Upper respiratory microbiome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA726992 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR15225300_1.fastq.gz | Fastqsanger.gz | |||
| SRR15225300_2.fastq.gz | Fastqsanger.gz | |||
| SRR15225301_1.fastq.gz | Fastqsanger.gz | |||
| SRR15225301_2.fastq.gz | Fastqsanger.gz | |||
| SRR15225302_1.fastq.gz | Fastqsanger.gz |
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Project description:Full understanding of the pathophysiology of COVID-19 is critical for adequate treatment and development of vaccine and therapeutics. Although Golden hamster has been emerged as animal model of COVID-19, it is unknown how SARS-CoV-2 enters and infects targeted epithelial cells at molecular and cellular levels. Here, by applying single cell RNA sequencing in the upper respiratory tract, lung, kidney and intestine of golden hamster, we show that the expression profiles of host factors for SARS-CoV-2 infection in specific cell types are similar to that of human. These data can be applied to a larger investigation (data not provided here) into the expression patterns of host cell entry factors of SARS-CoV-2 in golden hamster organs.
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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.
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Project description:Severe acute respiratory syndrome virus (SARS-CoV) that lacks the envelope (E) gene (rSARS-CoV-ΔE) is attenuated in vivo [1,2]. To identify factors that contribute to rSARS-CoV-ΔE attenuation, gene expression in cells infected by SARS-CoV with or without E gene was compared. Twenty-five stress response genes were preferentially upregulated during infection in the absence of the E gene. In addition, genes involved in signal transduction, transcription, cell metabolism, immunoregulation, inflammation, apoptosis and cell cycle and differentiation were differentially regulated in cells infected with rSARS-CoV with or without the E gene. Administration of E protein in trans reduced the stress response in cells infected with rSARS-CoV-ΔE, with respiratory syncytial virus, or treated with drugs, such as tunicamycin and thapsigarcin that elicit cell stress by different mechanisms. In addition, SARS-CoV E protein down-regulated the signaling pathway inositol-requiring enzyme 1 (IRE-1) of the unfolded protein response, but not the PKR-like ER kinase (PERK) or activating transcription factor 6 (ATF-6) pathways, and reduced cell apoptosis. Overall, the activation of the IRE-1 pathway was not able to restore cell homeostasis, and apoptosis was induced probably as a meassure to protect the host by limiting virus production and dissemination. The expression of proinflammatory cytokines was reduced in rSARS-CoV-ΔE-infected cells compared to rSARS-CoV-infected cells, suggesting that the increase in stress responses and the reduction of inflammation in the absence of the E gene contributed to the attenuation of rSARS-CoV-ΔE. We used Affymetrix microarrays (Human Genome U133 plus 2.0) to compare global gene expression between SARS-CoV-infected, mock-infected and SARS-CoV-ΔE-infected cells. For ech type of sample three hybridizations were carried-out (independent biological replicates).
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