Exploration of potential mechanism of SARS-CoV-2 induced immune inflammatory response leading to progression of atherosclerosis and prediction of traditional Chinese medicine for preventing and treating based on bioinformatics.

Objective To explore the core targets and important pathways of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) induced atherosclerosis (AS) progression from the perspective of immune inflammation, so as to predict the potential prevention and treatment of traditional Chinese medicine (TCM). Methods Microarray data were obtained from the Gene Expression Omnibus (GEO) database for coronavirus disease 2019 (COVID-19) patients and AS patients, and the "limmar" and "Venn" packages were used to screen out the common differentially expressed genes (DEGs) genes in both diseases. The gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses were performed on the common DEGs to annotate their functions and important pathways. The two gene sets were scored for immune cells and immune function to assess the level of immune cell infiltration. The protein-protein interaction (PPI) network was constructed by STRING database, and the CytoHubba plug-in of Cytoscape was used to identify the hub genes. Two external validation datasets were introduced to validate the hub genes and obtain the core genes. Immuno-infiltration analysis and gene set enrichment analysis (GSEA) were performed on the core genes respectively. Finally the potential TCM regulating the core genes were predicted by Coremine Medical database. Results A total of 7898 genes related to COVID-19, 471 genes related to AS progression;And 51 common DEGs, including 32 highly expressed genes and 19 low expressed genes were obtained. GO and KEGG analysis showed that common DEGs, which were mainly localized in cypermethrin-encapsulated vesicles, platelet alpha particles, phagocytic vesicle membranes and vesicles, were involved in many biological processes such as myeloid differentiation factor 88 (MyD88)-dependent Toll-like receptor signaling pathway transduction, interleukin-8 (IL-8) production and positive regulation, IL-6 production and positive regulation to play a role in regulating nicotinamide adenine dinucleotide phosphate oxidase activity, Toll-like receptor binding and lipopeptide and glycosaminoglycan binding through many biological pathways, including Toll-like receptor signaling pathways, neutrophil extracellular trap formation, complement and coagulation cascade reactions. The results of immune infiltration analysis demonstrated the state of immune microenvironment of COVID-19 and AS. A total of 5 hub genes were obtained after screening, among which Toll-like receptor 2 (TLR2), cluster of differentiation 163 (CD163) and complement C1q subcomponent subunit B (C1QB) genes passed external validation as core genes. The core genes showed strong correlation with immune process and inflammatory response in both immune infiltration analysis and GSEA enrichment analysis. A total of 35 TCMs, including Chuanxiong (Chuanxiong Rhizoma), Taoren (Persicae Semen), Danggui (Angelicae Sinensis Radix), Huangqin (Scutellariae Radix), Pugongying (Taraxaci Herba), Taizishen (Pseudostellariae Radix), Huangjing (Polygonati Rhizoma), could be used as potential therapeutic agents. Conclusion TLR2, CD163 and C1QB were the core molecules of SARS-CoV-2-mediated immune inflammatory response promoting AS progression, and targeting predicted herbs were potential drugs to slow down AS progression in COVID-19 patients.Copyright © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.

Comparing artificial intelligence based diagnosis with expert results in SARS-COV-2 RT-qPCR

Objectives: Reverse transcription and real-time polymerase chain reaction (RT-qPCR) based on the SARS-CoV-2 viral RNA demonstration is the gold standard in diagnosis. Data files obtained from PCR devices should be analysed by a specialist physician and results should be transferred to Laboratory Information Management System (LIMS). CAtenA Smart PCR (Ventura, Ankara, Turkiye) program is a local bioinformatics software that assess PCR data files with artificial intelligence, submits to expert approval and transfers the approved results to LIMS. The aim of this study is to investigate its accuracy and matching success rate with expert analysis. Method(s): A total of 9400 RT-qPCR test results studied in Ankara Provincial Health Directorate Public Health Molecular Diagnosis Laboratory were compared with respect to expert evaluation and CAtenA results. Result(s): It was determined that the preliminary evaluation results of the CAtenA matched 86% of the negative and 90% of the positive results provided by expert analysis. 987 tests which CAtenA determined as inconclusive and suggested repeating PCR were found either negative or positive by expert analysis. A significant difference between positive and negative matching success rates and artificial intelligence (AI) based software overall accuracy was found and associated with the missed tests of the AI. Conclusion(s): As a result, it was suggested there is a low risk of confirming false positive results without expert analysis and test repetitions would cause losing time along with extra test costs. It was agreed that the PCR analysis used in CAtenA should be improved particularly in terms of test repetitions.Copyright © 2023 by Prusa Medical Publishing.

