The Role of Syntrophic Bacteria in Methanogenic Metabolism in the Human Gut

合养细菌在人类肠道产甲烷代谢中的作用

• 批准号: 8029419
• 负责人: Catherine Lozupone
• 金额: $ 15.11万
• 依托单位: UNIVERSITY OF COLORADO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-02-01 至 2015-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8029419
• 关键词: Acetates; Affect; Alcohols; Archaea; Area; Automobile Driving; Bacteria; Biochemical Pathway; Bioinformatics; Biological; Biology; Bioreactors; Calories; Carbon Dioxide; Cells; Collection; Colorado; Communities; Complex; Computational Technique; Data; Diet; Disease; Doctor of Philosophy; Environment; Environmental sludge; Feces; Fermentation; Flow Cytometry; Fluorescent in Situ Hybridization; Food; Formates; Generations; Genes; Genome; Genomics; Gnotobiotic; Goals; Grant; Growth; Harvest; Health; High Performance Computing; Human; Human Genome; Human Microbiome; Hydrogen; Individual; Individual Differences; Knowledge; Laboratories; Lead; Link; Longitudinal Studies; Malnutrition; Mentors; Metabolic; Metabolism; Metagenomics; Methanobacteria; Methanobrevibacter; Microbe; Microscopic; Modeling; Mus; Nature; Nutrient; Nutritional Requirements; Obesity; Organism; Pattern; Plants; Polysaccharides; Population; Positioning Attribute; Postdoctoral Fellow; Prevalence; Process; Property; RNA, Ribosomal, 16S; Reaction; Recording of previous events; Relative (related person); Research; Ribosomal RNA; Role; Sampling; Science; Sequence Analysis; Shotgun Sequencing; Shotguns; Soil; Structure; Students; Surveys; Taxon; Techniques; Testing; Training; Universities; Volatile Fatty Acids; Washington; Work; analog; base; combat; computer science; computerized tools; database design; design; experience; genome sequencing; gut microbiota; human data; human subject; insight; interest; member; metagenomic sequencing; microbial; microbial community; microbiome; microorganism; microorganism interaction; mouse model; network models; nutrition; preference; prevent; reconstruction; research study; skills; trait

DESCRIPTION (provided by applicant): The human gut harbors 10-100 trillion microorganisms that enable the harvest of nutrients/energy from otherwise undigestible components of our diet (e.g. complex plant polysaccharides). Syntrophic (cooperative) metabolism, where one microbe produces compounds that the other requires for growth or removes compounds that inhibit the progress of metabolic reactions, has a high impact on the efficiency at which our microbes extract calories from our food. Knowledge of how different human gut bacteria fit within the cascade of metabolic interactions of the anaerobic degradation process will help to relate community composition information to the function and efficiency of the gut bioreactor. The goal of this work is to use both metagenomic (16S ribosomal RNA or shotgun) sequences from human stool samples and genome sequences from cultured gut isolates to predict microbial interactions that can be further explored/verified with laboratory experiments. This work focuses on interactions between bacteria and Methanobrevibacter smithii, the most prominent archaeal methanogen in the human gut. Methanogenic archaea were chosen because 1) they can increase the efficiency of bacterial fermentation by preventing the accumulation of metabolic products such as hydrogen 2) they are thought to be a "keystone" species, (i.e. have a higher influence on community composition and function than their prevalence would suggest) and 3) they closely associate with specific syntrophic bacteria in other environments such as sludge digestors, but whether there is an analog in the gut is not known. The goal of Specific Aim 1 is to use metagenomic sequence data from human stool samples to identify species (phylotypes) and genes whose prevalence are correlated with the presence/absence of M. smithii. The preliminary analysis of 191 samples that were collected through an ongoing longitudinal study of the effects of obesity on the gut microbiota, has identified 27 bacterial phylotypes, representing at least 3 deep bacterial lineages that appear to have conserved the traits that lead to co-occurrence with M. smithii. Specific Aims 2 and 3 pursue a combination of laboratory and computational techniques to determine whether the co- occurrence between these bacteria and M. smithii is driven by syntrophy or by shared environmental preferences. Some of the co-occurring phylotypes are from uncultured lineages whose biological properties are completely unknown. Specific Aim 2 will yield information on these uncultured lineages and determine whether co-occurrence was driven by syntrophy by 1) microscopic determination of whether they form structured complexes with M. smithii using Fluorescence In Situ Hybridization (FISH) and 2) metagenomic sequencing of cell populations that were concentrated using flow cytometry. Specific Aim 3 further explores the underlying cause of co-occurrence patterns by developing and applying metabolic reconstruction-based techniques to predict interactions between microbes, including syntrophy and metabolic niche convergence. Finally, I will use this combined information to design confirmatory experiments in gnotobiotic mice. This work will facilitate the use of the growing collection of human-gut derived sequences to understand whether and how particular microbes interact, and will provide insights as to how to promote or discourage the activity M. smithii in the gut. This proposal is a natural extension of my Ph.D. and post-doctoral studies of the human microbiome. The proposed research will further develop the skills needed to achieve my goal of developing an independent research group with both computational and laboratory components. The bioinformatics work integrates my experience with analysis of 16S rRNA and genomic sequence data from the human gut, and extends my expertise into new areas, such as metabolic network modeling. The laboratory component draws upon my experience in performing culture-independent analysis of microbes in soil, and extends my training in FISH and flow-cytometry, for the generation of genomic information from uncultured microbial lineages. Extended training in working with human subjects will also help me to continue to perform human microbiome research. My current position as a post-doc with Dr. Rob Knight at the University of Colorado at Boulder, and the co-mentoring that I receive from Dr. Jeff Gordon from the Center for Genome Sciences at Washington University provide an excellent environment in which to reach these goals. The Knight lab is on the forefront of generating the computational tools required to utilize advances in high-throughput sequencing for the analysis of microbial communities, and is an environment where I can interact with a diverse collection of students, post-docs, and collaborators including individuals with backgrounds in biology (with computational and/or laboratory expertise), computer science (including high performance computing and database design), and applied math. The Gordon lab performs ground-breaking research on the association of the gut microbial community with diseases of nutrition (obesity and malnutrition) and the application of gnotobiotic mouse models to understanding microbial interactions in the gut. They produce massive amounts of sequence information from human gut samples that is central to the work proposed in this grant.

