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Artificial selection of microbial communities: what have we learnt and how can we improve?

Thomas, Joshua L; Rowland-Chandler, Jamila; Shou, Wenying; (2024) Artificial selection of microbial communities: what have we learnt and how can we improve? Current Opinion in Microbiology , 77 , Article 102400. 10.1016/j.mib.2023.102400. Green open access

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Abstract

Microbial communities are capable of performing diverse functions with important bioindustrial and medical applications. One approach to improving community function is to breed new communities by artificially selecting for those displaying high community function (‘community selection’). Importantly, community selection can improve the function of interest without needing to understand how the function arises, just like in classical artificial selection of individuals. However, experimental studies of community selection have had varied and largely limited success. Here, we review a conceptual framework to help foster an understanding of community selection and its associated challenges, and provide broad insights for designing effective selection strategies.

Type: Article
Title: Artificial selection of microbial communities: what have we learnt and how can we improve?
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.mib.2023.102400
Publisher version: https://doi.org/10.1016/j.mib.2023.102400
Language: English
Additional information: Crown Copyright © 2023. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment
URI: https://discovery.ucl.ac.uk/id/eprint/10184469
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