In silico identification of potential miRNAs -mRNA inflammatory networks implicated in the pathogenesis of COVID-19

COVID-19 has been found to affect the expression profile of several mRNAs and miRNAs, leading to dysregulation of a number of signaling pathways, particularly those related to inflammatory responses. In the current study, a systematic biology procedure was used for the analysis of high-throughput expression data from blood specimens of COVID-19 and healthy individuals. Differentially expressed miRNAs in blood specimens of COVID-19 vs. healthy specimens were then identified to construct and analyze miRNA-mRNA networks and predict key miRNAs and genes in inflammatory pathways. Our results showed that 171 miRNAs were expressed as outliers in box plot and located in the critical areas according to our statistical analysis. Among them, 8 miRNAs, namely miR-1275, miR-4429, miR-4489, miR-6721-5p, miR-5010-5p, miR-7110-5p, miR-6804-5p and miR-6881-3p were found to affect expression of key genes in NF-KB, JAK/STAT and MAPK signaling pathways implicated in COVID-19 pathogenesis. In addition, our results predicted that 25 genes involved in above-mentioned inflammatory pathways were targeted not only by these 8 miRNAs but also by other obtained miRNAs (163 miRNAs). The results of the current in silico study represent candidate targets for further studies in COVID-19.Copyright © 2023 Elsevier B.V.

Quercetin potentially suppresses renal fibrosis in patients with COVID-19 under hypoxic state

Introduction: Renal fibrosis is a main outcome of acute kidney injury in COVID-19 survivors, which is emerging as a global public health concern. Lung damage in the COVID-19 patients leads to acute and chronic hypoxia, which results in inflammation, epithelial-mesenchymal transformation, and fibrosis in kidney. Quercetin is an abundant flavonoid in plant materials. Previous studies indicate that quercetin alleviates the decline of renal function, suppress epithelial to mesenchymal transformation in renal tubules, and reduce fibrosis. The study aimed to explore potential targets of quercetin on treating renal fibrosis in patients with COVID-19-induced hoxpia. Method(s): Gene/protein targets related to COVID-19, renal fibrosis, or quercetin were searched from ten databases, and Cytoscape 3.8.2 was then used to construct the protein-protein interaction network and to identify the core targets. The Metascape platform was used for bioconcentration analysis, while AutoDock Vina was used as the primary molecular docking tool. In vitro, the combination model of hypoxia- and transforming growth factor-beta (TGF-beta)- treated human proximal tubule epithelial cells (HK2 cells) was applied to determine the reno-protective effect of quercetin. Result(s): The network analysis showed that quercetin targeted on TGF-beta pathway in treating COVID-19 induced renal fibrosis. In the intersection PPI network, 115 targets were obtained, and gene enrichment analysis was conducted on 109 key nodes. Molecular docking analysis revealed that quercetin could spontaneously bind to eight targets on the TGF-beta pathway, and the binding energy of TGF-beta1 was 29.82 kJ/mol. The in vitro experiment further showed that quercetin significantly suppressed fibrosis in TGF-beta and hypoxia treated HK2 cells in a dose dependent manner by inhibiting TGF-beta/Smad3 pathway. Conclusion(s): Quercetin could attenuate renal fibrosis in patients with COVID-19 by suppressing TGF-beta/Smad3 pathway. No conflict of interestCopyright © 2023

Genomic regulatory network of human olfactory neuroepithelial cells infected with novel coronavirus (SARS-COV-2).

