Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 285
Filter
Add filters

Document Type
Year range
1.
Proc Natl Acad Sci U S A ; 119(1)2022 01 04.
Article in English | MEDLINE | ID: covidwho-1595265

ABSTRACT

Infection by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) provokes a potentially fatal pneumonia with multiorgan failure, and high systemic inflammation. To gain mechanistic insight and ferret out the root of this immune dysregulation, we modeled, by in vitro coculture, the interactions between infected epithelial cells and immunocytes. A strong response was induced in monocytes and B cells, with a SARS-CoV-2-specific inflammatory gene cluster distinct from that seen in influenza A or Ebola virus-infected cocultures, and which reproduced deviations reported in blood or lung myeloid cells from COVID-19 patients. A substantial fraction of the effect could be reproduced after individual transfection of several SARS-CoV-2 proteins (Spike and some nonstructural proteins), mediated by soluble factors, but not via transcriptional induction. This response was greatly muted in monocytes from healthy children, perhaps a clue to the age dependency of COVID-19. These results suggest that the inflammatory malfunction in COVID-19 is rooted in the earliest perturbations that SARS-CoV-2 induces in epithelia.


Subject(s)
COVID-19/immunology , Epithelial Cells/immunology , Monocytes/immunology , SARS-CoV-2/pathogenicity , Adult , B-Lymphocytes/immunology , COVID-19/pathology , Child , Coculture Techniques , Ebolavirus/pathogenicity , Epithelial Cells/virology , Gene Expression Profiling , Humans , Inflammation , Influenza A virus/pathogenicity , Lung/immunology , Myeloid Cells/immunology , Species Specificity , Viral Proteins/immunology
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.
Front Immunol ; 12: 724936, 2021.
Article in English | MEDLINE | ID: covidwho-1592205

ABSTRACT

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


Subject(s)
COVID-19/genetics , Gene Expression Profiling/methods , Gene Expression Regulation , Immunity/genetics , Aged , COVID-19/epidemiology , COVID-19/immunology , Female , Gene Ontology , Gene Regulatory Networks , Humans , Male , Middle Aged , Pandemics/prevention & control , Protein Interaction Maps/genetics , SARS-CoV-2/immunology , SARS-CoV-2/physiology , Signal Transduction/genetics , Signal Transduction/immunology
5.
Front Immunol ; 12: 774776, 2021.
Article in English | MEDLINE | ID: covidwho-1581334

ABSTRACT

Both RNA N6-methyladenosine (m6A) modification of SARS-CoV-2 and immune characteristics of the human body have been reported to play an important role in COVID-19, but how the m6A methylation modification of leukocytes responds to the virus infection remains unknown. Based on the RNA-seq of 126 samples from the GEO database, we disclosed that there is a remarkably higher m6A modification level of blood leukocytes in patients with COVID-19 compared to patients without COVID-19, and this difference was related to CD4+ T cells. Two clusters were identified by unsupervised clustering, m6A cluster A characterized by T cell activation had a higher prognosis than m6A cluster B. Elevated metabolism level, blockage of the immune checkpoint, and lower level of m6A score were observed in m6A cluster B. A protective model was constructed based on nine selected genes and it exhibited an excellent predictive value in COVID-19. Further analysis revealed that the protective score was positively correlated to HFD45 and ventilator-free days, while negatively correlated to SOFA score, APACHE-II score, and crp. Our works systematically depicted a complicated correlation between m6A methylation modification and host lymphocytes in patients infected with SARS-CoV-2 and provided a well-performing model to predict the patients' outcomes.


