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1.
Commun Biol ; 5(1): 21, 2022 01 11.
Article in English | MEDLINE | ID: covidwho-1621284

ABSTRACT

Deciphering cell-cell communication is a key step in understanding the physiology and pathology of multicellular systems. Recent advances in single-cell transcriptomics have contributed to unraveling the cellular composition of tissues and enabled the development of computational algorithms to predict cellular communication mediated by ligand-receptor interactions. Despite the existence of various tools capable of inferring cell-cell interactions from single-cell RNA sequencing data, the analysis and interpretation of the biological signals often require deep computational expertize. Here we present InterCellar, an interactive platform empowering lab-scientists to analyze and explore predicted cell-cell communication without requiring programming skills. InterCellar guides the biological interpretation through customized analysis steps, multiple visualization options, and the possibility to link biological pathways to ligand-receptor interactions. Alongside convenient data exploration features, InterCellar implements data-driven analyses including the possibility to compare cell-cell communication from multiple conditions. By analyzing COVID-19 and melanoma cell-cell interactions, we show that InterCellar resolves data-driven patterns of communication and highlights molecular signals through the integration of biological functions and pathways. We believe our user-friendly, interactive platform will help streamline the analysis of cell-cell communication and facilitate hypothesis generation in diverse biological systems.


Subject(s)
Transcriptome , COVID-19
2.
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
3.
Genet Res (Camb) ; 2021: 2728757, 2021.
Article in English | MEDLINE | ID: covidwho-1593203

ABSTRACT

Coronavirus disease 2019 (COVID-19) is acutely infectious pneumonia. Currently, the specific causes and treatment targets of COVID-19 are still unclear. Herein, comprehensive bioinformatics methods were employed to analyze the hub genes in COVID-19 and tried to reveal its potential mechanisms. First of all, 34 groups of COVID-19 lung tissues and 17 other diseases' lung tissues were selected from the GSE151764 gene expression profile for research. According to the analysis of the DEGs (differentially expressed genes) in the samples using the limma software package, 84 upregulated DEGs and 46 downregulated DEGs were obtained. Later, by the Database for Annotation, Visualization, and Integrated Discovery (DAVID), they were enriched in the Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. It was found that the upregulated DEGs were enriched in the type I interferon signaling pathway, AGE-RAGE signaling pathway in diabetic complications, coronavirus disease, etc. Downregulated DEGs were in cellular response to cytokine stimulus, IL-17 signaling pathway, FoxO signaling pathway, etc. Then, based on GSEA, the enrichment of the gene set in the sample was analyzed in the GO terms, and the gene set was enriched in the positive regulation of myeloid leukocyte cytokine production involved in immune response, programmed necrotic cell death, translesion synthesis, necroptotic process, and condensed nuclear chromosome. Finally, with the help of STRING tools, the PPI (protein-protein interaction) network diagrams of DEGs were constructed. With degree ≥13 as the cutoff degree, 3 upregulated hub genes (ISG15, FN1, and HLA-G) and 4 downregulated hub genes (FOXP3, CXCR4, MMP9, and CD69) were screened out for high degree. All these findings will help us to understand the potential molecular mechanisms of COVID-19, which is also of great significance for its diagnosis and prevention.


Subject(s)
COVID-19 , Computational Biology , Gene Expression Profiling , Humans , SARS-CoV-2 , Signal Transduction , Transcriptome
4.
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
5.
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
6.
Sci Immunol ; 5(44)2020 02 21.
Article in English | MEDLINE | ID: covidwho-1575907