Objective To explore the genomic changes of human olfactory neuroepithelial cells after the novel coronavirus (SARS-COV-2) infecting the human body, and establish a protein-protein interaction (PPI) network of differentially expressed genes (DEGs), in order to understand the impact of SARS-COV-2 infection on human olfactory neuroepithelial cells, and provide reference for the prevention and treatment of new coronavirus pneumonia. Methods The public dataset GSE151973 was analyzed by NetworkAnalyst. DEGs were selected by conducting Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway analysis. PPI network, DEGs-microRNA regulatory network, transcription factor-DEGs regulatory network, environmental chemicals-DEGs regulatory network, and drug-DEGs regulatory network were created and visualized by using Cytoscape 3.7.2. Results After SAR-COV-2 invading human olfactory neuroepithelial cells, part of the gene expression profile was significantly up-regulated or down-regulated. A total of 568 DEGs were found, including 550 up-regulated genes (96.8%) and 18 down-regulated genes (3.2%). DEGs were mainly involved in biological processes such as endothelial development and angiogenesis of the olfactory epithelium, and the expression of molecular functions such as the binding of the N-terminal myristylation domain. PPI network suggested that RTP1 and RTP2 were core proteins. MAZ was the most influential transcription factor. Hsa-mir-26b-5p had the most obvious interaction with DEGs regulation. Environmental chemical valproic acid and drug ethanol had the most influence on the regulation of DEG. Conclusion The gene expression of olfactory neuroepithelial cells is significantly up-regulated or down-regulated after infection with SAR-COV-2. SARS-CoV-2 may inhibit the proliferation and differentiation of muscle satellite cells by inhibiting the function of PAX7. RTP1 and RTP2 may resist SARS-CoV-2 by promoting the ability of olfactory receptors to coat the membrane and enhancing the ability of olfactory receptors to respond to odorant ligands. MAZ may regulate DEGs by affecting cell growth and proliferation. Micro RNA, environmental chemicals and drugs also play an important role in the anti-SAR-COV-2 infection process of human olfactory neuroepithelial cells.Copyright © 2022 Editorial Department of Journal of Shanghai Second Medical University. All rights reserved.

Genomic regulatory network of human olfactory neuroepithelial cells infected with novel coronavirus (SARS-COV-2)

Objective To explore the genomic changes of human olfactory neuroepithelial cells after the novel coronavirus (SARS-COV-2) infecting the human body, and establish a protein-protein interaction (PPI) network of differentially expressed genes (DEGs), in order to understand the impact of SARS-COV-2 infection on human olfactory neuroepithelial cells, and provide reference for the prevention and treatment of new coronavirus pneumonia. Methods The public dataset GSE151973 was analyzed by NetworkAnalyst. DEGs were selected by conducting Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway analysis. PPI network, DEGs-microRNA regulatory network, transcription factor-DEGs regulatory network, environmental chemicals-DEGs regulatory network, and drug-DEGs regulatory network were created and visualized by using Cytoscape 3.7.2. Results After SAR-COV-2 invading human olfactory neuroepithelial cells, part of the gene expression profile was significantly up-regulated or down-regulated. A total of 568 DEGs were found, including 550 up-regulated genes (96.8%) and 18 down-regulated genes (3.2%). DEGs were mainly involved in biological processes such as endothelial development and angiogenesis of the olfactory epithelium, and the expression of molecular functions such as the binding of the N-terminal myristylation domain. PPI network suggested that RTP1 and RTP2 were core proteins. MAZ was the most influential transcription factor. Hsa-mir-26b-5p had the most obvious interaction with DEGs regulation. Environmental chemical valproic acid and drug ethanol had the most influence on the regulation of DEG. Conclusion The gene expression of olfactory neuroepithelial cells is significantly up-regulated or down-regulated after infection with SAR-COV-2. SARS-CoV-2 may inhibit the proliferation and differentiation of muscle satellite cells by inhibiting the function of PAX7. RTP1 and RTP2 may resist SARS-CoV-2 by promoting the ability of olfactory receptors to coat the membrane and enhancing the ability of olfactory receptors to respond to odorant ligands. MAZ may regulate DEGs by affecting cell growth and proliferation. Micro RNA, environmental chemicals and drugs also play an important role in the anti-SAR-COV-2 infection process of human olfactory neuroepithelial cells.

