The Evolution of Host Specialization in an Insect Pathogen

Niche breadth coevolution between biotic partners underpins theories of diversity and co-existence and influences patterns of disease emergence and transmission in host-parasite systems. Despite these broad implications, we still do not fully understand how the breadth of parasites’ infectivity evolves, the nature of any associated costs, or the genetic basis of specialization. Here, we serially passage a granulosis virus on multiple inbred populations of its Plodia interpunctella host to explore the dynamics and outcomes of specialization. In particular, we collect time series of phenotypic and genetic data to explore the dynamics of host genotype specialization throughout the course of experimental evolution and examine two fitness components. We find that the Plodia interpunctella granulosis virus consistently evolves increases in overall specialization, but that our two fitness components evolve independently such that lines specialize in either productivity or infectivity. Furthermore, we find that specialization in our experiment is a highly polygenic trait best explained by a combination of evolutionary mechanisms including conditionally positive fitness asymmetries and mutation accumulation. These results are important for understanding the evolution of specialization in host-parasite interactions and its broader implications for co-existence, diversification, and infectious disease management.

Asymmetric evolvability leads to specialization without trade-offs

Many ideas about the evolution of specialization rely on trade-offs—an inability for one organism to express maximal performance in two or more environments. However, optimal foraging theory suggests that populations can evolve specialization on a superior resource without explicit trade-offs. Classical results in population genetics show that the process of adaptation can be biased toward further improvement in already productive environments, potentially widening the gap between superior and inferior resources. Here I synthesize these approaches with new insights on evolvability at low recombination rates, showing that emergent asymmetries in evolvability can push a population toward specialization in the absence of trade-offs. Simulations are used to demonstrate how adaptation to a more common environment interferes with adaptation to a less common but otherwise equal alternative environment. Shaped by recombination rates and other population-genetic parameters, this process results in either the retention of a generalist niche without trade-offs or entrapment at the local optimum of specialization on the common environment. These modeling results predict that transient differences in evolvability across traits during an episode of adaptation could have long-term consequences for a population’s niche.

Evolution of Specialization in Heterogeneous Environments: Equilibrium Between Selection, Mutation and Migration

Adaptation in spatially heterogeneous environments results from the balance between local selection, mutation, and migration. We study the interplay among these different evolutionary forces and demography in a classical two-habitat scenario with asexual reproduction. We develop a new theoretical approach that goes beyond the Adaptive Dynamics framework, and allows us to explore the effect of high mutation rates on the stationary phenotypic distribution. We show that this approach improves the classical Gaussian approximation, and captures accurately the shape of this equilibrium phenotypic distribution in one- and two-population scenarios. We examine the evolutionary equilibrium under general conditions where demography and selection may be nonsymmetric between the two habitats. In particular, we show how migration may increase differentiation in a source–sink scenario. We discuss the implications of these analytic results for the adaptation of organisms with large mutation rates, such as RNA viruses.

Evolution of Specialization in Dynamic Fluids

Previously we found mechanical factors involving diffusion and fluid shear promote evolution of social behavior in microbial populations Uppal and Vural (2018). Here, we extend this model to study the evolution of specialization using realistic physical simulations of bacteria that secrete two public goods in a dynamic fluid. Through this first principles approach, we find physical factors such as diffusion, flow patterns, and decay rates are as influential as fitness economics in governing the evolution of community structure, to the extent that when mechanical factors are taken into account, (1) Generalist communities can resist becoming specialists, despite the invasion fitness of specialization (2) Generalist and specialists can both resist cheaters despite the invasion fitness of free-riding. (3) Multiple community structures can coexist despite the opposing force of competitive exclusion. Our results emphasize the role of spatial assortment and physical forces on niche partitioning and the evolution of diverse community structures.

Evolution of specialization in heterogeneous environments: equilibrium between selection, mutation and migration

Adaptation in spatially heterogeneous environments results from the balance between local selection, mutation and migration. We study the interplay among these different evolutionary forces and demography in a classical two habitat scenario with asexual reproduction. We develop a new theoretical approach that fills a gap between the restrictive assumptions of Adaptive Dynamics and Quantitative Genetics. This analysis yields more accurate predictions of the equilibrium phenotypic distribution in different habitats. We examine the evolutionary equilibrium under general conditions where demography and selection may be non-symmetric between the two habitats. In particular we show how migration may increase differentiation in a source-sink scenario. We discuss the implications of these analytic results for the adaptation of organisms with large mutation rates such as RNA viruses.

Individual-versus group-optimality in the production of secreted bacterial compounds

How unicellular organisms optimize the production of compounds is a fundamental biological question. While it is typically thought that production is optimized at the individual-cell level, secreted compounds could also allow for optimization at the group level, leading to a division of labor where a subset of cells produces and shares the compound with everyone. Using mathematical modelling, we show that the evolution of such division of labor depends on the cost function of compound production. Specifically, for any trait with saturating benefits, linear costs promote the evolution of uniform production levels across cells. Conversely, production costs that diminish with higher output levels favor the evolution of specialization – especially when compound shareability is high. When experimentally testing these predictions with pyoverdine, a secreted iron-scavenging compound produced by Pseudomonas aeruginosa, we found linear costs and, consistent with our model, detected uniform pyoverdine production levels across cells. We conclude that for shared compounds with saturating benefits, the evolution of division of labor is facilitated by a diminishing cost function. More generally, we note that shifts in the level of selection from individuals to groups do not solely require cooperation, but critically depend on mechanistic factors, including the distribution of compound synthesis costs.