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Strong environmental memory revealed by experimental evolution in static and fluctuating environments
Evolution in a static environment, such as a laboratory setting with constant and uniform conditions, often proceeds via large-effect beneficial mutations that may become maladaptive in other environments. Conversely, natural settings require populations to endure environmental fluctuations. A sensi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10515930/ https://www.ncbi.nlm.nih.gov/pubmed/37745585 http://dx.doi.org/10.1101/2023.09.14.557739 |
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author | Abreu, Clare I. Mathur, Shaili Petrov, Dmitri A. |
author_facet | Abreu, Clare I. Mathur, Shaili Petrov, Dmitri A. |
author_sort | Abreu, Clare I. |
collection | PubMed |
description | Evolution in a static environment, such as a laboratory setting with constant and uniform conditions, often proceeds via large-effect beneficial mutations that may become maladaptive in other environments. Conversely, natural settings require populations to endure environmental fluctuations. A sensible assumption is that the fitness of a lineage in a fluctuating environment is the time-average of its fitness over the sequence of static conditions it encounters. However, transitions between conditions may pose entirely new challenges, which could cause deviations from this time-average. To test this, we tracked hundreds of thousands of barcoded yeast lineages evolving in static and fluctuating conditions and subsequently isolated 900 mutants for pooled fitness assays in 15 environments. We find that fitness in fluctuating environments indeed often deviates from the expectation based on static components, leading to fitness non-additivity. Moreover, closer examination reveals that fitness in one component of a fluctuating environment is often strongly influenced by the previous component. We show that this environmental memory is especially common for mutants with high variance in fitness across tested environments, even if the components of the focal fluctuating environment are excluded from this variance. We employ a simple mathematical model and whole-genome sequencing to propose mechanisms underlying this effect, including lag time evolution and sensing mutations. Our results demonstrate that environmental fluctuations have large impacts on fitness and suggest that variance in static environments can explain these impacts. |
format | Online Article Text |
id | pubmed-10515930 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-105159302023-09-23 Strong environmental memory revealed by experimental evolution in static and fluctuating environments Abreu, Clare I. Mathur, Shaili Petrov, Dmitri A. bioRxiv Article Evolution in a static environment, such as a laboratory setting with constant and uniform conditions, often proceeds via large-effect beneficial mutations that may become maladaptive in other environments. Conversely, natural settings require populations to endure environmental fluctuations. A sensible assumption is that the fitness of a lineage in a fluctuating environment is the time-average of its fitness over the sequence of static conditions it encounters. However, transitions between conditions may pose entirely new challenges, which could cause deviations from this time-average. To test this, we tracked hundreds of thousands of barcoded yeast lineages evolving in static and fluctuating conditions and subsequently isolated 900 mutants for pooled fitness assays in 15 environments. We find that fitness in fluctuating environments indeed often deviates from the expectation based on static components, leading to fitness non-additivity. Moreover, closer examination reveals that fitness in one component of a fluctuating environment is often strongly influenced by the previous component. We show that this environmental memory is especially common for mutants with high variance in fitness across tested environments, even if the components of the focal fluctuating environment are excluded from this variance. We employ a simple mathematical model and whole-genome sequencing to propose mechanisms underlying this effect, including lag time evolution and sensing mutations. Our results demonstrate that environmental fluctuations have large impacts on fitness and suggest that variance in static environments can explain these impacts. Cold Spring Harbor Laboratory 2023-09-21 /pmc/articles/PMC10515930/ /pubmed/37745585 http://dx.doi.org/10.1101/2023.09.14.557739 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Abreu, Clare I. Mathur, Shaili Petrov, Dmitri A. Strong environmental memory revealed by experimental evolution in static and fluctuating environments |
title | Strong environmental memory revealed by experimental evolution in static and fluctuating environments |
title_full | Strong environmental memory revealed by experimental evolution in static and fluctuating environments |
title_fullStr | Strong environmental memory revealed by experimental evolution in static and fluctuating environments |
title_full_unstemmed | Strong environmental memory revealed by experimental evolution in static and fluctuating environments |
title_short | Strong environmental memory revealed by experimental evolution in static and fluctuating environments |
title_sort | strong environmental memory revealed by experimental evolution in static and fluctuating environments |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10515930/ https://www.ncbi.nlm.nih.gov/pubmed/37745585 http://dx.doi.org/10.1101/2023.09.14.557739 |
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