Identification of shared genes and possible therapeutic target between systemic lupus erythematosus and COVID-19

Background/purpose: Coronavirus disease 2019 (COVID-19) has led to a rapid increase in mortality worldwide. Systemic lupus erythematosus (SLE) was a high-risk factor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV- 2) infection, Whereas the molecular mechanisms underlying SLE and CVOID-19 are not well understood. This study aims to discover the common molecular mechanisms and genetic biomarkers of SLE and COVID-19, providing new ideas for the treatment of COVID-19. Method(s): RNA sequencing data of peripheral blood mononuclear cells (PBMC) from 6 SLE datasets and 8 COVID-19 datasets were obtained from the GEO database. Highly related modular genes associated with COVID-19 and SLE were identified by weighted gene co-expression network analysis (WGCNA). The differentially expressed genes (DEGs) between patients and healthy controls (HCs) were identified by the limma package. Common shared DEGs from COVID-19 and SLE were identified. Cytoscape and MCODE plugin were utilized for exploring the protein-protein interaction network (PPI) and identifying shared hub genes. Potential biological functions and pathways were also explored from the common DEGs. For better analysis of detailed biological mechanisms, both xCell algorithm and the cMap in CLUE (https://clue.io/) were utilized for discovering immune cell infiltration and predicting potential drugs that negatively regulate the highly expressed genes. Result(s): With identified 498 up-regulated common DEGs in SLE and COVID-19 related genes, total 11 and 13 gene modules of SLE and COVID-19 were identified espectively After overlapping differential genes, the final intersection gene set contains 218 genes. The PPI, especially the functional subnet module consists of upregulated genes by MCODE showed a great deal IFN related genes involved in the regulation of immunity. GO biological processes also showed possible functions were defense response to virus and mitotic cell cycle. Moreover, changes of most immune cells were strongly consistent between SLE and COVID-19. CDK inhibitors identified may be more likely to inhibit two diseases. Conclusion(s): Our study examined in detail the common molecular mechanisms of SLE and COVID-19, in which cellular response to cytokine stimulus, like regulating IFN, which might be the key target of both diseases. CDK is associated with the progression of SLE and COVID-19, which may be the potential therapeutic drug for SLE patients with COVID-19 infection.

Genomic regulatory network of human olfactory neuroepithelial cells infected with novel coronavirus (SARS-COV-2)

Objective To explore the genomic changes of human olfactory neuroepithelial cells after the novel coronavirus (SARS-COV-2) infecting the human body, and establish a protein-protein interaction (PPI) network of differentially expressed genes (DEGs), in order to understand the impact of SARS-COV-2 infection on human olfactory neuroepithelial cells, and provide reference for the prevention and treatment of new coronavirus pneumonia. Methods The public dataset GSE151973 was analyzed by NetworkAnalyst. DEGs were selected by conducting Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway analysis. PPI network, DEGs-microRNA regulatory network, transcription factor-DEGs regulatory network, environmental chemicals-DEGs regulatory network, and drug-DEGs regulatory network were created and visualized by using Cytoscape 3.7.2. Results After SAR-COV-2 invading human olfactory neuroepithelial cells, part of the gene expression profile was significantly up-regulated or down-regulated. A total of 568 DEGs were found, including 550 up-regulated genes (96.8%) and 18 down-regulated genes (3.2%). DEGs were mainly involved in biological processes such as endothelial development and angiogenesis of the olfactory epithelium, and the expression of molecular functions such as the binding of the N-terminal myristylation domain. PPI network suggested that RTP1 and RTP2 were core proteins. MAZ was the most influential transcription factor. Hsa-mir-26b-5p had the most obvious interaction with DEGs regulation. Environmental chemical valproic acid and drug ethanol had the most influence on the regulation of DEG. Conclusion The gene expression of olfactory neuroepithelial cells is significantly up-regulated or down-regulated after infection with SAR-COV-2. SARS-CoV-2 may inhibit the proliferation and differentiation of muscle satellite cells by inhibiting the function of PAX7. RTP1 and RTP2 may resist SARS-CoV-2 by promoting the ability of olfactory receptors to coat the membrane and enhancing the ability of olfactory receptors to respond to odorant ligands. MAZ may regulate DEGs by affecting cell growth and proliferation. Micro RNA, environmental chemicals and drugs also play an important role in the anti-SAR-COV-2 infection process of human olfactory neuroepithelial cells. Copyright © 2022 Editorial Department of Journal of Shanghai Second Medical University. All rights reserved.

