Within-host stochastic emergence dynamics of immune-escape mutants

PLoS Computational Biology
Matthew Hartfield, Samuel Alizon

Abstract

Predicting the emergence of new pathogenic strains is a key goal of evolutionary epidemiology. However, the majority of existing studies have focussed on emergence at the population level, and not within a host. In particular, the coexistence of pre-existing and mutated strains triggers a heightened immune response due to the larger total pathogen population; this feedback can smother mutated strains before they reach an ample size and establish. Here, we extend previous work for measuring emergence probabilities in non-equilibrium populations, to within-host models of acute infections. We create a mathematical model to investigate the emergence probability of a fitter strain if it mutates from a self-limiting strain that is guaranteed to go extinct in the long-term. We show that ongoing immune cell proliferation during the initial stages of infection causes a drastic reduction in the probability of emergence of mutated strains; we further outline how this effect can be accurately measured. Further analysis of the model shows that, in the short-term, mutant strains that enlarge their replication rate due to evolving an increased growth rate are more favoured than strains that suffer a lower immune-mediated death rate ('immune t...Continue Reading

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Citations

Sep 7, 2018·Proceedings of the National Academy of Sciences of the United States of America·Bradley R JonesZabrina L Brumme
Apr 18, 2019·BMC Bioinformatics·Lubna PinkyHana M Dobrovolny
Apr 9, 2019·Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences·Carmen Lía Murall, Samuel Alizon

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