文献类型：期刊文献

英文题名：Interaction variability shapes succession of synthetic microbial ecosystems

作者：Liu, Feng[1,2,3,4];Mao, Junwen[1,2,5];Kong, Wentao[1,2];Hua, Qiang[3,4];Feng, Youjun[6];Bashir, Rashid[1,7,8];Lu, Ting[1,2,9,10,11]

机构：[1]Univ Illinois, Dept Bioengn, Urbana, IL 61801 USA;[2]Univ Illinois, Carl R Woese Inst Genom Biol, Urbana, IL 61801 USA;[3]East China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai, Peoples R China;[4]East China Univ Sci & Technol, Sch Bioengn, Shanghai, Peoples R China;[5]Huzhou Univ, Dept Phys, Huzhou, Peoples R China;[6]Zhejiang Univ, Sch Med, Hangzhou, Peoples R China;[7]Univ Illinois, Micro & Nanotechnol Lab, Urbana, IL USA;[8]Carle Illinois Coll Med, Urbana, IL USA;[9]Univ Illinois, Dept Phys, Urbana, IL 61801 USA;[10]Univ Illinois, Ctr Biophys & Quantitat Biol, Urbana, IL 61801 USA;[11]Univ Illinois, Natl Ctr Supercomp Applicat, Urbana, IL 61801 USA

年份：2020

卷号：11

期号：1

外文期刊名：NATURE COMMUNICATIONS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000511911600009)】；

基金：We thank Prof. Jon Nissen-Meyer and Prof. Todd Klaenhammer for their generous. pngts of DNA materials. This work was supported by the National Science Foundation (1553649), Office of Naval Research (N000141612525) and Department of Energy (DE-SC0019185). F.L. was supported by the China Scholarship Council. J.M. was supported by the China Scholarship Council and the National Natural Science Foundation of China (11575059 and 11847315). Q.H. was supported by the Research Program of the State Key Laboratory of Bioreactor Engineering and 111 Project (B18022).

语种：英文

摘要：Cellular interactions are a major driver for the assembly and functioning of microbial communities. Their strengths are shown to be highly variable in nature; however, it is unclear how such variations regulate community behaviors. Here we construct synthetic Lactococcus lactis consortia and mathematical models to elucidate the role of interaction variability in ecosystem succession and to further determine if casting variability into modeling empowers bottom-up predictions. For a consortium of bacteriocin-mediated cooperation and competition, we find increasing the variations of cooperation, from either altered labor partition or random sampling, drives the community into distinct structures. When the cooperation and competition are additionally modulated by pH, ecosystem succession becomes jointly controlled by the variations of both interactions and yields more diversified dynamics. Mathematical models incorporating variability successfully capture all of these experimental observations. Our study demonstrates interaction variability as a key regulator of community dynamics, providing insights into bottom-up predictions of microbial ecosystems.