ExoMod: Design of a targeted microbiome exometabolome modulation approach for the rational design of microbiome-based therapies for metabolic disease

微生物组作为宿主健康和疾病的重要调节剂越来越受到关注。虽然已经确定了微生物组组成变化与2型糖尿病（T2 D）疾病过程之间的大量联系，但将这些发现转化为治疗方法的关键限制是缺乏靶向调节微生物组-宿主相互作用的方法。虽然纤维或益生菌的营养补充对微生物组组成有影响，但这不允许对单个微生物物种或功能进行靶向调节。类似地，粪便微生物群移植转移了整个微生物群落，从而不仅转移了所需的性状。该项目的目的是通过开发一种结合实验-理论的工作流程来设计微生物群靶向调节代谢产物产生的方法，从而克服建立基于微生物群的疗法的局限性。为此，我们将重点关注微生物群产生的核苷酸，我们和其他人的先前研究表明，微生物群在代谢疾病的发病机制中起着重要作用。在我们的工作中，我们将首先关注SIHUMix，这是一个最小的微生物组模型社区，我们将在迭代的理论-实验工作流程中从大量实验数据中重建准确的计算机模型。使用这种计算机模型，我们将提出可以通过微生物群促进核苷酸生产的代谢物组，这些代谢物组将通过实验进行测试。与此同时，我们将建立T2 D患者微生物群落的体外和计算机模型，作为代谢性疾病的特定病例，我们将研究微生物核苷酸生产能力的变化。这些社区将用于进一步验证所制定的干预办法。因此，该项目旨在为靶向微生物组疗法的发展铺平道路，作为治疗T2 D和其他微生物组驱动疾病的新治疗选择。

The microbiome is increasingly receiving attention as an important modulator of host health and disease. While a considerable number of links between changes in microbiome composition and disease processes in Type 2 Diabetes (T2D) have been identified, a key limitation in the translation of these findings into therapies is a lack of approaches for the targeted modulation of microbiome-host interactions. While the nutritional supplementation with fibers or probiotics has an effect on microbiome composition, this does not allow for a targeted modulation of individual microbial species or functions. Similarly, fecal microbiota transplants transfer entire microbial communities and thereby not only desired traits. The aim of this project is to overcome this limitation in the establishment of microbiome-based therapies by developing a combined experimental-theoretical workflow for the design of approaches for targeted modulation of metabolite production by the microbiota. For this purpose, we will focus on the production of nucleotides by the microbiota for which prior research by us and others indicates an important role in the pathogenesis of metabolic diseases. In our work, we will start with focusing on SIHUMIx, a minimal microbiome model community for which we will reconstruct accurate in silico models from a large array of experimental data in an iterative theoretical-experimental workflow. Using this in silico model, we will propose metabolite sets that can boost nucleotide production by the microbiota which will be tested experimentally. In parallel, we will establish in vitro as well as in silico models of the microbial communities T2D patients as a specific case of metabolic disease for which we will investigate changes in the microbial nucleotide production capacity. These communities will be used for further validation of the developed intervention approaches. Thus, this project aims to pave the way toward the development of targeted microbiome therapies as a novel therapeutic option in the treatment of T2D and other microbiome-driven diseases.