Computational Annotation of Orphan Metabolic Activities

孤儿代谢活动的计算注释

• 批准号: 8697980
• 负责人: Dennis Vitkup
• 金额: $ 51.11万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-05-15 至 2018-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8697980
• 关键词: Active Sites; Anti-Bacterial Agents; Antibiotics; Area; Bacteria; Bacterial Genome; Biochemical Pathway; Biology; Collaborations; Communities; Computing Methodologies; Data; Development; Dreams; Enzymes; Funding; Genome; Genomics; Growth; Human; Joints; Lead; Left; Letters; Life; Malaria; Measures; Medical Research; Metabolic; Metabolism; Metagenomics; Methodology; Methods; Microbe; Military Personnel; Modality; Modeling; Mycobacterium tuberculosis; Nutrient; Online Systems; Orphan; Parasites; Pathway interactions; Phenotype; Positioning Attribute; Property; Proteins; Publications; Research; Research Personnel; Role; Route; Sampling; Sequence Homology; Services; Source; Structural Protein; Study models; System; Technology; Therapeutic; Work; abstracting; base; improved; innovation; interest; killings; metabolomics; microbial; pathogen; pathogenic bacteria; protein structure; public health relevance; reconstruction; resistant strain; simulation; success

DESCRIPTION: An avalanche of sequencing and genomic data has a potential to revolutionize our understanding of microbial biology and transform medical research. Accurate reconstructions of bacterial metabolism often provide the most direct route toward understanding the biology of sequenced species, their growth and environmental properties, and possible interactions with other species in metagenomic communities. Reconstructed metabolic networks can also guide the development of new antibacterial therapeutics. In this application we propose to use the GLOBUS framework to build an integrated, accurate, and fully probabilistic system for the annotation of bacterial metabolism; we will integrate into the framework key data modalities that, according to our preliminary results, will significantly improve the method's coverage and accuracy. Specifically, we will a.) integrate protein structural information into GLOBUS, using analyses of enzyme active sites; b.) extend the GLOBUS framework to accommodate metabolomics data by joint sampling of metabolomics and protein annotations; and c.) integrate into the annotation framework phenotypic information, including growth on multiple nutrient sources measured by the widely used BiOLOG platform for high-throughput bacterial phenotyping. We will implement and make the developed methodology publically available through a transparent web-based portal. This will make it possible for other researchers to use the GLOBUS methodology to annotate any sequenced bacterial species of interest. The portal will be transparent, enabling users to identify the sources of the predictions We will also obtain relevant phenotypic information from our experimental collaborators and use GLOBUS to generate accurate probabilistic annotations for all major bacterial species (~50 bacteria) that are pathogenic to humans.

描述：测序和基因组数据的雪崩具有彻底改变我们对微生物生物学的理解并改变医学研究的潜力。细菌代谢的准确重建通常为理解测序物种的生物学，其生长和环境特性以及与元基因组社区中其他物种的可能相互作用提供最直接的途径。重建的代谢网络还可以指导新的抗菌疗法的发展。在此应用程序中，我们建议使用Globus框架来构建一个综合，准确且完全概率的系统，以注释细菌代谢。我们将集成到框架关键数据模式中，根据我们的初步结果，该模式将大大提高该方法的覆盖范围和准确性。具体而言，我们将使用酶活性位点的分析将蛋白质结构信息整合到Globus中； b。）扩展Globus框架以通过代谢组学和蛋白质注释的联合采样来适应代谢组学数据；和c。）整合到注释框架表型信息中，包括通过广泛使用的生物学平台测量的多种营养来源的生长，用于高通量细菌表型。我们将通过透明的基于Web的门户公开实施并使开发的方法公开获得。这将使其他研究人员使用Globus方法来注释任何测序的细菌感兴趣。该门户网站将是透明的，使用户能够从我们的实验合作者那里获得相关的表型信息，从而使用户能够从我们的实验合作者那里获得相关的表型信息，并使用Globus为所有主要细菌物种（〜50个细菌）生成准确的概率注释，这些物种对人类具有致病性。