Longitudinal host transcriptional responses to SARS-CoV-2 infection in adults with extremely high viral load
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ABSTRACT: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the etiologic agent of the coronavirus disease 2019 (COVID-19) pandemic. We conducted a longitudinal study to investigate gene expression patterns during the acute SARS-CoV-2 illness. The cases included SARS-CoV-2 infected individuals with an extremely high viral load early in their illness matched to individuals who either had a low SARS-CoV-2 viral load early in their infection or were otherwise stable patients who tested negative for SARS-CoV-2 prior to their outpatient surgical or aerosol generating procedure. We detected hundreds of up-regulated genes that were highly correlated to the SARS-CoV-2 viral load. Many of these up-regulated genes were enriched in cellular pathways involved in the innate immune response, antiviral interferon and cytokine signaling, and cell death.
Project description:We examined host gene expression across infection status, viral load, age, and sex among RNA-sequencing profiles of nasopharyngeal swabs from 430 individuals with SARS-CoV-2 and 54 negative controls. SARS-CoV-2 induced a strong interferon-driven antiviral response and reduced transcription of ribosomal proteins. Expression of interferon-responsive genes, including ACE2, increased as a function of viral load. B cells and neutrophils were higher in patients with lower viral load. Older individuals had reduced expression of chemokines CXCL9/10/11, their cognate receptor CXCR3, and CD8A and granzyme B. Males had reduced B and NK cell-specific transcripts and increased NFkB inhibitors. Our data demonstrate that host responses to SARS-CoV-2 are dependent on viral load and infection time course, with observed differences due to age and sex that may contribute to disease severity.
Project description:The coronavirus disease 2019 (COVID-19) pandemic has affected nearly 700 million and claimed more than 6 million lives. However, the large heterogeneity in disease susceptibility and severity of illness (SOI) remains poorly understood. A growing body of evidence suggests that alveolar epithelial cell type 2 (AT2), which constitute 10-15% of all alveolar cells and are critical for alveolar homeostasis, are the primary targets of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection and damage to AT2s may directly contribute to disease severity and poor prognosis in COVID-19 patients. Our in-vitro modeling of SARS-CoV-2 infection, in well-characterized, highly uniform, (r2 at 95% CI = 0.92 ± 0.03), induced pluripotent stem cell (iPSC) derived AT2s from 10 participants of our Mexican American Family Study, showed interindividual variability in infection susceptibility and the post-infection cellular viral load. To understand the underlying mechanism of the AT2’s capacity to regulate SARS-CoV-2 infection and cellular viral load, we performed a systematic characterization of the pre- and post-SARS-CoV-2 challenged AT2 transcriptomes. A total of 1,393 genes were found significantly (Oneway ANOVA FDR corrected p ≤ 0.05; FC abs ≥ 2.0) differentially expressed (DE) between pre- and post-SARS-CoV-2 infection-challenged AT2 and suggest significant upregulation of viral infection-related cellular innate immune response pathways (p-value ≤ 0.05; activation z-score ≥ 3.5), whilst the cholesterol and xenobiotic related metabolic pathways were significantly downregulated (p-value ≤ 0.05; activation z-score ≤ - 3.5). Interestingly, pre-infection expression of 238 DE genes showed a high correlation with the post-infection SARS-CoV-2 viral load (FDR corrected p-value ≤ 0.05, and r2-absolute ≥ 0.57). The 85 genes whose expression was negatively correlated with the viral load showed significant enrichment in viral recognition and cytokine-mediated innate immune GO biological processes (p-value range: 4.65x10-10 to 2.24x10-6). The 153 genes whose expression was positively correlated with the viral load showed significant enrichment in cholesterol homeostasis, extracellular matrix, and MAPK/ERK pathway-related GO biological processes (p-value range: 5.06x10-5 to 6.53x10-4). Overall, our results strongly suggest that AT2s pre-infection innate immunity and metabolic state affects their susceptibility to SARS-CoV-2 infection and viral load.
Project description:COVID-19 is the third outbreak of zoonotic coronavirus (CoV) of the century after the epidemic Severe acute respiratory syndrome CoV (SARS-CoV) in 2003 and Middle East respiratory syndrome CoV (MERS-CoV) in 2012. Treatment options for CoVs are largely lacking. Here, we show that clofazimine, an anti-leprosy drug with favorable safety and pharmacokinetics profile, possesses pan-coronaviral inhibitory activity, and can antagonize SARS-CoV-2 replication in multiple in vitro systems, including the human embryonic stem cell-derived cardiomyocytes and ex vivo lung cultures. The FDA-approved molecule was found to inhibit multiple steps of viral replication, suggesting polypharmacology is likely underlying its antiviral activity. In a hamster model of SARS-CoV-2 pathogenesis, prophylactic and therapeutic administration of clofazimine significantly reduced lung viral load and fecal viral shedding, as well as reversal of cytokine storm. Additionally, clofazimine exhibited antiviral drug synergy when administered with remdesivir. Since clofazimine is orally bioavailable and has a comparatively low manufacturing cost, it is an attractive clinical candidate for outpatient treatment and remdesivir-based combinatorial therapy for hospitalized COVID-19 patients, particularly in developing countries. Taken together, our data provide evidence that clofazimine may prove effective against current pandemic SARS-CoV-2, endemic MERS-CoV in the Middle East, and, possibly most importantly, emerging CoV of the future.
Project description:The amount of SARS-CoV-2 detected in the upper respiratory tract (URT viral load) is a key driver of transmission of infection. Current evidence suggests that mechanisms constraining URT viral load are different from those controlling lower respiratory tract viral load and disease severity. Understanding such mechanisms may help to develop treatments and vaccine strategies to reduce transmission. Combining mathematical modelling of URT viral load dynamics with transcriptome analyses we aimed to identify mechanisms controlling URT viral load. COVID-19 patients were recruited in Spain during the first wave of the pandemic. RNA sequencing of peripheral blood and targeted NanoString nCounter transcriptome analysis of nasal epithelium were performed and gene expression analysed in relation to paired URT viral load samples collected within 15 days of symptom onset. Proportions of major immune cells in blood were estimated from transcriptional data using computational differential estimation. Weighted correlation network analysis (adjusted for cell proportions) and fixed transcriptional repertoire analysis were used to identify associations with URT viral load, quantified as standard deviations (z-scores) from an expected trajectory over time.
Project description:In this study, we tested the efficacy of five commercial probes panels at detecting SARS-CoV-2 genome including panels from Illumina, Twist Bioscience and Arbor Bioscience. To do so, we used 19 patient nasal swab samples broken down into 5 series of 4 samples of equivalent SARS-CoV-2 viral load (cycle threshold (CT): low CT means a high viral load – CT26, CT29, CT32, CT35 and CT36+).
Project description:In this study, we tested the efficacy of five commercial probes panels at detecting SARS-CoV-2 genome including panels from Illumina, Twist Bioscience and Arbor Bioscience. To do so, we used 19 patient nasal swab samples broken down into 5 series of 4 samples of equivalent SARS-CoV-2 viral load (cycle threshold (CT): low CT means a high viral load – CT26, CT29, CT32, CT35 and CT36+).
Project description:In this study, we tested the efficacy of five commercial probes panels at detecting SARS-CoV-2 genome including panels from Illumina, Twist Bioscience and Arbor Bioscience. To do so, we used 19 patient nasal swab samples broken down into 5 series of 4 samples of equivalent SARS-CoV-2 viral load (cycle threshold (CT): low CT means a high viral load – CT26, CT29, CT32, CT35 and CT36+).
Project description:In this study, we tested the efficacy of five commercial probes panels at detecting SARS-CoV-2 genome including panels from Illumina, Twist Bioscience and Arbor Bioscience. To do so, we used 19 patient nasal swab samples broken down into 5 series of 4 samples of equivalent SARS-CoV-2 viral load (cycle threshold (CT): low CT means a high viral load – CT26, CT29, CT32, CT35 and CT36+).
Project description:In this study, we tested the efficacy of five commercial probes panels at detecting SARS-CoV-2 genome including panels from Illumina, Twist Bioscience and Arbor Bioscience. To do so, we used 19 patient nasal swab samples broken down into 5 series of 4 samples of equivalent SARS-CoV-2 viral load (cycle threshold (CT): low CT means a high viral load – CT26, CT29, CT32, CT35 and CT36+).
Project description:In this study, we tested the efficacy of five commercial probes panels at detecting SARS-CoV-2 genome including panels from Illumina, Twist Bioscience and Arbor Bioscience. To do so, we used 19 patient nasal swab samples broken down into 5 series of 4 samples of equivalent SARS-CoV-2 viral load (cycle threshold (CT): low CT means a high viral load – CT26, CT29, CT32, CT35 and CT36+).