Microbial consortia are an exciting alternative for increasing the performances of bioprocesses for the production of complex metabolic products. However, the functional properties of microbial communities remain challenging to control, considering the complex interaction mechanisms occurring between co-cultured microbial species. Indeed, microbial communities are highly dynamic and can adapt to changing environmental conditions through complex mechanisms, such as phenotypic diversification. We focused on stabilizing a co-culture of Saccharomyces cerevisiae and Escherichia coli in continuous cultures. Our preliminary data pointed out that transient diauxic shifts could lead to stable co-culture by providing periodic fitness advantages to the yeast. Based on a computational toolbox called MONCKS (for MONod-type Co-culture Kinetic Simulation), we were able to predict the dynamics of diauxic shift for both species based on a cybernetic approach. This toolbox was further used to predict the frequency of diauxic shift to be applied to reach co-culture stability. These simulations were successfully reproduced experimentally in continuous bioreactors with glucose pulsing. Finally, based on a bet-hedging reporter, we observed that the yeast population exhibited an increased phenotypic diversification process in co-culture compared with mono-culture, suggesting that this mechanism could be the basis of the metabolic fitness of the yeast.
Microbial populations can adapt to adverse environmental conditions either by appropriately sensing and responding to the changes in their surroundings or by stochastically switching to an alternative phenotypic state. Recent data point out that these two strategies can be exhibited by the same cellular system, depending on the amplitude/frequency of the environmental perturbations and on the architecture of the genetic circuits involved in the adaptation process. Accordingly, several mitigation strategies have been designed for the effective control of microbial populations in different contexts, ranging from biomedicine to bioprocess engineering. Technically, such control strategies have been made possible by the advances made at the level of computational and synthetic biology combined with control theory. However, these control strategies have been applied mostly to synthetic gene circuits, impairing the applicability of the approach to natural circuits. In this review, we argue that it is possible to expand these control strategies to any cellular system and gene circuits based on a metric derived from this information theory, i.e., mutual information (MI). Indeed, based on this metric, it should be possible to characterize the natural frequency of any gene circuits and use it for controlling gene circuits within a population of cells.
Microbial consortia are exciting platforms for the bioproduction of complex metabolic products. However, the functional properties of microbial communities remain challenging to control, given the complex interactions between the co-cultured organisms. Microbial communities are invariably heterogeneous, possessing different phenotypic states compartmentalised in each microorganism. Furthermore, each strain can switch to alternative phenotypic states exhibiting different metabolic and fitness potentials. These transitions are related to the biological behaviour exhibited by cellular systems, leading to phenotypic diversification and fitness evolution processes. In this work, Escherichia coli and Saccharomyces cerevisiae were co-cultured with different feeding profiles designed to generate transitory environmental conditions and metabolic shifts, leading to the co-existence of the two microbial strains in continuous cultures. Intermittent feeding profiles allowed to generate temporal niches, providing fitness advantages to each strain and further ensuring co-culture stability. Single-strain cultures were used for inferring the growth and metabolic parameters for each strain. These parameters were then used to design a simplified cybernetic model for the co-culture, which simulated the consortium performance under continuous and intermittent feeding profiles at various frequencies, feed step times and dilution rates. Two discontinuous feeding profiles were selected for co-culture experiments. Models and experiments pointed out that the intermittent process conditions allowed to produce alternating periodic conditions promoting the growth of E. coli and S. cerevisiae, enabling temporal niche fitness advantages for both strains. E. coli response was found to be less prone to substrate co-utilisation due to its greater catabolic repression features, while S. cerevisiae exhibited more flexibility regarding simultaneous carbon source utilisation. Experiments pointed out that the given intermittent feeding profiles could dynamically stabilise the co-existence of the two strains during long-lasting continuous cultivations. Furthermore, these specific frequencies and feeding profiles affected cellular interaction and community composition.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.