Decoding metabolic niche to engineer microbiome communities

Abstract
Microbial communities are all around us and have tremendous impact on health, agriculture, industry and the environment. However, predicting how microbial communities assemble or change over time, or making targeted modifications, is an unsolved problem due to the vast number of species and the complexity of ecological interactions. Making these communities tractable could enable, for example, the introduction of beneficial species or the removal of animal or plant pathogen. This research proposal aims to develop predictive models for understanding and manipulating microbial communities, with a focus on colonisation resistance - the phenomenon where a healthy microbiota prevents pathogen invasion, which is seen in both plants and animals. Recent work established nutrient blocking as a principle behind colonisation resistance. This project aims to use empirical approaches, such as machine learning, to make predictions based on real-world data, as well as mechanistic approaches, such as metabolic modelling, to understand the roles of specific nutrients and species in shaping microbial communities and colonisation resistance.
Addressing the following UKRI-BBSRC priorities:
Integrative microbiome research
Technology development for the biosciences
Systems approaches to biosciences
Animal health