ArticleNature communications2024
Artificial selection improves pollutant degradation by bacterial communities.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Article
- Microbial biotechnology meets ecological theory: a unified framework to design industrial microbial consortia.International microbiology : the official journal of the Spanish Society for Microbiology · 2026Review
- Translational microbiomes in agriculture: microbial communities as tools to effect host and system health for improved crop production.Applied and environmental microbiology · 2026Review
- Novel artificial selection method improves function of simulated microbial communities.PLoS computational biology · 2026Article
- Potentiators empower synthetic microbiomes as silent guardians against co-contamination.Nature communications · 2025Article
- Evolution of One Species Increases Resistance to Invasion in a Simple Synthetic Community.Microbial ecology · 2025Article
- The success of artificial selection for collective composition hinges on initial and target values.eLife · 2025Article
- Vulnerability of soil food webs to chemical pollution and climate change.Nature ecology & evolution · 2025Review
- Designing synthetic microbial communities for enhanced anaerobic waste treatment.Applied and environmental microbiology · 2025Review
- Ecology and Evolutionary Biology as Frameworks to Study Wine Fermentations.Microbial biotechnology · 2025Review
- Directed Evolution of Microbial Communities in Fermented Foods: Strategies, Mechanisms, and Challenges.Foods (Basel, Switzerland) · 2025Review
- Ecological design of high-performance synthetic microbial communities: from theoretical foundations to functional optimization.ISME communications · 2025Review
- Environmental Impact of Xenobiotic Aromatic Compounds and Their Biodegradation Potential inInternational journal of molecular sciences · 2024Review
- Artificial selection improves pollutant degradation by bacterial communities.Nature communications · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
Artificial selection is a promising way to improve microbial community functions, but previous experiments have only shown moderate success. Here, we experimentally evaluate a new method that was inspired by genetic algorithms to artificially select small bacterial communities of known species composition based on their degradation of an industrial pollutant. Starting from 29 randomly generated four-species communities, we repeatedly grew communities for four days, selected the 10 best-degrading communities, and rearranged them into 29 new communities composed of four species of equal ratios whose species compositions resembled those of the most successful communities from the previous round. The best community after 18 such rounds of selection degraded the pollutant better than the best community in the first round. It featured member species that degrade well, species that degrade badly alone but improve community degradation, and free-rider species that did not contribute to community degradation. Most species in the evolved communities did not differ significantly from their ancestors in their phenotype, suggesting that genetic evolution plays a small role at this time scale. These experiments show that artificial selection on microbial communities can work in principle, and inform on how to improve future experiments.
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