Dynamics of SARS-CoV-2 host cell interactions inferred from transcriptome analyses

Abstract

The worldwide spread of severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) caused an urgent need for an in-depth understanding of interactions between the virus and its host. Here, we dissected the dynamics of virus replication and the host cell transcriptional response to SARS-CoV-2 infection at a systems level by combining time-resolved RNA sequencing with mathematical modeling. We observed an immediate transcriptional activation of inflammatory pathways linked to the anti-viral response followed by increased expression of genes involved in ribosome and mitochondria function, thus hinting at rapid alterations in protein production and cellular energy supply. At later stages, metabolic processes, in particular those depending on cytochrome P450 enzymes, were downregulated. To gain a deeper understanding of the underlying transcriptional dynamics, we developed an ODE model of SARS-CoV-2 infection and replication. Iterative model reduction and refinement revealed that a negative feedback from virus proteins on the expression of anti-viral response genes was essential to explain our experimental dataset. Our study provides insights into SARS-CoV-2 virus-host interaction dynamics and facilitates the identification of druggable host pathways supporting virus replication.