.
Front Biosci (Landmark Ed) ; 26(10): 740-751, 2021 10 30.
Article in English | MEDLINE | ID: covidwho-1498507

ABSTRACT

Objectives: To quantify the integrated levels of ACE2 and TMPRSS2, the two well-recognized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry-related genes, and to further identify key factors contributing to SARS-CoV-2 susceptibility in head and neck squamous cell carcinoma (HNSC). Methods: We developed a metric of the potential for tissue infected with SARS-CoV-2 ("TPSI") based on ACE2 and TMPRSS2 transcript levels and compared TPSI levels between tumor and matched normal tissues across 11 tumor types. For further analysis of HNSC, weighted gene co-expression network analysis (WGCNA), functional analysis, and single sample gene set enrichment analysis (ssGSEA) were conducted to investigate TPSI-relevant biological processes and their relationship with the immune landscape. TPSI-related factors were identified from clinical and mutational domains, followed by lasso regression to determine their relative effects on TPSI levels. Results: TPSI levels in tumors were generally lower than in the normal tissues. In HNSC, the genes highly associated with TPSI were enriched in viral entry-related processes, and TPSI levels were positively correlated with both eosinophils and T helper 17 (Th17) cell infiltration. Furthermore, the site of onset, human papillomaviruses (HPV) status, and nuclear receptor binding SET domain protein 1 (NSD1) mutations were identified as the most important factors shaping TPSI levels. Conclusions: This study identified the infection risk of SARS-CoV-2 between tumor and normal tissues, and provided evidence for the risk stratification of HNSC.


Subject(s)
Angiotensin-Converting Enzyme 2/genetics , COVID-19/genetics , Carcinoma, Squamous Cell/genetics , Head and Neck Neoplasms/genetics , Serine Endopeptidases/genetics , Angiotensin-Converting Enzyme 2/metabolism , COVID-19/metabolism , COVID-19/virology , Carcinoma, Squamous Cell/metabolism , Carcinoma, Squamous Cell/virology , Gene Expression Profiling/methods , Gene Expression Regulation, Neoplastic , Gene Regulatory Networks , Head and Neck Neoplasms/metabolism , Head and Neck Neoplasms/virology , Humans , Reverse Transcriptase Polymerase Chain Reaction/methods , SARS-CoV-2/metabolism , SARS-CoV-2/physiology , Serine Endopeptidases/metabolism , Virus Internalization
7.
Front Endocrinol (Lausanne) ; 12: 714909, 2021.
Article in English | MEDLINE | ID: covidwho-1497067

ABSTRACT

Background: Clinically, evidence shows that uterine corpus endometrial carcinoma (UCEC) patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may have a higher death-rate. However, current anti-UCEC/coronavirus disease 2019 (COVID-19) treatment is lacking. Plumbagin (PLB), a pharmacologically active alkaloid, is an emerging anti-cancer inhibitor. Accordingly, the current report was designed to identify and characterize the anti-UCEC function and mechanism of PLB in the treatment of patients infected with SARS-CoV-2 via integrated in silico analysis. Methods: The clinical analyses of UCEC and COVID-19 in patients were conducted using online-accessible tools. Meanwhile, in silico methods including network pharmacology and biological molecular docking aimed to screen and characterize the anti-UCEC/COVID-19 functions, bio targets, and mechanisms of the action of PLB. Results: The bioinformatics data uncovered the clinical characteristics of UCEC patients infected with SARS-CoV-2, including specific genes, health risk, survival rate, and prognostic index. Network pharmacology findings disclosed that PLB-exerted anti-UCEC/COVID-19 effects were achieved through anti-proliferation, inducing cytotoxicity and apoptosis, anti-inflammation, immunomodulation, and modulation of some of the key molecular pathways associated with anti-inflammatory and immunomodulating actions. Following molecular docking analysis, in silico investigation helped identify the anti-UCEC/COVID-19 pharmacological bio targets of PLB, including mitogen-activated protein kinase 3 (MAPK3), tumor necrosis factor (TNF), and urokinase-type plasminogen activator (PLAU). Conclusions: Based on the present bioinformatic and in silico findings, the clinical characterization of UCEC/COVID-19 patients was revealed. The candidate, core bio targets, and molecular pathways of PLB action in the potential treatment of UCEC/COVID-19 were identified accordingly.


