Dietary and Microbial Reprogramming of Intestinal Microbiota-Produced Metabolites

描述（由申请人提供）：生活在人类肠道微生物群中的微生物具有新颖且不明确的代谢能力。这种微生物生态系统产生的许多代谢物被人体吸收，最终由肾脏排出。当肾衰竭时，这些溶质积累，并且包括在维持透析的患者的血浆中以非常高的水平发现的“尿毒症”溶质的显著部分。对甲酚硫酸盐（PCS）、吲哚酚硫酸盐（IS）和三甲基胺-N-氧化物（TMAO）是三种主要的尿毒症溶质，其依赖于饮食衍生分子的微生物代谢。每一种都表现出产生的数量的个体间差异，表明微生物产生这些分子的能力不同。PCS和IS与肾脏患者的不良结局相关，TMAO与人类的心血管事件相关。这项研究的最终目标是了解如何调节人类肠道微生物群以减少这些化合物的产生。主要目的是阐明（i）微生物基因和物种是PCS，IS和TMAO生产的关键贡献者;（ii）饮食对这些溶质生产的影响;以及（iii）通过施用其他肠道衍生物种将高产微生物群重新编程为低产表型的最佳方法。在Aim 1中，一种新的机器学习软件Aimterraf将用于查询约900个测序的肠道微生物群基因组，以预测有助于PCS，IS或TMAO生成的基因和基因盒。预测将在纯培养和体内验证，使用单一和多个物种定殖的gnotobiotic小鼠模型。基因预测将使用基因缺失或异源表达进行遗传学验证。在目标2中，将鉴定具有稳定的高和低尿TMAO、PCS和IS产生的健康杂食性人。将通过使用基于16 S rRNA的微生物群计数、宏基因组学和元转录组学分析这些个体的粪便样本来确定与溶质产生表型相关的微生物群编码基因和分类群。目标3将使用目标1中验证的细菌聚生体定殖的无菌小鼠和人源化小鼠模型来解决饮食是否影响TMAO、PCS或IS的产生，所述人源化小鼠模型由目标2中鉴定的TMAO、PCS或IS的高产和低产的人粪便微生物群定殖的无菌小鼠组成。饮食将包括高纤维与低纤维，高蛋白与低蛋白，或左旋肉碱补充与素食。TMAO、PCS和/或IS产生的减少将与微生物群组成和功能的变化相关。目的4将鉴定用于人源化小鼠中微生物群重编程的最有效方法，以使用完整微生物群、供体微生物群产生的培养物收集物或典型菌株代表的移植物来减少TMAO、PCS和IS产生。移植前抗生素的使用和饮食强化的影响将作为帮助微生物群重新编程的方法进行测试。

DESCRIPTION (provided by applicant): The microbes that live in the human gut microbiota possess novel and ill-defined metabolic capabilities. Many of the metabolites produced by this microbial ecosystem are absorbed by the human host and ultimately excreted by the kidneys. Such solutes accumulate when the kidneys fail and comprise a significant portion of the "uremic" solutes found at very high level in the plasma of patients maintained on dialysis. p-cresol sulfate (PCS), indoxyl sulfate (IS), and trimethylamine-N-oxide (TMAO) are three prominent uremic solutes that depend upon microbial metabolism of diet-derived molecules. Each exhibits inter-individual variability in the quantities produced, suggesting that microbiotas differ in their ability to produce these molecules. PCS and IS have been associated with poor outcomes in renal patients and TMAO has been linked to cardiovascular events in humans. The ultimate goal of this research is to understand how the human gut microbiota may be modulated to decrease the production of these compounds. The main objectives are to elucidate (i) the microbial genes and species that are the key contributors to PCS, IS, and TMAO production; (ii) the impact of diet on the production of these solutes; and (iii) the best method for reprogramming a high-producing microbiota to a low-producing phenotype via administration of other gut-derived species. In Aim 1 a new machine learning software, ClusterFinder, will be used to query ~900 sequenced gut microbiota genomes to predict genes and gene cassettes that contribute to PCS, IS, or TMAO generation. Predictions will be validated in pure culture and in vivo, using a gnotobiotic mouse model in single and multiple species colonizations. Gene predictions will be genetically validated using gene deletion or heterologous expression. In Aim 2 healthy omnivorous humans with stable high and low urinary TMAO, PCS and IS production will be identified. Microbiome-encoded genes and taxa associated with solute production phenotypes will be determined by analyzing stool samples for these individuals using 16S rRNA-based microbiota enumerations, metagenomics, and metatranscriptomics. Aim 3 will address whether diet affects the production of TMAO, PCS, or IS using either gnotobiotic mice colonized with bacterial consortia validated in Aim 1, and a humanized mouse model, consisting of ex-germ-free mice colonized with the human fecal microbiota identified in Aim 2 of high- and low-producers of TMAO, PCS, or IS. Diets will include high vs. low fiber, high vs. low protein, or L-carnitine supplemented vs. vegetarian. Decreases in TMAO, PCS and/or IS production will be associated with changes in microbiota composition and function. Aim 4 will identify the most effective method for microbiota reprogramming in humanized mice to decrease TMAO, PCS and IS production using transplants of an intact microbiota, donor microbiota generated culture collections, or type strain representatives. The use of antibiotics before transplant and the influence of dietary reinforcement will be tested as methods of aiding microbiota reprogramming.