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，用来描述一组微生物及其在特定环境中的功能。研究人员正在对各种微生物群进行采样，包括海洋、土壤和与宿主相关的(例如植物、动物和人类)。与寄主相关的微生物群是寄主的重要组成部分，有助于新陈代谢能力、防御有害病原体和训练寄主免疫系统。这些微生物群是由数千个物种和数百万个基因组成的复杂群落，它们不仅相互作用，而且与环境相互作用。为了理解这些相互作用，需要帮助处理大型数据集和识别生物相关模式的计算方法。这项研究计划追求几种新的计算策略，以了解这些微生物群落中的机制以及它们如何与宿主相互作用。特别是，它试图建立一种方法，可以预测密切相关的微生物何时具有不同的功能能力，并基于微生物组信息改进宿主样本分类。这一研究计划对于利用世界各地正在进行的微生物组研究中的大多数知识至关重要，并将为将这些知识转化为现实世界的应用提供基础。其中包括更有效和更具成本效益的微生物群分析方法，利用微生物群改进各种人类疾病的诊断或治疗的能力，以及确定新的微生物和微生物功能，这些都是宿主-微生物相互作用的关键决定因素。