DISSERTATION RESEARCH: Quantitative test of evolutionary bet-hedging theory in a mirobial model system

该项目将提供对影响在不断变化的环境中适应的基本原则的理解。进化理论预测，在不断变化的环境中，自然选择将有利于性状，只要它们随着时间的推移带来净效益。这种在不断变化的环境中适应的背景对于理解许多特征至关重要，例如感知和响应环境的能力以及病原微生物的耐药性。因此，这项研究将有助于阐明医学上重要特征的进化过程。研究人员还将制定并分发一个课程计划，旨在向高中生教授在不断变化的环境中适应的基本原则，从而帮助提高公众对一个生物学相关问题的认识。生物性状，如表型可塑性和赌注对冲，被认为是通过增加血统的长期几何平均适应度来进化的。这个框架作为一个有用的描述性状的平均选择优势在一个可变的环境。然而，这种方法存在已知的理论局限性，因为它不能明确地捕获进化种群的进化动力学，因此不能提供对诸如下注对冲等性状的进化起源和维持的机械描述。使用适应快速环境压力的实验室酵母菌群，研究人员将通过实验测量可变环境中竞争性赌注对冲策略的进化动态。研究人员将使用基因组测序和反向遗传学的组合来构建一组荧光标记的酵母菌株，这些酵母菌株表达不同的下注对冲策略。通过在可变环境中的竞争实验过程中仔细跟踪竞争菌株的丰度，研究人员将直接将实验室中的进化变化与不同环境中适应的计算模型的预测进行比较。在这样做的过程中，研究将产生必要的数据，直接测试的几何平均健身概念，并将实验确定其局限性的程度来描述适应不同的环境。

This project will provide understanding of the fundamental principles that influence adaptation in changing environments. Evolutionary theory predicts that natural selection in changing environments will favor traits so long as they confer a net benefit over time. This context of adaptation in changing environments is central to understanding many traits, such as the ability to sense and respond to the environment, and drug resistance of pathogenic microorganisms. This research will therefore help to elucidate the evolutionary processes underlying medically important traits. The researchers will also develop and distribute a lesson plan aimed at teaching the basic tenets of adaptation in changing environments to high school students, thus helping to raise public awareness about a biologically relevant problem.Biological traits such as phenotypic plasticity and bet-hedging are presumed to evolve by increasing the long-term geometric mean fitness of a lineage. This framework serves as a useful description of the average selective advantage of traits in a variable environment. However, there are known theoretical limitations with this approach since it fails to explicitly capture evolutionary dynamics of evolving populations and thus does not provide a mechanistic description of the evolutionary origin and maintenance of traits such as bet-hedging. Using laboratory yeast populations adapted to rapid periods of environmental stress, the researchers will experimentally measure evolutionary dynamics of competing bet-hedging strategies in a variable environment. The researchers will use a combination of genome sequencing and reverse genetics to construct a panel of fluorescently labeled yeast strains that express differing bet-hedging strategies. By carefully tracking the abundance of competing strains during the course of competition experiments in variable environments, the researchers will directly compare evolutionary changes in the laboratory to the predictions of computational models of adaptation in varying environments. In doing so, the research will generate data necessary to directly test of the geometric mean fitness concept and will experimentally determine the extent of its limitations for describing adaptation to varying environments.