Biological and biomedical implications of the co-evolution of pathogens and their hosts

Co-evolution between host and pathogen is, in principle, a powerful determinant of the biology and genetics of infection and disease. Yet co-evolution has proven difficult to demonstrate rigorously in practice, and co-evolutionary thinking is only just beginning to inform medical or veterinary research in any meaningful way, even though it can have a major influence on how genetic variation in biomedically important traits is interpreted. Improving our understanding of the biomedical significance of co-evolution will require changing the way in which we look for it, complementing the phenomenological approach traditionally favored by evolutionary biologists with the exploitation of the extensive data becoming available on the molecular biology and molecular genetics of host–pathogen interactions

Data from: Quantifying the coevolutionary potential of multistep immune defenses

Coevolutionary models often assume host infection by parasites depends on a single bout of molecular recognition. As detailed immunological studies accumulate, however, it becomes increasingly apparent that the outcome of host-parasite interactions more generally depends on complex multiple step infection processes. For example, in plant and animal innate immunity, recognition steps are followed by downstream effector steps that kill recognized parasites, with the outcome depending on an escalatory molecular arms race. Here, we explore the consequences of such multi-step infection processes for coevolution using a genetically explicit model. Model analyses reveal that polymorphism is much greater at recognition loci than effector loci, that host-genotype by parasite-genotype (Gh x Gp) interactions are larger for the recognition step, and that the recognition step contributes more to local adaptation than the effector step. These results suggest that (1) local adaptation is more likely when fitness measures are related to recognition versus downstream effectors, (2) effector loci, while mechanistically important, are less likely to harbor the Gh x Gp variation that fuels coevolution, and (3) recognition loci are better candidates for genomic hotspots of coevolution

Simulation code (C++)

This C++ code performs coevolutionary simulations as described within the paper

Consumer resource interactions and the evolution of migration

Theoretical studies have demonstrated that selection will favor increased migration when fitnesses vary both temporally and spatially, but it is far from clear how pervasive those theoretical conditions are in nature. While consumer-resource interactions are omnipresent in nature and can generate spatial and temporal variation, it is unknown even in theory whether these dynamics favor the evolution of migration. We develop a mathematical model to address whether and how migration evolves when variability in fitness is determined at least in part by consumer-resource coevolutionary interactions. Our analyses show that such interactions can drive the evolution of migration in the resource, consumer, or both species and thus supplies a general explanation for the pervasiveness of migration. Over short time scales, we show the direction of change in migration rate is determined primarily by the state of local adaptation of the species involved: rates increase when a species is locally maladapted and decrease when locally adapted. Our results reveal that long-term evolutionary trends in migration rates can differ dramatically depending on the strength or weakness of interspecific interactions and suggest an explanation for the evolutionary divergence of migration rates among interacting species

Appendix C. A figure of the fitted growth curves for all populations at 12ºC, 18ºC, and 24ºC.

A figure of the fitted growth curves for all populations at 12ºC, 18ºC, and 24ºC

Identifying coevolving loci using interspecific genetic correlations

Evaluating the importance of coevolution for a wide range of evolutionary questions, such as the role parasites play in the evolution of sexual reproduction, requires that we understand the genetic basis of coevolutionary interactions. Despite its importance, little progress has been made identifying the genetic basis of coevolution, largely because we lack tools designed specifically for this purpose. Instead, coevolutionary studies are often forced to re‐purpose single species techniques. Here, we propose a novel approach for identifying the genes mediating locally adapted coevolutionary interactions that relies on spatial correlations between genetic marker frequencies in the interacting species. Using individual‐based multi‐locus simulations, we quantify the performance of our approach across a range of coevolutionary genetic models. Our results show that when one species is strongly locally adapted to the other and a sufficient number of populations can be sampled, our approach accurately identifies functionally coupled host and parasite genes. Although not a panacea, the approach we outline here could help to focus the search for coevolving genes in a wide variety of well‐studied systems for which substantial local adaptation has been demonstrated

Identifying coevolving loci using interspecific genetic correlations

Evaluating the importance of coevolution for a wide range of evolutionary questions, such as the role parasites play in the evolution of sexual reproduction, requires that we understand the genetic basis of coevolutionary interactions. Despite its importance, little progress has been made identifying the genetic basis of coevolution, largely because we lack tools designed specifically for this purpose. Instead, coevolutionary studies are often forced to re‐purpose single species techniques. Here, we propose a novel approach for identifying the genes mediating locally adapted coevolutionary interactions that relies on spatial correlations between genetic marker frequencies in the interacting species. Using individual‐based multi‐locus simulations, we quantify the performance of our approach across a range of coevolutionary genetic models. Our results show that when one species is strongly locally adapted to the other and a sufficient number of populations can be sampled, our approach accurately identifies functionally coupled host and parasite genes. Although not a panacea, the approach we outline here could help to focus the search for coevolving genes in a wide variety of well‐studied systems for which substantial local adaptation has been demonstrated

Phenotypic plasticity of the introduced New Zealand mud snail, Potamopyrgus antipodarum, compared to sympatric native snails.

Phenotypic plasticity is likely to be important in determining the invasive potential of a species, especially if invasive species show greater plasticity or tolerance compared to sympatric native species. Here in two separate experiments we compare reaction norms in response to two environmental variables of two clones of the New Zealand mud snail, Potamopyrgus antipodarum, isolated from the United States, (one invasive and one not yet invasive) with those of two species of native snails that are sympatric with the invader, Fossaria bulimoides group and Physella gyrina group. We placed juvenile snails in environments with high and low conductivity (300 and 800 mS) in one experiment, and raised them at two different temperatures (16 °C and 22 °C) in a second experiment. Growth rate and mortality were measured over the course of 8 weeks. Mortality rates were higher in the native snails compared to P. antipodarum across all treatments, and variation in conductivity influenced mortality. In both experiments, reaction norms did not vary significantly between species. There was little evidence that the success of the introduced species is a result of greater phenotypic plasticity to these variables compared to the sympatric native species