Modeling poliovirus replication dynamics from live time-lapse single-cell imaging data.

ABSTRACT: Viruses experience selective pressure on the timing and order of events during infection to maximize the number of viable offspring they produce. Additionally, they may experience variability in cellular environments encountered, as individual eukaryotic cells can display variation in gene expression among cells. This leads to a dynamic phenotypic landscape that viruses must face to replicate. To examine replication dynamics displayed by viruses faced with this variable landscape, we have developed a method for fitting a stochastic mechanistic model of viral infection to time-lapse imaging data from high-throughput single-cell poliovirus infection experiments. The model's mechanistic parameters provide estimates of several aspects associated with the virus's intracellular dynamics. We exam

SUBMITTER: Teufel AI 

PROVIDER: S-EPMC8100109 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature