Microbial communities are characterized by complex interaction, including cooperation and cheating, which have significant ecological and applied implications. However, the factors determining the success of cooperators in the presence of cheaters remain poorly understood. Here, we investigate the dynamics of cooperative interactions in a consortium consisting of a cross-feeding pair and a cheater strain using individual-based simulations and an engineered L. cremoris toy consortium. Our simulations reveal first contact time between cooperators as a critical predictor for cooperator success. By manipulating the relative distances between cooperators and cheaters or the background growth rates, influenced by the cost of cooperation, we can modulate this first contact time and influence cooperator success. Our study underscores the importance of cooperators coming into contact with each other on time, which provides a simple and generalizable framework for understanding and designing cooperative interactions in microbial communities. These findings contribute to our understanding of cross-feeding dynamics and offer practical insights for synthetic and biotechnological applications.@en

It is common practice in the development of bioprocesses to genetically modify a microorganism and study a large number of resulting mutants in order to select the ones that perform best for use at the industrial scale. At industrial scale, strict nutrient-controlled growth conditions are imposed to control the metabolic activity and growth rate of the microorganism, thereby enhancing the expression of the product of interest. Although it is known that microorganisms that perform best under these strictly controlled conditions are not the same as the ones that perform best under uncontrolled batch conditions, screening, and selection is predominantly performed under batch conditions. Tools that afford high throughput on the one hand and dynamic control over cultivation conditions on the other hand are not yet available. Microbioreactors offer the potential to address this problem, resolving the gap between bioprocess development and industrial scale use. In this review, we highlight the current state-of-the-art of microbioreactors that offer the potential to screen microorganisms under dynamically controlled conditions. We classify them into: (i) microtiter plate-based platforms, (ii) microfluidic chamber-based platforms, and (iii) microfluidic droplet-based platforms. We conclude this review by discussing the opportunities of nutrient-fed microbioreactors in the field of biotechnology.

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Microbial community engineering aims for enrichment of a specific microbial trait by imposing specific cultivation conditions. This work demonstrates that things may be more complicated than typically presumed and that microbial competition can be affected by seemingly insignificant variables, like in this case the type of acid used for pH control. Aerobic bioreactors pulse fed with acetate operated with hydrochloric acid resulted in the enrichment of Plasticicumulans acidivorans, and changing the pH controlling agent to sulfuric acid shifted the community towards Zoogloea sp. Further research demonstrated that the change in community structure was not directly caused by the change in acid used for pH control, but resulted from the difference in corrosive strength of both acids and the related iron leaching from the bioreactor piping. Neither system was iron deficient, suggesting that the biological availability of iron is affected by the leaching process. Our results demonstrate that microbial competition and process development can be affected dramatically by secondary factors related to nutrient supply and bioavailability, and is way more complex than generally assumed in a single carbon substrate limited process.

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As natural selection acts on individual organisms the evolution of costly cooperation between microorganisms is an intriguing phenomenon. Introduction of spatial structure to privatize exchanged molecules can explain the evolution of cooperation. However, in many natural systems cells can also grow to low cell concentrations in the absence of these exchanged molecules, thus showing “cooperation-independent background growth”. We here serially propagated a synthetic cross-feeding consortium of lactococci in the droplets of a water-in-oil emulsion, essentially mimicking group selection with varying founder population sizes. The results show that when the growth of cheaters completely depends on cooperators, cooperators outcompete cheaters. However, cheaters outcompete cooperators when they can independently grow to only ten percent of the consortium carrying capacity. This result is the consequence of a probabilistic effect, as low founder population sizes in droplets decrease the frequency of cooperator co-localization. Cooperator-enrichment can be recovered by increasing the founder population size in droplets to intermediate values. Together with mathematical modelling our results suggest that co-localization probabilities in a spatially structured environment leave a small window of opportunity for the evolution of cooperation between organisms that do not benefit from their cooperative trait when in isolation or form multispecies aggregates.

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During storage and ripening of fermented foods, Lactococcus cremoris is predominantly in a non-growing state. L. cremoris can become stationary due to starvation or acidification, and its metabolism in these non-growing states affects the fermented product. Available studies on the response of L. cremoris to acid and starvation stress are based on population level data. We here characterized the energetic state and the protein synthesis capacity of stationary L. cremoris cultures at the single cell level. We show that glucose starved stationary cells are energy-depleted, while acid-induced stationary cells are energized and can maintain a pH gradient over their membrane. In the absence of glucose and arginine, a small pH gradient can still be maintained. Subpopulations of stationary cells can synthesize protein without a nitrogen source, and the subpopulation size decreases with increasing stationary phase length. Protein synthesis capacity during starvation only benefits culturability after 6 days. These results highlight significant differences between glucose starved stationary and acid-induced stationary cells. Furthermore, they show that the physiology of stationary phase L. cremoris cells is multi-facetted and heterogeneous, and the presence of an energy source during stationary phase impacts the cells capacity to adapt to their environment.

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Metabolic interactions between cells affect microbial community compositions and hence their function in ecosystems. It is well-known that under competition for the exchanged metabolite, concentration gradients constrain the distances over which interactions can occur. However, interaction distances are typically quantified in two-dimensional systems or without accounting for competition or other metabolite-removal, conditions which may not very often match natural ecosystems. We here analyze the impact of cell-to-cell distance on unidirectional cross-feeding in a three-dimensional aqueous system with competition for the exchanged metabolite. Effective interaction distances were computed with a reaction-diffusion model and experimentally verified by growing a synthetic consortium of 1 µm-sized metabolite producer, receiver, and competitor cells in different spatial structures. We show that receivers cannot interact with producers located on average 15 µm away from them, as product concentration gradients flatten close to producer cells. We developed an aggregation protocol and varied the receiver cells’ product affinity, to show that within producer–receiver aggregates even low-affinity receiver cells could interact with producers. These results show that competition or other metabolite-removal of a public good in a three-dimensional system reduces metabolic interaction distances to the low µm-range, highlighting the importance of concentration gradients as physical constraint for cellular interactions.

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