Metagenomic Analysis of the Structure and Function of the Human Gut Microbiota in

描述：炎症性肠病(IBD)，如克罗恩病，是一种慢性免疫调节疾病，具有严重的医学后果。目前的假设是，这些疾病是由于对共生肠道细菌亚群的过度侵略性免疫反应。迄今为止关于IBD的研究表明，这种疾病可能是由细菌和宿主易感性共同引起的；然而，这些疾病的病因仍然是一个谜。在这一应用中，我们建议通过阐明与疾病症状相关的特定生物标记物(细菌菌株、基因或蛋白质)来开发和展示在前所未有的分子水平上描述克罗恩病的能力。为了实现这一目标，我们将使用基于元基因组和元蛋白质组分子工具的多学科方法来阐明健康或表现出克罗恩病的同卵双胞胎的共生微生物群的组成(对于协和的，两个都是疾病的；对于不协调的，一个是健康的，一个是疾病的)。这一建议的中心假设是(1)与健康人相比，克罗恩病患者胃肠道(GI)微生物区系的特定成员和/或功能活动不同，(2)通过整合从基于16S rRNA的分子指纹、元基因组学和元蛋白质组学方法获得的数据，将有可能阐明与该疾病的发生和发展相关的微生物特征。为了解决这些假设，提出了五个具体目标：1)获得关于健康双胞胎和克罗恩病双胞胎子集的社区基因含量(元基因组)的数据，以评估与CD相关的肠道微生物区系的潜在差异；2)获得关于健康双胞胎和克罗恩病双胞胎子集的社区蛋白质含量(元蛋白质组)的数据，以评估与CD相关的表达蛋白的状态；3)根据HMP指南，前瞻性地从80名接受手术切除以治疗炎性肠病的患者中获得活检和粪便样本，4)扩大我们在分子指纹、元蛋白质组学、并以代谢蛋白质组学为基础，进一步探讨肠道微生物群落结构变化与CD功能的关系。这些研究将包括：(I)完成瑞典同卵双胞胎肠道微生物组的元基因组和元蛋白质组特征；(Ii)使用分子指纹方法从瑞典双胞胎登记处的一组个人的粪便样本中测量，评估肠道微生物组随时间的稳定性；(Iii)多个CD患者队列的肠道活检组织中微生物群落组成的分子指纹和元蛋白质组比较；以及(Iv)对健康个体和CD患者肠道微生物组中含量较少的成员进行分子指纹和元基因组分析，以及5)应用各种统计聚类和分类方法，将微生物群落组成、基因和蛋白质含量与患者元数据相关联包括代谢产物谱和临床表型。这些努力的最终目标是为CD的非侵入性诊断寻找新的生物标志物，并最终确定用于治愈或抑制疾病症状的药物靶点(即细菌菌株)。

DESCRIPTION: Inflammatory bowel diseases (IBD), such as Crohn's disease, are chronic, immunologically mediated disorders that have severe medical consequences. The current hypothesis is that these diseases are due to an overly aggressive immune response to a subset of commensal enteric bacteria. Studies to date on IBD have suggested that the disorder may be caused by a combination of bacteria and host susceptibility; however the etiologies of these diseases remain an enigma. In this application, we propose to develop and demonstrate the ability to profile Crohn's disease at an unprecedented molecular level by elucidation of specific biomarkers (bacterial strains, genes, or proteins) that correlate to disease symptoms. To achieve this goal, we will employ a multidisciplinary approach based on metagenomic and metaproteomic molecular tools to elucidate the composition of the commensal microbiota in monozygotic twins that are either healthy or exhibit Crohn's disease (for concordant, both are diseased; for discordant, one is healthy and one is diseased). The central hypotheses of this proposal are (1) that specific members and/or functional activities of the gastrointestinal (GI) microbiota differ in patients with Crohn's disease as compared to healthy individuals, and (2) that it will be possible to elucidate microbial signatures which correlate with the occurrence and progression of this disease by integration of data obtained from 16S rRNA-based molecular fingerprinting, metagenomics, and metaproteomics approaches. To address these hypotheses, five specific aims are proposed: 1) Obtain data on community gene content (metagenome) in a subset of healthy twins and twins with Crohn's Disease to assess potential differences in the metabolic capabilities of the gut microbiota associated with CD, 2) Obtain data on community protein content (metaproteome) in a subset of healthy twins and twins with Crohn's Disease to assess the state of expressed proteins associated with CD, 3) Prospectively obtain biopsy and fecal samples from a cohort of 80 patients undergoing surgical resections for the treatment of inflammatory bowel according to HMP guidelines, 4) Extend our efforts in molecular fingerprinting, metagenomics, and metaproteomics to a larger population to further explore the relationship between changes in gut microbial community structure and function in CD. These studies will include: (i) completion of the metagenomic and metaproteomic characterization of the gut microbiota from the Swedish monozygotic twins, (ii) evaluation of gut microbiota stability over time, as measured in fecal samples from a group of individuals from the Swedish twin registry using molecular fingerprinting approaches, (iii) molecular fingerprinting and metaproteomic comparison of microbial community composition in intestinal biopsies from multiple CD patient cohorts, and (iv) molecular fingerprinting and metagenomic analysis of the less abundant members of the gut microbiota in healthy individuals and CD patients, and 5) Apply various statistical clustering and classification methods to correlate/associate microbial community composition, gene and protein content with patient metadata, including metabolite profiles and clinical phenotype. The ultimate goal of these efforts is to identify novel biomarkers for non-invasive diagnostics of CD and to eventually identify drug targets (i.e. bacterial strains) for cure or suppression of disease symptoms.