Subject(s)
Adenosine/analogs & derivatives , COVID-19/immunology , COVID-19/virology , Host-Pathogen Interactions/immunology , Leukocytes/immunology , RNA, Viral/genetics , SARS-CoV-2/physiology , Adenosine/metabolism , Cluster Analysis , Computational Biology/methods , Disease Susceptibility/immunology , Gene Expression Profiling , Humans , Leukocytes/metabolism , RNA, Viral/metabolism , ROC Curve
6.
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
7.
Viruses ; 13(12)2021 12 17.
Article in English | MEDLINE | ID: covidwho-1580425

ABSTRACT

BACKGROUND: The SARS-CoV-2 spike protein mediates attachment of the virus to the host cell receptor and fusion between the virus and the cell membrane. The S1 subunit of the spike glycoprotein (S1 protein) contains the angiotensin converting enzyme 2 (ACE2) receptor binding domain. The SARS-CoV-2 variants of concern contain mutations in the S1 subunit. The spike protein is the primary target of neutralizing antibodies generated following infection, and constitutes the viral component of mRNA-based COVID-19 vaccines. METHODS: Therefore, in this work we assessed the effect of exposure (24 h) to 10 nM SARS-CoV-2 recombinant S1 protein on physiologically relevant human bronchial (bro) and alveolar (alv) lung mucosa models cultured at air-liquid interface (ALI) (n = 6 per exposure condition). Corresponding sham exposed samples served as a control. The bro-ALI model was developed using primary bronchial epithelial cells and the alv-ALI model using representative type II pneumocytes (NCI-H441). RESULTS: Exposure to S1 protein induced the surface expression of ACE2, toll like receptor (TLR) 2, and TLR4 in both bro-ALI and alv-ALI models. Transcript expression analysis identified 117 (bro-ALI) and 97 (alv-ALI) differentially regulated genes (p ≤ 0.01). Pathway analysis revealed enrichment of canonical pathways such as interferon (IFN) signaling, influenza, coronavirus, and anti-viral response in the bro-ALI. Secreted levels of interleukin (IL) 4 and IL12 were significantly (p < 0.05) increased, whereas IL6 decreased in the bro-ALI. In the case of alv-ALI, enriched terms involving p53, APRIL (a proliferation-inducing ligand) tight junction, integrin kinase, and IL1 signaling were identified. These terms are associated with lung fibrosis. Further, significantly (p < 0.05) increased levels of secreted pro-inflammatory cytokines IFNγ, IL1ꞵ, IL2, IL4, IL6, IL8, IL10, IL13, and tumor necrosis factor alpha were detected in alv-ALI, whereas IL12 was decreased. Altered levels of these cytokines are also associated with lung fibrotic response. CONCLUSIONS: In conclusion, we observed a typical anti-viral response in the bronchial model and a pro-fibrotic response in the alveolar model. The bro-ALI and alv-ALI models may serve as an easy and robust platform for assessing the pathogenicity of SARS-CoV-2 variants of concern at different lung regions.


Subject(s)
Lung/metabolism , Respiratory Mucosa/metabolism , SARS-CoV-2/pathogenicity , Spike Glycoprotein, Coronavirus/metabolism , Angiotensin-Converting Enzyme 2/metabolism , Bronchi/metabolism , Cytokines/metabolism , Gene Expression Profiling , Humans , Models, Biological , Protein Interaction Domains and Motifs , Recombinant Proteins/chemistry , Recombinant Proteins/metabolism , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/chemistry , Toll-Like Receptor 2/metabolism , Toll-Like Receptor 4/metabolism
8.
Sci Rep ; 11(1): 23928, 2021 12 14.
Article in English | MEDLINE | ID: covidwho-1585797

ABSTRACT

Identification of transcriptional regulatory mechanisms and signaling networks involved in the response of host cells to infection by SARS-CoV-2 is a powerful approach that provides a systems biology view of gene expression programs involved in COVID-19 and may enable the identification of novel therapeutic targets and strategies to mitigate the impact of this disease. In this study, our goal was to identify a transcriptional regulatory network that is associated with gene expression changes between samples infected by SARS-CoV-2 and those that are infected by other respiratory viruses to narrow the results on those enriched or specific to SARS-CoV-2. We combined a series of recently developed computational tools to identify transcriptional regulatory mechanisms involved in the response of epithelial cells to infection by SARS-CoV-2, and particularly regulatory mechanisms that are specific to this virus when compared to other viruses. In addition, using network-guided analyses, we identified kinases associated with this network. The results identified pathways associated with regulation of inflammation (MAPK14) and immunity (BTK, MBX) that may contribute to exacerbate organ damage linked with complications of COVID-19. The regulatory network identified herein reflects a combination of known hits and novel candidate pathways supporting the novel computational pipeline presented herein to quickly narrow down promising avenues of investigation when facing an emerging and novel disease such as COVID-19.


Subject(s)
COVID-19/genetics , Gene Expression Profiling/methods , SARS-CoV-2/pathogenicity , Sequence Analysis, RNA/methods , A549 Cells , Cell Line , Epithelial Cells/chemistry , Epithelial Cells/cytology , Epithelial Cells/virology , Gene Expression Regulation , Humans , Models, Biological , Systems Biology
9.
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
10.
Viruses ; 13(12)2021 12 11.
Article in English | MEDLINE | ID: covidwho-1572660

ABSTRACT

Patients with COVID-19 generally raise antibodies against SARS-CoV-2 following infection, and the antibody level is positively correlated to the severity of disease. Whether the viral antibodies exacerbate COVID-19 through antibody-dependent enhancement (ADE) is still not fully understood. Here, we conducted in vitro assessment of whether convalescent serum enhanced SARS-CoV-2 infection or induced excessive immune responses in immune cells. Our data revealed that SARS-CoV-2 infection of primary B cells, macrophages and monocytes, which express variable levels of FcγR, could be enhanced by convalescent serum from COVID-19 patients. We also determined the factors associated with ADE, and found which showed a time-dependent but not viral-dose dependent manner. Furthermore, the ADE effect is not associated with the neutralizing titer or RBD antibody level when testing serum samples collected from different patients. However, it is higher in a medium level than low or high dilutions in a given sample that showed ADE effect, which is similar to dengue. Finally, we demonstrated more viral genes or dysregulated host immune gene expression under ADE conditions compared to the no-serum infection group. Collectively, our study provides insight into the understanding of an association of high viral antibody titer and severe lung pathology in severe patients with COVID-19.


Subject(s)
Antibody-Dependent Enhancement/immunology , Leukocytes/virology , SARS-CoV-2/pathogenicity , COVID-19/immunology , Cells, Cultured , Gene Expression Profiling , Humans , Immune Sera/immunology , Leukocytes/metabolism , Receptors, IgG/metabolism , Virus Replication/immunology
11.
Cells ; 10(12)2021 12 10.
Article in English | MEDLINE | ID: covidwho-1572376

ABSTRACT

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


Subject(s)
COVID-19/genetics , Down-Regulation/genetics , Gene Expression Profiling , Receptors, LDL/genetics , Aged , COVID-19/virology , Gene Ontology , Gene Regulatory Networks , Humans , Leukocytes, Mononuclear/metabolism , Male , Middle Aged , RNA-Seq , SARS-CoV-2/physiology
12.
Front Immunol ; 12: 733539, 2021.
Article in English | MEDLINE | ID: covidwho-1572288

ABSTRACT

The response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is largely impacted by the level of virus exposure and status of the host immunity. The nature of protection shown by direct asymptomatic contacts of coronavirus disease 2019 (COVID-19)-positive patients is quite intriguing. In this study, we have characterized the antibody titer, SARS-CoV-2 surrogate virus neutralization, cytokine levels, single-cell T-cell receptor (TCR), and B-cell receptor (BCR) profiling in asymptomatic direct contacts, infected cases, and controls. We observed significant increase in antibodies with neutralizing amplitude in asymptomatic contacts along with cytokines such as Eotaxin, granulocyte-colony stimulating factor (G-CSF), interleukin 7 (IL-7), migration inhibitory factor (MIF), and macrophage inflammatory protein-1α (MIP-1α). Upon single-cell RNA (scRNA) sequencing, we explored the dynamics of the adaptive immune response in few representative asymptomatic close contacts and COVID-19-infected patients. We reported direct asymptomatic contacts to have decreased CD4+ naive T cells with concomitant increase in CD4+ memory and CD8+ Temra cells along with expanded clonotypes compared to infected patients. Noticeable proportions of class switched memory B cells were also observed in them. Overall, these findings gave an insight into the nature of protection in asymptomatic contacts.


