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1.
BMC Genom Data ; 23(1): 22, 2022 Mar 28.
Article in English | MEDLINE | ID: covidwho-1793989

ABSTRACT

OBJECTIVES: American shad (Alosa sapidissima) is an important migratory fish under Alosinae and has long been valued for its economic, nutritional and cultural attributes. Overfishing and barriers across the passage made it vulnerable to sustain. To protect this valuable species, aquaculture action plans have been taken though there are no published genetic resources prevailing yet. Here, we reported the first de novo assembled and annotated transcriptome of A. sapidissima using blood and brain tissues. DATA DESCRIPTION: We generated 160,481 and 129,040 non-redundant transcripts from brain and blood tissues. The entire work strategy involved RNA extraction, library preparation, sequencing, de novo assembly, filtering, annotation and validation. Both coding and non-coding transcripts were annotated against Swissprot and Pfam datasets. Nearly, 83% coding transcripts were functionally assigned. Protein clustering with clupeiform and non-clupeiform taxa revealed ~ 82% coding transcripts retained the orthologue relationship which improved confidence over annotation procedure. This study will serve as a useful resource in future for the research community to elucidate molecular mechanisms for several key traits like migration which is fascinating in clupeiform shads.


Subject(s)
Conservation of Natural Resources , Transcriptome , Animals , Brain , Fisheries , Fishes/genetics , Transcriptome/genetics
2.
Am J Physiol Cell Physiol ; 322(4): C787-C793, 2022 Apr 01.
Article in English | MEDLINE | ID: covidwho-1745645

ABSTRACT

Similar to epigenetic DNA modification, RNA can be methylated and altered for stability and processing. RNA modifications, namely, epitranscriptomes, involve the following three functions: writing, erasing, and reading of marks. Methods for measurement and position detection are useful for the assessment of cellular function and human disease biomarkers. After pyrimidine 5-methylcytosine was reported for the first time a hundred years ago, numerous techniques have been developed for studying nucleotide modifications, including RNAs. Recent studies have focused on high-throughput and direct measurements for investigating the precise function of epitranscriptomes, including the characterization of severe acute respiratory syndrome coronavirus 2. The current study presents an overview of the development of detection techniques for epitranscriptomic marks and briefs about the recent progress in this field.


Subject(s)
COVID-19 , Transcriptome , Epigenesis, Genetic , Humans , RNA/genetics , RNA/metabolism , RNA Processing, Post-Transcriptional , Transcriptome/genetics
3.
J Appl Genet ; 63(2): 423-428, 2022 May.
Article in English | MEDLINE | ID: covidwho-1739445

ABSTRACT

Analysis of the SARS-CoV-2 transcriptome has revealed a background of low-frequency intra-host genetic changes with a strong bias towards transitions. A similar pattern is also observed when inter-host variability is considered. We and others have shown that the cellular RNA editing machinery based on ADAR and APOBEC host-deaminases could be involved in the onset of SARS-CoV-2 genetic variability. Our hypothesis is based both on similarities with other known forms of viral genome editing and on the excess of transition changes, which is difficult to explain with errors during viral replication. Zong et al. criticize our analysis on both conceptual and technical grounds. While ultimate proof of an involvement of host deaminases in viral RNA editing will depend on experimental validation, here, we address the criticism to suggest that viral RNA editing is the most reasonable explanation for the observed intra- and inter-host variability.


Subject(s)
COVID-19 , RNA Editing , Adenosine Deaminase/genetics , Adenosine Deaminase/metabolism , COVID-19/genetics , Humans , RNA Editing/genetics , SARS-CoV-2/genetics , Transcriptome/genetics
4.
Int J Mol Sci ; 23(5)2022 Feb 24.
Article in English | MEDLINE | ID: covidwho-1715406