Mechanism and Experimental Verification of the Use of Rhodiola crenulata to Cytokine Storm Based on Network Pharmacology and Molecular Docking

Objective: To identify the potential biological mechanisms by which Rhodiola crenulata (RC) treats cytokine storm (CS) using network pharmacology, molecular docking, and experimental verification. Method(s): The ingredients and targets of RC were collected from the Organchem database. CS-related genes were collected using the GeneCards and OMIM databases. Cytoscape 3.7.2 software was used to construct the RC-CS network diagram. These data were inputted into the STRING database to construct a protein-protein interaction network. we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analysis using DAVID and R software. Molecular docking of the active ingredient and pathway-related targets was carried out using AutoDock Vina and PyMOL, and then a CS model was established in rats induced by lipopolysaccharide for in vivo experimental verification. Result(s): The network pharmacology results showed that kaempferol was the most important active component of RC in the treatment of CS, and IL6 and STAT3 were identified as key targets. Molecular docking results showed that RC active components kaempferol had a good binding ability to IL6/STAT3. At the same time, compared with the model group, different doses of kaempferol could down-regulate the expression of inflammatory factors (P <.05), and protect against systemic inflammatory response multiple organ damage. Conclusion(s): This study preliminarily revealed that RC can prevent and treat CS by regulating the expression of inflammatory factors, inhibiting the systemic inflammatory response induced by lipopolysaccharide, and providing a theoretical basis for the study of its pharmacodynamic material basis and mechanism of action. Copyright © The Author(s) 2022.

Mechanism of "Child prevention prescription" of Hunan province in prevention and treatment of COVID-19 based on network pharmacology and molecular docking

To analyze the mechanism of novel coronavirus prevention prescription in Hunan province by using network pharmacology method. Methods TCMSP, Batman-TCM and ETCM were used to retrieve drug composition and target information, and GeneCards, OMIM, DrugBank, TTD and PharmGkb were used to screen disease targets. The visualization network diagram of "drug-active component-target" was constructed by Cytoscape, the protein interaction network was drawn by STRING, the core targets of PPI network were analyzed by CytoNCA, GO function and KEGG pathway were analyzed, and the mechanism of action was predicted. Results A total of 418 active ingredients, 1 715 drug targets, 1 289 disease targets and 266 intersection targets were screened out. Quercetin, luteolin, kaempferol, baicalein, ursolic acid and naringin were identified as the key components, and 6 core targets were obtained: RELA, AKT1, STAT3, JUN, MAPK1 and MAPK3. The results of molecular docking showed that the binding potential and activity of the key active ingredients to the core target were good. Conclusions "Child prevention formula" has the characteristics of multi-target, multi-approach and multi-faceted prevention and treatment, which plays a role in prevention and treatment of COVID-19 among children. Copyright © 2022 Publication Centre of Anhui Medical University. All rights reserved.

Differential expression of platelet microRNAs in hospitalized patients with severe COVID-19

Background: Coronavirus disease 2019 (COVID-19) is often associated with enhanced platelet activation and thrombotic complications which may be reflected by altered microRNA (miRNA) levels in blood cells. Aim(s): We here investigated the expression of miRNAs in the background of platelet reactivity in severe COVID-19 and evaluated them for the prediction of disease mortality. Method(s): Platelet miRNAs were isolated from leukocyte-depleted platelets and profiled in COVID-19 survivors and non-survivors vs healthy controls using TaqMan Open Array. Candidate miRNAs showing at least 2-fold alteration between two groups were validated by RT-qPCR in 10 individuals from each group, and these data were correlated with clinical outcome in COVID-19. Differentially regulated miRNAs were bioinformatically analyzed to identify their mRNA targets and Cytoscape ClueGO was used for functional enrichment analysis. Platelet reactivity was evaluated via quantification of P-selectin expression, platelet-leukocyte aggregates and platelet-derived microparticles (PMPs) by flow cytometry. Result(s): Increased platelet activation was detected via elevated level of P-selectin positivity (6.5 vs 1.1%, P < 0.0001), platelet-monocyte aggregates (40 vs 17 %, P = 0.0315) and PMPs (22 vs 18 PMPs/10

