CAREER: Impact of Eco-Evolutionary Feedbacks on the Dynamics of Adaptation

微生物的适应速度有多快？虽然这个问题已经探讨了很大的努力和数量上的成功，在良好的混合种群，自然种群表现出空间结构的理论和实验之间有很大的差距。这使我们在理解进化反应方面严重损失，例如，微生物菌落或生物膜，并使其无法预测耐药性演变的步伐。私家侦探在过去的研究中，他证明了理论和实验可以有效地结合起来，剖析空间结构引起的进化过程。这一成果通过使用创新的实验设计，如工程微生物系统来跟踪可选择的突变克隆的自发出现，以及允许准确处理波动和生态进化反馈的理论概念，将这项工作推向了一个新的水平。该项目的结果将促进我们对适应的时空方面的理解，并具体阐明种群如何应对环境恶化，这是从合理设计战略以保护面临环境变化的物种到减轻耐药性演变等努力的关键。这项实验研究产生的数据集，结合新的理论和模拟，将使社区重新评估关于微生物种群适应的既定范式。该研究将邀请新的跨学科活动，以了解，预测和控制空间结构微生物种群的适应。跨学科研究与广泛的教育努力密切配合，旨在促进传统学科边界的跨越，以实现对进化过程的新思维方式，如耐药性进化，超越标准平均场进化理论的局限性。在研究生和本科阶段，研究将伴随着一个新的跨学科课程，细胞和人口的统计生物物理学，PI提供给物理，化学，生物学和数学的学生。此外，PI还与伯克利的劳伦斯科学馆建立了紧密的合作关系，为高中生和本科生准备新的教育资源，以探索微生物种群的普遍性和进化潜力，并建立生态学和进化之间的关键联系。这些资源包括一个学习模块和实践活动，将以书面形式记录下来，并通过现有的国家科学基金会资助的网络基础设施平台免费在线提供。人口统计学和进化紧密交织在一起。个体在空间上的分布决定了新突变的涌入、遗传漂变的强度和基因型之间的竞争。另一方面，进化影响着人口的规模和密度，个体如何迁移，如何与彼此和环境相互作用，以及它们如何繁殖和死亡。在进化的混合种群的标准模型中，种群动态和进化之间的反馈是不存在的。然而，它限制了适应的速度，进化结果的可预测性和空间结构种群的进化反应。该项目的目标是通过量化微生物种群中相关的生态进化反馈及其对适应的影响来填补这一空白。为此，PI提出了严格控制的微生物进化实验，以量化人口动态如何改变分子进化模式，以及新的人口遗传学理论，弥合实验室实验和自然人口之间的时空尺度上的差距。具体目标是：1.确定细胞如何产生遗传漂变和选择的群体水平模式的随机动力学，以及这些模式如何控制有益突变的命运。在混合种群中推广成熟的进化理论，以捕捉实验的生态进化反馈动力学。2.确定空间结构种群如何适应环境挑战（i）通过预先存在的突变和（ii）通过新突变的积累。3.建立一个新的课程，无意的偏见和本科生指导，以增加在干在加州大学伯克利分校领域的多样性研讨会。该项目正在由物理学和细胞集群和系统和合成生物学集群在分子和细胞生物科学的分工物理学的生活系统程序的联合支持。

How fast do microbes adapt? While this question has been explored in well-mixed populations with great effort and quantitative success, there is a large gap between theory and experiments for natural populations exhibiting spatial structure. This leaves us at a serious loss in understanding the evolutionary response of, e.g., microbial colonies or biofilms, and makes it impossible to predict the pace of drug-resistance evolution. The P.I. has demonstrated in his past research that theory and experiments can be joined effectively to dissect the evolutionary processes induced by spatial structure. This effprt puts this work onto a new level by the use of innovative experimental designs such as engineered microbial systems to track the spontaneous emergence of selectable mutant clones, and theoretical concepts that allow dealing with fluctuations and eco-evolutionary feedbacks exactly. The results of this project will advance our understanding of spatio-temporal aspects of adaptation, and elucidate specifically how populations respond to environmental deterioration, which is key to efforts ranging from the rational design of strategies to conserve species in the face of environmental change to mitigating drug resistance evolution. The data set generated by this experimental research, combined with novel theory and simulations, will allow the community to reassess established paradigms about adaptation of microbial populations. The research will invite novel interdisciplinary activities in the quest to understand, predict and control adaptation of spatially-structured microbial populations. The interdisciplinary research is closely orchestrated with broad educational efforts designed to promote crossing of traditional disciplinary boundaries to achieve new ways of thinking about evolutionary processes, such as drug resistance evolution, that transcend the limitations of the standard mean-field theories of evolution. At the graduate and undergraduate level, the research will be accompanied by a new interdisciplinary course, Statistical Biophysics of Cells and Populations, that the PI offers to students of physics, chemistry, biology and mathematics. In addition, the PI has established a firm collaboration with the Lawrence Hall of Science at Berkeley to prepare novel educational resources for high-school students and undergraduates to explore the ubiquity and evolutionary potential of microbial populations and to establish the crucial link between ecology and evolution. These resources, which include a learning module and hands-on activities, will be documented in write-ups and made freely available online through existing NSF-funded cyber-infrastructure platforms.Demography and evolution are tightly intertwined. The distribution of individuals in space determines the influx of new mutations, the strength of genetic drift and the competition between genotypes. Evolution on the other hand, influences the sizes and densities populations can attain, how individuals migrate and interact with each other and the environment and how they reproduce and die. The feedback between population dynamics and evolution is absent in standard models of evolving well-mixed populations. Yet, it constrains the pace of adaptation, the predictability of evolutionary outcomes and the evolutionary response of spatially-structured populations. The objective of this project is to fill this gap by quantifying the associated eco-evolutionary feedback in microbial populations and its consequences for adaptation. To this end, the P.I. proposes tightly-controlled microbial evolution experiments to quantify how population dynamics alters patterns of molecular evolution, and new population genetics theory that bridges the gap in spatio-temporal scales between laboratory experiments and natural populations. The specific aims are: 1. Determine how the stochastic dynamics of how cells generate population-level patterns of genetic drift and selection and how these patterns control the fate of beneficial mutations. Generalize well-established theories of evolution in well-mixed populations to capture the eco-evolutionary feedback dynamics of the experiments. 2. Determine how spatially-structured populations adapt to environmental challenges (i) via pre-existing mutations and (ii) via the accumulation of new mutations. 3. Establish a new course, a workshop on unintentional biases and undergraduate mentoring to increase diversity in the STEM fields at UC Berkeley.This project is being jointly supported by the Physics of Living Systems program in the Division of Physics and the Cellular Cluster and the Systems and Synthetic Biology clusters in the Division of Molecular and Cellular Biosciences.