Continuous evolution of user-defined genes at 1-million-times the genomic mutation rate
Open accessPreprint — published as 10.1126/science.adm9073 · Paper page
Abstract
When nature maintains or evolves a gene’s function over millions of years at scale, it produces a diversity of homologous sequences whose patterns of conservation and change contain rich structural, functional, and historical information about the gene. However, natural gene diversity likely excludes vast regions of functional sequence space and includes phylogenetic and evolutionary eccentricities, limiting what information we can extract. We introduce an accessible experimental approach for compressing long-term gene evolution to laboratory timescales, allowing for the direct observation of extensive adaptation and divergence followed by inference of structural, functional, and environmental constraints for any selectable gene. To enable this approach, we developed a new orthogonal DNA replication (OrthoRep) system that durably hypermutates chosen genes at a rate of >10 −4 substitutions per base in vivo . When OrthoRep was used to evolve a conditionally essential maladapted enzyme, we obtained thousands of unique multi-mutation sequences with many pairs >60 amino acids apart (>15% divergence), revealing known and new factors influencing enzyme adaptation. The fitness of evolved sequences was not predictable by advanced machine learning models trained on natural variation. We suggest that OrthoRep supports the prospective and systematic discovery of constraints shaping gene evolution, uncovering of new regions in fitness landscapes, and general applications in biomolecular engineering.
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Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
Large language models generate functional protein sequences across diverse families
Madani, A., Krause, B., Greene, E. R., Subramanian, S., Mohr, B. P., Holton, J. M., Olmos, J. L., Xiong, C., Sun, Z. Z., Socher, R., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-022-01618-2 · Cited by 1,078 · cited 2× · see citing works
“…at extracting meaningful representations of biomolecular structure and function from the extensive diversity within and across gene families, as exemplified by their ability to predict functional effects of mutations 26–28 , design functional sequences 29–31 , and predict protein structures 32–34 .”
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- Authors
- Rix, G., Williams, R. L., Spinner, H., Hu, V. J., Marks, D. S., & Liu, C. C.
- Affiliations
- University of California, Irvine (US)
- Broad Institute (US)
- Corresponding author
- Liu, Chang C.
- Venue
- Science
- Publisher
- openRxiv
- Published
- 2023-11-14
- Volume
- 386
- Issue
- 6722
- Pages
- eadm9073-eadm9073
- ISSN
- 0036-8075 (ISSN-L)
- PMC
- PMC11750425
- OpenAlex
- W4404125138
- Cited by
- 71
- References
- 2
- Citations by year
- 2026: 33 · 2025: 34 · 2024: 4
- FWCI
- 18.84
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Science (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (submittedVersion)
- Funders
- Fondation pour la Recherche Médicale
- National Institutes of Health
- National Cancer Institute (R01CA260415)
- National Institute of General Medical Sciences (R35GM136297)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Enzyme Catalysis and Immobilization
- Keywords
- yeast, biosynthetic enzymes, sequence space exploration, fitness landscape, biomolecular engineering
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