Ecology and Evolutionary Biology as Frameworks to Study Wine Fermentations
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2025
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John Wiley & Sons
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Belda, I., Benitez-Dominguez, B., Izquierdo-Gea, S., Vila, J. C. C., & Ruiz, J. (2025). Ecology and Evolutionary Biology as Frameworks to Study Wine Fermentations. En Microbial Biotechnology (Vol. 18, Número 3). John Wiley and Sons Ltd. https://doi.org/10.1111/1751-7915.70078
Abstract
Winemaking has leveraged microbiology to enhance wine quality, typically by engineering and inoculating individual yeast strains with desirable traits. However, yeast strains do not grow alone during wine fermentation, rather they are embedded in diverse and evolving microbial communities exhibiting complex ecological dynamics. Understanding and predicting the interplay between the yeast community over the course of the species succession and the chemical matrix of wine can benefit from recognising that wine, like all microbial ecosystems, is subject to general ecological and evolutionary rules. In this piece, we outline how conceptual and methodological frameworks from community ecology and evolutionary biology can assist wine yeast researchers in improving wine fermentation processes by understanding the mechanisms governing population dynamics, predicting and engineering these important microcosms, and unlocking the genetic potential for wine strain development.
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We thank members of Sanchez, Petrov and Microbial Interactions and Ecology Lab for helpful discussion. Recent research by Ignacio Belda's laboratory 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. Belen Benítez-Dominguez acknowledges her predoctoral grant PRE2022-103063 funded by ICIU/AEI/10.13039/501100011033 and by ESF+. Sergio Izquierdo-Gea acknowledges his predoctoral grant FPU21/06830 funded by the Spanish Ministry of Science, Innovation and Universities. JCC Vila was partially funded by a Center for Computational (CEHG), and Evolutionary and Human Genomics postdoctoral fellowship at Stanford.