ABSTRACT

To better understand the molecular basis of respiratory diseases of viral origin, high-throughput gene-expression data are frequently taken by means of DNA microarray or RNA-seq technology. Such data can also be useful to classify infected individuals by molecular signatures in the form of machine-learning models with genes as predictor variables. Early diagnosis of patients by molecular signatures could also contribute to better treatments. An approach that has rarely been considered for machine-learning models in the context of transcriptomics is data augmentation. For other data types it has been shown that augmentation can improve classification accuracy and prevent overfitting. Here, we compare three strategies for data augmentation of DNA microarray and RNA-seq data from two selected studies on respiratory diseases of viral origin. The first study involves samples of patients with either viral or bacterial origin of the respiratory disease, the second study involves patients with either SARS-CoV-2 or another respiratory virus as disease origin. Specifically, we reanalyze these public datasets to study whether patient classification by transcriptomic signatures can be improved when adding artificial data for training of the machine-learning models. Our comparison reveals that augmentation of transcriptomic data can improve the classification accuracy and that fewer genes are necessary as explanatory variables in the final models. We also report genes from our signatures that overlap with signatures presented in the original publications of our example data. Due to strict selection criteria, the molecular role of these genes in the context of respiratory infectious diseases is underlined.


Subject(s)
COVID-19/genetics , Gene Expression Profiling/methods , Machine Learning , Neural Networks, Computer , RNA-Seq/methods , Transcriptome/genetics , Algorithms , COVID-19/classification , COVID-19/virology , Gene Ontology , Humans , Reproducibility of Results , SARS-CoV-2/physiology
5.
Cells ; 11(4)2022 02 11.
Article in English | MEDLINE | ID: covidwho-1688673

ABSTRACT

Transmembrane proteins of adherens and tight junctions are known targets for viruses and bacterial toxins. The coronavirus receptor ACE2 has been localized at the apical surface of epithelial cells, but it is not clear whether ACE2 is localized at apical Cell-Cell junctions and whether it associates with junctional proteins. Here we explored the expression and localization of ACE2 and its association with transmembrane and tight junction proteins in epithelial tissues and cultured cells by data mining, immunoblotting, immunofluorescence microscopy, and co-immunoprecipitation experiments. ACE2 mRNA is abundant in epithelial tissues, where its expression correlates with the expression of the tight junction proteins cingulin and occludin. In cultured epithelial cells ACE2 mRNA is upregulated upon differentiation and ACE2 protein is widely expressed and co-immunoprecipitates with the transmembrane proteins ADAM17 and CD9. We show by immunofluorescence microscopy that ACE2 colocalizes with ADAM17 and CD9 and the tight junction protein cingulin at apical junctions of intestinal (Caco-2), mammary (Eph4) and kidney (mCCD) epithelial cells. These observations identify ACE2, ADAM17 and CD9 as new epithelial junctional transmembrane proteins and suggest that the cytokine-enhanced endocytic internalization of junction-associated protein complexes comprising ACE2 may promote coronavirus entry.


Subject(s)
Angiotensin-Converting Enzyme 2/metabolism , Intercellular Junctions/metabolism , Intercellular Junctions/virology , ADAM17 Protein/metabolism , Adherens Junctions/metabolism , Angiotensin-Converting Enzyme 2/genetics , Cadherins/metabolism , Carrier Proteins/metabolism , Cell Line , Cell Membrane Permeability , Coronavirus/metabolism , Epithelial Cells/metabolism , Epithelial Cells/virology , Gene Expression/genetics , Tetraspanin 29/metabolism , Tight Junction Proteins/metabolism , Tight Junctions/metabolism , Transcriptome/genetics
6.
Front Immunol ; 12: 781100, 2021.
Article in English | MEDLINE | ID: covidwho-1686474

ABSTRACT

Multiple studies have investigated the role of blood circulating proteins in COVID-19 disease using the Olink affinity proteomics platform. However, study inclusion criteria and sample collection conditions varied between studies, leading to sometimes incongruent associations. To identify the most robust protein markers of the disease and the underlying pathways that are relevant under all conditions, it is essential to identify proteins that replicate most widely. Here we combined the Olink proteomics profiles of two newly recruited COVID-19 studies (N=68 and N=98) with those of three previously published COVID-19 studies (N=383, N=83, N=57). For these studies, three Olink panels (Inflammation and Cardiovascular II & III) with 253 unique proteins were compared. Case/control analysis revealed thirteen proteins (CCL16, CCL7, CXCL10, CCL8, LGALS9, CXCL11, IL1RN, CCL2, CD274, IL6, IL18, MERTK, IFNγ, and IL18R1) that were differentially expressed in COVID-19 patients in all five studies. Except CCL16, which was higher in controls, all proteins were overexpressed in COVID-19 patients. Pathway analysis revealed concordant trends across all studies with pathways related to cytokine-cytokine interaction, IL18 signaling, fluid shear stress and rheumatoid arthritis. Our results reaffirm previous findings related to a COVID-19 cytokine storm syndrome. Cross-study robustness of COVID-19 specific protein expression profiles support the utility of affinity proteomics as a tool and for the identification of potential therapeutic targets.


