焊剂(冶金)
扩散
生化工程
通量平衡分析
人口
代谢通量分析
产品(数学)
代谢途径
微生物种群生物学
多样性(控制论)
降级(电信)
生物
生物系统
化学
计算机科学
计算生物学
生物化学
新陈代谢
数学
工程类
物理
遗传学
热力学
统计
细菌
人口学
社会学
有机化学
电信
几何学
作者
Xiaoli Chen,Miaoxiao Wang,Yexin Xing -,Yong Nie,Xiao‐Lei Wu
标识
DOI:10.1021/acssynbio.3c00022
摘要
Metabolic division of labor (MDOL) represents one of the most commonly occurring interactions within natural microbial communities. Specifically, in a variety of MDOL systems engaged in hydrocarbon degradation, a sequential degradation is performed by several members with final products that are necessary for the growth of each member. In these MDOL systems, each strain catalyzes one or more specific reactions of a multistep metabolic pathway, whose end products are then allocated among the participants. While the benefit allocation is independent of metabolic flux in well-mixed environments, it remains unclear how the benefits are allocated when diffusion is limited. Here, we investigated how MDOL communities assemble in a diffusion-limited environment, by combining mathematical modeling with experimental inquiry using a synthetic consortium engaged in MDOL. Our model analysis in a diffusion-limited environment showed that, when the growth of all populations in the community relies on the final product that can only be produced by the last population, a diffusion gradient of the final products may create a bias favoring the member producing the final products, resulting in a higher relative abundance of the final product producer. Moreover, such asymmetric allocation of the final products is enhanced by both the lower diffusion rate and the higher metabolic flux (i.e., the higher yields of the final products) in the MDOL. Our results show that in a diffusively confined environment, metabolic flux constitutes a determining factor in the assembly of the MDOL community. Together, our findings are critical for a better understanding of how resource-sharing microbial communities are established and should assist in designing such communities for improved biomanufacturing and bioremediation.
科研通智能强力驱动
Strongly Powered by AbleSci AI