TY - JOUR T1 - Substrate traits shape the structure of microbial community engaged in metabolic division of labor JF - bioRxiv DO - 10.1101/2020.11.18.387787 SP - 2020.11.18.387787 AU - Miaoxiao Wang AU - Xiaoli Chen AU - Yue-Qin Tang AU - Yong Nie AU - Xiao-Lei Wu Y1 - 2021/01/01 UR - http://biorxiv.org/content/early/2021/10/19/2020.11.18.387787.abstract N2 - Metabolic division of labor (MDOL) is widespread in nature, whereby a complex metabolic pathway is shared between different strains within a community for mutual benefit. However, little is known about how the mutual interactions in the microbial community engaged in MDOL are regulated. We hypothesized that when degradation of an organic compound is carried out via MDOL, the substrate traits (i.e., concentration and its toxicity) modulate the benefit allocation between the two microbial populations, thus affecting the structure of this community. We tested this hypothesis by combining mathematical modelling with experiments using engineered synthetic microbial consortia. Numerous modelling analyses suggested that the proportion of the population executing the first metabolic step can be simply estimated by Monod-like formulas governed by substrate traits. The model and the proposed formula quantitatively predicted the structure of our synthetic consortia composed of two strains degrading salicylate through MDOL. Individual-based modelling and colony pattern formation assays further indicated that our rule is also applicable to estimating community structure in spatially structured environments. Our results demonstrate that the structure of the microbial communities can be quantitatively predicted from simple environmental factors, such as substrate concentration and its toxicity, which provides novel perspectives on understanding the assembly of natural communities, as well as insights into how to manage artificial microbial systems.Competing Interest StatementThe authors have declared no competing interest. ER -