ArticlePLoS biology2019
Simulations reveal challenges to artificial community selection and possible strategies for success.
Article in PLoS biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Seed-microbiome interactions: Mechanistic insights and utilization toward seed performance for sustainable agriculture.Plant communications · 2026Review
- Novel artificial selection method improves function of simulated microbial communities.PLoS computational biology · 2026Article
- The success of artificial selection for collective composition hinges on initial and target values.eLife · 2025Article
- Directed Evolution of Microbial Communities in Fermented Foods: Strategies, Mechanisms, and Challenges.Foods (Basel, Switzerland) · 2025Review
- Adaptive laboratory evolution enhances cell yield and lipid production ofFrontiers in microbiology · 2025Article
- Artificial selection improves pollutant degradation by bacterial communities.Nature communications · 2024Article
- Stability of ecologically scaffolded traits during evolutionary transitions in individuality.Nature communications · 2024Article
- Article
- Geometry of ecological coexistence and niche differentiation.Physical review. E · 2023Article
- Partner-assisted artificial selection of a secondary function for efficient bioremediation.iScience · 2023Article
- Geometry of ecological coexistence and niche differentiation.bioRxiv : the preprint server for biology · 2023Article
- Understanding cellular growth strategies via optimal control.Journal of the Royal Society, Interface · 2023Article
- Ecological landscapes guide the assembly of optimal microbial communities.PLoS computational biology · 2023Article
- The effectiveness of artificial microbial community selection: a conceptual framework and a meta-analysis.Frontiers in microbiology · 2023Article
- Guided by the principles of microbiome engineering: Accomplishments and perspectives for environmental use.mLife · 2022Review
- Artificial selection methods from evolutionary computing show promise for directed evolution of microbes.eLife · 2022Article
- Artificial Selection on Microbiomes To Breed Microbiomes That Confer Salt Tolerance to Plants.mSystems · 2021Article
- Steering ecological-evolutionary dynamics to improve artificial selection of microbial communities.Nature communications · 2021Article
- Closed microbial communities self-organize to persistently cycle carbon.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Engineering complex communities by directed evolution.Nature ecology & evolution · 2021Article
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Abstract
Multispecies microbial communities often display "community functions" arising from interactions of member species. Interactions are often difficult to decipher, making it challenging to design communities with desired functions. Alternatively, similar to artificial selection for individuals in agriculture and industry, one could repeatedly choose communities with the highest community functions to reproduce by randomly partitioning each into multiple "Newborn" communities for the next cycle. However, previous efforts in selecting complex communities have generated mixed outcomes that are difficult to interpret. To understand how to effectively enact community selection, we simulated community selection to improve a community function that requires 2 species and imposes a fitness cost on one or both species. Our simulations predict that improvement could be easily stalled unless various aspects of selection are carefully considered. These aspects include promoting species coexistence, suppressing noncontributors, choosing additional communities besides the highest functioning ones to reproduce, and reducing stochastic fluctuations in the biomass of each member species in Newborn communities. These considerations can be addressed experimentally. When executed effectively, community selection is predicted to improve costly community function, and may even force species to evolve slow growth to achieve species coexistence. Our conclusions hold under various alternative model assumptions and are therefore applicable to a variety of communities.
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