Metabolic trade-offs and regulatory changes as drivers of metabolic cross-feeding interactions in simple microbial communities

微生物存在于复杂的、相互依存的生态群落中。这些组合的一个突出特征是群落成员之间必需代谢物的相互交换，这已被证明是决定特定微生物群落结构、功能和进化的关键。在许多情况下，这些代谢相互作用是强制性的，事实证明，营养不良基因型不能自主产生某些必需的代谢物，在这些社区中普遍存在。先前的研究表明，营养不良基因型在与其他基因型相互交叉喂养时可以获得显著的生长优势。然而，这种效应的生化和系统层面的基础仍然完全不清楚。为了在更广泛的范围内理解这种代谢分工，我们将比较分析一个原核生物（细菌）和一个真核微生物系统（酵母）。通过将系统级方法与数学模型相结合，我们建议定量确定引起氨基酸营养不良的突变如何影响细胞资源的分配，从而潜在地影响其他氨基酸或代谢物的生产水平。此外，我们将在这些系统中建立代谢权衡的存在，并从理论上和实验上测试通过代谢交叉喂养打破这些权衡是否为相互作用菌株相对于自主基因型提供了生长优势。这项工作将为推动微生物群落分工的生化和代谢因素提供基本的见解。迫切需要对控制群落组装和功能的规则进行定量理解，以便合理设计用于医疗或生物技术应用的微生物群落。

Microorganisms exist in complex, interdependent ecological communities. A prominent feature of these assemblages is the reciprocal exchange of essential metabolites between community members that has been shown to be key for determining the structure, function, and evolution of a given microbial community. In many cases, these metabolic interactions are obligate as evidenced by the fact that auxotrophic genotypes, which are unable to autonomously produce certain essential metabolites, are prevalent in such communities. Previous work has shown that auxotrophic genotypes can gain significant growth advantages when engaging in a reciprocal cross-feeding interaction with other genotypes. However, the biochemical and systems-level underpinnings of this effect remain completely unclear. To understand this metabolic division of labor on a broader scale, we will comparatively analyze a prokaryotic (bacteria) and a eukaryotic microbial system (yeast). By integrating systems-level approaches with mathematical models, we propose to quantitatively determine how an amino acid auxotrophy-causing mutation affects the allocation of cellular resources and thus, potentially, also the production levels of other amino acids or metabolites. In addition, we will establish the existence of metabolic trade-offs in these systems, and both theoretically and experimentally test whether the breaking of these trade-offs by metabolic cross-feeding provides growth advantages to interacting strains relative to autonomous genotypes. This work will provide fundamental insights into the biochemical and metabolic factors driving division of labor in microbial communities. Such a quantitative understanding of the rules governing community assembly and function is urgently required to rationally design microbial consortia for medical or biotechnological applications.