Speaker
Description
Microbial interactions are fundamental to the assembly and function of microbiomes. Yet, our understanding of how specific interaction mechanisms can drive broader ecological outcomes and population dynamics remains limited. We describe the use of a microfluidic geometry that enables direct population pairing, cell observation and tracking, as well as quantitative metabolite detection, to monitor interactions in bacteria associated with the leaf microbiome. This approach enabled the identification of key metabolic mediators, revealing recipient-specific patterns of carbon substrate and cofactor complementation. By linking these patterns to emergent dynamics observed between pairs of bacteria, we identified metabolically driven feedbacks that could lead to a variety of ecological outcomes – from outcompetition to coexistence characterized by oscillating population abundances. Our results provide a detailed mapping of metabolic mechanisms to emergent population trajectories among environmental microbes, which help inform strategies for designing microbiomes with desired steady states.