Design of highly functional genome editors by modelling CRISPR-Cas sequences

• 成果类型: Article
• 署名作者: Ruffolo, Jeffrey A.; Nayfach, Stephen; Gallagher, Joseph; Bhatnagar, Aadyot; Beazer, Joel; Hussain, Riffat; Russ, Jordan; Yip, Jennifer; Hill, Emily; Pacesa, Martin; Meeske, Alexander J.; Cameron, Peter; Madani, Ali
• 署名单位: Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; Swiss Institute of Bioinformatics; University of Washington; University of Washington Seattle
• 刊物名称: NATURE
• ISSN/ISSBN: 0028-0836; 1476-4687
• DOI: 10.1038/s41586-025-09298-z
• 发表日期: 2025-09-01
• 页码: 518-+
• 关键词: rna; dna; nucleases; EVOLUTION; variant

摘要

Gene editing has the potential to solve fundamental challenges in agriculture, biotechnology and human health. CRISPR-based gene editors derived from microorganisms, although powerful, often show notable functional tradeoffs when ported into non-native environments, such as human cells(1). Artificial-intelligence-enabled design provides a powerful alternative with the potential to bypass evolutionary constraints and generate editors with optimal properties. Here, using large language models(2) trained on biological diversity at scale, we demonstrate successful precision editing of the human genome with a programmable gene editor designed with artificial intelligence. To achieve this goal, we curated a dataset of more than 1million CRISPR operons through systematic mining of 26 terabases of assembled genomes and metagenomes. We demonstrate the capacity of our models by generating 4.8x the number of protein clusters across CRISPR-Cas families found in nature and tailoring single-guide RNA sequences for Cas9-like effector proteins. Several of the generated gene editors show comparable or improved activity and specificity relative to SpCas9, the prototypical gene editing effector, while being 400 mutations away in sequence. Finally, we demonstrate that an artificial-intelligence-generated gene editor, denoted as OpenCRISPR-1, exhibits compatibility with base editing. We release OpenCRISPR-1 to facilitate broad, ethical use across research and commercial applications.