Interfacing Metabolic Models of Maize and its Root Microbiome to Investigate Interkingdom Interactions

Abstract

Metabolite exchange plays a crucial role in host-microbiome interactions and is key to understanding how microbes affect their host and vice versa. Metabolic models provide a way to simulate these interactions and produce data that can inform future hypotheses without the need for complex experimental methods or equipment. Metabolic models for a seven-member subset of the root-associated microbiome of maize (Zea mays) were constructed and analyzed to predict individual and community bacterial growth in different environmental media: a synthetic laboratory medium and a medium containing a variety of more complex maize root exudates. Results indicate that the maize exudate medium supported a higher community diversity than the laboratory medium. While this work provides insight into the bacterial side of maize root metabolite exchange, it remains to be seen how the maize itself is impacted by bacterial presence. While comprehensive metabolic models of maize have been previously constructed, none have directly interfaced with models of its root-associated bacteria. This study aims to perform simulations in a multi-tissue maize metabolic model investigating root exudate production under different environmental scenarios to predict potential effects of direct plant-microbe interactions. Altogether, this work provides a more holistic understanding of metabolite exchange and mutual benefit between plant and microbes in the maize microbiome system. Data from these simulations can be used to improve the design of experimental trials and discover metabolic drivers of plant-microbe interactions.