Subject(s)
COVID-19 , Carcinoma, Endometrioid , Endometrial Neoplasms , Host-Pathogen Interactions , Naphthoquinones/pharmacology , Adult , Aged , Aged, 80 and over , COVID-19/complications , COVID-19/diagnosis , COVID-19/drug therapy , COVID-19/genetics , Calcium-Binding Proteins/drug effects , Calcium-Binding Proteins/metabolism , Carcinoma, Endometrioid/complications , Carcinoma, Endometrioid/diagnosis , Carcinoma, Endometrioid/drug therapy , Carcinoma, Endometrioid/genetics , Computational Biology , Drug Screening Assays, Antitumor/methods , Endometrial Neoplasms/complications , Endometrial Neoplasms/diagnosis , Endometrial Neoplasms/drug therapy , Endometrial Neoplasms/genetics , Female , Gene Expression Regulation, Neoplastic/drug effects , Gene Regulatory Networks/drug effects , Genetic Association Studies , Host-Pathogen Interactions/drug effects , Host-Pathogen Interactions/genetics , Humans , Membrane Proteins/drug effects , Membrane Proteins/metabolism , Middle Aged , Mitogen-Activated Protein Kinase 3/drug effects , Mitogen-Activated Protein Kinase 3/metabolism , Molecular Docking Simulation/methods , Naphthoquinones/therapeutic use , Prognosis , SARS-CoV-2/drug effects , SARS-CoV-2/physiology , Signal Transduction/drug effects , Signal Transduction/genetics , Tumor Necrosis Factor-alpha/drug effects , Tumor Necrosis Factor-alpha/metabolism , Uterus/drug effects , Uterus/metabolism , Uterus/pathology , Uterus/virology
8.
Front Immunol ; 12: 741502, 2021.
Article in English | MEDLINE | ID: covidwho-1477825

ABSTRACT

Host innate immune response follows severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and it is the driver of the acute respiratory distress syndrome (ARDS) amongst other inflammatory end-organ morbidities. Such life-threatening coronavirus disease 2019 (COVID-19) is heralded by virus-induced activation of mononuclear phagocytes (MPs; monocytes, macrophages, and dendritic cells). MPs play substantial roles in aberrant immune secretory activities affecting profound systemic inflammation and end-organ malfunctions. All follow the presence of persistent viral components and virions without evidence of viral replication. To elucidate SARS-CoV-2-MP interactions we investigated transcriptomic and proteomic profiles of human monocyte-derived macrophages. While expression of the SARS-CoV-2 receptor, the angiotensin-converting enzyme 2, paralleled monocyte-macrophage differentiation, it failed to affect productive viral infection. In contrast, simple macrophage viral exposure led to robust pro-inflammatory cytokine and chemokine expression but attenuated type I interferon (IFN) activity. Both paralleled dysregulation of innate immune signaling pathways, specifically those linked to IFN. We conclude that the SARS-CoV-2-infected host mounts a robust innate immune response characterized by a pro-inflammatory storm heralding end-organ tissue damage.


Subject(s)
COVID-19/virology , Immunity, Innate , Macrophages/virology , SARS-CoV-2/pathogenicity , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/metabolism , COVID-19/immunology , COVID-19/metabolism , Cells, Cultured , Cytokines/genetics , Cytokines/metabolism , Gene Expression Profiling , Gene Regulatory Networks , Host-Pathogen Interactions , Humans , Immunity, Innate/genetics , Inflammation Mediators/metabolism , Macrophages/immunology , Macrophages/metabolism , Proteome , Proteomics , Receptors, Virus/genetics , Receptors, Virus/metabolism , SARS-CoV-2/immunology , Signal Transduction , Transcriptome
9.
Sci Rep ; 11(1): 20687, 2021 10 19.
Article in English | MEDLINE | ID: covidwho-1475486

ABSTRACT

This analysis presents a systematic evaluation of the extent of therapeutic opportunities that can be obtained from drug repurposing by connecting drug targets with disease genes. When using FDA-approved indications as a reference level we found that drug repurposing can offer an average of an 11-fold increase in disease coverage, with the maximum number of diseases covered per drug being increased from 134 to 167 after extending the drug targets with their high confidence first neighbors. Additionally, by network analysis to connect drugs to disease modules we found that drugs on average target 4 disease modules, yet the similarity between disease modules targeted by the same drug is generally low and the maximum number of disease modules targeted per drug increases from 158 to 229 when drug targets are neighbor-extended. Moreover, our results highlight that drug repurposing is more dependent on target proteins being shared between diseases than on polypharmacological properties of drugs. We apply our drug repurposing and network module analysis to COVID-19 and show that Fostamatinib is the drug with the highest module coverage.


