Assembly and analysis software for exploring the human microbiome

用于探索人类微生物组的组装和分析软件

• 批准号: 7571986
• 负责人: Mihai Pop
• 金额: $ 26万
• 依托单位: UNIV OF MARYLAND, COLLEGE PARK
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-24 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7571986
• 关键词: Address; Algorithms; Bacteria; Bioinformatics; Characteristics; Communities; Complex; Computational algorithm; Computer software; DNA; Data; Data Set; Databases; Depth; Development; Disease; Elements; Environment; Eukaryota; Eukaryotic Cell; Experimental Designs; Future; Genes; Genome; Genomics; Goals; Health; Human; Human Microbiome; Human body; Hybrids; Imagery; Individual; Inflammatory Bowel Diseases; Lead; Life; Light; Metagenomics; Methods; Microbe; Mining; Numbers; Obesity; Oceans; Organism; Play; Population; Process; Public Health; Publishing; Research Infrastructure; Resource Sharing; Role; Scientist; Simulate; Soil; Source; Taxon; Technology; Translating; Variant; Water; commensal microbes; comparative; cost; data integration; high throughput technology; improved; insight; interest; member; metagenomic sequencing; microbial; microbial community; open source; programs; repository; software development; software systems; tool

DESCRIPTION (provided by applicant): Bacteria are the most abundant organisms on Earth, yet little is known about most members of this domain of life. Only about 1% of bacterial species can be easily grown in culture, and considerably fewer have been sequenced. Advances in sequencing technologies have made it possible to sequence bacteria directly from the environment, providing a dramatic new outlook on the diversity of bacteria populating our world. Initial studies have explored the bacteria present in mines, ocean water, and soil, as well as communities of commensal microbes that inhabit the human body. The latter have provided a glimpse at the complex symbiotic relationships between bacteria and their human hosts. Despite an increased interest in environmental sequencing (metagenomics), few specialized computational algorithms exist for the analysis of such data. For example, the assembly of environmental data is being performed with software originally intended for homogeneous DNA sources, such as clonal bacterial populations or inbred eukaryotes. These programs are ill-suited to the assembly of heterogeneous microbial communities and numerous "hacks" have been necessary to produce the assemblies published to date. This proposal aims to fill the need for specialized software for assembling and finding genes in metagenomic datasets. A particular focus will be on developing tools for uncovering genomic variation within the assemblies of microbial communities. The proposed software will specifically address issues arising from the use of new sequencing technologies in metagenomic projects. The low cost and high throughput of these technologies will allow a far deeper exploration of the microbial biosphere than was previously possible. Their broad application, however, depends on the availability of software systems adapted to their specific characteristics. In addition, new algorithms will be developed to allow the individual components of a metagenomic analysis pipeline to be tightly integrated, with the goal of improving the overall quality of both assembly and annotation, and to facilitate the extraction of other types of information from large sets of metagenomic data. The proposal further aims to investigate the impact of experimental design and choice of sequencing technology on the ability to assemble and analyze metagenomic data, through the development of software for simulating bacterial populations and emulating a variety sequencing strategies. Better experimental design can reduce the high costs currently associated with environmental sequencing and enhance subsequent analyses. All software developed as part of this proposal, as well as any simulated data and results of reanalyzing public datasets will be released freely through public databases and open-source software repositories. PUBLIC HEALTH RELEVANCE: Project Narrative Initial explorations of the communities of bacteria that inhabit our bodies have already provided insights into the complex relationships between microbes and the human host, as well as the contribution of bacteria to diseases such as obesity, and inflammatory bowel disease. Many more studies will be needed to help us fully understand the complex human-microbe interactions and to translate these discoveries into new therapies. The current proposal provides scientists with components of the software infrastructure that will be essential for genomic studies of the human microbiome.

描述(申请人提供)：细菌是地球上最丰富的生物，但对这一生命领域的大多数成员知之甚少。只有大约1%的细菌物种可以在培养中轻松生长，而且被测序的细菌数量要少得多。测序技术的进步使直接从环境中对细菌进行测序成为可能，为我们世界上细菌的多样性提供了一个戏剧性的新前景。初步研究探索了存在于矿山、海水和土壤中的细菌，以及居住在人体内的共生微生物群落。后者让我们得以一窥细菌与其人类宿主之间复杂的共生关系。尽管人们对环境测序(元基因组学)越来越感兴趣，但几乎没有专门的计算算法来分析这种数据。例如，环境数据的汇编是使用最初针对同质DNA来源的软件进行的，例如克隆细菌种群或近亲繁殖的真核生物。这些程序不适合于异质微生物群落的组装，而且到目前为止，生产已发表的组装件需要大量的“黑客”。这项提议旨在满足在元基因组数据集中组装和寻找基因的专门软件的需求。一个特别的重点将是开发工具，以揭示微生物群落集合内的基因组变异。拟议的软件将专门解决在元基因组项目中使用新的测序技术所产生的问题。这些技术的低成本和高吞吐量将使人们能够比以前更深入地探索微生物生物圈。然而，它们的广泛应用取决于适应其特定特征的软件系统的可用性。此外，将开发新的算法，以便将元基因组分析管道的各个组成部分紧密结合在一起，目的是提高汇编和注释的整体质量，并便利从大集合的元基因组数据中提取其他类型的信息。该提案还旨在通过开发模拟细菌种群和模拟各种测序策略的软件，来调查实验设计和测序技术的选择对收集和分析元基因组数据的能力的影响。更好的实验设计可以降低目前与环境测序相关的高昂成本，并增强后续分析。作为这项提议的一部分开发的所有软件以及任何模拟数据和重新分析公共数据集的结果将通过公共数据库和开放源码软件储存库免费发布。公共卫生相关性：项目叙述对栖息在我们体内的细菌群落的初步探索已经提供了对微生物和人类宿主之间的复杂关系的洞察，以及细菌对肥胖和炎症性肠病等疾病的贡献。还需要更多的研究来帮助我们充分了解复杂的人类-微生物相互作用，并将这些发现转化为新的疗法。目前的提议为科学家提供了对人类微生物组基因组研究至关重要的软件基础设施的组件。