Subject(s)
Blood Proteins/metabolism , COVID-19/blood , Cytokines/blood , Transcriptome/genetics , Aged , Biomarkers/blood , COVID-19/immunology , Cytokine Release Syndrome/blood , Cytokine Release Syndrome/pathology , Cytokines/metabolism , Female , Gene Expression Profiling , Humans , Inflammation/blood , Male , Middle Aged , Proteomics , SARS-CoV-2/immunology , Signal Transduction
7.
Sci Immunol ; 7(68): eabf2846, 2022 02 11.
Article in English | MEDLINE | ID: covidwho-1685480

ABSTRACT

Macrophages regulate protective immune responses to infectious microbes, but aberrant macrophage activation frequently drives pathological inflammation. To identify regulators of vigorous macrophage activation, we analyzed RNA-seq data from synovial macrophages and identified SLAMF7 as a receptor associated with a superactivated macrophage state in rheumatoid arthritis. We implicated IFN-γ as a key regulator of SLAMF7 expression and engaging SLAMF7 drove a strong wave of inflammatory cytokine expression. Induction of TNF-α after SLAMF7 engagement amplified inflammation through an autocrine signaling loop. We observed SLAMF7-induced gene programs not only in macrophages from rheumatoid arthritis patients but also in gut macrophages from patients with active Crohn's disease and in lung macrophages from patients with severe COVID-19. This suggests a central role for SLAMF7 in macrophage superactivation with broad implications in human disease pathology.


Subject(s)
Inflammation/immunology , Macrophage Activation/immunology , Signaling Lymphocytic Activation Molecule Family/immunology , Transcriptome/immunology , Acute Disease , Adult , Arthritis, Rheumatoid/genetics , Arthritis, Rheumatoid/immunology , Arthritis, Rheumatoid/metabolism , COVID-19/genetics , COVID-19/immunology , COVID-19/metabolism , COVID-19/virology , Cells, Cultured , Chronic Disease , Crohn Disease/genetics , Crohn Disease/immunology , Crohn Disease/metabolism , Female , Humans , Inflammation/genetics , Inflammation/metabolism , Macrophage Activation/genetics , RNA-Seq/methods , Reverse Transcriptase Polymerase Chain Reaction/methods , SARS-CoV-2/immunology , SARS-CoV-2/physiology , Signaling Lymphocytic Activation Molecule Family/genetics , Signaling Lymphocytic Activation Molecule Family/metabolism , Single-Cell Analysis/methods , Synovial Membrane/immunology , Synovial Membrane/metabolism , Synovial Membrane/pathology , Transcriptome/genetics
8.
Cells ; 11(3)2022 01 30.
Article in English | MEDLINE | ID: covidwho-1667057

ABSTRACT

The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still ongoing, as is research on the molecular mechanisms underlying cellular infection by coronaviruses, with the hope of developing therapeutic agents against this pandemic. Other important respiratory viruses such as 2009 pandemic H1N1 and H7N9 avian influenza virus (AIV), influenza A viruses, are also responsible for a possible outbreak due to their respiratory susceptibility. However, the interaction of these viruses with host cells and the regulation of post-transcriptional genes remains unclear. In this study, we detected and analyzed the comparative transcriptome profiling of SARS-CoV-2, panH1N1 (A/California/07/2009), and H7N9 (A/Shanghai/1/2013) infected cells. The results showed that the commonly upregulated genes among the three groups were mainly involved in autophagy, pertussis, and tuberculosis, which indicated that autophagy plays an important role in viral pathogenicity. There are three groups of commonly downregulated genes involved in metabolic pathways. Notably, unlike panH1N1 and H7N9, SARS-CoV-2 infection can inhibit the m-TOR pathway and activate the p53 signaling pathway, which may be responsible for unique autophagy induction and cell apoptosis. Particularly, upregulated expression of IRF1 was found in SARS-CoV-2, panH1N1, and H7N9 infection. Further analysis showed SARS-CoV-2, panH1N1, and H7N9 infection-induced upregulation of lncRNA-34087.27 could serve as a competitive endogenous RNA to stabilize IRF1 mRNA by competitively binding with miR-302b-3p. This study provides new insights into the molecular mechanisms of influenza A virus and SARS-CoV-2 infection.


