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: 8975782
• 负责人: Jillian Banfield
• 金额: $ 36.44万
• 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/8975782
• 关键词: Adult; Aerobic; Anti-Inflammatory Agents; Anti-inflammatory; Attention; Biochemical Process; Bioinformatics; 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; candidate marker; improved; interest; intestinal homeostasis; knowledge base; link protein; microbial; microbial colonization; microbial community; microbiome; microbiota; novel; protein expression; proteogenomics; tool

DESCRIPTION (provided by applicant): 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.

描述（由申请人提供）：该项目的目标是对一个可处理的自然发生的模型生态系统，即新生儿肠道进行时间序列蛋白质组学分析，以表征生态失调和肠道炎症之间的联系。在