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Title: Interaction variability shapes succession of synthetic microbial ecosystems

Abstract

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.

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [3]
  1. Univ. of Illinois at Urbana-Champaign, IL (United States); East China Univ. of Science and Technology, Shanghai (China)
  2. Univ. of Illinois at Urbana-Champaign, IL (United States); Huzhou Univ. (China)
  3. Univ. of Illinois at Urbana-Champaign, IL (United States)
  4. East China Univ. of Science and Technology, Shanghai (China)
  5. Zhejiang Univ., Hangzhou (China)
  6. Univ. of Illinois at Urbana-Champaign, IL (United States); Carle Illinois College of Medicine, Urbana, IL (United States)
Publication Date:
Research Org.:
University of Illinois at Urbana-Champaign
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Science Foundation (NSF); US Department of the Navy, Office of Naval Research (ONR); China Scholarship Council; National Natural Science Foundation of China (NNSFC)
OSTI Identifier:
1595091
Grant/Contract Number:  
SC0019185; 1553649; N000141612525; 11575059; 11847315
Resource Type:
Accepted Manuscript
Journal Name:
Nature Communications
Additional Journal Information:
Journal Volume: 11; Journal Issue: 1; Journal ID: ISSN 2041-1723
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Liu, Feng, Mao, Junwen, Kong, Wentao, Hua, Qiang, Feng, Youjun, Bashir, Rashid, and Lu, Ting. Interaction variability shapes succession of synthetic microbial ecosystems. United States: N. p., 2020. Web. doi:10.1038/s41467-019-13986-6.
Liu, Feng, Mao, Junwen, Kong, Wentao, Hua, Qiang, Feng, Youjun, Bashir, Rashid, & Lu, Ting. Interaction variability shapes succession of synthetic microbial ecosystems. United States. doi:10.1038/s41467-019-13986-6.
Liu, Feng, Mao, Junwen, Kong, Wentao, Hua, Qiang, Feng, Youjun, Bashir, Rashid, and Lu, Ting. Thu . "Interaction variability shapes succession of synthetic microbial ecosystems". United States. doi:10.1038/s41467-019-13986-6. https://www.osti.gov/servlets/purl/1595091.
@article{osti_1595091,
title = {Interaction variability shapes succession of synthetic microbial ecosystems},
author = {Liu, Feng and Mao, Junwen and Kong, Wentao and Hua, Qiang and Feng, Youjun and Bashir, Rashid and Lu, Ting},
abstractNote = {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.},
doi = {10.1038/s41467-019-13986-6},
journal = {Nature Communications},
number = 1,
volume = 11,
place = {United States},
year = {2020},
month = {1}
}

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