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Received: DecemAccepted: SeptemPublished: October 10, 2022Ĭopyright: © 2022 Karkaria et al. University of Illinois at Urbana-Champaign, UNITED STATES Our work is the first to look at chaos in synthetic microbial communities and indicates that chaos is an important design consideration.Ĭitation: Karkaria BD, Manhart A, Fedorec AJH, Barnes CP (2022) Chaos in synthetic microbial communities. We then explore the levers we can pull to bring these networks in and out of chaotic regimes. Out of 4182 interaction networks in these three strain communities, we identify the networks that have the highest propensity to produce chaos. We apply this approach to study a set of communities involving quorum sensing systems and amensal interactions through antimicrobial peptides. In this paper, we present a statistical pipeline that can tell us how, when and why chaos arises in small microbial communities.

Although we know that chaos can be observed in the complex networks of natural ecosystems, the field of biotechnology is interested in designing and building new microbial communities and the presence of chaotic behaviour is unexplored. In chaotic systems, infinitesimally small differences in the initial conditions will become amplified over time, making forecasting and prediction of behaviour impossible. This work is the first to query the existence of chaotic behaviour in synthetic microbial communities and has important ramifications for the fields of biotechnology, bioprocessing and synthetic biology. We have shown that we can expect to find chaotic states in relatively small synthetic microbial systems, understand the governing dynamics and provide insights into how to control such systems. Our model selection pipeline uses Approximate Bayesian Computation to first identify oscillatory behaviours as a route to finding chaotic behaviour. We developed a methodology to explore the potential for chaotic dynamics in small microbial communities governed by resource competition, intercellular communication and competitive bacteriocin interactions. Therefore understanding which systems show chaos is an important design consideration. As we move to building coordinated multicellular systems, the potential for such systems to display chaotic behaviour becomes a concern. Predictability is a fundamental requirement in biological engineering.

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