Subject(s)
COVID-19/drug therapy , Drug Repositioning/methods , Gene Regulatory Networks/drug effects , Protein Interaction Maps/genetics , SARS-CoV-2 , Antiviral Agents/pharmacology , Bayes Theorem , Computational Biology/methods , Drug Delivery Systems , Drug Discovery , Humans , Polypharmacology , Protein Interaction Mapping , United States , United States Food and Drug Administration
10.
Sci Rep ; 11(1): 19839, 2021 10 06.
Article in English | MEDLINE | ID: covidwho-1454816

ABSTRACT

Computational drug repositioning aims at ranking and selecting existing drugs for novel diseases or novel use in old diseases. In silico drug screening has the potential for speeding up considerably the shortlisting of promising candidates in response to outbreaks of diseases such as COVID-19 for which no satisfactory cure has yet been found. We describe DrugMerge as a methodology for preclinical computational drug repositioning based on merging multiple drug rankings obtained with an ensemble of disease active subnetworks. DrugMerge uses differential transcriptomic data on drugs and diseases in the context of a large gene co-expression network. Experiments with four benchmark diseases demonstrate that our method detects in first position drugs in clinical use for the specified disease, in all four cases. Application of DrugMerge to COVID-19 found rankings with many drugs currently in clinical trials for COVID-19 in top positions, thus showing that DrugMerge can mimic human expert judgment.


Subject(s)
Antineoplastic Agents/pharmacology , COVID-19/drug therapy , Drug Repositioning/methods , Neoplasms/drug therapy , Antiviral Agents , COVID-19/genetics , COVID-19/metabolism , COVID-19/virology , Computational Biology/methods , Databases, Genetic , Databases, Pharmaceutical , Gene Regulatory Networks , Humans , Neoplasms/genetics , Neoplasms/metabolism , Neoplasms/virology , SARS-CoV-2/isolation & purification
11.
J Ethnopharmacol ; 283: 114701, 2022 Jan 30.
Article in English | MEDLINE | ID: covidwho-1446835

ABSTRACT

ETHNOPHARMACOLOGICAL RELEVANCE: Xuanfei Baidu Decoction (XFBD), one of the "three medicines and three prescriptions" for the clinically effective treatment of COVID-19 in China, plays an important role in the treatment of mild and/or common patients with dampness-toxin obstructing lung syndrome. AIM OF THE STUDY: The present work aims to elucidate the protective effects and the possible mechanism of XFBD against the acute inflammation and pulmonary fibrosis. METHODS: We use TGF-ß1 induced fibroblast activation model and LPS/IL-4 induced macrophage inflammation model as in vitro cell models. The mice model of lung fibrosis was induced by BLM via endotracheal drip, and then XFBD (4.6 g/kg, 9.2 g/kg) were administered orally respectively. The efficacy and molecular mechanisms in the presence or absence of XFBD were investigated. RESULTS: The results proved that XFBD can effectively inhibit fibroblast collagen deposition, down-regulate the level of α-SMA and inhibit the migration of fibroblasts. IL-4 induced macrophage polarization was also inhibited and the secretions of the inflammatory factors including IL6, iNOS were down-regulated. In vivo experiments, the results proved that XFBD improved the weight loss and survival rate of the mice. The XFBD high-dose administration group had a significant effect in inhibiting collagen deposition and the expression of α-SMA in the lungs of mice. XFBD can reduce bleomycin-induced pulmonary fibrosis by inhibiting IL-6/STAT3 activation and related macrophage infiltration. CONCLUSIONS: Xuanfei Baidu Decoction protects against macrophages induced inflammation and pulmonary fibrosis via inhibiting IL-6/STAT3 signaling pathway.