Subject(s)
COVID-19/immunology , Immunity/immunology , Influenza A Virus, H1N1 Subtype/immunology , Influenza A Virus, H7N9 Subtype/immunology , Influenza, Human/immunology , RNA/immunology , Transcriptome/immunology , A549 Cells , Animals , COVID-19/genetics , COVID-19/virology , HEK293 Cells , Host-Pathogen Interactions/immunology , Humans , Immunity/genetics , Influenza A Virus, H1N1 Subtype/physiology , Influenza A Virus, H7N9 Subtype/physiology , Influenza, Human/genetics , Influenza, Human/virology , Interferon Regulatory Factor-1/genetics , Interferon Regulatory Factor-1/immunology , Interferon Regulatory Factor-1/metabolism , MicroRNAs/genetics , MicroRNAs/immunology , MicroRNAs/metabolism , Pandemics/prevention & control , RNA/genetics , RNA/metabolism , RNA, Long Noncoding/genetics , RNA, Long Noncoding/immunology , RNA, Long Noncoding/metabolism , RNA, Messenger/genetics , RNA, Messenger/immunology , RNA, Messenger/metabolism , RNA-Seq/methods , SARS-CoV-2/physiology , Signal Transduction/genetics , Signal Transduction/immunology , Transcriptome/genetics
9.
Sci Rep ; 12(1): 1626, 2022 01 31.
Article in English | MEDLINE | ID: covidwho-1661980

ABSTRACT

The ongoing COVID-19 pandemic is one of the biggest health challenges of recent decades. Among the causes of mortality triggered by SARS-CoV-2 infection, the development of an inflammatory "cytokine storm" (CS) plays a determinant role. Here, we used transcriptomic data from the bronchoalveolar lavage fluid (BALF) of COVID-19 patients undergoing a CS to obtain gene-signatures associated to this pathology. Using these signatures, we interrogated the Connectivity Map (CMap) dataset that contains the effects of over 5000 small molecules on the transcriptome of human cell lines, and looked for molecules which effects on transcription mimic or oppose those of the CS. As expected, molecules that potentiate immune responses such as PKC activators are predicted to worsen the CS. In addition, we identified the negative regulation of female hormones among pathways potentially aggravating the CS, which helps to understand the gender-related differences in COVID-19 mortality. Regarding drugs potentially counteracting the CS, we identified glucocorticoids as a top hit, which validates our approach as this is the primary treatment for this pathology. Interestingly, our analysis also reveals a potential effect of MEK inhibitors in reverting the COVID-19 CS, which is supported by in vitro data that confirms the anti-inflammatory properties of these compounds.


Subject(s)
Anti-Inflammatory Agents/therapeutic use , COVID-19/complications , COVID-19/drug therapy , Computer Simulation , Cytokine Release Syndrome/etiology , Cytokine Release Syndrome/prevention & control , Glucocorticoids/therapeutic use , Pandemics , Protein Kinase Inhibitors/therapeutic use , SARS-CoV-2 , Anti-Inflammatory Agents/pharmacology , Bronchoalveolar Lavage Fluid/virology , COVID-19/blood , COVID-19/epidemiology , Cytokine Release Syndrome/mortality , Cytokines/blood , Female , Gene Expression Profiling/methods , Glucocorticoids/pharmacology , Humans , MAP Kinase Kinase Kinases/antagonists & inhibitors , MAP Kinase Signaling System/drug effects , Male , Protein Kinase Inhibitors/pharmacology , Sex Factors , Transcriptome/genetics
10.
Med Sci Monit ; 28: e934102, 2022 Jan 25.
Article in English | MEDLINE | ID: covidwho-1651076

