ArticlePLoS computational biology2019
The genetic basis for adaptation of model-designed syntrophic co-cultures.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Growth-coupled microbial biosynthesis of the animal pigment xanthommatin.Nature biotechnology · 2026Article
- Systematic design of auxotrophic strains and media conditions to probe metabolic functions in E. coli.PLoS computational biology · 2026Article
- Adapting OptCouple to Identify Strategies with Increased Product Yields in Community Cohorts ofMetabolites · 2025Article
- Deciphering metabolic differentiation during Bacillus subtilis sporulation.Nature communications · 2025Article
- From microbiome composition to functional engineering, one step at a time.Microbiology and molecular biology reviews : MMBR · 2023Review
- Inferring microbial interactions with their environment from genomic and metagenomic data.PLoS computational biology · 2023Article
- Evolutionary repeatability of emergent properties of ecological communities.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Discovery of novel amino acid production traits by evolution of synthetic co-cultures.Microbial cell factories · 2023Article
- Assembling stable syntrophic Escherichia coli communities by comprehensively identifying beneficiaries of secreted goods.Cell systems · 2021Article
- Mechanistic models of microbial community metabolism.Molecular omics · 2021Review
- Modelling microbial communities: Harnessing consortia for biotechnological applications.Computational and structural biotechnology journal · 2021Review
- Methanol-dependent Escherichia coli strains with a complete ribulose monophosphate cycle.Nature communications · 2020Article
- The microbial exometabolome: ecological resource and architect of microbial communities.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020Review
- Deep reinforcement learning for the control of microbial co-cultures in bioreactors.PLoS computational biology · 2020Article
- The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology.Metabolic engineering · 2019Review
Corrections and comments
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Authors and funding
14 authors.
Funding
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 that empower the creation of cooperative communities.
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