New Tools for Understanding the Composition and Dynamics of Microbial Communities

人体内的微生物数量比人体细胞多一个数量级， 健康和疾病的许多方面，包括肥胖、阴道病和克罗恩病。理解这一 内源性微生物群正在成为理解人类基因组和人类基因组的关键延伸。 遗传变异对健康和疾病的作用。人类微生物组项目（HMP）将描述 使用宏基因组测序在大量个体健康人中检测微生物群落。 因此，解释序列数据以了解微生物群落组成的新方法 and dynamics动态are urgently迫切needed需要.这个项目结合了从生态学到进化生物学的学科 应用数学，开发新的方法来理解哪些身体栖息地或多或少 通过评估微生物多样性和变化的措施，在微生物群落方面相似， 创建所需的社区组成新指标。这将有助于了解临床上如何 相关参数，如年龄，性别，或特定身体栖息地的pH值影响这些社区，以及如何 个体内微生物群落的动态变化，个体之间的传播，以及 在人类和环境之间的传播。 该项目直接响应RFA计算新工具开发路线图 人类微生物组项目数据分析。这项建议的具体目标是： 目标1。开发、表征和应用丰富的微生物群落多样性描述符。 目标2.开发描述人类微生物群落如何随时间和空间变化的方法。 目标3.开发新的方法来追踪不同社区之间的生物流动。 拟议工作的一些关键方面是：发展新的统计方法， 生物体栖息地内的微生物多样性;开发用于描述微生物群落的富集方法 多样性;通过大规模比较微生物群落的方法的详尽验证 模拟，并通过使用最大的可用数据集，表征微生物群落的经验; 以及追踪人体微生物来源的新方法的发展 使用标记基因和全宏基因组数据。关键成果包括帮助确定 核心人类微生物组的存在程度，以及如何最好地采样人类微生物多样性。 所有开发的方法都将在开源许可证下提供，并将存放在HMP 数据分析和协调中心（DACC）。调查人员打算与其他人密切合作， 参与HMP的研究人员，以确保快速进展。

The microbes that inhabit human bodies outnumber the human cells by an order of magnitude, and impact many aspects of health and disease including obesity, vaginosis, and Crohn's disease. Understanding this endogenous microbiota is emerging as a key extension of efforts to understand the human genome and the role of genetic variation on health and disease. The Human Microbiome Project (HMP) will characterize microbial communities in a large number of individual healthy humans using metagenomic sequencing. Consequently, new methods for interpreting sequence data to understand microbial community composition and dynamics are urgently needed. This project unites disciplines ranging from ecology to evolutionary biology to applied mathematics, to develop new methods for understanding which body habitats are more or less similar in terms of their microbial communities, by evaluating measures of microbial diversity and change, and creating needed new metrics of community composition. This will enable understanding of how clinically relevant parameters such as age, sex, or the pH of specific body habitats affect these communities, and of how the dynamics of change in microbial communities within an individual, in transmission between individuals, and in transmission between humans and the environment. This project is directly responsive to the Roadmap RFA for Development of New tools for Computational Analysis of Human Microbiome Project Data. The specific aims of this proposal are: Aim 1. Develop, characterize, and apply enriched descriptors of microbial community diversity. Aim 2. Develop methods for describing how human microbial communities vary over time and space. Aim 3. Develop new methods for tracing the flow of organisms among different communities. Some key aspects of the proposed work are: the development of new statistical methods for estimating microbial diversity within a body habitat; development of enriched methods for describing microbial community diversity; exhaustive validation of methods for comparing microbial communities through large-scale simulations and by using the largest available data sets that characterize microbial communities empirically; and the development of new methods for tracing the sources of the microbes that inhabit the human body using both marker genes and whole-metagenome data. Key outcomes include the ability to help determine the extent to which there is a core human microbiome, and how best to sample human microbial diversity. All methods developed will be made available under open source licenses and will be deposited with the HMP Data Analysis and Coordination Center (DACC). The investigators intend to work closely with other researchers involved in the HMP in order to ensure rapid progress.