ArticleNature communications2025
Discovery of CRISPR-Cas12a clades using a large language model.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Machine-learning in optimization of CRISPR technology.Machine learning. Health · 2026Review
- Yeast species resource exploration and application in cell factories.Synthetic and systems biotechnology · 2026Review
- Structural mining and engineering of metagenome-derived Cas12a orthologs expands the CRISPR genome editing and multiplex diagnostics toolkit.Molecular therapy : the journal of the American Society of Gene Therapy · 2026Article
- Development of a Single-Tube Asymmetric ERA-CRISPR/Cas12a Assay for Rapid Visual Detection ofMicroorganisms · 2026Article
- Harnessing Deep Learning Models for Guide RNA Optimization and Off-Target Prediction in CRISPR Systems.Biotechnology journal · 2026Review
- Computation and deep-learning-driven advances in CRISPR genome editing.Nature structural & molecular biology · 2026Review
- Renal clearable CRISPR nanosensor targeting mitochondrial DNA mutation for noninvasive monitoring of tumor progression and metastasis.Science advances · 2025Article
- Expanding the CRISPR/Cas toolkit: applications in proteomics and theranostics.Frontiers in bioengineering and biotechnology · 2025Review
Corrections and comments
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Authors and funding
18 authors.
Funding
Abstract
CRISPR-Cas systems revolutionize life science. Metagenomes contain millions of unknown Cas proteins. Traditional mining relies on protein sequence alignments. In this work, we employ an evolutionary scale language model (ESM) to learn the information beyond sequences. Trained with CRISPR-Cas data, ESM accurately identifies Cas proteins without alignment. Limited experimental data restricts feature prediction, but integrating with machine learning enables trans-cleavage activity prediction of uncharacterized Cas12a. We discover 7 undocumented Cas12a subtypes with unique CRISPR loci. Structural analyses reveal 8 subtypes of Cas1, Cas2, and Cas4. Cas12a subtypes display distinct 3D-folds. CryoEM analyses unveil unique RNA interactions with the uncharacterized Cas12a. These proteins show distinct double-strand and single-strand DNA cleavage preferences and broad PAM recognition. Finally, we establish a specific detection strategy for the oncogene SNP without traditional Cas12a PAM. This study highlights the potential of language models in exploring undocumented Cas protein function via gene cluster classification.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.