ABSTRACT

Myeloid-derived suppressor cells (MDSCs) are innate immune cells that acquire the capacity to suppress adaptive immune responses during cancer. It remains elusive how MDSCs differ from their normal myeloid counterparts, which limits our ability to specifically detect and therapeutically target MDSCs during cancer. Here, we sought to determine the molecular features of breast cancer-associated MDSCs using the widely studied mouse model based on the mouse mammary tumor virus (MMTV) promoter-driven expression of the polyomavirus middle T oncoprotein (MMTV-PyMT). To identify MDSCs in an unbiased manner, we used single-cell RNA sequencing to compare MDSC-containing splenic myeloid cells from breast tumor-bearing mice with wild-type controls. Our computational analysis of 14,646 single-cell transcriptomes revealed that MDSCs emerge through an aberrant neutrophil maturation trajectory in the spleen that confers them an immunosuppressive cell state. We establish the MDSC-specific gene signature and identify CD84 as a surface marker for improved detection and enrichment of MDSCs in breast cancers.


Subject(s)
Breast Neoplasms/pathology , Myeloid-Derived Suppressor Cells/pathology , Single-Cell Analysis , Transcriptome , Animals , Biomarkers, Tumor/genetics , Biomarkers, Tumor/immunology , Breast Neoplasms/immunology , Cell Differentiation/genetics , Female , Humans , Mice , Mice, Inbred Strains , Mice, Transgenic , Myeloid-Derived Suppressor Cells/immunology , RNA, Neoplasm/genetics , RNA, Neoplasm/immunology , Signaling Lymphocytic Activation Molecule Family/genetics , Signaling Lymphocytic Activation Molecule Family/immunology
7.
Zhong Nan Da Xue Xue Bao Yi Xue Ban ; 46(11): 1203-1211, 2021 Nov 28.
Article in English, Chinese | MEDLINE | ID: covidwho-1575959

ABSTRACT

OBJECTIVES: Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 can damage the myocardium directly, or activate the immune system, trigger a cytokine storm, and cause inflammatory cells to infiltrate the myocardial tissue and damage the myocardium. This study is based on the sequencing data to analyze the changes in gene expression of cardiomyocytes and macrophages after SARS-CoV-2 infection, and explore the potential effects of SARS-CoV-2 on the heart and immune system. METHODS: The public data set GSE151879 was retrieved. The online software Network Analyst was used to preprocess the data, and the differentially expressed genes (DEGs) [log2(fold change)>2, adjusted P-value<0.05] screening between the infection group and the control group in cardiomyocytes, human embryonic stem cell-derived cardiomyocytes, and macrophages were screened. Consistent common differentially expressed genes (CCDEGs) with the same expression pattern in cardiomyocytes and macrophages were obtained, and the online analysis software String was used to conduct enrichment analysis of their biological functions and signal pathways. Protein-protein interaction network, transcription factor-gene interaction network, miRNA-gene interaction network and environmental chemical-gene interaction network were established, and Cytoscape 3.72 was used to perform visualization. RESULTS: After data standardization, the data quality was excellent and it can ensure reliable results. Myocardial cell infection with SARS-CoV-2 and gene expression spectrum were changed significantly, including a total of 484 DEGs in adult cardiomyoblasts, a total of 667 DEGs in macrophages, and a total of 1 483 DEGs in human embryo source of cardiomyopathy. The Stum, mechanosensory transduction mediator homolog (STUM), dehydrogenase/reductase 9 (DHRS9), calcium/calmodulin dependent protein kinase II beta (CAMK2B), claudin 1(CLDN1), C-C motif chemokine ligand 2 (CCL2), TNFAIP3 interacting protein 3 (TNIP3), G protein-coupled receptor 84 (GPR84), and C-X-C motif chemokine ligand 1 (CXCL1) were identical in expression patterns in 3 types of cells. The protein-protein interaction suggested that CAMK2B proteins may play a key role in the antiviral process in 3 types of cells; and silicon dioxide (SiO2), benzodiazepine (BaP), nickel (Ni), and estradiol (E2) affect anti-SARS-CoV-2 processes of the 3 types of cells. CONCLUSIONS: CAMK2B, CLDN1, CCL2, and DHRS9 genes play important roles in the immune response of cardiomyocytes against SARS-CoV-2. SiO2, BaP, Ni, E2 may affect the cell's antiviral process by increasing the toxicity of cardiomyocytes, thereby aggravating SARS-CoV-2 harm to the heart.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Macrophages , Myocytes, Cardiac , Silicon Dioxide , Transcriptome
8.
Proc Natl Acad Sci U S A ; 118(51)2021 12 21.
Article in English | MEDLINE | ID: covidwho-1573990

