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

微生物适应的速度有多快？虽然这个问题已经在混合良好的种群中进行了大量的探索，并取得了定量上的成功，但对于表现空间结构的自然种群，理论和实验之间存在很大的差距。这使我们在理解微生物菌落或生物膜等生物的进化反应方面陷入严重的困境，也使我们无法预测耐药性进化的速度。P.I.在他过去的研究中已经证明，理论和实验可以有效地结合起来，来剖析由空间结构引起的进化过程。这项工作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，以及允许精确处理波动和生态进化反馈的理论概念，将这项工作提升到一个新的水平。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，这是在面临环境变化时合理设计物种保护策略以减轻耐药性进化的关键。这项实验研究产生的数据集，结合新的理论和模拟，将允许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，以寻求理解、预测和控制空间结构微生物种群的适应性。跨学科研究与广泛的教育努力紧密结合，旨在促进跨越传统学科界限，以实现对进化过程的新思考方式，例如抗药性进化，超越了标准进化平均场理论的限制。在研究生和本科生阶段，这项研究将伴随着一门新的跨学科课程——细胞和种群的统计生物物理学，PI为物理、化学、生物和数学专业的学生开设了这门课程。此外，PI还与伯克利的劳伦斯科学馆建立了牢固的合作关系，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存在和进化潜力，并建立生态学与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nsf资助的网络基础设施平台免费在线提供。人口与进化紧密地交织在一起。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，进化影响着种群的规模和密度，影响着个体如何迁移，如何与环境相互作用，以及它们如何繁殖和死亡。在混合良好的种群进化的标准模型中，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，P.I.提出了严格控制的微生物进化实验，以量化群体动态如何改变分子进化模式，以及新的群体遗传学理论，在实验室实验和自然群体之间的时空尺度上弥合差距。具体目标是：1。确定细胞如何产生种群水平的遗传漂变和选择模式的随机动力学，以及这些模式如何控制有益突变的命运。在混合良好的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态。2. 确定空间结构种群如何(i)通过预先存在的突变和（ii）通过新突变的积累来适应环境挑战。3. 开设一门新课程，开设一个关于无意偏见和本科生指导的研讨会，以增加加州大学伯克利分校STEM领域的多样性。该项目由物理和细胞学部的生命系统物理学项目以及分子和细胞生物科学部的系统和合成生物学集群共同支持。

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.