Mapping and predicting metabolic fluxes between the ileal microbiome and host

绘制和预测回肠微生物组和宿主之间的代谢通量

• 批准号: 8791700
• 负责人: Jason Papin
• 金额: $ 34.8万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-15 至 2017-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8791700
• 关键词: Accounting; Acute Disease; Address; Antibiotics; Autistic Disorder; Bacteria; Bacteriophages; Biochemical Pathway; Biology; Biomass; Buffers; Cardiovascular Diseases; Chronic Disease; Clostridium difficile; Communities; Complex; Computer Simulation; Coupled; Crohn' s disease; Data; Development; Disease; Gene Expression Profile; Growth; Health; Human; In Vitro; Individual; Infection; Intestines; Lead; Link; Longitudinal Studies; Maps; Measures; Mediating; Metabolic; Metabolic Pathway; Metabolism; Metagenomics; Modeling; Mus; Nutrient; Nutritional; Obesity; Pathway interactions; Physiology; Probiotics; Reaction; Recovery; Sampling; Serum; Systems Biology; Testing; Therapeutic; Urine; Variant; human disease; in vivo; killings; member; microbial; microbial community; microbiome; network models; novel; programs; transcriptomics

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.

描述(由申请人提供)：肠道微生物群和人类疾病之间的关系得到了很好的理解，但了解得很少。肠道微生物群落动态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。据推测，TOTO中的营养交换是高度复杂和相互关联的；因此，功能途径和回路的特征仍然很差。这一拟议计划的主要假设是，尽管单个微生物组存在差异，但微生物组和宿主之间的营养流动相对稳定；尽管存在这种稳定性，但存在推动微生物组和宿主之间关键代谢反应的中心微生物物种，当受到干扰时，这些微生物物种会导致疾病。凭借我们在元基因组学、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，我们将以以下具体目标解决这一中心假设：(1)直接根据元转录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，直接从元转录数据重建微生物群落个体成员的代谢网络。我们将用来自改变的Schaedler菌群的体外合成微生物群落来验证这一方法；(2)表征回肠微生物组和宿主代谢组之间的体内相关性。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)和耦合样本的回肠微生物组。我们还将对相关微生物群的元转录体进行测序。回肠微生物组和宿主代谢组之间的这些映射将在抗生素介导的扰动和随后的恢复的纵向研究中描绘；以及(3)预测和验证肠道微生物组中稳定的微生物物种，这解释了宿主代谢组的稳健性，并描述了相应的代谢功能。我们将预测缓冲代谢组免受微生物组变化影响的关键物种，因此，当微生物组被破坏时，对代谢组的变化具有最显著的影响。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的生态位。我们将通过噬菌体疗法选择性地杀死目标物种来验证这些预测，并按照计算模型和抗生素介导的扰动和恢复研究的结果操纵代谢组。这项拟议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中的基本问题。了解微生物组组成和宿主代谢之间的关系将是发展益生菌、营养和其他治疗策略的关键。