ABSTRACT

The positive impact of meditation on human well-being is well documented, yet its molecular mechanisms are incompletely understood. We applied a comprehensive systems biology approach starting with whole-blood gene expression profiling combined with multilevel bioinformatic analyses to characterize the coexpression, transcriptional, and protein-protein interaction networks to identify a meditation-specific core network after an advanced 8-d Inner Engineering retreat program. We found the response to oxidative stress, detoxification, and cell cycle regulation pathways were down-regulated after meditation. Strikingly, 220 genes directly associated with immune response, including 68 genes related to interferon signaling, were up-regulated, with no significant expression changes in the inflammatory genes. This robust meditation-specific immune response network is significantly dysregulated in multiple sclerosis and severe COVID-19 patients. The work provides a foundation for understanding the effect of meditation and suggests that meditation as a behavioral intervention can voluntarily and nonpharmacologically improve the immune response for treating various conditions associated with excessive or persistent inflammation with a dampened immune system profile.


Subject(s)
Immune System/metabolism , Meditation , Transcriptome , Adult , COVID-19/immunology , COVID-19/metabolism , Diet, Vegan , Female , Genome, Human , Humans , Male , Multiple Sclerosis/immunology , Multiple Sclerosis/metabolism , Protein Interaction Maps
9.
BMC Med Genomics ; 14(Suppl 6): 289, 2021 12 14.
Article in English | MEDLINE | ID: covidwho-1571758

ABSTRACT

BACKGROUND: Virus screening and viral genome reconstruction are urgent and crucial for the rapid identification of viral pathogens, i.e., tracing the source and understanding the pathogenesis when a viral outbreak occurs. Next-generation sequencing (NGS) provides an efficient and unbiased way to identify viral pathogens in host-associated and environmental samples without prior knowledge. Despite the availability of software, data analysis still requires human operations. A mature pipeline is urgently needed when thousands of viral pathogen and viral genome reconstruction samples need to be rapidly identified. RESULTS: In this paper, we present a rapid and accurate workflow to screen metagenomics sequencing data for viral pathogens and other compositions, as well as enable a reference-based assembler to reconstruct viral genomes. Moreover, we tested our workflow on several metagenomics datasets, including a SARS-CoV-2 patient sample with NGS data, pangolins tissues with NGS data, Middle East Respiratory Syndrome (MERS)-infected cells with NGS data, etc. Our workflow demonstrated high accuracy and efficiency when identifying target viruses from large scale NGS metagenomics data. Our workflow was flexible when working with a broad range of NGS datasets from small (kb) to large (100 Gb). This took from a few minutes to a few hours to complete each task. At the same time, our workflow automatically generates reports that incorporate visualized feedback (e.g., metagenomics data quality statistics, host and viral sequence compositions, details about each of the identified viral pathogens and their coverages, and reassembled viral pathogen sequences based on their closest references). CONCLUSIONS: Overall, our system enabled the rapid screening and identification of viral pathogens from metagenomics data, providing an important piece to support viral pathogen research during a pandemic. The visualized report contains information from raw sequence quality to a reconstructed viral sequence, which allows non-professional people to screen their samples for viruses by themselves (Additional file 1).


Subject(s)
COVID-19 Testing/methods , COVID-19/diagnosis , Computational Biology/methods , Genome, Viral , Genomics , Metagenomics , SARS-CoV-2/genetics , Algorithms , Animals , Automation , Coronavirus Infections/genetics , High-Throughput Nucleotide Sequencing , Humans , Mass Screening/methods , Pandemics , Pangolins , Reference Values , Software , Transcriptome , Workflow
10.
Viruses ; 13(12)2021 12 11.
Article in English | MEDLINE | ID: covidwho-1572663

ABSTRACT

BACKGROUND: There is an urgent need for new antivirals with powerful therapeutic potential and tolerable side effects. METHODS: Here, we tested the antiviral properties of interferons (IFNs), alone and with other drugs in vitro. RESULTS: While IFNs alone were insufficient to completely abolish replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), IFNα, in combination with remdesivir, EIDD-2801, camostat, cycloheximide, or convalescent serum, proved to be more effective. Transcriptome and metabolomic analyses revealed that the IFNα-remdesivir combination suppressed SARS-CoV-2-mediated changes in Calu-3 cells and lung organoids, although it altered the homeostasis of uninfected cells and organoids. We also demonstrated that IFNα combinations with sofosbuvir, telaprevir, NITD008, ribavirin, pimodivir, or lamivudine were effective against HCV, HEV, FLuAV, or HIV at lower concentrations, compared to monotherapies. CONCLUSIONS: Altogether, our results indicated that IFNα can be combined with drugs that affect viral RNA transcription, protein synthesis, and processing to make synergistic combinations that can be attractive targets for further pre-clinical and clinical development against emerging and re-emerging viral infections.


Subject(s)
Antiviral Agents/pharmacology , Interferon-alpha/pharmacology , SARS-CoV-2/drug effects , Cell Line , Drug Synergism , Humans , Lung/drug effects , Lung/metabolism , Lung/virology , Metabolome/drug effects , Organoids , RNA, Viral/biosynthesis , RNA, Viral/drug effects , Signal Transduction/drug effects , Transcriptome/drug effects , Virus Replication/drug effects , Viruses/classification , Viruses/drug effects
11.
Methods Mol Biol ; 2401: 195-215, 2022.
Article in English | MEDLINE | ID: covidwho-1568331

ABSTRACT

The COVID-19 pandemic has hit heavily many aspects of our lives. At this time, genomic research is concerned with exploiting available datasets and knowledge to fuel discovery on this novel disease. Studies that can precisely characterize the gene expression profiles of human hosts infected by SARS-CoV-2 are of significant relevance. However, not many such experiments have yet been produced to date, nor made publicly available online. Thus, it is of paramount importance that data analysts explore all possibilities to integrate information coming from similar viruses and related diseases; interestingly, microarray gene profile experiments become extremely valuable for this purpose. This chapter reviews the aspects that should be considered when integrating transcriptomics data, considering mainly samples infected by different viruses and combining together various data types and also the extracted knowledge. It describes a series of scenarios from studies performed in literature and it suggests possible other directions of noteworthy integration.


Subject(s)
COVID-19 , Gene Expression Profiling , COVID-19/genetics , Genomics , Humans , Pandemics , Transcriptome
12.
Cell Rep ; 37(6): 109920, 2021 11 09.
Article in English | MEDLINE | ID: covidwho-1530684

ABSTRACT

It is urgent to develop disease models to dissect mechanisms regulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Here, we derive airway organoids from human pluripotent stem cells (hPSC-AOs). The hPSC-AOs, particularly ciliated-like cells, are permissive to SARS-CoV-2 infection. Using this platform, we perform a high content screen and identify GW6471, which blocks SARS-CoV-2 infection. GW6471 can also block infection of the B.1.351 SARS-CoV-2 variant. RNA sequencing (RNA-seq) analysis suggests that GW6471 blocks SARS-CoV-2 infection at least in part by inhibiting hypoxia inducible factor 1 subunit alpha (HIF1α), which is further validated by chemical inhibitor and genetic perturbation targeting HIF1α. Metabolic profiling identifies decreased rates of glycolysis upon GW6471 treatment, consistent with transcriptome profiling. Finally, xanthohumol, 5-(tetradecyloxy)-2-furoic acid, and ND-646, three compounds that suppress fatty acid biosynthesis, also block SARS-CoV-2 infection. Together, a high content screen coupled with transcriptome and metabolic profiling reveals a key role of the HIF1α-glycolysis axis in mediating SARS-CoV-2 infection of human airway epithelium.


Subject(s)
COVID-19/metabolism , Glycolysis/physiology , Hypoxia-Inducible Factor 1, alpha Subunit/metabolism , Lung/metabolism , Organoids/metabolism , Animals , Cell Line , Chlorocebus aethiops , Epithelial Cells/metabolism , HEK293 Cells , Humans , Pluripotent Stem Cells/metabolism , SARS-CoV-2/pathogenicity , Transcriptome/physiology , Vero Cells
13.
Front Immunol ; 12: 756288, 2021.
Article in English | MEDLINE | ID: covidwho-1518488

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic has caused many deaths worldwide. To date, the mechanism of viral immune escape remains unclear, which is a great obstacle to developing effective clinical treatment. RNA processing mechanisms, including alternative polyadenylation (APA) and alternative splicing (AS), are crucial in the regulation of most human genes in many types of infectious diseases. Because the role of APA and AS in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remains unknown, we performed de novo identification of dynamic APA sites using a public dataset of human peripheral blood mononuclear cell (PBMC) RNA-Seq data in COVID-19 patients. We found that genes with APA were enriched in innate immunity -related gene ontology categories such as neutrophil activation, regulation of the MAPK cascade and cytokine production, response to interferon-gamma and the innate immune response. We also reported genome-wide AS events and enriched viral transcription-related categories upon SARS-CoV-2 infection. Interestingly, we found that APA events may give better predictions than AS in COVID-19 patients, suggesting that APA could act as a potential therapeutic target and novel biomarker in those patients. Our study is the first to annotate genes with APA and AS in COVID-19 patients and highlights the roles of APA variation in SARS-CoV-2 infection.


Subject(s)
COVID-19/genetics , Polyadenylation , SARS-CoV-2 , Alternative Splicing , COVID-19/immunology , Female , Genome, Human , Humans , Immunity, Innate , Leukocytes, Mononuclear , Male , RNA, Messenger , Transcriptome
14.
BMC Genom Data ; 22(1): 49, 2021 11 14.
Article in English | MEDLINE | ID: covidwho-1518254

ABSTRACT

BACKGROUND: There is an urgent need to understand the key events driving pathogenesis of severe COVID-19 disease, so that precise treatment can be instituted. In this respect NETosis is gaining increased attention in the scientific community, as an important pathological process contributing to mortality. We sought to test if indeed there exists robust evidence of NETosis in multiple transcriptomic data sets from human subjects with severe COVID-19 disease. Gene set enrichment analysis was performed to test for up-regulation of gene set functional in NETosis in the blood of patients with COVID-19 illness. RESULTS: Blood gene expression functional in NETosis increased with severity of illness, showed negative correlation with blood oxygen saturation, and was validated in the lung of COVID-19 non-survivors. Temporal expression of IL-6 was compared between severe and moderate illness with COVID-19. Unsupervised clustering was performed to reveal co-expression of IL-6 with complement genes. In severe COVID-19 illness, there is transcriptional evidence of activation of NETosis, complement and coagulation cascade, and negative correlation between NETosis and respiratory function (oxygen saturation). An early spike in IL-6 is observed in severe COVID-19 illness that is correlated with complement activation. CONCLUSIONS: Based on the transcriptional dynamics of IL-6 expression and its downstream effect on complement activation, we constructed a model that links early spike in IL-6 level with persistent and self-perpetuating complement activation, NETosis, immunothrombosis and respiratory dysfunction. Our model supports the early initiation of anti-IL6 therapy in severe COVID-19 disease before the life-threatening complications of the disease can perpetuate themselves autonomously.


Subject(s)
COVID-19/immunology , Extracellular Traps , Interleukin-6 , Thrombosis/virology , Transcriptome , COVID-19/pathology , Complement System Proteins/genetics , Humans , Interleukin-6/genetics , Oxygen
15.
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
16.
Front Immunol ; 12: 724914, 2021.
Article in English | MEDLINE | ID: covidwho-1506196

ABSTRACT

The year 2019 has seen an emergence of the novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease of 2019 (COVID-19). Since the onset of the pandemic, biological and interdisciplinary research is being carried out across the world at a rapid pace to beat the pandemic. There is an increased need to comprehensively understand various aspects of the virus from detection to treatment options including drugs and vaccines for effective global management of the disease. In this review, we summarize the salient findings pertaining to SARS-CoV-2 biology, including symptoms, hosts, epidemiology, SARS-CoV-2 genome, and its emerging variants, viral diagnostics, host-pathogen interactions, alternative antiviral strategies and application of machine learning heuristics and artificial intelligence for effective management of COVID-19 and future pandemics.


Subject(s)
COVID-19/immunology , SARS-CoV-2/physiology , Artificial Intelligence , COVID-19/epidemiology , Comorbidity , Heuristics , Host-Pathogen Interactions , Humans , Pandemics , Proteomics , Transcriptome
17.
J Am Soc Nephrol ; 32(1): 86-97, 2021 01.
Article in English | MEDLINE | ID: covidwho-1496654

ABSTRACT

BACKGROUND: Cultured cell lines are widely used for research in the physiology, pathophysiology, toxicology, and pharmacology of the renal proximal tubule. The lines that are most appropriate for a given use depend upon the genes expressed. New tools for transcriptomic profiling using RNA sequencing (RNA-Seq) make it possible to catalog expressed genes in each cell line. METHODS: Fourteen different proximal tubule cell lines, representing six species, were grown on permeable supports under conditions specific for the respective lines. RNA-Seq followed standard procedures. RESULTS: Transcripts expressed in cell lines variably matched transcripts selectively expressed in native proximal tubule. Opossum kidney (OK) cells displayed the highest percentage match (45% of proximal marker genes [TPM threshold =15]), with pig kidney cells (LLC-PK1) close behind (39%). Lower-percentage matches were seen for various human lines, including HK-2 (26%), and lines from rodent kidneys, such as NRK-52E (23%). Nominally, identical OK cells from different sources differed substantially in expression of proximal tubule markers. Mapping cell line transcriptomes to gene sets for various proximal tubule functions (sodium and water transport, protein transport, metabolic functions, endocrine functions) showed that different lines may be optimal for experimentally modeling each function. An online resource (https://esbl.nhlbi.nih.gov/JBrowse/KCT/) has been created to interrogate cell line transcriptome data. Proteomic analysis of NRK-52E cells confirmed low expression of many proximal tubule marker proteins. CONCLUSIONS: No cell line fully matched the transcriptome of native proximal tubule cells. However, some of the lines tested are suitable for the study of particular metabolic and transport processes seen in the proximal tubule.


Subject(s)
Cell Culture Techniques/methods , Kidney Tubules, Proximal/metabolism , Transcriptome , Animals , Biological Transport , Cell Line , Chromatography, Liquid , Gene Expression Profiling , Humans , Internet , Mice , Opossums , Proteomics , RNA-Seq , Rats , Sequence Analysis, RNA , Species Specificity , Swine , Tandem Mass Spectrometry
18.
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
19.
Int J Mol Sci ; 22(21)2021 Oct 30.
Article in English | MEDLINE | ID: covidwho-1488618