Subject(s)
COVID-19/drug therapy , Drugs, Chinese Herbal , Inflammation/drug therapy , Macrophages/drug effects , SARS-CoV-2 , Signal Transduction/drug effects , Animals , Cell Survival/drug effects , Drugs, Chinese Herbal/pharmacology , Drugs, Chinese Herbal/therapeutic use , Fibroblasts/drug effects , Gene Expression Regulation/drug effects , Gene Regulatory Networks , Humans , Interleukin-6/antagonists & inhibitors , Interleukin-6/genetics , Interleukin-6/metabolism , Male , Mice , Mice, Inbred C57BL , NIH 3T3 Cells , Phytotherapy , Pulmonary Fibrosis/pathology , Pulmonary Fibrosis/prevention & control , RAW 264.7 Cells , STAT3 Transcription Factor/antagonists & inhibitors , STAT3 Transcription Factor/genetics , STAT3 Transcription Factor/metabolism
12.
Sci Rep ; 11(1): 18985, 2021 09 23.
Article in English | MEDLINE | ID: covidwho-1437690

ABSTRACT

The COVID-19 pandemic is raging. It revealed the importance of rapid scientific advancement towards understanding and treating new diseases. To address this challenge, we adapt an explainable artificial intelligence algorithm for data fusion and utilize it on new omics data on viral-host interactions, human protein interactions, and drugs to better understand SARS-CoV-2 infection mechanisms and predict new drug-target interactions for COVID-19. We discover that in the human interactome, the human proteins targeted by SARS-CoV-2 proteins and the genes that are differentially expressed after the infection have common neighbors central in the interactome that may be key to the disease mechanisms. We uncover 185 new drug-target interactions targeting 49 of these key genes and suggest re-purposing of 149 FDA-approved drugs, including drugs targeting VEGF and nitric oxide signaling, whose pathways coincide with the observed COVID-19 symptoms. Our integrative methodology is universal and can enable insight into this and other serious diseases.


Subject(s)
COVID-19/drug therapy , Drug Evaluation, Preclinical/methods , SARS-CoV-2/genetics , Antiviral Agents/therapeutic use , Artificial Intelligence , COVID-19/genetics , COVID-19/metabolism , Drug Repositioning/methods , Gene Regulatory Networks/genetics , Humans , Models, Theoretical , Pandemics , Pharmaceutical Preparations , SARS-CoV-2/drug effects , SARS-CoV-2/pathogenicity , Signal Transduction/genetics
13.
Cells ; 10(9)2021 09 09.
Article in English | MEDLINE | ID: covidwho-1408628

ABSTRACT

The present study sought to identify gene networks that are hallmarks of the developing inguinal subcutaneous adipose tissue (iWAT) and the interscapular brown adipose tissue (BAT) in the mouse. RNA profiling revealed that the iWAT of postnatal (P) day 6 mice expressed thermogenic and lipid catabolism transcripts, along with the abundance of transcripts associated with the beige adipogenesis program. This was an unexpected finding, as thermogenic BAT was believed to be the only site of nonshivering thermogenesis in the young mouse. However, the transcriptional landscape of BAT in P6 mice suggests that it is still undergoing differentiation and maturation, and that the iWAT temporally adopts thermogenic and lipolytic potential. Moreover, P6 iWAT and adult (P56) BAT were similar in their expression of immune gene networks, but P6 iWAT was unique in the abundant expression of antimicrobial proteins and virus entry factors, including a possible receptor for SARS-CoV-2. In summary, postnatal iWAT development is associated with a metabolic shift from thermogenesis and lipolysis towards fat storage. However, transcripts of beige-inducing signal pathways including ß-adrenergic receptors and interleukin-4 signaling were underrepresented in young iWAT, suggesting that the signals for thermogenic fat differentiation may be different in early postnatal life and in adulthood.


Subject(s)
Adipocytes, Beige/metabolism , Transcription, Genetic , Adipose Tissue, Brown/metabolism , Adipose Tissue, White/metabolism , Animals , Animals, Newborn , Biomarkers/metabolism , Cell Cycle/genetics , Gene Expression Regulation, Developmental , Gene Ontology , Gene Regulatory Networks , Male , Mice, Inbred C57BL , Models, Biological , Muscle Development/genetics , Neuropeptides/metabolism , RNA, Messenger/genetics , RNA, Messenger/metabolism , Signal Transduction
14.
Nat Commun ; 12(1): 652, 2021 01 28.
Article in English | MEDLINE | ID: covidwho-1397868

