Longitudinal host transcriptional responses to SARS-CoV-2 infection in adults with extremely high viral load

Current understanding of viral dynamics of SARS-CoV-2 and host responses driving the pathogenic mechanisms in COVID-19 is rapidly evolving. Here, we conducted a longitudinal study to investigate gene expression patterns during acute SARS-CoV-2 illness. Cases included SARS-CoV-2 infected individuals with extremely high viral loads early in their illness, individuals having low SARS-CoV-2 viral loads early in their infection, and individuals testing negative for SARS-CoV-2. We could identify widespread transcriptional host responses to SARS-CoV-2 infection that were initially most strongly manifested in patients with extremely high initial viral loads, then attenuating within the patient over time as viral loads decreased. Genes correlated with SARS-CoV-2 viral load over time were similarly differentially expressed across independent datasets of SARS-CoV-2 infected lung and upper airway cells, from both in vitro systems and patient samples. We also generated expression data on the human nose organoid model during SARS-CoV-2 infection. The human nose organoid-generated host transcriptional response captured many aspects of responses observed in the above patient samples, while suggesting the existence of distinct host responses to SARS-CoV-2 depending on the cellular context, involving both epithelial and cellular immune responses. Our findings provide a catalog of SARS-CoV-2 host response genes changing over time and magnitude of these host responses were significantly correlated to viral load.

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Publication Details

Journal
PLoS ONE
Published
2025-01-16
DOI
https://doi.org/10.1371/journal.pone.0317033
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Longitudinal host transcriptional responses to SARS-CoV-2 infection in adults with extremely high viral load

Joseph F. Petrosino, Ginger Metcalf, Anubama Rajan, Donna M. Muzny et al.
PLoS ONE
SARS-CoV-2 and COVID-19 Research
article

Longitudinal host transcriptional responses to SARS-CoV-2 infection in adults with extremely high viral load

Joseph F. Petrosino, Ginger Metcalf, Anubama Rajan, Donna M. Muzny, Chad J. Creighton, HarshaVardhan Doddapaneni, Richard Sucgang, Sara J. Javornik Cregeen, Richard A. Gibbs, Pedro A. Piedra, Vipin K. Menon, Vasanthi Avadhanula, Erin G. Nicholson, Kristi L. Hoffman, Laura Ferlic‐Stark, Yiqun Zhang, Divya Nagaraj
article en

Abstract

Current understanding of viral dynamics of SARS-CoV-2 and host responses driving the pathogenic mechanisms in COVID-19 is rapidly evolving. Here, we conducted a longitudinal study to investigate gene expression patterns during acute SARS-CoV-2 illness. Cases included SARS-CoV-2 infected individuals with extremely high viral loads early in their illness, individuals having low SARS-CoV-2 viral loads early in their infection, and individuals testing negative for SARS-CoV-2. We could identify widespread transcriptional host responses to SARS-CoV-2 infection that were initially most strongly manifested in patients with extremely high initial viral loads, then attenuating within the patient over time as viral loads decreased. Genes correlated with SARS-CoV-2 viral load over time were similarly differentially expressed across independent datasets of SARS-CoV-2 infected lung and upper airway cells, from both in vitro systems and patient samples. We also generated expression data on the human nose organoid model during SARS-CoV-2 infection. The human nose organoid-generated host transcriptional response captured many aspects of responses observed in the above patient samples, while suggesting the existence of distinct host responses to SARS-CoV-2 depending on the cellular context, involving both epithelial and cellular immune responses. Our findings provide a catalog of SARS-CoV-2 host response genes changing over time and magnitude of these host responses were significantly correlated to viral load.

PLoS ONEVol. 20(1)
Houston Methodist (US), Baylor College of Medicine (US), Baylor Genetics (US)
National Institutes of Health
Openalex Percentile: Top 99%
SARS-CoV-2 and COVID-19 Research
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