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Environmental memory alters the fitness effects of adaptive mutations in fluctuating environments

Nature Ecology & Evolution (2024)Cite this article

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Abstract

Evolution in a static laboratory environment 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. Here we find that fitness in fluctuating environments indeed often deviates from the time average, 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. We use a simple mathematical model and whole-genome sequencing to propose mechanisms underlying this effect, including lag time evolution and sensing mutations. Our results show that environmental fluctuations impact fitness and suggest that variance in static environments can explain these impacts.

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Fig. 1: Fitness assays test for non-additivity in mutants evolved from static and fluctuating environments.
Fig. 2: Non-additivity is common, but it masks even greater fitness changes.
Fig. 3: Fitness in one component of a fluctuating environment influences fitness in the other component.
Fig. 4: Fitness reversals in fluctuating environments are common and recapitulated by a simple model of lag time evolution.
Fig. 5: Environment-sensing mutations are associated with higher fitness variance and memory.

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Data availability

All sequencing data are deposited in Short Read Archive under BioProject identifier PRJNA1103172. The remaining data are available via GitHub at https://github.com/clare-abreu/environmental_memory. Barcoded yeast strains are available from the authors upon request. Source data are provided with this paper.

Code availability

All code used in this paper is available via GitHub at https://github.com/clare-abreu/environmental_memory.

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Acknowledgements

We are grateful to G. Kinsler for patiently training us in the experimental system, as well as for valuable advice about PCR and sequencing, data analysis and whole-genome sequencing analysis. We thank members of the Petrov Lab for helpful comments and suggestions. We thank A. Lyulina for assistance with preliminary experiments; S. Khristich for guidance on molecular biology troubleshooting; K. Xue, K. Solari, K. Schwartz and J. Tarkington for advice on library preparation protocols; and A. Mahadevan for advice on whole-genome sequencing analysis. For additional helpful discussions, we thank Y. Li, B. Good, D. Wong, J. Cremer, J. Gore, M. Dal Bello, M. Dunham and R. Stelkens. Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number F32GM145148 (C.I.A.) and Award Number R35GM118165 (D.A.P.).

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Authors and Affiliations

  1. Department of Biology, Stanford University, Stanford, CA, USA

    Clare I. Abreu, Shaili Mathur & Dmitri A. Petrov

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  1. Clare I. Abreu
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  2. Shaili Mathur
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Contributions

C.I.A., S.M. and D.A.P. conceived of the study. C.I.A. and S.M. conducted experiments, collected data and performed analyses, and C.I.A., S.M. and D.A.P. interpreted results. C.I.A. analysed the mathematical model. C.I.A. and D.A.P. acquired funding. C.I.A. wrote the original draft paper, and C.I.A., S.M. and D.A.P. reviewed and edited the paper.

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Correspondence to Clare I. Abreu or Dmitri A. Petrov.

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Nature Ecology & Evolution thanks Yitzhak Pilpel and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Fitness statistics for all mutants (also available via GitHub).

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Abreu, C.I., Mathur, S. & Petrov, D.A. Environmental memory alters the fitness effects of adaptive mutations in fluctuating environments. Nat Ecol Evol (2024). https://doi.org/10.1038/s41559-024-02475-9

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