Artificial selection improves pollutant degradation by bacterial communities.

Details

Serval ID
serval:BIB_CDC71B10EDEF
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Artificial selection improves pollutant degradation by bacterial communities.
Journal
Nature communications
Author(s)
Arias-Sánchez F.I., Vessman B., Haym A., Alberti G., Mitri S.
ISSN
2041-1723 (Electronic)
ISSN-L
2041-1723
Publication state
Published
Issued date
07/09/2024
Peer-reviewed
Oui
Volume
15
Number
1
Pages
7836
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
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.
Keywords
Bacteria/genetics, Bacteria/metabolism, Bacteria/classification, Biodegradation, Environmental, Microbiota/genetics, Selection, Genetic, Algorithms, Environmental Pollutants/metabolism
Pubmed
Web of science
Open Access
Yes
Create date
13/09/2024 13:56
Last modification date
29/10/2024 7:21
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