Comparative modelling of large-scale 3D genome re-arrangements in different viral infections

Viruses can re-structure the architecture of host cells genome and also alter their epigenomic landscape. In this study, we investigate with polymer physics modelling virus induced genome re-organization by using available datasets from different viral infections causing: COVID-19 syndrome (SARS-CoV-2 virus), human common cold (HCoV-OC43 virus) and avian influenza (IAV-H5N1 virus). By combining recent experimental Hi-C data from virally infected human cells with in-silico polymer models, we find that each pathogen induces peculiar re-structuring at the level of A/B compartments, which can be encoded by pathogen specific re-modulations of protein-chromatin binding affinities. Specifically, more pronounced effects are observed in SARS-CoV-2 and IAV-H5N1 infected cells, where a generally enhanced A/B mixing is observed, whose symmetry degree depends on the infection. On the other hand, HCoV-OC43 infection exhibits comparatively milder effects. Overall, our results suggest that viruses associated with more severe disease phenotypes could induce deeper, large-scale chromatin architectural changes.