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微生物群落组装中的功能吸引子

Functional attractors in microbial community assembly.

作者信息

Estrela Sylvie, Vila Jean C C, Lu Nanxi, Bajić Djordje, Rebolleda-Gómez Maria, Chang Chang-Yu, Goldford Joshua E, Sanchez-Gorostiaga Alicia, Sánchez Álvaro

机构信息

Department of Ecology and Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA.

Department of Ecology and Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA.

出版信息

Cell Syst. 2022 Jan 19;13(1):29-42.e7. doi: 10.1016/j.cels.2021.09.011. Epub 2021 Oct 14.

Abstract

For microbiome biology to become a more predictive science, we must identify which descriptive features of microbial communities are reproducible and predictable, which are not, and why. We address this question by experimentally studying parallelism and convergence in microbial community assembly in replicate glucose-limited habitats. Here, we show that the previously observed family-level convergence in these habitats reflects a reproducible metabolic organization, where the ratio of the dominant metabolic groups can be explained from a simple resource-partitioning model. In turn, taxonomic divergence among replicate communities arises from multistability in population dynamics. Multistability can also lead to alternative functional states in closed ecosystems but not in metacommunities. Our findings empirically illustrate how the evolutionary conservation of quantitative metabolic traits, multistability, and the inherent stochasticity of population dynamics, may all conspire to generate the patterns of reproducibility and variability at different levels of organization that are commonplace in microbial community assembly.

摘要

为了使微生物组生物学成为一门更具预测性的科学,我们必须确定微生物群落的哪些描述性特征是可重复和可预测的,哪些不是,以及原因。我们通过实验研究重复的葡萄糖限制生境中微生物群落组装的平行性和趋同性来解决这个问题。在这里,我们表明,之前在这些生境中观察到的科级趋同性反映了一种可重复的代谢组织,其中主要代谢组的比例可以用一个简单的资源分配模型来解释。反过来,重复群落之间的分类学差异源于种群动态中的多稳态。多稳态也会导致封闭生态系统中出现替代功能状态,但在元群落中不会。我们的研究结果通过实证说明了定量代谢特征的进化保守性、多稳态以及种群动态的内在随机性,可能如何共同作用,在微生物群落组装中不同组织层次上产生常见的可重复性和变异性模式。

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