Production of Cambodian rice wine involves complex microbial consortia. Indeed, previous studies focused on traditional microbial starters used for this product revealed that three microbial strains with complementary metabolic activities are required for an effective fermentation, i.e., filamentous fungi (Rhizopus oryzae), yeast (Saccharomyces cerevisiae), and lactic acid bacteria (Lactobacillus plantarum). Modulating the ratio between these three key players led to significant differences, not only in terms of ethanol and organic acid production, but also on the profile of volatile compounds, in comparison with natural communities. However, we observed that using an equal ratio of spores/cells of the three microbial strains during inoculation led to flavor profile and ethanol yield close to that obtained through the use of natural communities. Compartmentalization of metabolic tasks through the use of a biofilm cultivation device allows further improvement of the whole fermentation process, notably by increasing the amount of key components of the aroma profile of the fermented beverage (i.e., mainly phenylethyl alcohol, isobutyl alcohol, isoamyl alcohol, and 2-methyl-butanol) and reducing the amount of off-flavor compounds. This study is a step forward in our understanding of interkingdom microbial interactions with strong application potential in food biotechnology.

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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.