美国Profluent Bio公司Ali Madani团队通过模拟CRISPR-Cas序列设计高功能基因组编辑器。该项研究成果发表在2025年7月30日出版的《自然》上。

以大规模生物多样性训练的大型语言模型为主题，课题组研究人员展示了用人工智能设计的可编程基因编辑器成功地对人类基因组进行精确编辑。为了实现这一目标，该研究组策划了一个包含1个以上数据集的数据集 通过系统地挖掘26TB的组装基因组和宏基因组，获得了数百万个CRISPR操纵子。课题组人员通过在自然界中发现的CRISPR-Cas家族中产生4.8倍数量的蛋白质细胞，并为Cas9样效应蛋白定制单导RNA序列，证明了他们模型的能力。

与SpCas9（一种典型的基因编辑效应物）相比，几种生成的基因编辑器显示出相当或更好的活性和特异性，尽管序列上有400个突变。最后，课题组人员证明了人工智能生成的基因编辑器（表示为OpenCRISPR-1）与碱基编辑具有兼容性。该研究团队发布OpenCRISPR-1是为了在研究和商业应用中促进广泛的伦理主题。

据介绍，基因编辑有可能解决农业、生物技术和人类健康方面的根本挑战。来自微生物的基于CRISPR的基因编辑器虽然功能强大，但在移植到非原生环境（如人类细胞）时，往往会显示出显著的功能权衡。人工智能支持的设计提供了一个强大的替代方案，有可能绕过进化限制，生成具有最佳属性的编辑器。

附：英文原文

Title: Design of highly functional genome editors by modelling CRISPR–Cas sequences

Author: 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

Issue&Volume: 2025-07-30

Abstract: 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 cells1. 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 models2 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 4.8× 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.

DOI: 10.1038/s41586-025-09298-z

Source: https://www.nature.com/articles/s41586-025-09298-z