描述（由申请人提供）：人类肠道有10-100万亿微生物，可从我们饮食的原本无法消化的成分（例如，复杂的植物多糖）中收获营养/能量。综合症（合作）代谢，其中一种微生物会产生另一种需要生长或去除抑制代谢反应进展的化合物的化合物，对我们的微生物从食物中提取卡路里的卡路里的效率产生了很大的影响。了解人类肠道细菌如何适应厌氧降解过程的代谢相互作用级联反应的知识将有助于将社区组成信息与肠道生物反应器的功能和效率联系起来。 这项工作的目的是使用人的粪便样品中的元基因组（16S核糖体RNA或shot弹枪）序列，以及来自培养的肠分离株的基因组序列来预测可以通过实验室实验进一步探索/验证的微生物相互作用。这项工作的重点是细菌与甲烷摩托杆菌史密斯（Smithii）之间的相互作用，这是人类肠道中最突出的古细菌甲烷原。之所以选择甲烷古老的古细菌，是因为1）可以通过防止氢的代谢产物的积累来提高细菌发酵的效率2）它们被认为是一种“基石”物种（即对社区成分和功能具有更高的影响，而不是其流行程度更高，而与特定的疾病中的环境紧密相关，但它们是否与其他环境紧密相结合，是否与其他环境相关联，是否却在其他环境中与其他环境紧密相关。不知道。 特定目的1的目的是使用来自人粪样品的宏基因组序列数据鉴定物种（系统型）和患病率与Smithii的存在/不存在相关的基因。通过对肥胖对肠道微生物群的影响进行的持续纵向研究收集的191个样品的初步分析，已经鉴定出27种细菌系统型，这些细菌型至少代表了至少3个深细菌谱系，这些谱系似乎保留了与Smithii M. smithii的共同发生的特征。具体目的2和3追求实验室和计算技术的组合，以确定这些细菌和史密斯菌之间的共同发生是由综合症还是由共同的环境偏好驱动的。某些共发生的系统型来自未养殖的谱系，其生物学特性是完全未知的。具体目标2将对这些未养殖的谱系产生信息，并确定是否使用荧光原位杂交（FISH）和2）使用流式细胞术浓缩的细胞群的荧光原位杂交（FISH）和2）荧光原位杂交（FISH）来确定它们是否与Smithii形成结构化复合物。特定目标3通过开发和应用基于代谢重建的技术来预测微生物之间的相互作用，包括综合体和代谢细分市场的融合，进一步探讨了共发生模式的根本原因。最后，我将使用这些组合信息在gnotobiotic小鼠中设计验证性实验。这项工作将有助于使用不断增长的人脉衍生序列的收集，以了解微生物是否相互作用，并提供有关如何促进或劝阻肠道中史密斯的活动的见解。 该建议是我博士学位的自然扩展。和人类微生物组的博士后研究。拟议的研究将进一步发展我的目标，即我的目标是开发具有计算和实验室组件的独立研究小组。生物信息学的工作将我的经验与对人类肠道的16S rRNA和基因组序列数据的分析相结合，并将我的专业知识扩展到新领域，例如代谢网络建模。该实验室成分借鉴了我在土壤中对微生物进行培养独立分析的经验，并扩展了我在鱼类和流程术中的训练，以从未养殖的微生物谱系中产生基因组信息。与人类受试者合作的扩展培训还将帮助我继续进行人类的微生物组研究。 我目前与科罗拉多大学博尔德分校的罗布·奈特（Rob Knight）博士一起担任大约博士，以及我从华盛顿大学基因组科学中心从杰夫·戈登（Jeff Gordon）博士那里获得的董事，为实现这些目标提供了一个极好的环境。骑士实验室正处于生成在高通量测序中的进步所需的计算工具来分析微生物群落，并且是一个环境，是一个我可以与多种学生，后docs和包括具有生物学背景（计算和/或实验室专业化）的学生（包括计算机科学），计算机科学（包括计算机科学）（包括计算机科学）（包括高性能计算和数据）的环境进行互动。戈登实验室对肠道微生物群落与营养疾病（肥胖和营养不良）的关联进行了突破性的研究，并应用了金属生物小鼠模型来了解肠道中的微生物相互作用。它们从人类肠道样本中产生大量的序列信息，这是该赠款中提出的工作的核心。