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Title: The genetic basis for adaptation of model-designed syntrophic co-cultures

Abstract

Understanding the fundamental characteristics of microbial communities could have far reaching implications for human health and applied biotechnology. Despite this, much is still unknown regarding the genetic basis and evolutionary strategies underlying the formation of viable synthetic communities. By pairing auxotrophic mutants in co-culture, it has been demonstrated that viable nascent E. coli communities can be established where the mutant strains are metabolically coupled. A novel algorithm, OptAux, was constructed to design 61 unique multi-knockout E. coli auxotrophic strains that require significant metabolite uptake to grow. These predicted knockouts included a diverse set of novel non-specific auxotrophs that result from inhibition of major biosynthetic subsystems. Three OptAux predicted non-specific auxotrophic strains—with diverse metabolic deficiencies—were co-cultured with an L-histidine auxotroph and optimized via adaptive laboratory evolution (ALE). Time-course sequencing revealed the genetic changes employed by each strain to achieve higher community growth rates and provided insight into mechanisms for adapting to the syntrophic niche. A community model of metabolism and gene expression was utilized to predict the relative community composition and fundamental characteristics of the evolved communities. This work presents new insight into the genetic strategies underlying viable nascent community formation and a cutting-edge computational method to elucidate metabolic changes thatmore » empower the creation of cooperative communities.« less

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1];  [1]; ORCiD logo [1]; ORCiD logo [2];  [2];  [3]; ORCiD logo [4]; ORCiD logo [4]; ORCiD logo [4];  [4];  [5]; ORCiD logo [6];  [7]
  1. Univ. of California, San Diego, CA (United States). Dept. of Bioengineering
  2. Univ. of California, San Diego, CA (United States). Bioinformatics and Systems Biology Program
  3. Univ. of California, San Diego, CA (United States). Dept. of Pediatrics; Cornell Univ., Ithaca, NY (United States). Cornell Inst. of Host-Microbe Interactions and Disease
  4. Univ. of California, San Diego, CA (United States). Dept. of Pediatrics
  5. Univ. of California, San Diego, CA (United States). Dept. of Pediatrics; Univ. of California, San Diego, CA (United States). Center for Microbiome Innovation; Univ. of California, San Diego, CA (United States). Dept. of Computer Science and Engineering; Univ. of California, San Diego, CA (United States). Dept. of Bioengineering
  6. Univ. of California, San Diego, CA (United States). Dept. of Bioengineering; Technical Univ. of Denmark, Lyngby (Denmark). Novo Nordisk Foundation Center for Biosustainability
  7. Ecole Polytechnique Federale Lausanne (Switzlerland)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1499215
Alternate Identifier(s):
OSTI ID: 1497437; OSTI ID: 1530862
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Published Article
Journal Name:
PLoS Computational Biology (Online)
Additional Journal Information:
Journal Name: PLoS Computational Biology (Online); Journal Volume: 15; Journal Issue: 3; Journal ID: ISSN 1553-7358
Publisher:
Public Library of Science
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Lloyd, Colton J., King, Zachary A., Sandberg, Troy E., Hefner, Ying, Olson, Connor A., Phaneuf, Patrick V., O’Brien, Edward J., Sanders, Jon G., Salido, Rodolfo A., Sanders, Karenina, Brennan, Caitriona, Humphrey, Gregory, Knight, Rob, Feist, Adam M., and Hatzimanikatis, Vassily. The genetic basis for adaptation of model-designed syntrophic co-cultures. United States: N. p., 2019. Web. doi:10.1371/journal.pcbi.1006213.
Lloyd, Colton J., King, Zachary A., Sandberg, Troy E., Hefner, Ying, Olson, Connor A., Phaneuf, Patrick V., O’Brien, Edward J., Sanders, Jon G., Salido, Rodolfo A., Sanders, Karenina, Brennan, Caitriona, Humphrey, Gregory, Knight, Rob, Feist, Adam M., & Hatzimanikatis, Vassily. The genetic basis for adaptation of model-designed syntrophic co-cultures. United States. doi:10.1371/journal.pcbi.1006213.
Lloyd, Colton J., King, Zachary A., Sandberg, Troy E., Hefner, Ying, Olson, Connor A., Phaneuf, Patrick V., O’Brien, Edward J., Sanders, Jon G., Salido, Rodolfo A., Sanders, Karenina, Brennan, Caitriona, Humphrey, Gregory, Knight, Rob, Feist, Adam M., and Hatzimanikatis, Vassily. Fri . "The genetic basis for adaptation of model-designed syntrophic co-cultures". United States. doi:10.1371/journal.pcbi.1006213.
@article{osti_1499215,
title = {The genetic basis for adaptation of model-designed syntrophic co-cultures},
author = {Lloyd, Colton J. and King, Zachary A. and Sandberg, Troy E. and Hefner, Ying and Olson, Connor A. and Phaneuf, Patrick V. and O’Brien, Edward J. and Sanders, Jon G. and Salido, Rodolfo A. and Sanders, Karenina and Brennan, Caitriona and Humphrey, Gregory and Knight, Rob and Feist, Adam M. and Hatzimanikatis, Vassily},
abstractNote = {Understanding the fundamental characteristics of microbial communities could have far reaching implications for human health and applied biotechnology. Despite this, much is still unknown regarding the genetic basis and evolutionary strategies underlying the formation of viable synthetic communities. By pairing auxotrophic mutants in co-culture, it has been demonstrated that viable nascent E. coli communities can be established where the mutant strains are metabolically coupled. A novel algorithm, OptAux, was constructed to design 61 unique multi-knockout E. coli auxotrophic strains that require significant metabolite uptake to grow. These predicted knockouts included a diverse set of novel non-specific auxotrophs that result from inhibition of major biosynthetic subsystems. Three OptAux predicted non-specific auxotrophic strains—with diverse metabolic deficiencies—were co-cultured with an L-histidine auxotroph and optimized via adaptive laboratory evolution (ALE). Time-course sequencing revealed the genetic changes employed by each strain to achieve higher community growth rates and provided insight into mechanisms for adapting to the syntrophic niche. A community model of metabolism and gene expression was utilized to predict the relative community composition and fundamental characteristics of the evolved communities. This work presents new insight into the genetic strategies underlying viable nascent community formation and a cutting-edge computational method to elucidate metabolic changes that empower the creation of cooperative communities.},
doi = {10.1371/journal.pcbi.1006213},
journal = {PLoS Computational Biology (Online)},
number = 3,
volume = 15,
place = {United States},
year = {2019},
month = {3}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1371/journal.pcbi.1006213

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Works referenced in this record:

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