Overlapping host pathways between SARS-CoV-2 and its potential copathogens: An in silico analysis.
ABSTRACT: BACKGROUND:SARS-CoV-2 coinfection with other viral and bacterial pathogens and their interactions are increasingly recognized in the literature as potential determinants of COVID-19 phenotypes. The aim of this study was to determine infection induced, host transcriptomic overlap between SARS-CoV-2 and other pathogens. MATERIALS AND METHODS:SARS-CoV-2 infection induced gene expression data were used for gene set enrichment analysis (GSEA) via the Enrichr platform. GSEA compared the extracted signature to VirusMINT, Virus and Microbe perturbations from Gene Expression Omnibus (GEO) in order to detect overlap with other pathogen induced host gene signatures. For all analyses, a false discovery rate (FDR) <0.05 was considered statistically significant. RESULTS:GSEA via Enrichr revealed several significantly enriched sub-signatures associated with HSV1, EBV, HIV1, IAV, RSV, P.Aeruginosa, Staph. Aureus and Strep. Pneumoniae infections, among other pathogens (FDR < 0.05). These signatures were detected in at least 6 infection-induced transcriptomic studies from GEO and involved both bronchial epithelial and peripheral blood immune cells. DISCUSSION:SARS-CoV-2 infection may function synergistically with other viral and bacterial pathogens at the transcriptomic level. Notably, several meta-analyses of COVID-19 cohorts have furthermore corroborated viral and bacterial pathogens reported herein as coinfections with SARS-CoV-2. The identification of common, perturbed gene networks outlines a common host targetome for these pathogens, and furthermore provides candidates for biomarker discovery and drug design.
Project description:Identifying transcriptional responses that are most consistently associated with experimental coronavirus (CoV) infection can help illuminate human cellular signaling pathways impacted by CoV infection. Here, we distilled over 3,000,000 data points from publically archived CoV infection transcriptomic datasets into consensus regulatory signatures, or consensomes, that rank genes based on their transcriptional responsiveness to infection of human cells by MERS, SARS-CoV-1 and SARS-CoV-2 subtypes. We computed overlap between genes with elevated rankings in the CoV consensomes against those from transcriptomic and ChIP-Seq consensomes for nearly 880 cellular signaling pathway nodes. Validating the CoV infection consensomes, we identified robust overlap between their highly ranked genes and high confidence targets of signaling pathway nodes with known roles in CoV infection. We then developed a series of use cases that illustrate the utility of the CoV consensomes for hypothesis generation around mechanistic aspects of the cellular response to CoV infection. We make the CoV infection datasets and their universe of underlying data points freely accessible through the Signaling Pathways Project web knowledgebase at https://www.signalingpathways.org/datasets/index.jsf.
Project description:The SARS-CoV-2 (COVID-19) pandemic is a global crisis that threatens our way of life. As of November 18, 2020, SARS-CoV-2 has claimed more than 1,342,709 lives, with a global mortality rate of ~2.4% and a recovery rate of ~69.6%. Understanding the interaction of cellular targets with the SARS-CoV-2 infection is crucial for therapeutic development. Therefore, the aim of this study was to perform a comparative analysis of transcriptomic signatures of infection of SARS-CoV-2 compared to other respiratory viruses (EBOV, H1N1, MERS-CoV, and SARS-CoV), to determine a unique anti-SARS-CoV-2 gene signature. We identified for the first time that molecular pathways for heparin-binding, RAGE, miRNA, and PLA2 inhibitors were associated with SARS-CoV-2 infection. The NRCAM and SAA2 genes, which are involved in severe inflammatory responses, and the FGF1 and FOXO1 genes, which are associated with immune regulation, were found to be associated with the cellular gene response to SARS-CoV-2 infection. Moreover, several cytokines, most significantly IL-8 and IL-6, demonstrated key associations with SARS-CoV-2 infection. Interestingly, the only response gene that was shared among the five viral infections was SERPINB1. The protein-protein interaction (PPI) analysis shed light on genes with high interaction activity that SARS-CoV-2 shares with other viral infections. The findings showed that the genetic pathways associated with rheumatoid arthritis, the AGE-RAGE signaling system, malaria, hepatitis B, and influenza A were of high significance. We found that the virogenomic transcriptome of infection, gene modulation of host antiviral responses, and GO terms of SARS-CoV-2 and EBOV were more similar than to SARS, H1N1, and MERS. This work compares the virogenomic signatures of highly pathogenic viruses and provides valid targets for potential therapy against SARS-CoV-2.
Project description:The outbreak of the 2019 coronavirus disease (named, COVID?19), caused by the novel SARS?CoV?2 virus, represents a worldwide severe threat to public health. It is of the utmost importance to characterize the immune responses against the SARS?CoV?2 and the mechanisms of hyperinflammation, in order to design better therapeutic strategies for COVID?19. In the present study, a transcriptomic analysis was performed to profile the immune signatures in lung and the bronchoalveolar lavage fluid samples from COVID?19 patients and controls. Our data concordantly revealed increased humoral responses to infection. The elucidation of the host responses to SARS?CoV?2 infection may further improve our understanding of COVID?19 pathogenesis and suggest better therapeutic strategies.
Project description:BACKGROUND:Angiotensin receptor blockers (ARBs) reducing inflammation and protecting lung and brain function, could be of therapeutic efficacy in COVID-19 patients. METHODS:Using GSEA, we compared our previous transcriptome analysis of neurons injured by glutamate and treated with the ARB Candesartan (GSE67036) with transcriptional signatures from SARS-CoV-2 infected primary human bronchial epithelial cells (NHBE) and lung postmortem (GSE147507), PBMC and BALF samples (CRA002390) from COVID-19 patients. RESULTS:Hundreds of genes upregulated in SARS-CoV-2/COVID-19 transcriptomes were similarly upregulated by glutamate and normalized by Candesartan. Gene Ontology analysis revealed expression profiles with greatest significance and enrichment, including proinflammatory cytokine and chemokine activity, the NF-kappa B complex, alterations in innate and adaptive immunity, with many genes participating in the COVID-19 cytokine storm. CONCLUSIONS:There are similar injury mechanisms in SARS-CoV-2 infection and neuronal injury, equally reduced by ARB treatment. This supports the hypothesis of a therapeutic role for ARBs, ameliorating the COVID-19 cytokine storm.
Project description:Healthcare workers were recruited at St Bartholomew’s Hospital, London, UK in the week of lockdown in the United Kingdom (between 23rd and 31st March 2020). Participants underwent weekly evaluation using a questionnaire and biological sample collection (including serological assays) for up to 16 weeks when attending for work and self-declared as fit to attend work at each visit, with further follow up samples collected at 24 weeks. Blood RNA sequencing data was to be used to identify host-response biomarkers of early SARS-CoV-2 infection, to evaluate existing blood transcriptomic signatures of viral infection, and to describe the underlying biology during SARS-CoV-2 infection. This submission includes a total of 172 blood RNA samples from 99 participants. Of these, 114 samples (including 16 convalescent samples collected 6 months after infection) were obtained from 41 SARS-CoV-2 cases, with the remaining 58 from uninfected controls. Participants with available blood RNA samples who had PCR-confirmed SARS-CoV-2 infection during follow-up were included as ‘cases’. Those without evidence of SARS-CoV-2 infection on nasopharyngeal swabs and who remained seronegative by both Euroimmun anti S1 spike protein and Roche anti nucleocapsid protein throughout follow-up were included as uninfected controls. ‘Cases’ include all available RNA samples, including convalescent samples at week 24 of follow-up for a subset of participants. For uninfected controls, we included baseline samples only. Sample class denotes weekly interval to positive SARS-CoV-2 PCR; non-infected controls (NIC); convalescent samples (Conv)_.
Project description:UNLABELLED:Systems biology offers considerable promise in uncovering novel pathways by which viruses and other microbial pathogens interact with host signaling and expression networks to mediate disease severity. In this study, we have developed an unbiased modeling approach to identify new pathways and network connections mediating acute lung injury, using severe acute respiratory syndrome coronavirus (SARS-CoV) as a model pathogen. We utilized a time course of matched virologic, pathological, and transcriptomic data within a novel methodological framework that can detect pathway enrichment among key highly connected network genes. This unbiased approach produced a high-priority list of 4 genes in one pathway out of over 3,500 genes that were differentially expressed following SARS-CoV infection. With these data, we predicted that the urokinase and other wound repair pathways would regulate lethal versus sublethal disease following SARS-CoV infection in mice. We validated the importance of the urokinase pathway for SARS-CoV disease severity using genetically defined knockout mice, proteomic correlates of pathway activation, and pathological disease severity. The results of these studies demonstrate that a fine balance exists between host coagulation and fibrinolysin pathways regulating pathological disease outcomes, including diffuse alveolar damage and acute lung injury, following infection with highly pathogenic respiratory viruses, such as SARS-CoV. IMPORTANCE:Severe acute respiratory syndrome coronavirus (SARS-CoV) emerged in 2002 and 2003, and infected patients developed an atypical pneumonia, acute lung injury (ALI), and acute respiratory distress syndrome (ARDS) leading to pulmonary fibrosis and death. We identified sets of differentially expressed genes that contribute to ALI and ARDS using lethal and sublethal SARS-CoV infection models. Mathematical prioritization of our gene sets identified the urokinase and extracellular matrix remodeling pathways as the most enriched pathways. By infecting Serpine1-knockout mice, we showed that the urokinase pathway had a significant effect on both lung pathology and overall SARS-CoV pathogenesis. These results demonstrate the effective use of unbiased modeling techniques for identification of high-priority host targets that regulate disease outcomes. Similar transcriptional signatures were noted in 1918 and 2009 H1N1 influenza virus-infected mice, suggesting a common, potentially treatable mechanism in development of virus-induced ALI.
Project description:Although COVID-19 causes cardiac dysfunction in up to 25% of patients, its pathogenesis remains unclear. Exposure of human iPSC-derived heart cells to SARS-CoV-2 revealed productive infection and robust transcriptomic and morphological signatures of damage, particularly in cardiomyocytes. Transcriptomic disruption of structural proteins corroborated adverse morphologic features, which included a distinct pattern of myofibrillar fragmentation and numerous iPSC-cardiomyocytes lacking nuclear DNA. Human autopsy specimens from COVID-19 patients displayed similar sarcomeric disruption, as well as cardiomyocytes without DNA staining. These striking cytopathic features provide new insights into SARS-CoV-2 induced cardiac damage, offer a platform for discovery of potential therapeutics, and raise serious concerns about the long-term consequences of COVID-19.
Project description:Establishing consensus around the transcriptional interface between coronavirus (CoV) infection and human cellular signaling pathways can catalyze the development of novel anti-CoV therapeutics. Here, we used publicly archived transcriptomic datasets to compute consensus regulatory signatures, or consensomes, that rank human genes based on their rates of differential expression in MERS-CoV (MERS), SARS-CoV-1 (SARS1) and SARS-CoV-2 (SARS2)-infected cells. Validating the CoV consensomes, we show that high confidence transcriptional targets (HCTs) of MERS, SARS1 and SARS2 infection intersect with HCTs of signaling pathway nodes with known roles in CoV infection. Among a series of novel use cases, we gather evidence for hypotheses that SARS2 infection efficiently represses E2F family HCTs encoding key drivers of DNA replication and the cell cycle; that progesterone receptor signaling antagonizes SARS2-induced inflammatory signaling in the airway epithelium; and that SARS2 HCTs are enriched for genes involved in epithelial to mesenchymal transition. The CoV infection consensomes and HCT intersection analyses are freely accessible through the Signaling Pathways Project knowledgebase, and as Cytoscape-style networks in the Network Data Exchange repository.
Project description:hPSC-derived cadiomyocytes and primary endothelial cells were treated with lisinopril or losartan to assess whether antihypertensive drugs could impact SARS-CoV-2 entry in vitro Overall design: The pathogenicity of SARS-CoV-2 has been attributed to its ability to enter through the membrane bound angiotensin-converting enzyme 2 (ACE2) receptor. Therefore, it has been heavily suspected that angiotensin converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB) therapy may affect the susceptibility of patients to SARS-CoV-2 infection. In this study, we used human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) and primary human endothelial cells (hECs) to assess whether SARS-CoV-2 infection levels change in the presence of two widely prescribed antihypertensive medications, losartan and lisinopril, and to identify differences in the transcriptomic signatures of hPSC-CMs exposed to SARS-CoV-2. Significant enrichment of protein coding genes involved in inflammation, immunity and cardiomyocyte structural proteins were identified in SARS-CoV-2 treated cells. However, in vitro treatment of lisinopril or losartan in hPSC-CMs or hECs did not affect the susceptibility of cells to SARS-CoV-2 infection.
Project description:Given the severity of the SARS-CoV-2 pandemic, a major challenge is to rapidly repurpose existing approved drugs for clinical interventions. While a number of data-driven and experimental approaches have been suggested in the context of drug repurposing, a platform that systematically integrates available transcriptomic, proteomic and structural data is missing. More importantly, given that SARS-CoV-2 pathogenicity is highly age-dependent, it is critical to integrate aging signatures into drug discovery platforms. We here take advantage of large-scale transcriptional drug screens combined with RNA-seq data of the lung epithelium with SARS-CoV-2 infection as well as the aging lung. To identify robust druggable protein targets, we propose a principled causal framework that makes use of multiple data modalities. Our analysis highlights the importance of serine/threonine and tyrosine kinases as potential targets that intersect the SARS-CoV-2 and aging pathways. By integrating transcriptomic, proteomic and structural data that is available for many diseases, our drug discovery platform is broadly applicable. Rigorous in vitro experiments as well as clinical trials are needed to validate the identified candidate drugs.