Proteogenomic analysis of inflammation and dysbiosis in the infant gut

婴儿肠道炎症和生态失调的蛋白质组学分析

• 批准号: 8605019
• 负责人: Jillian Banfield
• 金额: $ 37.05万
• 依托单位: UT-BATTELLE, LLC-OAK RIDGE NATIONAL LAB
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-02-06 至 2017-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8605019
• 关键词: Adult; Aerobic; Anti-Inflammatory Agents; Anti-inflammatory; Attention; Biochemical Process; Bioinformatics; Biological Markers; Biological Models; Biology; Carbon; Communities; Companions; Crohn' s disease; Data; Data Analyses; Data Set; Development; Disease; Ecosystem; Epithelial; Fermentation; Generations; Genes; Goals; Health; Human; Human Microbiome; Human body; Hydrogen; Immune response; Infant; Inflammation; Inflammatory; Inflammatory Bowel Diseases; Inflammatory Response; Inflammatory disease of the intestine; Informatics; Intestinal Diseases; Intestines; Investigation; Life; Link; Maintenance; Mass Spectrum Analysis; Measurement; Measures; Metabolic Pathway; Metabolism; Metagenomics; Methods; Microbe; Modeling; Monitor; Natural Immunity; Necrotizing Enterocolitis; Newborn Infant; Nitrogen; Onset of illness; Organism; Oxidation-Reduction; Pathogenesis; Pathway interactions; Pattern; Premature Infant; Production; Proteins; Proteome; Proteomics; Research; Resolution; Respiration; Sampling; Series; Study models; Sulfur Metabolism Pathway; System; Testing; Time; United States National Institutes of Health; Virulence Factors; Volatile Fatty Acids; Work; base; improved; interest; intestinal homeostasis; knowledge base; link protein; microbial; microbial colonization; microbial community; microbiome; novel; protein expression; public health relevance; tool

The goal of this project is to conduct time-series proteomic analyses of a tractable and naturally- occurring model ecosystem, the newborn intestinal tract, in order to characterize links between dysbiosis and intestinal inflammation. At present, we lack a mechanistic understanding of the relationships between the microbiota and inflammatory disorders such as necrotizing enterocolitis (NEC) and inflammatory bowel disease. We also lack tools to clarify which microbial biochemical processes are active in the human gut. Over the past decade, our research group has developed methods to pair community metagenomics with high-throughput mass spectrometry-based proteomic analyses to accurately identify proteins with strain-level resolution. An important component of this approach has been the development of bioinformatics tools that enable the integration and analysis of "omic" data. Recently, we adapted these methods to simultaneously measure human and microbial proteins in time series infant fecal samples. Here, we propose to test the hypothesis that inflammation in the premature infant gut is triggered by aberrations in microbial community metabolism. This project will leverage samples and a large amount of metagenomic data obtained in a companion NIH study of the microbiota in babies with and without NEC. The specific Aims of this project are: Aim 1. Characterize gut microbial community function during the first month of life in healthy infants, by determining which microbial genes and metabolic pathways are most important during early colonization, with specific attention to the transition from aerobic to anaerobic community metabolism. Aim 2. Characterize time-dependent signatures of human proteins linked to intestinal inflammation in fecal samples from newborn infants, by evaluating the abundances of human proteins linked to intestinal homeostasis, inflammation, and redox biology in the context of changes in the microbial proteome. Aim 3. Test the hypothesis that babies with NEC developed inflammation as a consequence of a delayed transition to anaerobic microbial metabolism in the gut, by comparing temporal patterns of human and microbial protein expression in babies with and without NEC to determine if dysbiosis precedes inflammation This work will rely on a bioinformatics strategy for analysis of large time series datasets that will deployed in the context of GGKbase, a novel knowledgebase framework that will facilitate collaborative data analysis and sharing of "omic" information with the scientific community. This research uses the developing infant gut as a model system to uncover general features of gut microbial community function, and to clarify the relationships between aberrant function and inflammation. Our results and the informatics tools that we develop will contribute to an improved understanding of the dynamics of the relationship between the human body and the human microbiome. 1

该项目的目的是对可进行的且自然的时间序列蛋白质组学分析进行 发生模型生态系统，新生儿肠道，以表征失调与 肠炎。 目前，我们对微生物群和 炎症性疾病，例如坏死性小肠结肠炎（NEC）和炎症性肠病。我们也缺乏 阐明哪些微生物生化过程的工具在人肠中活跃。在过去的十年中，我们 研究小组开发了将社区宏基因组学与高通量质量配对的方法 基于光谱法的蛋白质组学分析可准确鉴定具有应变水平分辨率的蛋白质。一个 这种方法的重要组成部分是开发生物信息学工具，可以使 “ OMIC”数据的集成和分析。最近，我们调整了这些方法以同时测量 时间序列婴儿粪便样品中的人和微生物蛋白。 在这里，我们建议检验以下假设：早产婴儿肠道中的炎症是由畸变触发的 在微生物社区代谢中。该项目将利用样品和大量的宏基因组数据 在有或没有NEC的婴儿的伴侣NIH研究中获得的Microbiota研究。具体目的 该项目是：AIM 1。在生命的第一个月中表征肠道微生物社区功能 健康婴儿，通过确定哪些微生物基因和代谢途径在 早期殖民化，特别注意从有氧厌氧群落代谢的过渡。 目的2。表征与肠炎有关的人蛋白的时间依赖性特征 通过评估与肠道有关的人类蛋白质的丰度，来自新生婴儿的粪便样本 在微生物蛋白质组变化的背景下，稳态，炎症和氧化还原生物学。目标3。测试 NEC婴儿由于过渡到 通过比较人和微生物蛋白的时间模式，肠道中的微生物代谢 有或没有NEC的婴儿的表达以确定营养不良是否在炎症之前 依靠生物信息学策略来分析大型时间序列数据集，这些数据集将在 GGKBASE，一个新颖的知识基础框架，将促进协作数据分析和共享 科学界的“ OMIC”信息。 这项研究使用发育中的婴儿肠道作为模型系统，以发现肠道的一般特征 微生物社区功能，并阐明异常功能与炎症之间的关系。 我们开发的结果和信息学工具将有助于改善对 人体与人类微生物组之间关系的动力学。 1