ABSTRACT

Injury and loss of oligodendrocytes can cause demyelinating diseases such as multiple sclerosis. To improve our understanding of human oligodendrocyte development, which could facilitate development of remyelination-based treatment strategies, here we describe time-course single-cell-transcriptomic analysis of developing human stem cell-derived oligodendrocyte-lineage-cells (hOLLCs). The study includes hOLLCs derived from both genome engineered embryonic stem cell (ESC) reporter cells containing an Identification-and-Purification tag driven by the endogenous PDGFRα promoter and from unmodified induced pluripotent (iPS) cells. Our analysis uncovers substantial transcriptional heterogeneity of PDGFRα-lineage hOLLCs. We discover sub-populations of human oligodendrocyte progenitor cells (hOPCs) including a potential cytokine-responsive hOPC subset, and identify candidate regulatory genes/networks that define the identity of these sub-populations. Pseudotime trajectory analysis defines developmental pathways of oligodendrocytes vs astrocytes from PDGFRα-expressing hOPCs and predicts differentially expressed genes between the two lineages. In addition, pathway enrichment analysis followed by pharmacological intervention of these pathways confirm that mTOR and cholesterol biosynthesis signaling pathways are involved in maturation of oligodendrocytes from hOPCs.


Subject(s)
Genetic Heterogeneity , Genetic Variation , Induced Pluripotent Stem Cells/metabolism , Oligodendrocyte Precursor Cells/metabolism , Single-Cell Analysis/methods , Transcriptome/genetics , Astrocytes/cytology , Astrocytes/metabolism , Cell Differentiation/genetics , Cell Line , Cell Lineage/genetics , Cholesterol/biosynthesis , Embryonic Stem Cells/cytology , Embryonic Stem Cells/metabolism , Gene Regulatory Networks/genetics , Humans , Induced Pluripotent Stem Cells/cytology , Oligodendrocyte Precursor Cells/cytology , Receptor, Platelet-Derived Growth Factor alpha/genetics , Receptor, Platelet-Derived Growth Factor alpha/metabolism , Signal Transduction/genetics , TOR Serine-Threonine Kinases/genetics , TOR Serine-Threonine Kinases/metabolism
15.
Viruses ; 13(1)2021 Jan 16.
Article in English | MEDLINE | ID: covidwho-1389525

ABSTRACT

Our recent study identified seven key microRNAs (miR-8066, 5197, 3611, 3934-3p, 1307-3p, 3691-3p, 1468-5p) similar between SARS-CoV-2 and the human genome, pointing at miR-related mechanisms in viral entry and the regulatory effects on host immunity. To identify the putative roles of these miRs in zoonosis, we assessed their conservation, compared with humans, in some key wild and domestic animal carriers of zoonotic viruses, including bat, pangolin, pig, cow, rat, and chicken. Out of the seven miRs under study, miR-3611 was the most strongly conserved across all species; miR-5197 was the most conserved in pangolin, pig, cow, bat, and rat; miR-1307 was most strongly conserved in pangolin, pig, cow, bat, and human; miR-3691-3p in pangolin, cow, and human; miR-3934-3p in pig and cow, followed by pangolin and bat; miR-1468 was most conserved in pangolin, pig, and bat; while miR-8066 was most conserved in pangolin and pig. In humans, miR-3611 and miR-1307 were most conserved, while miR-8066, miR-5197, miR-3334-3p and miR-1468 were least conserved, compared with pangolin, pig, cow, and bat. Furthermore, we identified that changes in the miR-5197 nucleotides between pangolin and human can generate three new miRs, with differing tissue distribution in the brain, lung, intestines, lymph nodes, and muscle, and with different downstream regulatory effects on KEGG pathways. This may be of considerable importance as miR-5197 is localized in the spike protein transcript area of the SARS-CoV-2 genome. Our findings may indicate roles for these miRs in viral-host co-evolution in zoonotic hosts, particularly highlighting pangolin, bat, cow, and pig as putative zoonotic carriers, while highlighting the miRs' roles in KEGG pathways linked to viral pathogenicity and host responses in humans. This in silico study paves the way for investigations into the roles of miRs in zoonotic disease.


