The Evolution of Evolvability in Microbial Populations

微生物种群进化能力的演变

• 批准号: 1914916
• 负责人: Michael Desai
• 金额: $ 79.77万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-15 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1914916&HistoricalAwards=false
• 关键词: Evolution; Evolvability; Microbial; Populations

Models of evolutionary dynamics often treat the evolutionary parameters as fixed. Yet these parameters can themselves be modified by mutations, which are then acted on by natural selection, a phenomenon known as the evolution of evolvability. For example, mutator or antimutator alleles that increase or decrease mutation rates often spread through microbial populations, and mutations that open up or close off future adaptive trajectories can alter "adaptability". Despite extensive work, our understanding of the evolution of evolvability in microbial populations remains very limited. The basic problem is that in the large and mostly asexual populations characteristic of many microbes and viruses, evolution often acts in ways that challenge traditional models, because there is too much going on at once. Many mutations are often present simultaneously, and because recombination is limited, selection cannot act on each separately. Rather, mutations are constantly occurring in a variety of combinations linked together on physical chromosomes, and selection can only act on these combinations as a whole. These effects, known as interference selection, place enormous constraints on microbial evolution, and have made it difficult to analyze how natural selection acts on mutations that modify evolutionary parameters. The PI will address this question by using a combination of mathematical models and experimental evolution in budding yeast to analyze the evolution of evolvability in microbial populations where these interference selection effects are widespread. This project will produce extensive data describing fixed mutations, sequence diversity, and changes in fitness in sexual and asexual yeast populations, along with a corresponding library of strains, which will serve as a resource for the community. In the process, this work will provide broad interdisciplinary training in methods from evolutionary biology, molecular genetics, population genetics, and applied math for a postdoc and graduate and undergraduate students in the PI's lab. To help train the broader community of potential quantitative biologists in these diverse fields, the PI will develop outreach efforts to disseminate a new curriculum he has developed for introductory undergraduate biology, which provides an integrated introduction to biology, physics, chemistry, computer science, and mathematics. Finally, the PI will develop a new textbook providing an introduction to evolution and population genetics, aimed at mathematicians and physical scientists. This textbook will provide a mathematically sophisticated introduction to the field, without any biological prerequisites, based on materials the PI developed for an undergraduate course on this subject and on a summer course organized by the PI. The traveling wave framework described in this proposal is a key theoretical underpinning of much of this subject, and will play an important role in the book. High-throughput experimental techniques and advances in sequencing technology now illustrate the pervasive importance of interference selection throughout microbial evolution. Motivated by this, much recent work has analyzed interference in large asexual populations. However, this work is limited to simple situations where the evolutionary parameters are fixed, and hence cannot explain the evolution of evolvability. In this project, the PI will address this question by combining novel theoretical methods inspired by statistical physics with direct observation of evolution in experimental populations of budding yeast. The PI will focus on analyzing alleles that modify mutation rates, adaptability, and robustness. The central goals are to predict (1) how interference selection affects the evolutionary dynamics and fates of these modifier alleles and hence the long-term evolution of evolvability in microbial populations, (2) how the modifiers of evolvability affect the dynamics of sequence diversity within the population, and (3) how recombination affects the evolution of evolvability.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.

进化动力学模型通常将进化参数视为固定的。然而，这些参数本身可以被突变所改变，然后被自然选择所作用，这一现象被称为进化。例如，增加或降低突变率的突变或反突变等位基因通常会在微生物种群中传播，而开启或关闭未来适应轨迹的突变可能会改变“适应性”。尽管进行了广泛的工作，但我们对微生物种群中可进化性进化的理解仍然非常有限。基本的问题是，在以许多微生物和病毒为特征的庞大且主要是无性的种群中，进化的方式往往挑战传统模式，因为同时发生的事情太多了。许多突变通常是同时存在的，因为重组是有限的，选择不能单独作用于每个突变。相反，突变经常发生在物理染色体上连接在一起的各种组合中，而选择只能作为一个整体对这些组合起作用。这些被称为干扰选择的效应对微生物的进化施加了巨大的限制，使得分析自然选择如何作用于改变进化参数的突变变得困难。PI将通过使用数学模型和发芽酵母的实验进化相结合的方式来解决这个问题，以分析这些干扰选择效应普遍存在的微生物种群的进化。该项目将产生大量数据，描述有性和无性酵母种群的固定突变、序列多样性和适应性变化，以及相应的菌株库，这将作为社区的资源。在此过程中，这项工作将为PI实验室的博士后、研究生和本科生提供广泛的跨学科方法培训，包括进化生物学、分子遗传学、种群遗传学和应用数学。为了帮助培训这些不同领域的更广泛的潜在数量生物学家社区，PI将开展外联工作，传播他为本科生生物学入门开发的新课程，该课程提供生物、物理、化学、计算机科学和数学的综合入门。最后，PI将为数学家和物理学家开发一本新的教科书，提供进化论和种群遗传学的入门知识。这本教科书将提供一个复杂的数学领域的介绍，没有任何生物学的先决条件，基于国际和平协会为本科课程开发的关于这一主题的材料和由国际和平协会组织的暑期课程。本提案中描述的行波框架是本主题大部分内容的关键理论基础，并将在本书中发挥重要作用。高通量实验技术和测序技术的进步现在说明了干扰选择在整个微生物进化过程中的普遍重要性。受此启发，最近的工作分析了对大量无性恋人群的干扰。然而，这项工作仅限于进化参数固定的简单情况，因此不能解释进化性的进化。在这个项目中，PI将通过将统计物理学启发的新理论方法与对萌芽酵母实验种群进化的直接观察相结合来解决这个问题。PI将专注于分析改变突变率、适应性和稳健性的等位基因。中心目标是预测(1)干扰选择如何影响这些修饰等位基因的进化动态和命运，从而影响微生物种群的长期进化，(2)进化的修饰物如何影响种群内序列多样性的动态，以及(3)重组如何影响进化的进化。这一奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Spatial structure alters the site frequency spectrum produced by hitchhiking

空间结构改变了搭便车产生的场地频谱

• DOI: 10.1093/genetics/iyac139
• 发表时间: 2022
• 期刊: Genetics
• 影响因子: 3.3
• 作者: Min, Jiseon;Gupta, Misha;Desai, Michael M.;Weissman, Daniel B.;Novembre, ed., J.
• 通讯作者: Novembre, ed., J.

Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast.

• DOI: 10.7554/elife.73983
• 发表时间: 2022-02-11
• 期刊: eLife
• 影响因子: 7.7
• 作者: Nguyen Ba AN;Lawrence KR;Rego-Costa A;Gopalakrishnan S;Temko D;Michor F;Desai MM
• 通讯作者: Desai MM

Hierarchical sequence-affinity landscapes shape the evolution of breadth in an anti-influenza receptor binding site antibody.

• DOI: 10.7554/elife.83628
• 发表时间: 2023-01-10
• 期刊: ELIFE
• 影响因子: 7.7
• 作者: Phillips, Angela M.;Maurer, Daniel P.;Brooks, Caelan;Dupic, Thomas;Schmidt, Aaron G.;Desai, Michael M.
• 通讯作者: Desai, Michael M.

Population genetics of polymorphism and divergence in rapidly evolving populations

快速进化群体中多态性和分化的群体遗传学

• DOI: 10.1093/genetics/iyac053
• 发表时间: 2022
• 期刊: Genetics
• 影响因子: 3.3
• 作者: Melissa, Matthew J;Good, Benjamin H;Fisher, Daniel S;Desai, Michael M
• 通讯作者: Desai, Michael M