Study on effective components of Ganoderma applanation and its mechanism of action in preventing COVID-19 based on UHPLC-Q- Exactive-Orbitrap-MS integrated network pharmacology

Aim To elucidate the effective components of Ganoderma applanatum and its mechanism of preventing the coronavirus disease 2019(COVID-19).Methods To begin with, UHPLC-Q-Exactive-Orbitrap-MS was established to identify the main chemical constituents of G.applanatum.Then, the predicted targets of G.applanatum were selected by Swiss Target Prediction.GO analysis and KEGG analysis of core target genes were performed using the DAVID database.Finally, to explore the potential mechanism of G.applanatum against COVID-19, core functional components-core target-metabolism path network diagram was constructed using Cytoscape 3.8.0, and molecular docking was used to analyze the binding force of the core effective compounds with angiotensin-converting enzyme II(ACE2)and three SARS CoV-2 proteins, nonstructural protein-15 Endoribonuclease(NSP15), the receptor-binding domain of spike protein(RBD of S protein), and main protease(Mpro/3CLpro).Results Sixty-two components were identified from G.applanatum by UHPLC-Q-Exactive-Orbitrap-MS study;30 active components were closely associated with 32 core targets including IL6, PTGS2, and MAPK1;KEGG analysis showed that it might treat COVID-19 through signaling pathways, such as PI3K-Akt signaling pathway, TNF signaling pathway, tuberculosis, and so on;molecular docking analysis showed that 1,4-Dihydroxy-2-naphthoic acid, parthenolide, 7,8-Dihydroxycoumarin, and other vital compounds had a certain degree of affinity with ACE2 and three SARS CoV-2 proteins.Conclusion This study clarifies the chemical composition and the potential mechanism of G.applanatum, providing a scientific basis for screening the effective ingredients of G.applanatum. Copyright © 2022 Publication Centre of Anhui Medical University. All rights reserved.

Exploring effective components and molecular targets of Guizhi decoction for treatment of COVID-19 combined with allergic rhinitis based on network pharmacology and molecular docking

Aim To explore the effeetive components and molecular targets of Guizhi decoetion in treating COVID-19 combined with allergic rhinitis.Methods The potential targets assoeiated with Guizhi deeoetion, allergie rhinitis and COVID-19 were sereened from TC- MSP and Gene Cards databases.Draw Venn Diagram website, String database, and Cytoscape software were used to obtain the common targets of drugs and diseases, followed by generation of PPI network and " herbal-active component-target" network as well as screening of core targets and key components based on the degree value.Metascape and KEGG databases were used for GO and KEGG enrichment analysis.Molecular docking was utilized to validate the affinity between the core targets and the key components.Results A total of 127 effective components of Guizhi decoction were screened, of which 108 components could combine with 52 common targets to exert the therapeutic effects.Common targets were mainly enriched in 1523 (X) terms and 145 KEGG signaling pathways.Molecular docking confirmed that the core targets could spontaneously combine with key components.Conclusions Guizhi decoction is mainly involved in the regulation of viral, immune and inflammation-related signaling pathways and biological cellular processes through the binding of active components such as flavonoids, phy- tosterols and phenols to common targets ( IL-6, TNF, MAPK3, etc.) , ultimately achieving the goal of treating COVID-19 and allergic rhinitis. Copyright © 2022 Publication Centre of Anhui Medical University. All rights reserved.

Mechanism of Huo-Xiang-Zheng-Qi in Preventing and Treating COVID-19: A Study Based on Network Pharmacology and Molecular Docking Techniques

