Understanding and predicting how bacteriophages structure the microbiome

了解和预测噬菌体如何构建微生物组

• 批准号: 2628092
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2628092
• 关键词: Understanding; predicting; how; bacteriophages; structure

Background: Microbiomes play important roles in human health and nutrition. The performance of these functions is expected to be higher in more diverse microbiomes. Thus, the ecological stability of microbiomes - particularly their ability to recover from perturbations like antibiotic treatment - is believed to be an important predictor of their healthy function. To control and improve the benefits of microbiomes to human health we first need to understand the ecological and evolutionary rules that govern their structure and stability (Foster et al. 2017). Bacteriophages, viruses that infect bacteria, are universal in bacterial communities, driving their ecology and evolution (Koskella & Brockhurst 2014), but how bacteriophages affect the structure and stability of human microbiomes is currently unknown. Project: In this project we will explore how bacteriophages influence the structure and stability of human airway microbiome communities. Specifically, we will use a combination of ecological theory (Coyte et al. 2015) and simplified experimental communities (Davies et al. 2015) to predict and test the impact of bacteriophages on the structure and stability of microbiome communities with or without antibiotic perturbation. Then, we will use metagenomics to track the longitudinal dynamics of bacteriophages and bacteria within human airways (Layeghifard et al. 2019), testing our predictions in a real-world and clinically-relevant context. This research will advance understanding of the ecology and evolution of the human microbiome. This is vital for improving microbiome function (e.g. though microbiome restoration and transplants) and understanding the broader impacts of antimicrobial treatments (e.g. antibiotics and phage therapy) on human health.Training and supervision: This project offers a broad interdisciplinary training, including mathematical and computational modelling, microbiology, experimental evolution, evolutionary biology, genomics and bioinformatics. The supervisory team provides expertise in ecological theory for microbiomes (Katherine Coyte, UoManchester), experimental approaches to understanding microbial ecology and evolution (Michael Brockhurst, UoManchester), and genomics methods and bioinformatics (David Guttman, UoToronto). The project will be based at UoManchester with a 12-month placement at UoToronto enabling you to experience diverse research environments. You will be part of vibrant research labs alongside postdocs, technicians and students working on related projects investigating microbial evolution and ecology, offering an exciting and supportive training environment.

背景：微生物组在人类健康和营养中起着重要作用。预计这些功能的性能在更多样化的微生物组中更高。因此，微生物组的生态稳定性-特别是它们从抗生素治疗等扰动中恢复的能力-被认为是其健康功能的重要预测因素。为了控制和改善微生物组对人类健康的益处，我们首先需要了解控制其结构和稳定性的生态和进化规则（Foster et al. 2017）。噬菌体，感染细菌的病毒，在细菌群落中是普遍存在的，驱动着它们的生态和进化（Koskella & Brockhurst 2014），但噬菌体如何影响人类微生物组的结构和稳定性目前尚不清楚。在这个项目中，我们将探索噬菌体如何影响人类气道微生物群落的结构和稳定性。具体来说，我们将结合生态学理论（Coyte et al. 2015）和简化的实验群落（Davies et al. 2015）来预测和测试噬菌体对微生物群落结构和稳定性的影响，无论是否有抗生素干扰。然后，我们将使用宏基因组学来跟踪人体气道内噬菌体和细菌的纵向动态（Layeghifard et al. 2019），在现实世界和临床相关的背景下测试我们的预测。这项研究将促进对人类微生物组生态和进化的理解。这对于改善微生物组功能（例如通过微生物组恢复和移植）和了解抗菌治疗（例如抗生素和噬菌体治疗）对人类健康的更广泛影响至关重要。培训和监督：该项目提供广泛的跨学科培训，包括数学和计算建模，微生物学，实验进化，进化生物学，基因组学和生物信息学。监督团队提供微生物组生态理论（凯瑟琳科伊特，UoManchester），理解微生物生态学和进化的实验方法（Michael Brockhurst，UoManchester）以及基因组学方法和生物信息学（大卫古特曼，UoToronto）的专业知识。该项目将以UoManchester为基础，在UoToronto进行为期12个月的实习，使您能够体验多样化的研究环境。您将与博士后，技术人员和学生一起参与充满活力的研究实验室，研究微生物进化和生态学的相关项目，提供令人兴奋和支持性的培训环境。