文献类型：期刊文献

英文题名：Synthetic, Context-Dependent Microbial Consortium of Predator and Prey

作者：Liu, Feng[1,2];Mao, Junwen[3];Lu, Ting[2,4,5,6,7];Hua, Qiang[1]

机构：[1]East China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai 200237, Peoples R China;[2]Univ Illinois, Dept Bioengn, Urbana, IL 61801 USA;[3]Huzhou Univ, Dept Phys, Huzhou 313000, Peoples R China;[4]Univ Illinois, Dept Phys, Urbana, IL 61801 USA;[5]Univ Illinois, Ctr Biophys & Quantitat Biol, Urbana, IL 61801 USA;[6]Univ Illinois, Carl R Woese Inst Genom Biol, Urbana, IL 61801 USA;[7]Univ Illinois, Natl Ctr Supercomp Applicat, Urbana, IL 61801 USA

年份：2019

卷号：8

期号：8

起止页码：1713

外文期刊名：ACS SYNTHETIC BIOLOGY

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000481979300003)】；

基金：F.L. was supported by the Chinese Scholarship Council. J.M. was supported by the National Natural Science Foundation of China (11575059) and Key Laboratory of Vector Biology and Pathogen Control of Zhejiang Province. T.L. was supported by the National Science Foundation (1553649), Department of Energy (DE-SC0019185), and Office of Naval Research (N000141612525). Q.H. was supported by the National Natural Science Foundation of China (21776081).

语种：英文

外文关键词：synthetic biology; microbial consortia; predator-prey; context dependence; microbial interactions; ecosystem dynamics

摘要：Synthetic microbial consortia are a rapidly growing area of synthetic biology. So far, most consortia are designed without considering their environments; however, in nature, microbial interactions are constantly modulated by cellular contexts, which, in principle, can dramatically alter community behaviors. Here we present the construction, validation, and characterization of an engineered bacterial predator-prey consortium that involves a chloramphenicol (CM)-mediated, context-dependent cellular interaction. We show that varying the CM level in the environment can induce success in the ecosystem with distinct patterns from predator dominance to prey-predator crossover to ecosystem collapse. A mathematical model successfully captures the essential dynamics of the experimentally observed patterns. We also illustrate that such a dependence enriches community dynamics under different initial conditions and further test the resistance of the consortium to invasion with engineered bacterial strains. This work exemplifies the role of the context dependence of microbial interactions in modulating ecosystem dynamics, underscoring the importance of including contexts into the design of engineered ecosystems for synthetic biology applications.