Novel Computational Tools for Studying the Human Microbiome

描述（由申请人提供）：人类微生物组项目将从rRNA基因PCR产物和宏基因组DNA中产生数十亿个高通量序列读数;这些数据有可能彻底改变我们对人类微生物居民、这些微生物的推定功能及其与健康和疾病的关联的理解。然而，我们处理大量数据的能力有限，这阻碍了我们做出推论或得出结论的能力。具体地，用于从DNA或RNA序列鉴定微生物的通常可用的方法不能鉴定物种水平的生物体，并且可能无法执行到属水平或更高水平的置信分配，尽管有足够的系统发育信息来这样做。因此，许多公开可用的分类工具将代表不同物种的序列归类为不太具体的分类类别，正如我们在将这些工具应用于与阴道疾病相关的几种新型细菌时所发现的那样。这一提议意义重大，因为它通过开发和改进新的计算工具为这些基本问题提供了解决方案;这些工具的原型已经证明了显着改进的结果。我们免费提供的软件将通过提高微生物鉴定的速度、准确性和特异性，以及提供样本间比较的方法，帮助促进对人类微生物组的研究。这项建议有几个创新的特点。首先，计算效率高的最大似然树上的序列系统发育的位置将提供一个强大的方法来识别微生物和区分新奇和不确定性。第二，该提案将提供准确注释的参考序列集合，可以促进存在于主要人体部位的生物体的分类。更重要的是，该提案将开发软件工具，使个人研究人员能够使用一种方法组装参考序列集，该方法最大限度地提高每个代表分类单元内的序列多样性，同时排除质量差和错误标记的序列。第三，该提案将开发新的分析和可视化工具，以帮助跨空间和时间的微生物群落的统计比较，并帮助捕捉这些直观的可视化复杂变化。目标1：开发和优化系统发育定位软件，用于分析16 S rRNA和其他遗传信息位点，以更好地描述细菌多样性和群落组成。这一目标将推进我们的系统发育放置软件ppaser的发展，包括增加分类注释和物种划分的算法，实施改进的不确定性措施，以及低级别的代码优化。目标2：开发计算工具，从公共资源库和当地来源中管理特定项目的参考序列集。这一目标的动机是我们的观察，适当选择的参考序列和准确的同源性是一个关键的和限制性的组成部分的分类过程。目标3：开发一个软件管道来整合高通量测序数据分析，包括预处理，系统发育放置，统计比较和系统发育可视化。这一目标将导致两个可交付成果，扩展了广泛的研究人员的能力：为重视简单性的用户提供的Web服务，以及为重视模块化，可重复性和可扩展性的用户提供的R / Bioconductor软件包。 公共卫生相关性：与人类相关的微生物可以通过促进有益的相互作用（如促进营养吸收）或通过破坏宿主组织从而产生疾病对人类健康产生重大影响。新的测序技术为探索微生物与人类之间的关系提供了前所未有的机会，但我们的计算工具还没有跟上表征微生物种群的技术。该项目旨在通过开发用于分析高通量序列数据的计算工具来缩小这一差距，以便测序技术的全部力量可以用于准确识别微生物并评估它们与人类健康的关系。

DESCRIPTION (provided by applicant): The Human Microbiome Project will generate billions of high throughput sequence reads from rRNA gene PCR products and metagenomic DNA; these data have the potential to revolutionize our understanding of the microbial inhabitants of humans, the putative functions of these microbes, and their associations with health and disease. However, limitations in our ability to process this flood of data hinder our ability to make inferences or draw conclusions. Specifically, commonly available methods for identifying microbes from DNA or RNA sequences do not identify organisms to the species level, and may fail to perform confident assignment to the genus level or higher despite sufficient phylogenetic information to do so. As a result, many publicly available classification tools lump sequences representing distinct species into less specific taxonomic categories, as we have found when applying these tools to several novel bacteria linked with vaginal disease. This proposal is significant because it offers solutions to these fundamental problems by developing and refining novel computational tools; prototypes of these tools have already demonstrated significantly improved results. Our freely available software will help catalyze research on the human microbiome by increasing the speed, accuracy, and specificity of microbial identification, as well as offering methods for between-sample comparison. There are several innovative features of this proposal. First, computationally efficient maximum-likelihood phylogenetic placement of sequences on trees will provide a robust method for identifying microbes and distinguishing between novelty and uncertainty. Second, this proposal will provide accurately annotated collections of reference sequences that can facilitate classification of organisms present in major human body sites. More importantly, this proposal will develop software tools that will enable individual researchers to assemble sets of reference sequences using an approach that maximizes sequence diversity within each represented taxon while excluding poor quality and mislabeled sequences. Third, this proposal will develop new analysis and visualization tools to aid statistical comparison of microbial communities across space and time, and help capture these complex changes in intuitive visualizations. Aim 1: Develop and optimize phylogenetic placement software for the analysis of 16S rRNA and other phylogenetically informative loci to better describe bacterial diversity and community composition. This aim will advance the development of our phylogenetic placement software pplacer, including the addition of algorithms for taxonomic annotation and species delineation, implementation of improved measures of uncertainty, and low-level code optimization. Aim 2: Develop computational tools to curate project-specific sets of reference sequences from public repositories and local sources. This aim is motivated by our observation that appropriately selected reference sequences and accurate phylogenies are a critical and limiting component of the classification process. Aim 3: Develop a software pipeline to integrate high throughput sequencing data analysis, including preprocessing, phylogenetic placement, statistical comparison, and phylogenetic visualization. This aim will result in two deliverables extending the capabilities of a broad spectrum of researchers: a web service for users who value simplicity, as well as R / Bioconductor software packages for users who value modularity, reproducibility, and extensibility. PUBLIC HEALTH RELEVANCE: Human-associated microbes can have a major impact on human health, either by promoting beneficial interactions (such as facilitating nutrient absorption) or by damaging host tissues thereby producing disease. New sequencing technologies provide an unprecedented opportunity to explore the relationships between microbes and humans, but our computational tools have not kept pace with the technology for characterizing microbial populations. This project seeks to close this gap by developing computational tools for analyzing high throughput sequence data so that the full power of sequencing technologies can be used to accurately identify microbes and assess their relationships with human health.