本项目以微生物群落宏基因组为研究对象，包括环境微生物和申请人获得的一批人体肠道菌群样本及其宏基因组高通量测序数据，围绕环境适应性这一重要问题，在近年来自主发展的一系列生物信息学新方法和新工具的基础上，首先进行宏基因组学的功能基因组学注释及分析，并进一步发展适用于大批量样本的比较宏基因组学新算法和工具，通过样本特征量比较分析、比较基因组学、功能分类、代谢通路，进而分析微生物群落的关键基因及其相互关系网络，从分子水平研究微生物对环境的适应和作用；进一步地，运用宏基因组学方法研究微生物群落中多物种的合作、竞争等复杂的社会关系，并发展基于基因相互作用信息的宏基因组种群动力学数学模型，探讨微生物群落在特定环境下的种群结构演化和适应环境的分子机制。本项目既有宏基因组生物信息学方法的自主研究基础，又有自然环境与临床研究获得的宏基因组高通量测序数据，体现了基于高通量测序数据的系统、整体的基因组学研究特点。

This proposal selects the metagenomes of microbiota as our study target, including the environmental microbes and a supply of human intestinal flora sample with metagenomic sequencing data. Based on a series of bioinformatics methods and tools developed by our lab, we aim to perform following studies focused on the issue of environmental adaption of microbiota. (1) Have the functionary genomics annotation and analysis for microbiota genomic sequences, and then develop a novel method of comparative metagenomics for a large batch of samples; (2) Further have the analysis of the essential genes and their interaction networks for microbial community, by means of sample properties analysis, comparative genomics, function classification, and metabolic pathways etc.; (3) Then study the complex social relations as cooperation and competition among multi-strains in a microbial community; (4) And develop a population dynamics math modelling based on the gene interaction, to discuss the dynamic evolution of population structure and the molecular mechanism of environmental adaption of the microbial community as a whole. The proposal has the solid foundation of metagenomic bioinformatics methods and tools, most of them have been developed by our lab. Also, we have obtained a amount of high throughput sequencing data for metagenomes from both natural environments and clinic researches. Overall, the proposal demonstrates a systematic and integrating way of metagenomics studies under current high throughput NGS sequencing technologies.