Increasing evenness and stability in synthetic microbial consortia

Construction of successful synthetic microbial consortia will harbour a new era in the field of agriculture, bioremediation, and human health. Engineering communities is a complex, multi-dimensional problem with several considerations ranging from the choice of consortia members and spatial factors to genetic circuit performances. There has been a growing number of computational strategies to aid in synthetic microbial consortia design, but a framework to optimize communities for two essential properties, evenness and stability, is missing. We investigated how the structure of different social interactions (cooperation, competition, and predation) in quorum-sensing based circuits impacts robustness of synthetic microbial communities and specifically affected evenness and stability. Our proposed work predicts engineering targets and computes their operating ranges to maximize the probability of synthetic microbial consortia to have high evenness and high stability. Our exhaustive pipeline for rapid and thorough analysis of large and complex parametric spaces further allowed us to dissect the relationship between evenness and stability for different social interactions. Our results showed that in cooperation, the speed at which species stabilizes is unrelated to evenness, however the region of stability increases with evenness. The opposite effect was noted for competition, where evenness and stable regions are negatively correlated. In both competition and predation, the system takes significantly longer to stabilize following a perturbation in uneven microbial conditions. We believe our study takes us one step closer to resolving the pivotal debate of evenness-stability relationship in ecology and has contributed to computational design of synthetic microbial communities by optimizing for previously unaddressed properties allowing for more accurate and streamlined ecological engineering.