Objective: The Chinese herbal formula Huo-Xiang-Zheng-Qi (HXZQ) is effective in preventing and treating coronavirus disease 19 (COVID-19) infection;however, its mechanism remains unclear. This study used network pharmacology and molecular docking techniques to investigate the mechanism of action of HXZQ in preventing and treating COVID-19. Methods: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to search for the active ingredients and targets of the 10 traditional Chinese medicines (TCMs) of HXZQ prescription (HXZQP). GeneCards, Online Mendelian Inheritance in Man (OMIM), Pharmacogenomics Knowledge Base (PharmGKB), Therapeutic Target Database (TTD), and DrugBank databases were used to screen COVID-19-related genes and intersect them with the targets of HXZQP to obtain the drug efficacy targets. Cytoscape 3.8 software was used to construct the drug-active ingredient–target interaction network of HXZQP and perform protein–protein interaction (PPI) network construction and topology analysis. R software was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Finally, AutoDock Vina was utilized for molecular docking of the active ingredients of TCM and drug target proteins. Results: A total of 151 active ingredients and 250 HXZQP targets were identified. Among these, 136 active ingredients and 67 targets of HXZQP were found to be involved in the prevention and treatment of COVID-19. The core proteins identified in the PPI network were MAPK1, MAPK3, MAPK8, MAPK14, STAT3, and PTGS2. Using GO and KEGG pathway enrichment analysis, HXZQP was found to primarily participate in biological processes such as defense response to a virus, cellular response to biotic stimulus, response to lipopolysaccharide, PI3K-Akt signaling pathway, Th17 cell differentiation, HIF-1 signaling pathway, and other signaling pathways closely related to COVID-19. Molecular docking results reflected that the active ingredients of HXZQP have a reliable affinity toward EGFR, MAPK1, MAPK3, MAPK8, and STAT3 proteins. Conclusion: Our study elucidated the main targets and pathways of HXZQP in the prevention and treatment of COVID-19. The study findings provide a basis for further investigation of the pharmacological effects of HXZQP.

Introducing Markers which are Involved in COVID-19 Disease Severe Condition Versus Mild State, a Network Analysis

Background: Coronavirus disease 2019 (COVID-19) had a pandemic spread worldwide. Most infected patients had a good prognosis, but some developed severe illnesses, which led to fatalities. It is urgent to define markers that reveal the severity of the disease. This study aimed to introduce the main plasma protein biomarkers involved in severe conditions versus mild infection states. Materials and Methods: A total of 91 significant differentially expressed proteins (DEPs) in the sera of the patients with the severe condition versus mild states were extracted from an original article. The protein interaction is included in a network designed via STRING database and Cytoscape software to find the critical proteins which differentiate severe conditions versus mild states. Results: A total of 6 hub nodes identified as critical target proteins were: APOB, SERPINA1, CP, ORM1, HASPA8, and VW, according to the Degree value of nodes. Conclusion: The expression of different biomarkers in the sera of COVID-19 patients can be considered differential markers that separate severe conditions from mild states;however, a more thorough investigation is required.

A comprehensive genome report for COVID-19 patients: GENCOV Study Canada

Background: Severe acute respiratory syndrome coronavirus (SARSCoV- 2) is a novel virus that causes Coronavirus Disease 2019 (COVID- 19). High-throughput sequencing technologies such as whole genome sequencing (WGS) and sequencing of viral genome DNA are being implemented to identify and report on genetic factors that may influence variability in symptom severity and immune response among patients infected by SARS-CoV-2. Genome sequencing has been useful for clinical diagnostic purposes, and can reveal other useful information such as disease risk factors that might lead to disease prevention or patient management strategies. UsingWGS and bioinformatics software tools, we describe a novel pipeline for the analysis of medically relevant genetic results and other findings identified in COVID-19 positive individuals, and the generation of a genome report that can effectively communicate these results to patients and their physicians. Study design: Enrollment will include up to 1500 patients with a positive COVID-19 nasopharyngeal swab. Blood samples will be collected at baseline, 1 month, 6 months, and 1 year after diagnosis. Antibody isotype (IgG, IgA, and IgM), titers, and viral neutralization will be analyzed. DNA will be isolated from blood lymphocytes and host genomes will be sequenced. Whole genomes will be assessed using ACMG criteria for the interpretation of pathogenic sequence variation using in-house and third-party software tools, and publicly available disease and control databases. Comprehensive gene panels will be implemented to allow for patients to receive clinically significant findings, including risk factor and carrier status, from multiple categories of potential genetic conditions including blood and immunology, endocrine, metabolic/mitochondrial, musculoskeletal, hearing loss, neurology, cardiology, ophthalmology, renal, skin, and gastrointestinal disorders. Common disease risk will be assessed using polygenic risk scores calculated for 6 diseases (atrial fibrillation, coronary artery disease, type 2 diabetes, prostate cancer, colorectal cancer, breast cancer). Pharmacogenomic gene variants that alter metabolizer phenotype and drug response in individuals will be reported, in addition to patient HLA-type. The genomic predictions fromABO and Rh blood types will be summarized and reported. Largescale continental ancestry estimation will be performed using publicly available reference populations. Finally, using viral genome DNA sequencing, the SARS-CoV-2 viral lineage will be identified and reported. An appointment with the study genetic counsellor will be scheduled to discuss results identified in the genome report and manage appropriate clinical referrals if necessary. Serology results will be reported. Regression models will examine associations between antibody response (titer, antigen target, viral neutralization ability), physiological response (biochemical, hematological and clinical characteristics), patient outcomes, viral lineage and genomic results. Significance: This study will link clinically relevant genomic results, in addition to other biological and serological characteristics, to potential factors that contribute to variability in SARS-CoV-2 outcomes. Results will be shared with family physicians for clinical follow up. This study will establish an efficient workflow using highthroughput genomic sequencing technology coupled with emerging bioinformatics platforms for the generation of comprehensive genome reports to aid in COVID-19 patient management and follow-up.

