A Time-Series Metabolomic Analysis of SARS-CoV-2 Infection in a Ferret Model.

ABSTRACT: The global threat of COVID-19 has led to an increased use of metabolomics to study SARS-CoV-2 infections in animals and humans. In spite of these efforts, however, understanding the metabolome of SARS-CoV-2 during an infection remains difficult and incomplete. In this study, metabolic responses to a SAS-CoV-2 challenge experiment were studied in nasal washes collected from an asymptomatic ferret model (n = 20) at different time points before and after infection using an LC-MS-based metabolomics approach. A multivariate analysis of the nasal wash metabolome data revealed several statistically significant features. Despite no effects of sex or interaction between sex and time on the time course of SARS-CoV-2 infection, 16 metabolites were significantly different at all time points pos

SUBMITTER: Karpe AV 

PROVIDER: S-EPMC9699618 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature