Functional activity and inter-organismal interactions in the human microbiome

描述(申请人提供)：高通量测序提供了一种能够观察人类微生物群的工具，但表征这些微生物群落的生物学作用和代谢潜力仍然是一个重大挑战。越来越多的证据表明，基因产物的功能活性，而不是群落分类组成，是微生物区系与其宿主关系的最有力描述，也是调节人类健康的潜在干预点。现有的用于探索新测序的元基因组的计算工具严重依赖于序列同源性，还没有利用来自数千个公开可用的功能实验结果的信息。同样，以前没有任何方法提供基因组规模的计算工具，用于产生关于微生物区系之间和与人类宿主之间的特定分子相互作用的生物学假说。这项建议旨在开发计算方法来解释微花群落的功能活动：1.整合分类学、元基因组和元翻译数据集的功能信息。我们将开发方法学，通过整合来自大规模功能基因组数据集合的信息来统一这三种微生物组组成的代表。2.确定种间功能活动的基因组预测因子，包括宿主/微生物区系的相互作用和社区范围的调节反馈点。我们将通过计算筛选微生物组分析，以寻找跨越群落中多个生物体的分子相互作用和调控基序。3.将这些技术作为公开可用的、可访问的和可解释的工具来实施。我们将提供这种方法的免费、开源、可下载和基于网络的实现，供生物信息学和生物界使用。随着高通量测序越来越广泛地被用于研究人类微生物组和环境中的微生物群落，计算工具将是必要的，以总结它们的全球功能活动和系统水平的调节相互作用。从长远来看，通过提供在分子水平上了解人类微生物组的方法，我们希望未来能够将其用作诊断指标和作为改善人类健康的干预点。 与公共健康相关：DNA测序技术最近使我们能够检查自然存在于人体内和体内的微生物，其中许多是有益的，有些可能是有害的。虽然我们现在可以收集关于这些微生物的细胞行为以及它们与人类相互作用的数据，但需要计算工具来解释这些信息。通过开发研究这些微生物群落的新软件，我们希望最终能够检测到它们可能导致疾病的时间，并修改它们的组成，以改善人类健康。

DESCRIPTION (provided by applicant): High-throughput sequencing has provided a tool capable of observing the human microbiome, but characterizing the biological roles and metabolic potential of these microbial communities remains a significant challenge. Increasing evidence points to the functional activity of gene products, rather than community taxonomic composition, as the most robust descriptor of the microflora's relationship with its host and as a potential point of intervention in modulating human health. Existing computational tools for exploring a newly sequenced metagenome rely heavily on sequence homology and do not yet leverage information from the thousands of publicly available functional experimental results. Likewise, no previous methods have provided genome-scale computational tools for biological hypothesis generation regarding specific molecular interactions among the microflora and with a human host. This proposal aims to develop computational methodology to interpret the functional activity of microfloral communities: 1. Integrate functional information from taxonomic, metagenomic, and metatranscriptomic datasets. We will develop methodology to unify these three representations of microbiome composition by incorporating information from large scale functional genomic data collections. 2. Identify genomic predictors of inter-species functional activity, including host/microflora interactions and points of community-wide regulatory feedback. We will computationally screen microbiome assays for molecular interactions and regulatory motifs spanning multiple organisms in the community. 3. Implement these technologies as publicly available, accessible, and interpretable tools. We will provide freely available, open source, downloadable and web-based implementations of this methodology for use by the bioinformatic and biological communities. As high-throughput sequencing becomes more widely used to study microbial communities in the human microbiome and in the environment, computational tools will be necessary to summarize their global functional activity and systems-level regulatory interactions. In the long term, by providing methodology to understand the human microbiome at the molecular level, we hope to enable its future use as a diagnostic indicator and as a point of intervention to improve human health. PUBLIC HEALTH RELEVANCE: DNA sequencing technology has recently allowed us to examine the microorganisms naturally residing in and on the human body, many of which are beneficial and some of which can be harmful. Although we can now gather data on the cellular behavior of these microbes and on their interactions with human beings, computational tools are needed to interpret this information. By developing new software to study these communities of microorganisms, we hope to eventually be able to detect when they may be causing disease and modify their composition to improve human health.