Systems-level analysis of the metabolism and ecology of genetically intractable gut bacteria

项目摘要/摘要 尽管人类肠道微生物群在健康和疾病中具有根本重要性，但一个具有凝聚力的 对许多人类肠道细菌物种的核心代谢途径缺乏了解。这个 Lenta放线杆菌就是一个明显的例子：它非常流行，与菌血症和 自身免疫性疾病的发展，并能够不同程度地转化内源性和 异源生物化合物，但对其营养需求、代谢调节和生态学知之甚少 利基市场。该项目将在多个尺度上调查龙须草的代谢和生态特性。会的 使用实验和计算相结合的方法来评估这些跨品系的特性 和鹅膏科的物种，利用新的菌株分离和基因组资源。 初步实验建立了支持生长的已定义的最低限度的介质配方 Eggerthellaceae，并确定了关键的生长决定因素，包括意外的生长受益于醋酸盐。 中试代谢组学分析显示，在最低限度的培养香菇上下文特定的代谢和 产生与寄主相关的代谢物。该项目将首先量化生长、代谢产物通量和基因。 Eggerthellaceae菌株在最低营养环境中的表达。生成的数据资源将是 用于构建和分析这些分类群的计算基因组规模的代谢模型。其次，共同文化 对香菇菌株与其他肠道微生物分类群的研究将阐明它们之间的生态相互作用和可能的 代谢物交换。最后，从公开收集的新的鹅膏科基因组 将分析元基因组数据集，以评估基因组和代谢特征与宿主的关联 疾病、地理、年龄和微生物群组成。总体而言，这项工作将提供对 这一分支的代谢、生态和进化特性及其在人类健康和疾病中的作用。 此外，体外图谱、跨菌株比较分析和计算建模的集成 这里展示了一个扩展对新陈代谢的科学理解的概括性框架。 肠道微生物特征不佳。奖学金培训计划将包括以下方面的技能发展 实验生物学、研究指导和专业技能；由合作和成功的 一家顶级机构的微生物组研究社区。

Project Summary/Abstract Despite the fundamental importance of the human gut microbiome in health and disease, a cohesive understanding of the core metabolic pathways of many human gut bacterial species is lacking. The Actinobacterium Eggerthella lenta is a notable example: it is highly prevalent, associated with bacteremia and the development of autoimmune disease, and capable of diverse transformations of endogenous and xenobiotic compounds, yet little is known about its nutrient requirements, metabolic regulation, and ecological niche. This project will investigate metabolic and ecological properties of E. lenta across multiple scales. It will use a combination of experimental and computational approaches to evaluate these properties across strains and species in the family Eggerthellaceae, taking advantage of a new resource of strain isolates and genomes. Preliminary experiments established defined minimal media formulations that support the growth of Eggerthellaceae and identified key growth determinants, including an unexpected growth benefit from acetate. Pilot metabolomics analysis of E. lenta cultured in minimal media revealed context-specific metabolism and production of host-relevant metabolites. This project will first quantify growth, metabolite fluxes, and gene expression of Eggerthellaceae strains across minimal nutrient contexts. The resulting data resource will be used to construct and analyze computational genome-scale metabolic models of these taxa. Next, co-culture studies of E. lenta strains with other gut microbial taxa will elucidate their ecological interactions and possible metabolite exchanges. Lastly, newly available collections of Eggerthellaceae genomes assembled from public metagenomic datasets will be analyzed to evaluate associations of genomic and metabolic features with host disease, geography, age, and microbiome composition. Overall, this work will provide insights into the metabolic, ecological, and evolutionary properties of this clade and its role in human health and disease. Moreover, the integration of in vitro profiling, cross-strain comparative analyses, and computational modeling demonstrated here is a generalizable framework for expanding scientific understanding of the metabolism of poorly characterized gut microbes. The fellowship training program will include skill development in experimental biology, research mentoring, and professional skills; supported by a collaborative and successful microbiome research community at a top-ranked institution.