Predicting the assembly and function of microbial consortia: a systems biology approach

预测微生物群落的组装和功能：系统生物学方法

• 批准号: 9797021
• 负责人: Alvaro Sanchez De Andres
• 金额: $ 41.84万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9797021
• 关键词: Address; Affect; Agriculture; Animals; Biochemical Pathway; Biotechnology; Carbon; Communities; Complex; Computer Simulation; Environment; Faculty; Family; Five-Year Plans; Future; Genomics; Goals; Health; Human; Industry; Laboratories; Maps; Mathematics; Metabolic; Metabolism; Methods; Microbe; Mission; Modeling; Molecular; Monitor; Nutrient; Pattern; Planet Earth; Positioning Attribute; Postdoctoral Fellow; Process; Research; Resources; Source; Structure; Surface; System; Systems Biology; Taxonomy; Work; design; experimental study; genome-wide; insight; microbial; microbial community; microbiota; novel; predictive modeling; programs; self assembly; tenure track; theories; virtual

Project Summary/Abstract Mission and background: I am a systems biologist, and my research program is focused on building predictive quantitative models of microbial community assembly. Microbes inhabit virtually every surface on earth, and they are rarely found alone. Rather, they form complex ecological communities whose composition and collective metabolism has profound implications for biogeochemical cycles, human and animal health, agriculture, and industry. The ultimate goal of my research is to develop a quantitative, predictive understanding of how microbial communities form and how they respond to external and environmental drivers. Our research will reveal rational strategies to design synthetic microbial consortia for biotechnology purposes, and will provide insights into how nutrient shifts and other ecological processes may be used to externally manipulate the composition and function of natural microbial communities. Overview of work in my laboratory: Our work combines computation, experiment, and ecological theory. Experimentally, we monitor the self-assembly of natural microbial communities in well-controlled and defined synthetic environments. The nutrient composition of these environments can be modulated at will, allowing us to quantitatively map the shifts this induces on the taxonomic structure and function of microbial communities. Our results are compared with the predictions of ecological theory, which we have adapted for microbial communities. Finally we use genome-wide computational metabolic models that take the metabolic networks from each species as inputs and predict community metabolism and dynamics. We have been able to show that community assembly follows predictable patterns at the family and functional levels in synthetic environments. These can be understood and interpreted from first metabolic principles, and are consistent with the predictions of ecological theory. Future directions: Over the next five years, we plan to ask how environmental resources quantitatively affect the composition and function of microbial communities. Can we predict community assembly on novel metabolic environments? Can we predict quantitative patterns of carbon source utilization from genomic information? How prevalent are high-order interactions, facilitation, and non-transitive competition in structuring the spontaneous assembly of microbial communities? The computational and experimental methods and systems that I have developed over the past five year as an independent postdoc at Harvard and a tenure track faculty at Yale, uniquely position my lab to address these questions. Our findings will represent a milestone towards developing quantitative, predictive models of microbial community assembly.

项目总结/摘要 使命和背景：我是一名系统生物学家，我的研究项目集中在建立 微生物群落组装的预测定量模型。微生物几乎栖息在每一个表面上 地球，他们很少单独发现。相反，它们形成了复杂的生态群落， 组成和集体代谢对地球化学循环，人类和 动物健康、农业和工业。我研究的最终目标是建立一个定量的， 预测了解微生物群落如何形成，以及它们如何对外部和 环境驱动力。我们的研究将揭示合理的策略，设计合成的微生物财团， 生物技术的目的，并将提供深入了解如何养分转移和其他生态过程 可用于外部操纵天然微生物群落的组成和功能。 在我的实验室工作概述：我们的工作结合了计算，实验和生态理论。 在实验上，我们监测自然微生物群落的自组装， 定义合成环境。这些环境的营养成分可以随意调节， 这使我们能够定量地绘制这一变化对微生物分类结构和功能的影响， 社区.我们的结果与生态理论的预测进行了比较，我们已经适应了 微生物群落最后，我们使用全基因组计算代谢模型， 从每个物种的代谢网络作为输入，并预测社区代谢和动态。我们 我已经能够证明，社区大会遵循可预测的模式，在家庭和功能 在合成环境中。这些可以从第一代谢原理来理解和解释， 与生态学理论的预测相一致。 未来的方向：在未来五年，我们计划问环境资源如何量化 影响微生物群落的组成和功能。我们能预测小说中的社区集会吗 代谢环境？我们能否从基因组中预测碳源利用的定量模式 信息？在人类社会中，高阶相互作用、促进作用和非传递竞争有多普遍 构建微生物群落的自发集合计算和实验 我在过去五年里作为哈佛的独立博士后开发的方法和系统 以及耶鲁大学的终身教职，使我的实验室能够解决这些问题。我们的发现将 代表了开发微生物群落组装的定量预测模型的里程碑。