Subject(s)
Biological Coevolution , MicroRNAs/genetics , SARS-CoV-2/genetics , Animals , COVID-19/transmission , COVID-19/virology , Chickens , Gene Regulatory Networks , Genome/genetics , Host Specificity , Humans , Mammals , MicroRNAs/chemistry , MicroRNAs/metabolism , SARS-CoV-2/pathogenicity , SARS-CoV-2/physiology , Sequence Alignment , Tissue Distribution , Zoonoses/transmission , Zoonoses/virology
16.
Arch Virol ; 166(1): 271-274, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-1384460

ABSTRACT

Viral RNAs can perturb the miRNA regulatory network, competing with host RNAs as part of their infective process. An in silico competing endogenous RNA (ceRNA) analysis has been carried on SARS-CoV-2. The results suggest that, in humans, the decrease of microRNA activity caused by viral RNAs can lead to a perturbation of vesicle trafficking and the inflammatory response, in particular by enhancing KLF10 activity. The results suggest also that, during the study of the mechanics of viral infections, it could be of general interest to investigate the competition of viral RNA with cellular transcripts for shared microRNAs.


Subject(s)
Gene Regulatory Networks/genetics , RNA, Messenger/genetics , RNA, Viral/genetics , SARS-CoV-2/genetics , A549 Cells , COVID-19/pathology , Cell Line, Tumor , Early Growth Response Transcription Factors/genetics , Early Growth Response Transcription Factors/metabolism , Humans , Kruppel-Like Transcription Factors/genetics , Kruppel-Like Transcription Factors/metabolism , MicroRNAs/genetics
17.
Nat Commun ; 12(1): 724, 2021 02 01.
Article in English | MEDLINE | ID: covidwho-1387326

ABSTRACT

Recent advances in cell-free synthetic biology have given rise to gene circuit-based sensors with the potential to provide decentralized and low-cost molecular diagnostics. However, it remains a challenge to deliver this sensing capacity into the hands of users in a practical manner. Here, we leverage the glucose meter, one of the most widely available point-of-care sensing devices, to serve as a universal reader for these decentralized diagnostics. We describe a molecular translator that can convert the activation of conventional gene circuit-based sensors into a glucose output that can be read by off-the-shelf glucose meters. We show the development of new glucogenic reporter systems, multiplexed reporter outputs and detection of nucleic acid targets down to the low attomolar range. Using this glucose-meter interface, we demonstrate the detection of a small-molecule analyte; sample-to-result diagnostics for typhoid, paratyphoid A/B; and show the potential for pandemic response with nucleic acid sensors for SARS-CoV-2.


Subject(s)
Biosensing Techniques/methods , Gene Regulatory Networks/genetics , Glucose/analysis , Nucleic Acids/analysis , Point-of-Care Systems , Point-of-Care Testing , Biosensing Techniques/instrumentation , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/virology , Glucose/metabolism , Humans , Nucleic Acids/genetics , Pandemics , SARS-CoV-2/isolation & purification , SARS-CoV-2/physiology , Typhoid Fever/blood , Typhoid Fever/diagnosis , Typhoid Fever/microbiology
18.
Scand J Immunol ; 94(5): e13100, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1388399

ABSTRACT

The SARS-CoV-2 epidemic infections in Australia during 2020 were small in number in epidemiological terms and are well described. The SARS-CoV-2 genomic sequence data of many infected patients have been largely curated in a number of publicly available databases, including the corresponding epidemiological data made available by the Victorian Department of Health and Human Services. We have critically analysed the available SARS-CoV-2 haplotypes and genomic sequences in the context of putative deficits in innate immune APOBEC and ADAR deaminase anti-viral responses. It is now known that immune impaired elderly co-morbid patients display clear deficits in interferon type 1 (α/ß) and III (λ) stimulated innate immune gene cascades, of which APOBEC and ADAR induced expression are part. These deficiencies may help explain some of the clear genetic patterns in SARS-CoV-2 genomes isolated in Victoria, Australia, during the 2nd Wave (June-September, 2020). We tested the hypothesis that predicted lowered innate immune APOBEC and ADAR anti-viral deaminase responses in a significant proportion of elderly patients would be consistent with/reflected in a low level of observed mutagenesis in many isolated SARS-CoV-2 genomes. Our findings are consistent with this expectation. The analysis also supports the conclusions of the Victorian government's Department of Health that essentially one variant or haplotype infected Victorian aged care facilities where the great majority (79%) of all 820 SARS-CoV-2 associated deaths occurred. The implications of our data analysis for other localized epidemics and efficient coronavirus vaccine design and delivery are discussed.


