The Community Function Landscape: A Rational Framework for Translational Microbiome Engineering

The metabolic activity of microbial communities is essential for environmental and host health, influencing processes from bioremediation to host immune health. Given this importance, the rational design of microbiomes with targeted functional properties is an important objective. Designing microbial consortia with targeted functions is challenging due to complex community interactions and environmental heterogeneity. In this thesis, we introduce the Community Function Landscape - a statistical framework that maps the composition of a community to its function. Validation on six datasets of microbial community function reveal that the landscapes capture the average functional impact of each strain, enabling accurate predictions of community function. We apply the functional landscape to two highly complex microbial functions: the degradation of the toxic organic compound BPA, and the suppression of the human gut pathogen Klebsiela pneumoniae. In both cases, the functional landscape revealed statistical interactions ('epistasis') between strains that guided the design of consortia with optimal functional performance. Overall, the results of this thesis establish the Community Function Landscape as a framework for the rational design of microbial communities for application in contexts relevant for human and environmental health.