Relationship between genealogies and biophysical processes during spatial growth.

空间生长过程中谱系与生物物理过程之间的关系。

• 批准号: 10669638
• 负责人: Kirill Sergeevich Korolev
• 金额: $ 28.88万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-11 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10669638
• 关键词: Address; Affect; Antibiotic Resistance; Behavior; Biological Process; Biology; Biophysical Process; Biophysics; Chemicals; Chemistry; Cues; Data; Dependence; Diffusion; Disease Vectors; Drug resistance; Endowment; Epidemic; Evolution; Genealogical Tree; Genealogy; Genetic; Genetic Processes; Genetic Programming; Genetic Variation; Goals; Growth; Heterogeneity; Individual; Infection; Intervention; Joints; Learning; Letters; Link; Malignant Neoplasms; Mammalian Cell; Mathematics; Medicine; Methods; Microbe; Microbial Biofilms; Minor; Modeling; Morphology; Movement; Mutation; Nutrient; Outcome; Pattern; Population; Population Density; Population Dynamics; Population Genetics; Population Growth; Population Heterogeneity; Population Process; Population Size and Growth; Process; Reaction; Research; Sampling; Science; Shapes; Stationary Populations; Structure; Technology; Testing; Theoretical model; Visit; Work; analytical method; biophysical model; climate change; cost; density; experience; falls; fighting; innovation; interest; mechanical drive; mechanical force; mechanical pressure; microbial colonization; microbiome; neglect; physical process; response; simulation; spatiotemporal; theories; tool; tumor

Project Summary / Abstract Population dynamics are central to many pressing problems in biomedicine. Whether we look at epidemics, microbiome, or cancer, we need to understand how populations grow, spread, and evolve. The outcome of these processes is largely controlled by ecological and genetic diversity of the population. Moreover, the patterns of diversity are often the only available cues about the factors that drive population dynamics. Although a lot of effort went into characterizing the diversity of stationary populations (both well-mixed and spatially structured) the understanding of evolutionary processes in growing populations is much more limited. Our recent work found that seemingly innocuous changes in the growth dynamics can fundamentally alter how populations evolve during spatial expansions. To understand such phenomena, we developed powerful theoretical tools, which lead to the discovery of hidden universality classes in the standard reaction-diffusion models of population genetics. Preliminary data strongly supports the hypothesis that each universality class has a unique structure of genealogies. Moreover, neutral evolution in some spatially expanding populations seems to produce genealogies identical to those in rapidly-adapting well-mixed populations, which suggests that some common signatures of selection need to be revisited. The first aim is to develop this theory further and test it in numerical simulations. The second aim is to examine how the universal behavior of genealogies is affected by common biophysical process, which are neglected in standard one-component reaction-diffusion models. Specifically, we will extend our theory of evolutionary dynamics to include the influence of mechanical pressure, nutrient diffusion, and movement in response to environmental gradients. The third aim is focused on establishing a connection between genetic diversity and growth instabilities that produce typical population morphologies. Taken together, these lines of research will lay the groundwork to interpret spatially-resolved genetic data and use it to predict and control the course of evolution. Such capabilities are essential for our fight against cancer, antibiotic resistance, and epidemics. The mathematical innovations developed in the course of this work should also be useful across a wide set of applications because reaction- diffusion models find numerous uses in chemistry, biology, and medicine.

项目概要/摘要 人口动态是生物医学中许多紧迫问题的核心。无论我们看 流行病、微生物组或癌症，我们需要了解人口如何增长、传播和传播 发展。这些过程的结果很大程度上受生态和遗传多样性控制 的人口。此外，多样性模式往往是关于多样性的唯一可用线索。 驱动人口动态的因素。尽管在描绘特征方面付出了很多努力 固定人口的多样性（充分混合和空间结构） 不断增长的人口的进化过程要有限得多。我们最近的工作发现 增长动态中看似无害的变化可以从根本上改变人口的生活方式 在空间扩张过程中演化。为了理解这些现象，我们开发了强大的 理论工具，导致发现标准中隐藏的普遍性类 群体遗传学的反应扩散模型。初步数据有力地支持了 假设每个普遍性类别都有独特的谱系结构。此外，中立 一些空间扩张的种群的进化似乎产生了与 那些快速适应的混合人群，这表明一些共同的特征 的选择需要重新审视。第一个目标是进一步发展这一理论并在 数值模拟。第二个目的是研究家谱的普遍行为如何 受到常见生物物理过程的影响，在标准单组分中被忽略 反应扩散模型。具体来说，我们将把进化动力学理论扩展到 包括机械压力、养分扩散和响应运动的影响 环境梯度。第三个目标是建立遗传之间的联系 产生典型种群形态的多样性和生长不稳定性。综合起来， 这些研究方向将为解释空间分辨的遗传数据和使用奠定基础 它可以预测和控制进化过程。这些能力对于我们的抗击疫情至关重要 癌症、抗生素耐药性和流行病。数学创新发展于 这项工作的过程也应该在广泛的应用中有用，因为反应- 扩散模型在化学、生物学和医学领域有着广泛的用途。

项目成果

A mechanistic statistical approach to infer invasion characteristics of human-dispersed species with complex life cycle.

一种推断具有复杂生命周期的人类分散物种入侵特征的机械统计方法。

• 发表时间: 2024-02-12
• 作者: Goel, Nikunj;Liebhold, Andrew M;Bertelsmeier, Cleo;Hooten, Mevin B;Korolev, Kirill S;Keitt, Timothy H
• 通讯作者: Keitt, Timothy H