Bioinformatics analysis of high-throughput sequencing to identify key genes and signaling pathways in vero E6 cells infected by SARS-CoV-2

Background: In 2020, the coronavirus disease 2019 began spreading widely across the world. We aim to study the biological changes of SARS-CoV-2 infected Vero cells using high-throughput sequencing data, which will be helpful for vaccine development and drug screening. Methods: The data GSE153940 was obtained from the Gene Expression Omnibus database. R software was used to screen out differentially expressed genes and perform Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The protein-protein interaction network was built by STRING. Cytoscape 3.7.2 was applied for the visualization of the protein-protein interaction network and the identification of the hub genes. GraphPad Prism 8.4.3 was used to perform the statistical analysis to verify the obtained central genes. Results: A total of 3640 differentially expressed genes were obtained. The most significant enrichment items of Gene Ontology in the biological process, cellular component, and molecular function were the regulation of mRNA metabolic process, organelle inner membrane, and cadherin binding respectively. Ten enrichment pathways were identified by the Kyoto Encyclopedia of Genes and Genomes analyses. A protein-protein interaction network with 328 nodes and 498 edges was established. Six hub genes were screened out, among which four genes (MRPS7, DAP3, CHCHD1 and MRPL3) were confirmed to be statistically significant. Conclusions: Our results suggest that mitochondrial activity has a significant role in the process of SARS-CoV-2 infecting Vero E6 cells. Further experimental studies are needed to obtain abundant data to verify the predicted results of the bioinformatics analysis.

Predicting the Molecular Mechanism of Sini Jia Renshen Decoction in Treating Severe COVID-19 Patients Based on Network Pharmacology and Molecular Docking

Objective: To explore the potential mechanism of Sini jia Renshen Decoction (SJRD) in the treatment of COVID-19 based on network pharmacology and molecular docking. Methods: The active compounds and potential therapeutic targets of SJRD were collected through the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). Then a string database was used to build a protein–protein interactions (PPI) network between proteins, and use the David database to perform gene ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on core targets. Then we used Cytoscape software to construct an active ingredients-core target-signaling pathway network, and finally the active ingredients of SJRD were molecularly docked with the core targets to predict the mechanism of SJRD in the treatment of COVID-19. Results: A total of 136 active compounds, 51 core targets and 93 signaling pathways were selected. Molecular docking results revealed that quercetin, 3,22-dihydroxy-11-oxo-delta(12)-oleanene-27-alpha-methoxycarbonyl-29-oic acid, 18α-hydroxyglycyrrhetic acid, gomisin B and ignavine had considerable binding ability with ADRB2, PRKACA, DPP4, PIK3CG and IL6. Conclusions: This study preliminarily explored the mechanism of multiple components，multiple targets，and multiple pathways of SJRD in the treatment of COVID-19 by network pharmacology．