Por favor, use este identificador para citar o enlazar este ítem: http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/8657
Mathematical model of replication-mutation dynamics in coronaviruses
Konstantin Blyuss
Yuliya Kyrychko
Acceso Abierto
Atribución-NoComercial-SinDerivadas
https://doi.org/10.1101/2024.01.29.577716
https://www.biorxiv.org/content/10.1101/2024.01.29.577716v1
RNA viruses are known for their fascinating evolutionary dynamics, characterised by high mutation rates, fast replication, and ability to form quasispecies - clouds of genetically related mutants. Fast replication in RNA viruses is achieved by a very fast but error-prone RNA-dependent RNA polymerase (RdRP). High mutation rates are a double-edged sword: they provide RNA viruses with a mechanism of fast adaptation to a changing environment or host immune system, but at the same time they pose risk to virus survivability in terms of virus mutating beyond its error threshold. Coronaviruses, being a subset of RNA viruses, are unique in having a special enzyme, exoribonuclease (ExoN), responsible for proofreading and correcting errors induced by the RdRP. In this paper we consider replication dynamics of coronaviruses with account for mutations that can be neutral, deleterious or lethal, as well as ExoN. Special attention is paid to different virus replication modes that are known to be crucial for controlling the dynamics of virus populations. We analyse extinction, mutant-only and quasispecies steady states, and study their stability in terms of different parameters, identifying regimes of error catastrophe and lethal mutagenesis. With coronaviruses being responsible for some of the largest pandemics in the last twenty years, we also model the effects of antiviral treatment with various replication inhibitors and mutagenic drugs.
bioRxiv
29-01-2024
Preimpreso
Inglés
Público en general
VIRUS RESPIRATORIOS
Versión publicada
publishedVersion - Versión publicada
Aparece en las colecciones: Materiales de Consulta y Comunicados Técnicos

Cargar archivos: