AI mirrors experimental science to uncover a mechanism of gene transfer crucial to bacterial evolution
Open accessPublished version of a preprint
Abstract
Artificial intelligence (AI) models have been proposed for hypothesis generation, but testing their ability to drive high-impact research is challenging since an AI-generated hypothesis can take decades to validate. Here, we challenge the ability of a recently developed large language model (LLM)-based platform, AI co-scientist, to generate high-level hypotheses by posing a question that took years to resolve experimentally but remained unpublished: how could capsid-forming phage-inducible chromosomal islands (cf-PICIs) spread across bacterial species? Remarkably, the AI co-scientist's top-ranked hypothesis matched our experimentally confirmed mechanism: cf-PICIs hijack diverse phage tails to expand their host range. We critically assess its five highest-ranked hypotheses, showing that some opened new research avenues in our laboratories. We benchmark its performance against other LLMs and outline best practices for integrating AI into scientific discovery. Our findings suggest that AI can act not just as a tool but as a creative engine, accelerating discovery and reshaping how we generate and test scientific hypotheses.
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Cites
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- Authors
- Penadés, J. R., Gottweis, J., He, L., Patkowski, J. B., Daryin, A., Weng, W.-H., Tu, T., Palepu, A., Myaskovsky, A., Pawlosky, A., Natarajan, V., Karthikesalingam, A., & Costa, T. R. D.
- Affiliations
- Universidad Cardenal Herrera CEU (ES)
- Google (United States) (US)
- Imperial College London (GB)
- Corresponding author
- Penadés, José R.
- Natarajan, Vivek
- Karthikesalingam, Alan
- Costa, Tiago R.D.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2025-11
- Volume
- 188
- Issue
- 23
- Pages
- 6654-6665.e2
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W4414152979
- Cited by
- 42
- References
- 8
- Citations by year
- 2026: 31 · 2025: 11
- FWCI
- 22.22
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- Spiral (Imperial College London) (submittedVersion, cc-by)
- Funders
- Medical Research Council (BB/V009583/1, BB/V002376/1)
- Biotechnology and Biological Sciences Research Council
- European Research Council (215164/Z/18/Z/WT, 101118890)
- Engineering and Physical Sciences Research Council (EP/X026671/1)
- Topics
- Physical Sciences › Environmental Science › Ecology › Bacteriophages and microbial interactions
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- large language models, gene transfer, bacterial evolution, host range expansion, hypothesis testing
- MeSH terms
- Artificial Intelligence, Bacteria, Bacteriophages, Evolution, Molecular, Gene Transfer, Horizontal, Genomic Islands
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