From pattern to function: eco-evolutionary representations of complex spatial structure for the new era of spatial biology

从模式到功能：空间生物学新时代复杂空间结构的生态进化表征

• 批准号: 10501428
• 负责人: Oana Carja
• 金额: $ 38.05万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-27 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10501428
• 关键词: Architecture; Area; Biology; Cations; Complex; Computer Interface; Computer Vision Systems; Data Set; Demographic Survey; Disease; Evolution; Genetic Models; Image; Imaging Techniques; Industrialization; Link; Mathematics; Medical; Modeling; Modernization; Molecular; Molecular Biology; Mutation; Organoids; Outcome; Pathogenicity; Pattern; Population; Population Genetics; Process; Property; Research; Role; Screening procedure; Shapes; Structure; System; Technology; Time; Variant; biological systems; cell community; complex data; data streams; design; high resolution imaging; innovation; interest; migration; programs; protein complex; theories

Through innovations in both imaging techniques and the ability to process these images at scale, high- resolution imaging is transforming the eld of molecular biology, yet its power has yet to be fully utilized for asking questions in evolutionary biology. Just as demographic surveys can reveal more or less densely populated areas where, for example, a contagious disease may spread at di erent rates, these imaging datasets can help us quantify cellular and molecular patterns of spatial variation and understand how this variation a ects rates of evolution, by impeding or accelerating the spread of new variants through the population. My research program, at the interface of computer vision and evolutionary biology, is exploring how molecular and cellular communities spatially organize, and how the resulting spatial topologies can be generated, stably maintained and further shape the outcome of the evolutionary process. What are spatial topologies that act to amplify the selective advantage of new mutations in the pop- ulation, versus structures that dampen the force of selection and slow down rates of evolution? We build theoretical evolutionary models that explore how the rate of evolution is shaped by complex spatial struc- ture and nd the relevant spatial features for evolutionary ampli cation or selective suppression. We link these theoretical population genetic models to high-resolution imaging datasets and study the resulting spatial architectures. This allows us to go beyond simply describing patterns of cellular or molecular spatial variation, and enables exploration of the generative processes, as well as of the evolutionary trajectories of the system. Beyond the purely theoretical interest in these questions, understanding the role of spatial structure in shaping the mode and tempo of evolutionary dynamics is particularly timely because, by using modern microfuidics and organoid technologies, we can start building population structures that control the topol- ogy and migration patterns of a molecular or cellular population, amplifying the selective bene t of chosen mutations, boosting the ability to nd optimized protein complexes for medical or industrial applications, or as a screening tool for faster replicating pathogenic variants.

通过成像技术的创新和按大规模处理这些图像的能力，高 分辨率成像正在改变分子生物学的ELD，但其功率尚未得到充分利用 在进化生物学中提出问题。就像人口调查可以揭示或多或少密集 人口稠密的地区，例如，传染病可能以不同的速度传播，这些成像 数据集可以帮助我们量化空间变化的细胞和分子模式，并了解如何 通过阻碍或加速新变体通过该变化的变化速率 人口。我的研究计划，在计算机视觉和进化生物学的界面，正在探索 分子和细胞群落如何在空间上组织，以及产生的空间拓扑如何可以 可以生成，稳定维护并进一步塑造进化过程的结果。 哪些空间拓扑作用可以放大流行中新突变的选择性优势 Ulation，与结构减弱了选择力并减缓进化速率的结构？我们建造 理论进化模型探讨了如何通过复杂的空间结构来影响进化速率 TURE和ND相关的空间特征，用于进化扩展或选择性抑制。我们链接 这些理论种群遗传模型用于高分辨率成像数据集并研究了结果 空间体系结构。这使我们可以简单地描述细胞或分子空间的模式 变化，并可以探索生成过程，以及的进化轨迹 系统。 除了在这些问题上纯粹的理论兴趣之外，了解空间结构的作用 在塑造进化动力学的模式和速度时尤其及时，因为使用现代 微枢纽和器官技术，我们可以开始建立控制topol-的种群结构 分子或细胞种群的OGY和迁移模式，扩大了所选的选择性好处 突变，增强对医疗或工业应用优化蛋白质复合物的功能， 或作为更快复制病原变体的筛查工具。