Genome-based Modeling and Design of Microbial Communities

基于基因组的微生物群落建模和设计

• 批准号: RGPIN-2017-06755
• 负责人: Mahadevan, Radhakrishnan
• 金额: $ 2.7万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=637964
• 关键词: Genome; based; Modeling; Design; Microbial

Metabolism is the source of energy required for powering cellular processes in all living things. Understanding metabolism in an integrated way allows the opportunity to harness the power of natural metabolic networks for several applications including the manufacture of renewable fuels and non-natural chemicals, clean-up of contaminated groundwater, and potentially for maintaining a healthy gut microbiome through nutritional and probiotic interventions. However, there are several challenges in engineering metabolism for these practical applications. A key limitation is the ability to quantitatively describe the dynamics of metabolic transience within the cells and the metabolic interactions with other species in microbial communities. Advances in genome sequencing and omics methods have enabled the unprecedented characterization of cellular metabolism and have paved the way for developing genome-scale metabolic models. While such genome-scale modeling methods have been extensively applied to studying metabolism in industrially relevant microbes such as Escherichia coli, there are relatively few models of bacteria relevant to gut microbiome and even fewer models of microbial communities. Hence, one of the longer term objectives of our research is to develop integrated models of human metabolism and genome-scale models of microbes relevant to the gut. Specifically, in the shorter term, we will focus on developing models of the microbes present in gut microbiome and common probiotics and integrate them into a community model in order to simulate the dynamics of community in response to dietary changes.The successful completion of the proposal will enable the development of novel tools for modeling and engineering metabolism in individual cells and communities and lead to 1) robust microbial communities for non-natural chemical production and 2) potential nutritional strategies for maintaining a healthy gut microbiome. Further, the computational and experimental tools developed will provide the foundations for improved understanding and engineering of metabolism in complex environments and will drive the application to other significant problems including bioconversion of CO2 to value-added chemicals, bioremediation and personalized nutrition and medicine.The ultimate objective is the application of these tools for the development of commercializable bioprocess for the manufacture of non-natural chemicals and model-based design for personalized nutrition and medicine.

新陈代谢是所有生物中为细胞过程提供动力所需的能量来源。以综合的方式了解代谢，可以有机会利用天然代谢网络的力量进行多种应用，包括制造可再生燃料和非天然化学品，清理受污染的地下水，并可能通过营养和益生菌干预来维持健康的肠道微生物组。然而，在这些实际应用的工程代谢中存在几个挑战。一个关键的限制是定量描述细胞内代谢瞬态的动态以及与微生物群落中其他物种的代谢相互作用的能力。基因组测序和组学方法的进步使细胞代谢的前所未有的表征成为可能，并为开发基因组规模的代谢模型铺平了道路。虽然这种基因组规模的建模方法已被广泛应用于研究工业相关微生物如大肠杆菌的代谢，但与肠道微生物组相关的细菌模型相对较少，微生物群落模型甚至更少。因此，我们研究的长期目标之一是开发人体代谢的综合模型和与肠道相关的微生物的基因组规模模型。具体来说，从短期来看，我们将专注于开发肠道微生物组和常见益生菌中存在的微生物模型，并将其整合到群落模型中，以模拟群落对饮食变化的动态响应。该提案的成功完成将有助于开发用于单个细胞和群落中建模和工程代谢的新工具，并导致1）用于非天然化学品生产的强大微生物群落和2）用于维持健康肠道微生物组的潜在营养策略。 此外，开发的计算和实验工具将为改善复杂环境中代谢的理解和工程提供基础，并将推动应用于其他重要问题，包括将CO2生物转化为增值化学品，生物修复和个性化的营养和药物。最终目标是应用这些工具开发商业化的生物工艺，用于生产非生物制品。天然化学品和基于模型的个性化营养和药物设计。