Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments
Adaptive Laboratory Evolution (ALE) is a powerful tool for engineering and understanding microbial physiology. ALE relies on the selection and enrichment of mutations that enable survival or faster growth under a selective condition imposed by the experimental setup. Phenotypic fitness landscapes ar...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Metabolic Engineering Communications |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S221403012300010X |
| _version_ | 1797405450377887744 |
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| author | Alexander C. Carpenter Adam M. Feist Fergus S.M. Harrison Ian T. Paulsen Thomas C. Williams |
| author_facet | Alexander C. Carpenter Adam M. Feist Fergus S.M. Harrison Ian T. Paulsen Thomas C. Williams |
| author_sort | Alexander C. Carpenter |
| collection | DOAJ |
| description | Adaptive Laboratory Evolution (ALE) is a powerful tool for engineering and understanding microbial physiology. ALE relies on the selection and enrichment of mutations that enable survival or faster growth under a selective condition imposed by the experimental setup. Phenotypic fitness landscapes are often underpinned by complex genotypes involving multiple genes, with combinatorial positive and negative effects on fitness. Such genotype relationships result in mutational fitness landscapes with multiple local fitness maxima and valleys. Traversing local maxima to find a global maximum often requires an individual or sub-population of cells to traverse fitness valleys. Traversing involves gaining mutations that are not adaptive for a given local maximum but are necessary to ‘peak shift’ to another local maximum, or eventually a global maximum. Despite these relatively well understood evolutionary principles, and the combinatorial genotypes that underlie most metabolic phenotypes, the majority of applied ALE experiments are conducted using constant selection pressures. The use of constant pressure can result in populations becoming trapped within local maxima, and often precludes the attainment of optimum phenotypes associated with global maxima. Here, we argue that oscillating selection pressures is an easily accessible mechanism for traversing fitness landscapes in ALE experiments, and provide theoretical and practical frameworks for implementation. |
| first_indexed | 2024-03-09T03:11:10Z |
| format | Article |
| id | doaj.art-9cda84a8ff8247b3962bd063e0d29514 |
| institution | Directory Open Access Journal |
| issn | 2214-0301 |
| language | English |
| last_indexed | 2024-03-09T03:11:10Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Metabolic Engineering Communications |
| spelling | doaj.art-9cda84a8ff8247b3962bd063e0d295142023-12-04T05:21:52ZengElsevierMetabolic Engineering Communications2214-03012023-12-0117e00227Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experimentsAlexander C. Carpenter0Adam M. Feist1Fergus S.M. Harrison2Ian T. Paulsen3Thomas C. Williams4Department of Molecular Sciences and ARC Centre of Excellence in Synthetic Biology, Centre Headquarters, Macquarie University, Sydney, SW, 2109, Australia; CSIRO Synthetic Biology Future Science Platform, Canberra, ACT, 2601, AustraliaDepartment of Bioengineering, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA; Joint BioEnergy Institute, 5885 Hollis Street, 4th Floor, Emeryville, CA, 94608, USA; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Kgs, Lyngby, DenmarkDepartment of Molecular Sciences and ARC Centre of Excellence in Synthetic Biology, Centre Headquarters, Macquarie University, Sydney, SW, 2109, AustraliaDepartment of Molecular Sciences and ARC Centre of Excellence in Synthetic Biology, Centre Headquarters, Macquarie University, Sydney, SW, 2109, AustraliaDepartment of Molecular Sciences and ARC Centre of Excellence in Synthetic Biology, Centre Headquarters, Macquarie University, Sydney, SW, 2109, Australia; CSIRO Synthetic Biology Future Science Platform, Canberra, ACT, 2601, Australia; Corresponding author. Department of Molecular Sciences and ARC Centre of Excellence in Synthetic Biology, Centre Headquarters, Macquarie University, Sydney, SW, 2109, Australia.Adaptive Laboratory Evolution (ALE) is a powerful tool for engineering and understanding microbial physiology. ALE relies on the selection and enrichment of mutations that enable survival or faster growth under a selective condition imposed by the experimental setup. Phenotypic fitness landscapes are often underpinned by complex genotypes involving multiple genes, with combinatorial positive and negative effects on fitness. Such genotype relationships result in mutational fitness landscapes with multiple local fitness maxima and valleys. Traversing local maxima to find a global maximum often requires an individual or sub-population of cells to traverse fitness valleys. Traversing involves gaining mutations that are not adaptive for a given local maximum but are necessary to ‘peak shift’ to another local maximum, or eventually a global maximum. Despite these relatively well understood evolutionary principles, and the combinatorial genotypes that underlie most metabolic phenotypes, the majority of applied ALE experiments are conducted using constant selection pressures. The use of constant pressure can result in populations becoming trapped within local maxima, and often precludes the attainment of optimum phenotypes associated with global maxima. Here, we argue that oscillating selection pressures is an easily accessible mechanism for traversing fitness landscapes in ALE experiments, and provide theoretical and practical frameworks for implementation.http://www.sciencedirect.com/science/article/pii/S221403012300010X |
| spellingShingle | Alexander C. Carpenter Adam M. Feist Fergus S.M. Harrison Ian T. Paulsen Thomas C. Williams Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments Metabolic Engineering Communications |
| title | Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments |
| title_full | Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments |
| title_fullStr | Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments |
| title_full_unstemmed | Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments |
| title_short | Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments |
| title_sort | have you tried turning it off and on again oscillating selection to enhance fitness landscape traversal in adaptive laboratory evolution experiments |
| url | http://www.sciencedirect.com/science/article/pii/S221403012300010X |
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