ABSTRACT

BACKGROUND Heat-clearing and detoxifying herbs (HDHs) play an important role in the prevention and treatment of coronavirus infection. However, their mechanism of action needs further study. This study aimed to explore the anti-coronavirus basis and mechanism of HDHs. MATERIAL AND METHODS Database mining was performed on 7 HDHs. Core ingredients and targets were screened according to ADME rules combined with Neighborhood, Co-occurrence, Co-expression, and other algorithms. GO enrichment and KEGG pathway analyses were performed using the R language. Finally, high-throughput molecular docking was used for verification. RESULTS HDHs mainly acts on NOS3, EGFR, IL-6, MAPK8, PTGS2, MAPK14, NFKB1, and CASP3 through quercetin, luteolin, wogonin, indirubin alkaloids, ß-sitosterol, and isolariciresinol. These targets are mainly involved in the regulation of biological processes such as inflammation, activation of MAPK activity, and positive regulation of NF-kappaB transcription factor activity. Pathway analysis further revealed that the pathways regulated by these targets mainly include: signaling pathways related to viral and bacterial infections such as tuberculosis, influenza A, Ras signaling pathways; inflammation-related pathways such as the TLR, TNF, MAPK, and HIF-1 signaling pathways; and immune-related pathways such as NOD receptor signaling pathways. These pathways play a synergistic role in inhibiting lung inflammation and regulating immunity and antiviral activity. CONCLUSIONS HDHs play a role in the treatment of coronavirus infection by regulating the body's immunity, fighting inflammation, and antiviral activities, suggesting a molecular basis and new strategies for the treatment of COVID-19 and a foundation for the screening of new antiviral drugs.


Subject(s)
COVID-19/drug therapy , Coronavirus/drug effects , Drugs, Chinese Herbal/pharmacology , SARS-CoV-2/drug effects , Alkaloids/chemistry , Alkaloids/pharmacology , Caspase 3/drug effects , Caspase 3/genetics , Coronavirus/metabolism , Coronavirus Infections/drug therapy , Cyclooxygenase 2/drug effects , Cyclooxygenase 2/genetics , Databases, Pharmaceutical , Drugs, Chinese Herbal/chemistry , Drugs, Chinese Herbal/therapeutic use , Flavanones/chemistry , Flavanones/pharmacology , Humans , Indoles/chemistry , Indoles/pharmacology , Interleukin-6/genetics , Lignin/chemistry , Lignin/pharmacology , Luteolin/chemistry , Luteolin/pharmacology , Mitogen-Activated Protein Kinase 14/drug effects , Mitogen-Activated Protein Kinase 14/genetics , Mitogen-Activated Protein Kinase 8/drug effects , Mitogen-Activated Protein Kinase 8/genetics , Molecular Docking Simulation , NF-kappa B p50 Subunit/drug effects , NF-kappa B p50 Subunit/genetics , Naphthols/chemistry , Naphthols/pharmacology , Nitric Oxide Synthase Type III/drug effects , Nitric Oxide Synthase Type III/genetics , Protein Interaction Maps , Quercetin/chemistry , Quercetin/pharmacology , SARS-CoV-2/metabolism , Signal Transduction , Sitosterols/chemistry , Sitosterols/pharmacology , Transcriptome/drug effects , Transcriptome/genetics
11.
Cell Rep Med ; 3(2): 100522, 2022 02 15.
Article in English | MEDLINE | ID: covidwho-1650891

ABSTRACT

The molecular mechanisms underlying the clinical manifestations of coronavirus disease 2019 (COVID-19), and what distinguishes them from common seasonal influenza virus and other lung injury states such as acute respiratory distress syndrome, remain poorly understood. To address these challenges, we combine transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues to define body-wide transcriptome changes in response to COVID-19. We then match these data with spatial protein and expression profiling across 357 tissue sections from 16 representative patient lung samples and identify tissue-compartment-specific damage wrought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, evident as a function of varying viral loads during the clinical course of infection and tissue-type-specific expression states. Overall, our findings reveal a systemic disruption of canonical cellular and transcriptional pathways across all tissues, which can inform subsequent studies to combat the mortality of COVID-19 and to better understand the molecular dynamics of lethal SARS-CoV-2 and other respiratory infections.


