Evolution favors protein mutational robustness in sufficiently large populations
Open accessAbstract
BACKGROUND: An important question is whether evolution favors properties such as mutational robustness or evolvability that do not directly benefit any individual but can influence the course of future evolution. Functionally similar proteins can differ substantially in their robustness to mutations and capacity to evolve new functions, but it has remained unclear whether any of these differences might be due to evolutionary selection for these properties. RESULTS: Here, we use laboratory experiments to demonstrate that evolution favors protein mutational robustness if the evolving population is sufficiently large. We neutrally evolve cytochrome P450 proteins under identical selection pressures and mutation rates in populations of different sizes, and show that proteins from the larger and thus more polymorphic population tend towards higher mutational robustness. Proteins from the larger population also evolve greater stability, a biophysical property that is known to enhance both mutational robustness and evolvability. The excess mutational robustness and stability is well described by mathematical theory, and can be quantitatively related to the way that the proteins occupy their neutral network. CONCLUSION: Our work is the first experimental demonstration of the general tendency of evolution to favor mutational robustness and protein stability in highly polymorphic populations. We suggest that this phenomenon could contribute to the mutational robustness and evolvability of viruses and bacteria that exist in large populations.
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From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [35]
Long term batch cultivation on glucose led to a rapid decay of non-used metabolic functions, including growth on D-ribose and L-glutamine, in E. coli.
“On the other hand, long term batch cultivation on glucose led to a rapid decay of non-used metabolic functions, including growth on D-ribose and L-glutamine, in E. coli[35]”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [35]
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- Authors
- Bloom, J. D., Lu, Z., Chen, D., Raval, A., Venturelli, O. S., & Arnold, F. H.
- Affiliations
- California Institute of Technology (US)
- Claremont Graduate University (US)
- Corresponding author
- Bloom, Jesse D
- Arnold, Frances H
- Venue
- BMC Biology
- Published
- 2007-07-17
- Volume
- 5
- Issue
- 1
- Pages
- 29-29
- ISSN
- 1741-7007 (ISSN-L)
- PMC
- PMC1995189
- OpenAlex
- W2127157300
- Cited by
- 119
- References
- 58
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 5 · 2023: 5 · 2022: 6 · 2021: 7 · 2020: 6 · 2019: 4 · 2018: 6 · 2017: 4 · 2016: 8 · 2015: 2 · 2014: 9 · 2013: 7 · 2012: 5
- FWCI
- 5.53
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation (0523643, 0527023)
- Howard Hughes Medical Institute
- California Institute of Technology
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Keywords
- mutational robustness, protein stability, evolvability, population size, neutral networks, cytochrome P450, protein evolution, neutral evolution, polymorphism, bacteria
- MeSH terms
- Bacterial Proteins, Cytochrome P-450 Enzyme System, Enzyme Stability, Escherichia coli, Models, Theoretical, Mutation, Polymorphism, Genetic, Population Density, Proteins, Evolution, Molecular
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