From epigenetic landscape to phenotypic fitness landscape: Evolutionary effect of pathogens on host traits

Abstract

The epigenetic landscape illustrates how cells differentiate through the control of gene regulatory networks. Numerous studies have investigated epigenetic gene regulation but there are limited studies on how the epigenetic landscape and the presence of pathogens influence the evolution of host traits. Here, we formulate a multistable decision-switch model involving several phenotypes with the antagonistic influence of parasitism. As expected, pathogens can drive dominant (common) phenotypes to become inferior through negative frequency-dependent selection. Furthermore, novel predictions of our model show that parasitism can steer the dynamics of phenotype specification from multistable equilibrium convergence to oscillations. This oscillatory behavior could explain pathogen-mediated epimutations and excessive phenotypic plasticity. The Red Queen dynamics also occur in certain parameter space of the model, which demonstrates winnerless cyclic phenotype-switching in hosts and in pathogens. The results of our simulations elucidate the association between the epigenetic and phenotypic fitness landscapes and how parasitism facilitates non-genetic phenotypic diversity.

Coevolutionary theory of hosts and parasites

“…In contrast, GFG and range (unidirectional) models generally include trade‐offs (see ‘Pleiotropy and trade‐offs’) and types vary in their degree of generalism. These models can therefore produce a far broader range of outcomes, with stable monomorphic or polymorphic populations in either population (Ashby et al, 2019 ; Cortez et al, 2017 ; Fenton et al, 2009 ; Tellier & Brown, 2007a ), rapid oscillations occurring within levels of specialism (driven by negative frequency‐dependent selection) or slower oscillations occurring between levels of specialism (driven by trade‐offs) (Ashby & Boots, 2017 ). Moreover, the oscillations tend to be either stable limit cycles or damped cycles and are not structurally unstable as is common in matching models (Best et al, 2017 ; Kawecki, 1998 ; Kwiatkowski et al, 2012 ).…”

Antibiotic-driven escape of host in a parasite-induced Red Queen dynamics

“…Mathematical modelling is very useful in understanding host–parasite interaction and diseases [ 6 , 29 – 31 ]. The phenotype decision-switch network in figure 1 is used to illustrate the interaction among host phenotypes and parasites and the effect of antibiotic [ 25 ]. Here, the expression of host phenotype 1 (H1) inhibits the expression of host phenotype 2 (H2), and vice versa.…”

“…Inter-host type competition characterizes evolutionary selection among host types (genotype or phenotype) that will be commonly expressed in the host population. In multi-type host–parasite systems, multiple host types may coexist, but if canonical Red Queen dynamics arises, only one host type is common/dominant for a certain period of time [ 25 ].…”

A COVID-19 infection risk model for frontline health care workers

“…Mathematical models can be used for predicting scenarios and in prescribing solutions to problems (Rabajante 2020 ; Choudhury et al 2018 ; Ferrett et al 2020 ; Cortez 2017 ), such as addressing the COVID-19 pandemic. Based on the simulations and risk assessment, several recommendations are suggested to inhibit the spread of SARS-CoV-2, especially in health care facilities.…”