Subject(s)
COVID-19/genetics , COVID-19/pathology , Lung/pathology , SARS-CoV-2 , Transcriptome/genetics , Adult , Aged , Aged, 80 and over , COVID-19/metabolism , COVID-19/virology , Case-Control Studies , Cohort Studies , Female , Gene Expression Regulation , Humans , Influenza, Human/genetics , Influenza, Human/pathology , Influenza, Human/virology , Lung/metabolism , Male , Middle Aged , Orthomyxoviridae , RNA-Seq/methods , Respiratory Distress Syndrome/genetics , Respiratory Distress Syndrome/microbiology , Respiratory Distress Syndrome/pathology , Viral Load
12.
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
13.
Eur J Med Res ; 26(1): 146, 2021 Dec 17.
Article in English | MEDLINE | ID: covidwho-1582003

ABSTRACT

BACKGROUND: At the end of 2019, the world witnessed the emergence and ravages of a viral infection induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Also known as the coronavirus disease 2019 (COVID-19), it has been identified as a public health emergency of international concern (PHEIC) by the World Health Organization (WHO) because of its severity. METHODS: The gene data of 51 samples were extracted from the GSE150316 and GSE147507 data set and then processed by means of the programming language R, through which the differentially expressed genes (DEGs) that meet the standards were screened. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on the selected DEGs to understand the functions and approaches of DEGs. The online tool STRING was employed to construct a protein-protein interaction (PPI) network of DEGs and, in turn, to identify hub genes. RESULTS: A total of 52 intersection genes were obtained through DEG identification. Through the GO analysis, we realized that the biological processes (BPs) that have the deepest impact on the human body after SARS-CoV-2 infection are various immune responses. By using STRING to construct a PPI network, 10 hub genes were identified, including IFIH1, DDX58, ISG15, EGR1, OASL, SAMD9, SAMD9L, XAF1, IFITM1, and TNFSF10. CONCLUSION: The results of this study will hopefully provide guidance for future studies on the pathophysiological mechanism of SARS-CoV-2 infection.


Subject(s)
COVID-19/genetics , Computational Biology/methods , Gene Expression Regulation/genetics , Lung/pathology , Protein Interaction Maps/genetics , COVID-19/pathology , Databases, Genetic , Gene Expression Profiling , Gene Ontology , Humans , Immunity, Humoral/genetics , Immunity, Humoral/immunology , Lung/virology , Neutrophil Activation/genetics , Neutrophil Activation/immunology , Neutrophils/immunology , SARS-CoV-2 , Transcriptome/genetics
14.
Int J Mol Sci ; 22(24)2021 Dec 19.
Article in English | MEDLINE | ID: covidwho-1580688

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) triggered the pandemic Coronavirus Disease 19 (COVID-19), causing millions of deaths. The elderly and those already living with comorbidity are likely to die after SARS-CoV-2 infection. People suffering from Alzheimer's disease (AD) have a higher risk of becoming infected, because they cannot easily follow health roles. Additionally, those suffering from dementia have a 40% higher risk of dying from COVID-19. Herein, we collected from Gene Expression Omnibus repository the brain samples of AD patients who died of COVID-19 (AD+COVID-19), AD without COVID-19 (AD), COVID-19 without AD (COVID-19) and control individuals. We inspected the transcriptomic and interactomic profiles by comparing the COVID-19 cohort against the control cohort and the AD cohort against the AD+COVID-19 cohort. SARS-CoV-2 in patients without AD mainly activated processes related to immune response and cell cycle. Conversely, 21 key nodes in the interactome are deregulated in AD. Interestingly, some of them are linked to beta-amyloid production and clearance. Thus, we inspected their role, along with their interactors, using the gene ontologies of the biological process that reveals their contribution in brain organization, immune response, oxidative stress and viral replication. We conclude that SARS-CoV-2 worsens the AD condition by increasing neurotoxicity, due to higher levels of beta-amyloid, inflammation and oxidative stress.


