Department of Genetics, Physiology and Microbiology, Biology Faculty, Complutense University of Madrid, Madrid, Spain.
Department of Microbial and Plant Biotechnology, Centre for Biological Research (CIB-CSIC), Madrid, Spain.
Mol Syst Biol. 2023 Sep 12;19(9):e11613. doi: 10.15252/msb.202311613. Epub 2023 Aug 7.
Predictively linking taxonomic composition and quantitative ecosystem functions is a major aspiration in microbial ecology, which must be resolved if we wish to engineer microbial consortia. Here, we have addressed this open question for an ecological function of major biotechnological relevance: alcoholic fermentation in wine yeast communities. By exhaustively phenotyping an extensive collection of naturally occurring wine yeast strains, we find that most ecologically and industrially relevant traits exhibit phylogenetic signal, allowing functional traits in wine yeast communities to be predicted from taxonomy. Furthermore, we demonstrate that the quantitative contributions of individual wine yeast strains to the function of complex communities followed simple quantitative rules. These regularities can be integrated to quantitatively predict the function of newly assembled consortia. Besides addressing theoretical questions in functional ecology, our results and methodologies can provide a blueprint for rationally managing microbial processes of biotechnological relevance.
预测分类组成与定量生态系统功能之间的联系是微生物生态学的主要目标,如果我们希望设计微生物群落,就必须解决这个问题。在这里,我们针对一个具有重要生物技术相关性的生态功能解决了这个开放性问题:葡萄酒酵母群落中的酒精发酵。通过对大量自然发生的葡萄酒酵母菌株进行详尽的表型分析,我们发现大多数具有生态和工业相关性的特征表现出系统发育信号,从而可以根据分类学预测葡萄酒酵母群落中的功能特征。此外,我们证明,单个葡萄酒酵母菌株对复杂群落功能的定量贡献遵循简单的定量规则。这些规律可以整合起来,对新组装的群落的功能进行定量预测。除了解决功能生态学中的理论问题外,我们的结果和方法还可以为合理管理具有生物技术相关性的微生物过程提供蓝图。