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CAREER: Quantifying Genetic and Ecological Constraints on the Evolution of Thermal Performance Curves

$739,066FY2024BIONSF

Duke University, Durham NC

Investigators

Abstract

This research project will examine how a model, one-celled organism - Tetrahymena thermophila – adapts to changing temperatures. It aims to resolve a critical gap in our understanding of how rapid global climate change may affect all living organisms by studying whether and how a species belonging to one of the most abundant groups on Earth – one-celled organisms known as protists – may evolve to grow more rapidly as temperatures increase, and the biological factors that determine that evolution. Answering this seemingly simple question has myriad societal impacts. Indeed, evolution towards faster growth at warmer temperatures is also predicted to result in increased respiration rates – the process through which living organisms burn sugars to obtain energy while releasing carbon dioxide, a potent greenhouse gas – which would in turn worsen climate change. Additionally, since many protists are human pathogens responsible for diseases like malaria and sleeping sickness, understanding their evolution in changing climates is crucial for public health. Last, this project commits to broadening scientific participation by empowering students from diverse backgrounds, thus enhancing their academic and professional growth in the fields of ecology and evolutionary biology. Our research links thermal, population, and community ecology to the genetic-level processes responsible for determining the thermal performance curve of population growth rates (r-TPCs) in Tetrahymena thermophila, a microbial species of cosmopolitan distribution and importance, and which has a large library of genetic variants. The project will use microcosm experiments and mathematical models. In Aim 1 will quantify intraspecific variation (genetic, environmental, and genotype-environment interaction) in T. thermophila r-TPC using a model population composed of >50 unique genetic strains. These data will quantify selection and evolvability of r-TPCs in this model population to predict possible evolutionary trajectories under warming. Aim 2 will quantify experimentally the evolution of r-TPC in the short- and long-term under warming, and determine its predictablity. Aim 3 will assess how competition and predation influence r-TPC shape evolution within a simplified aquatic microbial food web. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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