Melissa Sui

Failures of the lysosome-autophagy system are a hallmark of ageing and many disease states. As a consequence, interventions that enhance lysosome function are of keen interest in the context of drug development. Throughout the biomedical literature, evolutionary biologists have found cases in which challenges faced by humans in clinical settings have been resolved by non-model organisms adapting to wild environments. Here, we used a primary cell culture approach to survey lysosomal characteristics in species of the genus Mus. We found that fibroblasts from M. spretus, a wild Mediterranean mouse, exhibited elevated lysosomal mass and enzyme activity along with reduced activity of β-galactosidase, a classical marker of cellular senescence, compared with those from M. musculus, a related species adapted to human-associated environments. We propose that classic laboratory models of lysosome function and senescence may reflect characters that diverge from the phenotypes of wild mice. The M. spretus phenotype may ultimately serve as a blueprint for interventions that ameliorate lysosomal dysfunction under conditions of stress and disease.

Host heterogeneity and spatial population structure each influence parasite evolution and may interact when space structures contacts between host types. Here, we experimentally evolve granulosis virus in microcosms of its natural Plodia interpunctella (Indian meal moth) host that differ in both spatial structure and host genetic diversity. We control spatial structure by manipulating the viscosity of the food that the larvae live within and host genetic diversity by adding larvae from either one or two non-evolving inbred lines to opposite microcosm ends. We preserve spatial structure across passages and assay virus from different positions within the microcosm on both host genotypes. We find that the lower contact rates between host genotypes resulting from spatial structure can lead to the evolution of locally specialized virus, even when the host population is genetically diverse overall. We also find that spatial structure changes how viruses specialize: viruses evolved in well-mixed environments had lower exploitation rates (proportion infected x virions) on the host they evolved with, while those in spatially structured environments exhibited higher exploitation of familiar hosts. These results demonstrate that spatial structure and host heterogeneity interact to shape pathogen specialization and that the evolutionary consequences of host diversity depend on population structure.

Failures of the lysosome-autophagy system are a hallmark of aging and many disease states. As a consequence, interventions that enhance lysosome function are of keen interest in the context of drug development. Throughout the biomedical literature, evolutionary biologists have found cases in which challenges faced by humans in clinical settings have been resolved by non-model organisms adapting to wild environments. Here, we used a primary cell culture approach to survey lysosomal characteristics in species of the genus Mus . We found that fibroblasts from M. spretus , a wild Mediterranean mouse, exhibited elevated lysosomal mass and enzyme activity along with reduced activity of β-galactosidase, a classical marker of cellular senescence, compared to those from M. musculus , a related species adapted to human-associated environments. We propose that classic laboratory models of lysosome function and senescence may reflect characters that diverge from the phenotypes of wild mice. The M. spretus phenotype may ultimately serve as a blueprint for interventions that ameliorate lysosomal dysfunction under conditions of stress and disease.

Host heterogeneity and spatial population structure each influence parasite evolution but may also interact because space structures contacts between host types. Here, we experimentally evolve granulosis virus in microcosms of its Plodia interpunctella (Indian meal moth) host that differ in both spatial structure and host genetic diversity. We control spatial structure by manipulating the viscosity of the food that the larvae live within and host genetic diversity by adding larvae from either a single or two inbred lines to opposite ends of the microcosm. We preserve spatial structure across passages and assay virus from different positions within the microcosm on both host genotypes. We find that the lower contact rates between host genotypes resulting from spatial structure can lead to the evolution of locally specialized virus, even when the host population is genetically diverse overall. We also find that spatial structure changes how viruses specialize: viruses evolved in well-mixed environments had lower exploitation of familiar hosts, while those in spatially structured environments exhibited higher exploitation of familiar hosts. These results demonstrate that spatial structure and host heterogeneity interact to shape pathogen specialization and that the evolutionary consequences of host diversity depends on the population structure.

There is increasing interest in the role that evolution may play in current and future pandemics, but there is often also considerable confusion about the actual evolutionary predictions. This may be, in part, due to a historical separation of evolutionary and medical fields, but there is a large, somewhat nuanced body of evidence-supported theory on the evolution of infectious disease. In this review, we synthesize this evolutionary theory in order to provide a framework for clearer understanding of the key principles. Specifically, we discuss the selection acting on zoonotic pathogens' transmission rates and virulence at spillover and during emergence. We explain how the direction and strength of selection during epidemics of emerging zoonotic disease can be understood by a three Ts framework: trade-offs, transmission, and time scales. Virulence and transmission rate may trade-off, but transmission rate is likely to be favoured by selection early in emergence, particularly if maladapted zoonotic pathogens have ‘no-cost’ transmission rate improving mutations available to them. Additionally, the optimal virulence and transmission rates can shift with the time scale of the epidemic. Predicting pathogen evolution, therefore, depends on understanding both the trade-offs of transmission-improving mutations and the time scales of selection.