ABSTRACT

The inflammatory response plays a central role in the complications of congenital pulmonary airway malformations (CPAM) and severe coronavirus disease 2019 (COVID-19). The aim of this study was to evaluate the transcriptional changes induced by SARS-CoV-2 exposure in pediatric MSCs derived from pediatric lung (MSCs-lung) and CPAM tissues (MSCs-CPAM) in order to elucidate potential pathways involved in SARS-CoV-2 infection in a condition of exacerbated inflammatory response. MSCs-lung and MSCs-CPAM do not express angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TRMPSS2). SARS-CoV-2 appears to be unable to replicate in MSCs-CPAM and MSCs-lung. MSCs-lung and MSCs-CPAM maintained the expression of stemness markers MSCs-lung show an inflammatory response (IL6, IL1B, CXCL8, and CXCL10), and the activation of Notch3 non-canonical pathway; this route appears silent in MSCs-CPAM, and cytokine genes expression is reduced. Decreased value of p21 in MSCs-lung suggested no cell cycle block, and cells did not undergo apoptosis. MSCs-lung appears to increase genes associated with immunomodulatory function but could contribute to inflammation, while MSCs-CPAM keeps stable or reduce the immunomodulatory receptors expression, but they also reduce their cytokines expression. These data indicated that, independently from their perilesional or cystic origin, the MSCs populations already present in a patient affected with CPAM are not permissive for SARS-CoV-2 entry, and they will not spread the disease in case of infection. Moreover, these MSCs will not undergo apoptosis when they come in contact with SARS-CoV-2; on the contrary, they maintain their staminality profile.


Subject(s)
Mesenchymal Stem Cells/metabolism , Respiratory System Abnormalities , SARS-CoV-2/physiology , Transcriptome , COVID-19/genetics , COVID-19/metabolism , COVID-19/pathology , Case-Control Studies , Cells, Cultured , Gene Expression Profiling , Host-Pathogen Interactions/genetics , Humans , Infant , Lung/abnormalities , Lung/metabolism , Lung/pathology , Male , Mesenchymal Stem Cells/pathology , Mesenchymal Stem Cells/virology , RNA-Seq , Respiratory System Abnormalities/genetics , Respiratory System Abnormalities/pathology , Respiratory System Abnormalities/virology
20.
Commun Biol ; 4(1): 1215, 2021 10 22.
Article in English | MEDLINE | ID: covidwho-1479821

ABSTRACT

SARS-CoV-2 replication requires the synthesis of a set of structural proteins expressed through discontinuous transcription of ten subgenomic mRNAs (sgmRNAs). Here, we have fine-tuned droplet digital PCR (ddPCR) assays to accurately detect and quantify SARS-CoV-2 genomic ORF1ab and sgmRNAs for the nucleocapsid (N) and spike (S) proteins. We analyzed 166 RNA samples from anonymized SARS-CoV-2 positive subjects and we observed a recurrent and characteristic pattern of sgmRNAs expression in relation to the total viral RNA content. Additionally, expression profiles of sgmRNAs, as determined by meta-transcriptomics sequencing of a subset of 110 RNA samples, were highly correlated with those obtained by ddPCR. By providing a comprehensive and dynamic snapshot of the levels of SARS-CoV-2 sgmRNAs in infected individuals, our results may contribute a better understanding of the dynamics of transcription and expression of the genome of SARS-CoV-2 and facilitate the development of more accurate molecular diagnostic tools for the stratification of COVID-19 patients.


Subject(s)
COVID-19 Nucleic Acid Testing/methods , COVID-19/genetics , COVID-19/metabolism , Coronavirus Nucleocapsid Proteins , Polymerase Chain Reaction/methods , RNA, Viral/metabolism , SARS-CoV-2 , Spike Glycoprotein, Coronavirus , Transcriptome , Computational Biology , Humans , Limit of Detection , Open Reading Frames , Phosphoproteins , RNA, Messenger/metabolism , Real-Time Polymerase Chain Reaction , Reproducibility of Results
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