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Zawartość zarchiwizowana w dniu 2024-06-18

INDIVIDUAL HETEROGENEITY AND THE EVOLUTION OF PHENOTYPIC VARIABILITY

Final Report Summary - PHENOTYPICVAR (Individual Heterogeneity and the Evolution of Phenotypic Variability)

This project aimed at extending our understanding of the maintenance and evolution of phenotypic variability, in particular variability in life history parameters. Using a cutting edge-microfluidic system we collected individual level demographic data on bacteria under highly controlled lab conditions, and made substantial advancements in image analyses of such data. Previously fluorescent protein markers needed to increase the contrast for cell segmentation needed to analyse the images, we overcome this limitation by improving data quality and writing novel tools for image analyses that make such protein markers obsolete. The experiments on the bacteria microfluidic system exploring distributions in longevity of isogenetic E. coli bacteria revealed substantial stochastic variability in lifespan, and, surprisingly, the scaled variability was similar between different temperatures. Such neutral variation has substantial consequences for population dynamics and evolutionary change in phenotypes as we showed through simulations and illustrations on empirical examples. We developed easy interpretable sensitivity analyses of age-stage structured populations that are simple to conduct. We investigated how rejuvenation of bacteria cells by division might not be as perfect as previously assumed, suggesting senescence in reproduction, less in the quantity of cells produced but rather in the quality of cells. Such findings suggest that the asymmetric division between mother and daughter cell is not sufficient to lead to perfect rejuvenation at old ages. We extended classical results of Lotka in describing the relationship between the amount of reproduction, the generation time, and the population growth rate, to stage-age structured populations. The project added to the development and implementation of a new framework for the study of dynamics in variability and life history evolution in stage-age-structured populations. The tools and findings are useful for population management, and developing conservation measures.