Subject(s)
Alzheimer Disease/genetics , COVID-19/complications , COVID-19/genetics , Alzheimer Disease/complications , Alzheimer Disease/virology , Amyloid beta-Peptides/metabolism , Brain/virology , COVID-19/physiopathology , Comorbidity/trends , Databases, Factual , Gene Expression/genetics , Gene Expression Profiling/methods , Humans , Inflammation/metabolism , Neurotoxicity Syndromes/metabolism , Oxidative Stress/physiology , Pandemics , SARS-CoV-2/metabolism , SARS-CoV-2/pathogenicity , Transcriptome/genetics
15.
Nat Cell Biol ; 23(12): 1314-1328, 2021 12.
Article in English | MEDLINE | ID: covidwho-1559292

ABSTRACT

The lung is the primary organ targeted by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), making respiratory failure a leading coronavirus disease 2019 (COVID-19)-related mortality. However, our cellular and molecular understanding of how SARS-CoV-2 infection drives lung pathology is limited. Here we constructed multi-omics and single-nucleus transcriptomic atlases of the lungs of patients with COVID-19, which integrate histological, transcriptomic and proteomic analyses. Our work reveals the molecular basis of pathological hallmarks associated with SARS-CoV-2 infection in different lung and infiltrating immune cell populations. We report molecular fingerprints of hyperinflammation, alveolar epithelial cell exhaustion, vascular changes and fibrosis, and identify parenchymal lung senescence as a molecular state of COVID-19 pathology. Moreover, our data suggest that FOXO3A suppression is a potential mechanism underlying the fibroblast-to-myofibroblast transition associated with COVID-19 pulmonary fibrosis. Our work depicts a comprehensive cellular and molecular atlas of the lungs of patients with COVID-19 and provides insights into SARS-CoV-2-related pulmonary injury, facilitating the identification of biomarkers and development of symptomatic treatments.


Subject(s)
COVID-19/genetics , Lung/metabolism , Transcriptome/genetics , Alveolar Epithelial Cells/metabolism , Alveolar Epithelial Cells/pathology , Alveolar Epithelial Cells/virology , COVID-19/metabolism , Fibrosis/metabolism , Fibrosis/pathology , Fibrosis/virology , Humans , Lung/pathology , Lung/virology , Proteomics/methods , SARS-CoV-2/pathogenicity
16.
Nat Commun ; 12(1): 6728, 2021 11 18.
Article in English | MEDLINE | ID: covidwho-1526074

ABSTRACT

Genes in SARS-CoV-2 and other viruses in the order of Nidovirales are expressed by a process of discontinuous transcription which is distinct from alternative splicing in eukaryotes and is mediated by the viral RNA-dependent RNA polymerase. Here, we introduce the DISCONTINUOUS TRANSCRIPT ASSEMBLYproblem of finding transcripts and their abundances given an alignment of paired-end short reads under a maximum likelihood model that accounts for varying transcript lengths. We show, using simulations, that our method, JUMPER, outperforms existing methods for classical transcript assembly. On short-read data of SARS-CoV-1, SARS-CoV-2 and MERS-CoV samples, we find that JUMPER not only identifies canonical transcripts that are part of the reference transcriptome, but also predicts expression of non-canonical transcripts that are supported by subsequent orthogonal analyses. Moreover, application of JUMPER on samples with and without treatment reveals viral drug response at the transcript level. As such, JUMPER enables detailed analyses of Nidovirales transcriptomes under varying conditions.


Subject(s)
COVID-19/genetics , SARS-CoV-2/genetics , Alternative Splicing/genetics , Gene Expression Profiling , Humans , Transcriptome/genetics
17.
PLoS Comput Biol ; 17(10): e1008794, 2021 10.
Article in English | MEDLINE | ID: covidwho-1523394

ABSTRACT

There has been a spate of interest in association networks in biological and medical research, for example, genetic interaction networks. In this paper, we propose a novel method, the extended joint hub graphical lasso (EDOHA), to estimate multiple related interaction networks for high dimensional omics data across multiple distinct classes. To be specific, we construct a convex penalized log likelihood optimization problem and solve it with an alternating direction method of multipliers (ADMM) algorithm. The proposed method can also be adapted to estimate interaction networks for high dimensional compositional data such as microbial interaction networks. The performance of the proposed method in the simulated studies shows that EDOHA has remarkable advantages in recognizing class-specific hubs than the existing comparable methods. We also present three applications of real datasets. Biological interpretations of our results confirm those of previous studies and offer a more comprehensive understanding of the underlying mechanism in disease.


Subject(s)
Computational Biology/methods , Gene Regulatory Networks/genetics , Protein Interaction Maps/genetics , Algorithms , Databases, Genetic , Humans , Microbiota/genetics , Transcriptome/genetics
18.
Cell Rep ; 37(7): 110020, 2021 11 16.
Article in English | MEDLINE | ID: covidwho-1509641

ABSTRACT

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types.


