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Steering ecological-evolutionary dynamics to improve artificial selection of microbial communities

Author

Listed:
  • Li Xie

    (Fred Hutchinson Cancer Research Center)

  • Wenying Shou

    (University College London)

Abstract

Microbial communities often perform important functions that depend on inter-species interactions. To improve community function via artificial selection, one can repeatedly grow many communities to allow mutations to arise, and “reproduce” the highest-functioning communities by partitioning each into multiple offspring communities for the next cycle. Since improvement is often unimpressive in experiments, we study how to design effective selection strategies in silico. Specifically, we simulate community selection to improve a function that requires two species. With a “community function landscape”, we visualize how community function depends on species and genotype compositions. Due to ecological interactions that promote species coexistence, the evolutionary trajectory of communities is restricted to a path on the landscape. This restriction can generate counter-intuitive evolutionary dynamics, prevent the attainment of maximal function, and importantly, hinder selection by trapping communities in locations of low community function heritability. We devise experimentally-implementable manipulations to shift the path to higher heritability, which speeds up community function improvement even when landscapes are high dimensional or unknown. Video walkthroughs: https://go.nature.com/3GWwS6j ; https://online.kitp.ucsb.edu/online/ecoevo21/shou2/ .

Suggested Citation

  • Li Xie & Wenying Shou, 2021. "Steering ecological-evolutionary dynamics to improve artificial selection of microbial communities," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26647-4
    DOI: 10.1038/s41467-021-26647-4
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    References listed on IDEAS

    as
    1. Niels Klitgord & Daniel Segrè, 2010. "Environments that Induce Synthetic Microbial Ecosystems," PLOS Computational Biology, Public Library of Science, vol. 6(11), pages 1-17, November.
    2. Eric D. Kelsic & Jeffrey Zhao & Kalin Vetsigian & Roy Kishony, 2015. "Counteraction of antibiotic production and degradation stabilizes microbial communities," Nature, Nature, vol. 521(7553), pages 516-519, May.
    3. Sasha F. Levy & Jamie R. Blundell & Sandeep Venkataram & Dmitri A. Petrov & Daniel S. Fisher & Gavin Sherlock, 2015. "Quantitative evolutionary dynamics using high-resolution lineage tracking," Nature, Nature, vol. 519(7542), pages 181-186, March.
    4. Lori Niehaus & Ian Boland & Minghao Liu & Kevin Chen & David Fu & Catherine Henckel & Kaitlin Chaung & Suyen Espinoza Miranda & Samantha Dyckman & Matthew Crum & Sandra Dedrick & Wenying Shou & Babak , 2019. "Microbial coexistence through chemical-mediated interactions," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
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