Improving metagenomic inference and sample classification in inflammatory bowel disease

改善炎症性肠病的宏基因组推断和样本分类

• 批准号: 491176-2015
• 负责人: Langille, Morgan
• 金额: $ 2.91万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=619177
• 关键词: Improving; metagenomic; inference; sample; classification

"Microbiome" is a relatively new term to describe the entire set of microbes and their functions within a particular environment. Researchers are sampling various microbiomes including the ocean, soil, and host-associated (e.g. plant, animal and human). The host-associated microbiomes are crucial components of their hosts contributing metabolic capabilities, defence against unwanted pathogens and training of the host immune system. These microbiomes are complex communities consisting of thousands of species and millions of genes that interact, not only amongst themselves, but also with their environment. To understand these interactions requires computational methods that help process large datasets and identify biologically relevant patterns. This research program pursues several new computational strategies for understanding the mechanisms within these microbial communities and how they interact with their hosts. In particular, it attempts to build methods that can predict when closely related microbes have different functional capabilities and improve host sample classification based on microbiome information. This research program is crucial for leveraging the most knowledge from on-going microbiome research around the world and will provide the foundations for translating this knowledge into real world applications. These include more efficient and cost effective methods for profiling microbiomes, the ability to use the microbiome to improve diagnosis or treatment of various human diseases, and to identify novel microbes and microbial functions that are key determinants in host-microbial interactions.

“微生物组”是一个相对较新的术语，可在特定环境中描述整个微生物及其功能。研究人员正在抽样各种微生物组，包括海洋，土壤和宿主相关（例如植物，动物和人）。与宿主相关的微生物组是其宿主的关键组成部分，促进代谢能力，防御不需要的病原体和宿主免疫系统的训练。这些微生物组是复杂的群落，由数千种物种和数百万基因组成，不仅与它们之间的环境相互作用，而且与环境相互作用。要了解这些相互作用需要计算方法来帮助处理大型数据集并确定与生物学相关的模式。该研究计划采用了几种新的计算策略，以了解这些微生物群落中的机制及其与宿主的互动方式。特别是，它试图构建可以预测何时密切相关的微生物具有不同功能功能并根据微生物组信息改善主机样品分类的方法。该研究计划对于利用世界各地正在进行的微生物组研究的最大知识至关重要，并将为将这些知识转化为现实世界应用的基础。其中包括用于分析微生物组的更有效和成本效益的方法，使用微生物组改善各种人类疾病的诊断或治疗的能力，以及鉴定新型的微生物和微生物功能，这些微生物和微生物功能是宿主微生物相互作用中的关键决定因素。