Wine Fermentation as a Model System for Microbial Ecology and Evolution
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2025
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Wiley
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Belda, I., Izquierdo-Gea, S., Benitez-Dominguez, B., Ruiz, J. and Vila, J.C.C. (2025), Wine Fermentation as a Model System for Microbial Ecology and Evolution. Environ Microbiol, 27: e70092. https://doi.org/10.1111/1462-2920.70092
Abstract
In vitro microbial communities have proven to be invaluable model systems for studying ecological and evolutionary processes experimentally. However, it remains unclear whether quantitative insights obtained from these laboratory systems can be applied to complex communities assembling and evolving in their natural ecological context. To bridge the gap between the lab and the ‘real-world’, there is a need for laboratory model systems that better approximate natural and semi-natural ecosystems. Wine fermentation presents an ideal system for this purpose, balancing experimental tractability with rich ecological and evolutionary dynamics. In this perspective piece we outline the key features that make wine fermentation a fruitful model system for ecologists and evolutionary biologists. We highlight the diversity of environmentally mediated interactions that shape community dynamics during fermentation, the complex evolutionary history of wine microbial populations, and the opportunity to study the impact of complex ecologies on evolutionary dynamics. By integrating knowledge from both wine research and microbial ecology and evolution we aim to enhance understanding and foster collaboration between these fields.
Description
Recent research by Ignacio Belda's lab has been supported by grants PID2019-105834GA-I00 (acronym Wineteractions) and PID2022-138343NB-I00 (acronym INDUSYNCON) funded by the Spanish State Research Agency/Science and Research Ministry (https://doi.org/10.13039/501100011033) and by ERDF/EU. Sergio Izquierdo-Gea acknowledges his predoctoral grant FPU21/06830 funded by the Spanish Ministry of Science, Innovation and Universities. Belen Benítez-Dominguez acknowledges her predoctoral grant PRE2022-103063 funded by MICIU/AEI/10.13039/501100011033 and by ESF+. JCC Vila was partially funded by a Center for Computational (CEHG), Evolutionary and Human Genomics postdoctoral fellowship at Stanford.