Subject(s)
Adaptive Immunity/immunology , COVID-19/immunology , Genomics/methods , SARS-CoV-2/immunology , Single-Cell Analysis/methods , Adaptive Immunity/genetics , Adult , Antibodies, Viral/immunology , COVID-19/genetics , COVID-19/virology , Cytokines/immunology , Cytokines/metabolism , Female , Gene Expression Profiling/methods , Humans , Male , /metabolism , Middle Aged , SARS-CoV-2/physiology , Sequence Analysis, RNA/methods , T-Lymphocytes/immunology , T-Lymphocytes/metabolism , T-Lymphocytes/virology , Young Adult
13.
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
15.
Virology ; 565: 73-81, 2022 01 02.
Article in English | MEDLINE | ID: covidwho-1545481

ABSTRACT

Bacillus Calmette-Guérin (BCG) vaccine is currently used to prevent tuberculosis infection. The vaccine was found to enhance resistance to certain types of infection including positive sense RNA viruses. The current COVID-19 pandemic is caused by positive sense RNA, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A higher mortality rate of COVID-19 patients was reported in countries where BCG vaccination is not routinely administered, when compared to the vaccinated ones. We hypothesized that BCG vaccine may control SARS-CoV2 infection via modulating the monocyte immune response. We analyzed GSE104149 dataset to investigate whether human monocytes of BCG-vaccinated individuals acquire resistance to SARS-CoV-2 infection. Differentially expressed genes obtained from the dataset were used to determine enriched pathways, biological processes, and molecular functions for monocytes post BCG vaccination. Our data show that BCG vaccine promotes a more effective immune response of monocytes against SARS-CoV2, but probably not sufficient to prevent the infection.


Subject(s)
BCG Vaccine/immunology , COVID-19/epidemiology , Vaccination/statistics & numerical data , BCG Vaccine/administration & dosage , COVID-19/prevention & control , Gene Expression Profiling , Humans , Inflammation , Monocytes/immunology , Monocytes/virology , SARS-CoV-2/physiology
16.
OMICS ; 25(11): 681-692, 2021 11.
Article in English | MEDLINE | ID: covidwho-1541502

ABSTRACT

Multiomics study designs have significantly increased understanding of complex biological systems. The multiomics literature is rapidly expanding and so is their heterogeneity. However, the intricacy and fragmentation of omics data are impeding further research. To examine current trends in multiomics field, we reviewed 52 articles from PubMed and Web of Science, which used an integrated omics approach, published between March 2006 and January 2021. From studies, data regarding investigated loci, species, omics type, and phenotype were extracted, curated, and streamlined according to standardized terminology, and summarized in a previously developed graphical summary. Evaluated studies included 21 omics types or applications of omics technology such as genomics, transcriptomics, metabolomics, epigenomics, environmental omics, and pharmacogenomics, species of various phyla including human, mouse, Arabidopsis thaliana, Saccharomyces cerevisiae, and various phenotypes, including cancer and COVID-19. In the analyzed studies, diverse methods, protocols, results, and terminology were used and accordingly, assessment of the studies was challenging. Adoption of standardized multiomics data presentation in the future will further buttress standardization of terminology and reporting of results in systems science. This shall catalyze, we suggest, innovation in both science communication and laboratory medicine by making available scientific knowledge that is easier to grasp, share, and harness toward medical breakthroughs.


