Statistical modeling, inference and methodology in microbial metagenomics data analysis and computational molecular evolution

微生物宏基因组数据分析和计算分子进化的统计建模、推理和方法

• 批准号: RGPIN-2017-05108
• 负责人: Gu, Hong
• 金额: $ 1.75万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=709954
• 关键词: Statistical; modeling; inference; methodology; microbial

Recent research has shown the enormous influence of the microbiome on our lives. Microbial communities play crucial roles in human health, agriculture and the environment. Despite their undisputed importance, we know very little about how the microbes interact with each other and function together in the microbial community. The main aim of my research program is to develop statistical methods and models to understand the compositions and functions of the microbial communities and their interaction with host genome and/or environment. Microbiome data present new statistical challenges, thus new statistical methods will be needed. These statistical methods will also advance the field of statistics, leading to further potential applications outside of microbiome research. The direct results of the proposed research will provide tools for analyzing the microbiome data. This will have benefits in multiple areas. On the human health front, knowledge about how the microbiome changes are related to different disease status will have the immediate clinical benefit on diagnostics and choices of treatment regime. For example, understanding the causes of IBD and the response of the microbiome to various treatments could lead to improved treatments in future, including new microbial treatments. There have already been successful applications of microbial treatments for some conditions, such as faecal transplants for treating C. Difficile and L. Plantarum probiotic treatments for preventing neonatal sepsis. Further research will improve these treatments and lead to new treatments. IBD is an emerging health problem associated with high morbidity and health care costs. IBD affects about 1 in 150 Canadians (among the highest rates in the world) with the estimated economic burden to Canadians as $2.8 billion per year. Another major health-related area of interest is obesity. Research has indicated a link between the gut microbiome and obesity, but little is known about the connection. The methods in my proposed research will help to shed light on the processes linking obesity and the microbiome, leading to preventative measures and treatment for obesity-related health conditions. On the environmental side, my collaboration with world renowned scientist, Julie Laroche, allows me to work on ocean microbiome data. The microbiome plays a critical role in the ocean ecosystem, and changes to the microbiome can have repercussions on the higher trophic levels. The effects of pollution and climate change on the ocean microbiome are therefore of great concern. I expect many of the conclusions and methods from this research project will also apply to other environmental microbiome samples.

最近的研究表明，微生物组对我们的生活产生了巨大的影响。微生物群落在人类健康、农业和环境中起着至关重要的作用。 尽管它们的重要性无可争议，但我们对微生物如何相互作用以及在微生物群落中共同发挥作用知之甚少。我的研究计划的主要目的是开发统计方法和模型，以了解微生物群落的组成和功能及其与宿主基因组和/或环境的相互作用。微生物组数据提出了新的统计挑战，因此需要新的统计方法。这些统计方法也将推动统计学领域的发展，导致微生物组研究之外的进一步潜在应用。拟议研究的直接结果将为分析微生物组数据提供工具。这将在多个领域带来好处。 在人类健康方面，了解微生物组的变化如何与不同的疾病状态相关，将对诊断和治疗方案的选择产生直接的临床效益。例如，了解IBD的原因以及微生物组对各种治疗的反应可能会导致未来改进治疗方法，包括新的微生物治疗方法。微生物治疗已经成功地应用于某些疾病，如粪便移植治疗C。Difficile和L.植物益生菌治疗预防新生儿败血症。进一步的研究将改善这些治疗方法，并导致新的治疗方法。 IBD是一种新兴的健康问题，与高发病率和医疗保健成本相关。IBD影响约1/150的加拿大人（世界上发病率最高的国家之一），估计加拿大人每年的经济负担为28亿美元。 另一个主要的健康相关领域是肥胖。研究表明肠道微生物组与肥胖之间存在联系，但对这种联系知之甚少。我提出的研究方法将有助于揭示肥胖与微生物组之间的联系，从而为肥胖相关的健康状况提供预防措施和治疗。 在环境方面，我与世界著名科学家Julie Laroche的合作使我能够研究海洋微生物组数据。微生物组在海洋生态系统中起着至关重要的作用，微生物组的变化可能对更高的营养水平产生影响。因此，污染和气候变化对海洋微生物组的影响令人极为关切。我希望这项研究项目的许多结论和方法也适用于其他环境微生物组样本。