Subject(s)
COVID-19/genetics , SARS-CoV-2/genetics , Chromosome Mapping/methods , Computational Biology/methods , Databases, Genetic , Gene Expression/genetics , Gene Expression Profiling/methods , Genetic Predisposition to Disease/genetics , Genetic Variation/genetics , Genome-Wide Association Study/methods , Humans , Organ Specificity/genetics , Polymorphism, Single Nucleotide/genetics , Quantitative Trait Loci/genetics , SARS-CoV-2/pathogenicity , Severity of Illness Index , Transcriptome/genetics
19.
Nat Commun ; 12(1): 6243, 2021 10 29.
Article in English | MEDLINE | ID: covidwho-1493101

ABSTRACT

Understanding the pathology of COVID-19 is a global research priority. Early evidence suggests that the respiratory microbiome may be playing a role in disease progression, yet current studies report contradictory results. Here, we examine potential confounders in COVID-19 respiratory microbiome studies by analyzing the upper (n = 58) and lower (n = 35) respiratory tract microbiome in well-phenotyped COVID-19 patients and controls combining microbiome sequencing, viral load determination, and immunoprofiling. We find that time in the intensive care unit and type of oxygen support, as well as associated treatments such as antibiotic usage, explain the most variation within the upper respiratory tract microbiome, while SARS-CoV-2 viral load has a reduced impact. Specifically, mechanical ventilation is linked to altered community structure and significant shifts in oral taxa previously associated with COVID-19. Single-cell transcriptomics of the lower respiratory tract of COVID-19 patients identifies specific oral bacteria in physical association with proinflammatory immune cells, which show higher levels of inflammatory markers. Overall, our findings suggest confounders are driving contradictory results in current COVID-19 microbiome studies and careful attention needs to be paid to ICU stay and type of oxygen support, as bacteria favored in these conditions may contribute to the inflammatory phenotypes observed in severe COVID-19 patients.


Subject(s)
COVID-19/microbiology , Gastrointestinal Microbiome/genetics , Gastrointestinal Microbiome/physiology , Humans , Microbiota/physiology , SARS-CoV-2/pathogenicity , Transcriptome/genetics
20.
Front Immunol ; 12: 746203, 2021.
Article in English | MEDLINE | ID: covidwho-1477828

ABSTRACT

The reasons behind the clinical variability of SARS-CoV-2 infection, ranging from asymptomatic infection to lethal disease, are still unclear. We performed genome-wide transcriptional whole-blood RNA sequencing, bioinformatics analysis and PCR validation to test the hypothesis that immune response-related gene signatures reflecting baseline may differ between healthy individuals, with an equally robust antibody response, who experienced an entirely asymptomatic (n=17) versus clinical SARS-CoV-2 infection (n=15) in the past months (mean of 14 weeks). Among 12.789 protein-coding genes analysed, we identified six and nine genes with significantly decreased or increased expression, respectively, in those with prior asymptomatic infection relatively to those with clinical infection. All six genes with decreased expression (IFIT3, IFI44L, RSAD2, FOLR3, PI3, ALOX15), are involved in innate immune response while the first two are interferon-induced proteins. Among genes with increased expression six are involved in immune response (GZMH, CLEC1B, CLEC12A), viral mRNA translation (GCAT), energy metabolism (CACNA2D2) and oxidative stress response (ENC1). Notably, 8/15 differentially expressed genes are regulated by interferons. Our results suggest that subtle differences at baseline expression of innate immunity-related genes may be associated with an asymptomatic disease course in SARS-CoV-2 infection. Whether a certain gene signature predicts, or not, those who will develop a more efficient immune response upon exposure to SARS-CoV-2, with implications for prioritization for vaccination, warrant further study.


Subject(s)
Antibodies, Viral/blood , Asymptomatic Infections , Immunity, Innate/genetics , SARS-CoV-2/immunology , Transcriptome/genetics , Adult , COVID-19/pathology , Female , Gene Expression Profiling , Humans , Immunity, Innate/immunology , Male , RNA, Messenger/genetics , Sequence Analysis, RNA , Severity of Illness Index
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