Subject(s)
Computational Biology/trends , Genomics/trends , Metabolomics/trends , Proteomics/trends , Animals , COVID-19 , Computer Graphics , Epigenomics/trends , Gene Expression Profiling/trends , Humans , Pharmacogenetics/trends , Publications , SARS-CoV-2 , Terminology as Topic
17.
Brief Bioinform ; 22(5)2021 09 02.
Article in English | MEDLINE | ID: covidwho-1528156

ABSTRACT

The low capture rate of expressed RNAs from single-cell sequencing technology is one of the major obstacles to downstream functional genomics analyses. Recently, a number of imputation methods have emerged for single-cell transcriptome data, however, recovering missing values in very sparse expression matrices remains a substantial challenge. Here, we propose a new algorithm, WEDGE (WEighted Decomposition of Gene Expression), to impute gene expression matrices by using a biased low-rank matrix decomposition method. WEDGE successfully recovered expression matrices, reproduced the cell-wise and gene-wise correlations and improved the clustering of cells, performing impressively for applications with sparse datasets. Overall, this study shows a potent approach for imputing sparse expression matrix data, and our WEDGE algorithm should help many researchers to more profitably explore the biological meanings embedded in their single-cell RNA sequencing datasets. The source code of WEDGE has been released at https://github.com/QuKunLab/WEDGE.


Subject(s)
Algorithms , Computational Biology/methods , Gene Expression Profiling/methods , RNA-Seq/methods , Single-Cell Analysis/methods , COVID-19/blood , COVID-19/genetics , COVID-19/virology , Cluster Analysis , Computer Simulation , Genomics/methods , Humans , Leukocytes, Mononuclear/classification , Leukocytes, Mononuclear/metabolism , Reproducibility of Results , SARS-CoV-2/physiology , Severity of Illness Index
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.
Sci Rep ; 11(1): 21872, 2021 11 08.
Article in English | MEDLINE | ID: covidwho-1506466

ABSTRACT

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


Subject(s)
COVID-19/drug therapy , COVID-19/immunology , COVID-19/virology , Drug Repositioning , Gene Expression Profiling , Gene Expression Regulation, Viral , SARS-CoV-2 , Computational Biology , Gene Regulatory Networks , Genes, Viral , Genetic Techniques , Humans , MicroRNAs/metabolism , Oligonucleotide Array Sequence Analysis , Systems Biology , Transcription Factors
20.
Front Immunol ; 12: 689065, 2021.
Article in English | MEDLINE | ID: covidwho-1502324

ABSTRACT

Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The US FDA has approved several therapeutics and vaccines worldwide through the emergency use authorization in response to the rapid spread of COVID-19. Nevertheless, the efficacies of these treatments are being challenged by viral escape mutations. There is an urgent need to develop effective treatments protecting against SARS-CoV-2 infection and to establish a stable effect-screening model to test potential drugs. Polyclonal antibodies (pAbs) have an intrinsic advantage in such developments because they can target rapidly mutating viral strains as a result of the complexity of their binding epitopes. In this study, we generated anti-receptor-binding domain (anti-RBD) pAbs from rabbit serum and tested their safety and efficacy in response to SARS-CoV-2 infection both in vivo and ex vivo. Primary human bronchial epithelial two-dimensional (2-D) organoids were cultured and differentiated to a mature morphology and subsequently employed for SARS-CoV-2 infection and drug screening. The pAbs protected the airway organoids from viral infection and tissue damage. Potential side effects were tested in mouse models for both inhalation and vein injection. The pAbs displayed effective viral neutralization effects without significant side effects. Thus, the use of animal immune serum-derived pAbs might be a potential therapy for protection against SARS-CoV-2 infection, with the strategy developed to produce these pAbs providing new insight into the treatment of respiratory tract infections, especially for infections with viruses undergoing rapid mutation.


Subject(s)
Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , SARS-CoV-2/immunology , Spike Glycoprotein, Coronavirus/immunology , Animals , Antibodies, Neutralizing/administration & dosage , Antibodies, Viral/administration & dosage , Binding Sites , Bronchi/cytology , COVID-19/genetics , COVID-19/therapy , Epithelial Cells , Gene Expression Profiling , Humans , Immunization, Passive , Mice , Mutation , Neutralization Tests , Organoids , Rabbits , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/genetics
SELECTION OF CITATIONS
SEARCH DETAIL
...