Subject(s)
APOBEC Deaminases/genetics , Adenosine Deaminase/genetics , COVID-19 Vaccines/immunology , COVID-19/immunology , RNA-Binding Proteins/genetics , SARS-CoV-2/physiology , APOBEC Deaminases/metabolism , Adenosine Deaminase/metabolism , Age Factors , Aged, 80 and over , COVID-19/epidemiology , COVID-19/virology , Female , Gene Regulatory Networks , Haplotypes , Humans , Immunity, Innate , Immunologic Deficiency Syndromes , Interferon Type I/genetics , Male , RNA-Binding Proteins/metabolism , Victoria/epidemiology
19.
Oxid Med Cell Longev ; 2021: 9998697, 2021.
Article in English | MEDLINE | ID: covidwho-1378094

ABSTRACT

The pandemic of the coronavirus disease 2019 (COVID-19) has posed huge threats to healthcare systems and the global economy. However, the host response towards COVID-19 on the molecular and cellular levels still lacks full understanding and effective therapies are in urgent need. Here, we integrate three datasets, GSE152641, GSE161777, and GSE157103. Compared to healthy people, 314 differentially expressed genes were identified, which were mostly involved in neutrophil degranulation and cell division. The protein-protein network was established and two significant subsets were filtered by MCODE: ssGSEA and CIBERSORT, which comprehensively revealed the alternation of immune cell abundance. Weighted gene coexpression network analysis (WGCNA) as well as GO and KEGG analyses unveiled the role of neutrophils and T cells during the progress of the disease. Based on the hospital-free days after 45 days of follow-up and statistical methods such as nonnegative matrix factorization (NMF), submap, and linear correlation analysis, 31 genes were regarded as the signature of the peripheral blood of COVID-19. Various immune cells were identified to be related to the prognosis of the patients. Drugs were predicted for the genes in the signature by DGIdb. Overall, our study comprehensively revealed the relationship between the inflammatory response and the disease course, which provided strategies for the treatment of COVID-19.


Subject(s)
COVID-19/genetics , COVID-19/immunology , Gene Regulatory Networks , Inflammation/genetics , Inflammation/immunology , SARS-CoV-2/immunology , Transcriptome , COVID-19/complications , COVID-19/virology , Case-Control Studies , Gene Expression Profiling , Humans , Inflammation/virology , Protein Interaction Maps
20.
Sci Rep ; 11(1): 17351, 2021 08 30.
Article in English | MEDLINE | ID: covidwho-1377921

ABSTRACT

Coronavirus disease 2019 (COVID-19) is raging worldwide. This potentially fatal infectious disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the complete mechanism of COVID-19 is not well understood. Therefore, we analyzed gene expression profiles of COVID-19 patients to identify disease-related genes through an innovative machine learning method that enables a data-driven strategy for gene selection from a data set with a small number of samples and many candidates. Principal-component-analysis-based unsupervised feature extraction (PCAUFE) was applied to the RNA expression profiles of 16 COVID-19 patients and 18 healthy control subjects. The results identified 123 genes as critical for COVID-19 progression from 60,683 candidate probes, including immune-related genes. The 123 genes were enriched in binding sites for transcription factors NFKB1 and RELA, which are involved in various biological phenomena such as immune response and cell survival: the primary mediator of canonical nuclear factor-kappa B (NF-κB) activity is the heterodimer RelA-p50. The genes were also enriched in histone modification H3K36me3, and they largely overlapped the target genes of NFKB1 and RELA. We found that the overlapping genes were downregulated in COVID-19 patients. These results suggest that canonical NF-κB activity was suppressed by H3K36me3 in COVID-19 patient blood.


Subject(s)
COVID-19/genetics , Gene Expression Profiling/methods , Gene Regulatory Networks , Histones/metabolism , NF-kappa B p50 Subunit/metabolism , Transcription Factor RelA/metabolism , Binding Sites , COVID-19/metabolism , Case-Control Studies , Epigenesis, Genetic , Gene Expression Regulation , Genetic Predisposition to Disease , Humans , Machine Learning , Signal Transduction
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