Mapping and predicting metabolic fluxes between the ileal microbiome and host

描述（由申请人提供）：肠道微生物群与人类疾病之间的关系得到了很好的认识，但知之甚少。肠道微生物群落动力学的核心是营养物质如何在群落成员之间以及群落与宿主之间流动。存在一种假设，即营养交换总体上是高度复杂和相互关联的；因此，功能通路和电路的特征仍然很差。该计划的主要假设是，尽管微生物组存在个体差异，但微生物组与宿主之间的营养流动相对稳定；尽管有这样的稳定性，但仍存在一些核心微生物物种，它们驱动微生物群和宿主之间的关键代谢反应，并在被破坏时导致疾病。凭借我们在宏基因组学、代谢组学、计算建模和肠道微生物组生物学方面的互补专业知识，我们将通过以下具体目标来解决这一中心假设：(1)直接从元转录组测序数据重建和验证体外合成微生物群落的代谢网络。我们开发了一种新的系统生物学方法，直接从元转录组学数据重建微生物群落个体成员的代谢网络。我们将通过从改变的Schaedler菌群中提取的体外合成微生物群落来验证这种方法；(2)表征回肠微生物组与宿主代谢组的体内相关性。我们将在改变微生物群落（广谱和窄谱抗生素）的条件下表征宿主（小鼠）代谢组（来自尿液、血清和回肠腔）和耦合样品的回肠微生物组。我们还将对相关微生物组的元转录组进行测序。回肠微生物组和宿主代谢组之间的这些映射将通过抗生素介导的扰动和随后的恢复的纵向研究来描述；(3)预测和验证肠道微生物组中稳定的微生物物种，这些微生物物种解释了宿主代谢组的稳健性，并描述了相应的代谢功能。我们将预测在微生物组变化中缓冲代谢组的关键物种，因此，当被破坏时，对代谢组的变化有最显著的影响。我们将描述微生物组中使宿主代谢组稳定的关键代谢途径生态位。我们将根据计算模型和抗生素介导的扰动和恢复研究的结果，通过噬菌体疗法选择性地杀死目标物种来操纵代谢组，从而验证这些预测。该计划的实施将解决宿主和微生物群之间复杂的营养流动动力学的基本问题。了解微生物组组成与宿主代谢之间的关系将是开发益生菌、营养和其他治疗策略的关键。

DESCRIPTION (provided by applicant): The relationship between the gut microbiome and human disease is well appreciated but poorly understood. Central to gut microbial community dynamics is how nutrients flow between community members as well as between the community and its host. A presumption exists that nutrient exchange in toto is highly complex and interconnected; as such, functional pathways and circuits remain poorly characterized. The main hypothesis for this proposed program is that nutrient flow between the microbiome and the host is relatively stable despite individual microbiome variation; notwithstanding such stability, there exist central microbial species that drive key metabolic reactions between microbiome and host and that lead to disease when disrupted. With our complementary expertise in metagenomics, metabonomics, computational modeling, and gut microbiome biology, we will address this central hypothesis with the following specific aims: (1) Reconstruct and validate metabolic networks of in vitro synthetic microbial communities directly from meta-transcriptomic sequencing data. We have developed a novel systems biology approach to reconstruct the metabolic networks of individual members of a microbial community directly from meta-transcriptomic data. We will validate this approach with in vitro synthetic microbial communities derived from the altered Schaedler flora; (2) Characterize the in vivo correlation between the ileal microbiome and host metabonome. We will characterize the host (mouse) metabonome (from urine, serum, and ileal lumen) and the ileal microbiome of coupled samples under conditions that alter the microbial community (broad- and narrow-spectrum antibiotics). We will also sequence the meta-transcriptomes of the associated microbiomes. These mappings between the ileal microbiome and host metabonome will be delineated over a longitudinal study with antibiotic-mediated perturbation and subsequent recovery; and (3) Predict and validate stabilizing microbial species within the gut microbiome that account for robustness of the host metabonome and describe corresponding metabolic functionalities. We will predict the keystone species that buffer the metabonome from changes in the microbiome and thus, when disrupted, have the most significant impact on variation in the metabonome. We will characterize the key metabolic pathway niches in the microbiome that enable stability of the host metabonome. We will validate these predictions by selectively killing target species via bacteriophage therapies t manipulate the metabonome as directed by results from the computational modeling and antibiotic-mediated perturbation and recovery studies. The implementation of this proposed program will address fundamental questions in the complex nutrient flow dynamics between host and microbiome. An understanding of the relationship between microbiome composition and host metabolism will be key to the development of probiotic, nutritional, and other therapeutic strategies.