(76e) Predicting Microbial Community Assembly and Function in Synthetic Human Gut Microbiomes | AIChE

(76e) Predicting Microbial Community Assembly and Function in Synthetic Human Gut Microbiomes

Authors 

Clark, R. L. - Presenter, University of Wisconsin - Madison
Venturelli, O., University of Wisconsin-Madison
Amador-Noguez, D., University of Wisconsin - Madison
Stevenson, D. M., University of Wisconsin - Madison
Microbial communities are complex systems that exist in nearly every observed environment on earth and carry out chemical transformations with critical impacts to society, including oceanic CO2 fixation impacting climate change, production of molecules in the plant rhizosphere impacting crop growth, and degradation of dietary substrates in the human gut impacting host health. The microbes in these communities have evolved to optimize their own growth in such environments, often times with undesired outcomes from the human perspective. Thus, microbiome engineering efforts have begun to investigate how we can design and control microbially communities for desired outcomes. Most studies to date have focused on understanding the ecological principles that determine microbial community composition (i.e. how much of each species), neglecting prediction of the functional outputs of these communities (e.g. chemical transformations).

Here, we have applied a model-guided iterative experimental approach to understand the key factors impacting production of butyrate by the human gut microbiome, an important microbial community function that protects the human host from a wide range of diseases, including diabetes, colitis, and colorectal cancer. Our empirically informed model includes a dynamic growth component to quantify how interspecies interactions impact the growth of each species and a statistical model to quantify how interspecies interactions impact the relative butyrate yield for each species. We began by minimally parameterizing our model using experimental observations of the growth and butyrate production of 25 human gut bacterial isolates in monoculture and two-species communities and used this model to design new experiments with increasing community complexity, improving our model at each iteration. We finally used the model to design a set of complex communities (10-25 species) with a wide range of butyrate production (0-50 mM) and used the model parameters to improve our understanding of the key interactions that impact butyrate production in the human gut microbiome. This approach is easily generalizable to any measurable microbial community function and could be used to develop solutions to many critical problems related to human health, energy, and environmental sustainability.