Fragment assembly and metabolic/species diversity analysis for Human microbiome p

人类微生物组的片段组装和代谢/物种多样性分析

基本信息

批准号：
7573747
负责人：
Yuzhen Ye
金额：
$ 25.61万
依托单位：
TRUSTEES OF INDIANA UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2008
资助国家：
美国
起止时间：
2008-09-26 至 2011-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7573747
关键词：
Address Algorithms Amino Acid Sequence Biochemical Biodiversity Biological Process Blast Cell Code Collection Communities Comparative Study Computing Methodologies DNA Sequence Data Data Analyses Databases Development Evaluation Facility Construction Funding Category Family Filtration Functional RNA Genes Genetic Genome Graph Homologous Protein Human Human Microbiome Human body Imagery Individual Life Maps Metabolic Metagenomics Methodology Methods Microbe Numbers Open Reading Frames Pathway interactions Peptide Sequence Determination Peptides Performance Phylogenetic Analysis Protein Databases Protein Family Proteins Public Health Reading Research Personnel Sampling Score Seeds Sensitivity and Specificity Software Tools Specialist Speed Surface System Techniques Text Variant base computer framework computerized tools gene function human disease improved markov model microbial genome microorganism novel strategies programs protein function scaffold software development tool

Address Algorithms Amino Acid Sequence Biochemical Biodiversity Biological Process Blast Cell Code Collection Communities Comparative Study Computing Methodologies DNA Sequence Data Data Analyses Databases Development Evaluation Facility Construction Funding Category Family Filtration Functional RNA Genes Genetic Genome Graph Homologous Protein Human Human Microbiome Human body Imagery Individual Life Maps Metabolic Metagenomics Methodology Methods Microbe Numbers Open Reading Frames Pathway interactions Peptide Sequence Determination Peptides Performance Phylogenetic Analysis Protein Databases Protein Family Proteins Public Health Reading Research Personnel Sampling Score Seeds Sensitivity and Specificity Software Tools Specialist Speed Surface System Techniques Text Variant base computer framework computerized tools gene function human disease improved markov model microbial genome microorganism novel strategies programs protein function scaffold software development tool

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项目摘要

DESCRIPTION (provided by applicant): The human microbiome contributes essential and complementary genetic and metabolic components to the host human. Until recently, microbiologists mainly studied individual culturable species of microbes, even though a vast majority (approximately 95%-98%) of microorganisms cannot live in pure culture. Facilitated by the rapid advancement of the DNA sequencing techniques, metagenomics attempts to directly determine the whole collection of genes within an environmental sample. To study the human microbiome at a global level, metagenomics becomes the methodology of choice for the Human Microbiome Project (HMP). We propose to develop computational methods addressing several challenges to the metagenomic analysis in HMP, namely, the assembly of short reads from pyrosequencing, the functional annotation of protein coding genes through database searching, and the characterization of the biodiversity in samples. We start with a novel approach to assembling short reads from metagenomics, called ORFome Assembly, by assembling putative ORFs from homologous proteins in the same family into a protein family graph (an Eulerian path approach). We then propose a network matching approach for the similarity search using the protein family graphs as queries. We anticipate that using protein family graphs will result in database searching with higher sensitivity and specificity than simply using unassembled sequencing reads. Finally, we propose to develop computational tools to simultaneously assess the biodiversity and biological functions in samples, by identifying the most likely set of coherent pathway variants covering the annotated gene functions within the metagenomic data based on the similarity search results. These software tools will enable researchers to efficiently and effectively analyze the data from HMP, which will enhance the understanding of the relationship between the human microbiota (i.e., the microbes living on the surface and inside human body) and human diseases, and hasten the development of better or new therapies. PUBLIC HEALTH RELEVANCE: We propose to develop computational methods addressing several challenges to the metagenomic analysis of human microbiome project (HMP) data. These software tools will enable researchers to efficiently and effectively analyze the data from HMP, which will enhance the understanding of the relationship between the human microbiota and human diseases, and hasten the development of better or new therapies.

描述（由申请人提供）：人类微生物组为宿主人类贡献了必不可少的遗传和代谢成分。直到最近，微生物学家主要研究了可培养的微生物物种，尽管绝大多数（约95％-98％）的微生物不能生活在纯文化中。 DNA测序技术的快速发展促进了宏基因组学试图直接确定环境样本中基因的整个集合。为了研究全球层面的人类微生物组，宏基因组学成为人类微生物组项目（HMP）的首选方法。我们建议开发针对HMP中元基因组分析的几个挑战的计算方法，即，从焦磷酸测序组装了简短读数，通过数据库搜索的蛋白质编码基因的功能注释以及样品中生物多样性的表征。我们从一种新的方法开始，将来自宏基因组学（称为Orfome组装的简短读数）组装，通过将同一家族同源蛋白的推定ORF组装成蛋白质家族图（Eulerian Path方法）。然后，我们建议使用蛋白质家族图作为查询的网络匹配方法进行相似性搜索。我们预计，使用蛋白质家族图将导致数据库搜索具有更高的灵敏度和特异性，而不是简单地使用未组装的测序读数。最后，我们建议开发计算工具，以通过识别基于相似性搜索结果的元基因组数据中涵盖带注释基因功能的最有可能的相干途径变体来同时评估样品中的生物多样性和生物学功能。这些软件工具将使研究人员能够有效地分析HMP的数据，这将增强人们对人类微生物群（即生活在人体内部和人体内部的微生物）和人类疾病之间关系的理解，并加快发展更好或新疗法的发展。公共卫生相关性：我们建议开发计算方法，以解决人类微生物组项目（HMP）数据的宏基因组分析的几个挑战。这些软件工具将使研究人员能够有效地分析HMP的数据，这将增强对人类微生物群与人类疾病之间关系的理解，并加快更好或新疗法的发展。