18-BBSRC-NSF/BIO - Understanding the origin and evolution of metabolic interactions using synthetic microbial communities

微生物群落无处不在，是调节宿主健康和疾病以及生态系统中元素循环的关键角色。物种间的代谢相互作用影响群落功能和稳定性。然而，代谢相互作用的出现和演变知之甚少。在这个项目中，我们将利用易于处理的合成酵母菌群和数学建模，从实验和理论上研究代谢相互作用的起源和进化。我们将采取一种完全集成的合作方法，结合美国和英国在代谢建模，合成生物学和微生物生态学和进化方面的专业知识。首先，我们将使用统计热力学和微分方程来模拟代谢溢出。接下来，我们将通过实验表征代谢溢出以及使用靶向代谢组学，荧光显微镜和单细胞电化学测量的关键细胞参数。我们将使用这些实验结果来约束、测试和改进模型。然后，我们将把测试模型嵌入到计算机进化框架中来模拟进化，并预测初始群落条件（例如营养环境、基因型和初始物种相互作用）将如何影响新代谢相互作用的进化，正如我们在初步工作中所观察到的那样。最后，我们将通过在恒化器和恒浊器中从这些不同的起始条件进化合成酵母群落来测试模型预测，并表征新兴的代谢相互作用。

Microbial communities are ubiquitous, and are critical players in mediating host health and disease and in the cycling of elements in ecosystems. Metabolic interactions between species impact community function and stability. However, the emergence and evolution of metabolic interactions is poorly understood. In this project, we will take advantage of tractable synthetic yeast communities and mathematical modelling to experimentally and theoretically study the origin and evolution of metabolic interactions.We will undertake a fully integrated, collaborative approach that combines the expertise of US and UK groups on metabolic modeling, synthetic biology, and microbial ecology and evolution. First, we will use statistical thermodynamics and differential equations to model metabolic overflows. Next, we will experimentally characterize metabolic overflows as well as key cellular parameters using targeted metabolomics, fluorescence microscopy, and single cell electrochemical measurements. We will use these experimental results to constrain, test, and refine the model. We will then embed the tested model within an in silico evolution framework to simulate evolution, and predict how initial community conditions (e.g. nutrient environment, genotypes, and initial species interactions) will affect the evolution of new metabolic interactions, as we have observed in preliminary work. Finally, we will test model predictions by evolving synthetic yeast communities from these different starting conditions in chemostats and turbidostats, and characterize emerging metabolic interactions.