Department of Ecology & Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, United States.
Department of Microbial Biotechnology, Centro Nacional de Biotecnología, CSIC, Cantoblanco, Madrid, Spain.
Elife. 2021 Apr 20;10:e65948. doi: 10.7554/eLife.65948.
A major open question in microbial community ecology is whether we can predict how the components of a diet collectively determine the taxonomic composition of microbial communities. Motivated by this challenge, we investigate whether communities assembled in pairs of nutrients can be predicted from those assembled in every single nutrient alone. We find that although the null, naturally additive model generally predicts well the family-level community composition, there exist systematic deviations from the additive predictions that reflect generic patterns of nutrient dominance at the family level. Pairs of more-similar nutrients (e.g. two sugars) are on average more additive than pairs of more dissimilar nutrients (one sugar-one organic acid). Furthermore, sugar-acid communities are generally more similar to the sugar than the acid community, which may be explained by family-level asymmetries in nutrient benefits. Overall, our results suggest that regularities in how nutrients interact may help predict community responses to dietary changes.
微生物群落生态学中的一个主要开放性问题是，我们能否预测饮食的各个组成部分如何共同决定微生物群落的分类组成。受这一挑战的启发，我们研究了仅由单一营养素组装而成的群落是否可以预测由成对的营养素组装而成的群落。我们发现，尽管零假设的自然加和模型通常可以很好地预测科水平的群落组成，但存在与加和预测存在系统偏差，这些偏差反映了科水平上营养优势的一般模式。更相似的营养素（例如两种糖）对的加和性通常高于更不相似的营养素（一种糖-一种有机酸）对的加和性。此外，糖-酸群落通常与糖群落更为相似，而与酸群落的差异较大，这可能是由于营养益处的科水平不对称性所致。总的来说，我们的结果表明，营养物质相互作用的规律可能有助于预测群落对饮食变化的反应。
