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

Journal: Nature
Published Date: Jul 30, 2025

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 cells. 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 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 1 million 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.

Authors

  • Jeffrey A Ruffolo
    Program in Molecular Biophysics, The Johns Hopkins University, Baltimore, MD 21218, USA.
  • Stephen Nayfach
    Profluent Bio, Berkeley, CA, USA.
  • Joseph Gallagher
    University College Dublin, Dublin, Ireland.
  • Aadyot Bhatnagar
    Profluent Bio, Berkeley, CA, USA.
  • Joel Beazer
    Profluent Bio, Berkeley, CA, USA.
  • Riffat Hussain
    Profluent Bio, Berkeley, CA, USA.
  • Jordan Russ
    Profluent Bio, Berkeley, CA, USA.
  • Jennifer Yip
    Profluent Bio, Berkeley, CA, USA.
  • Emily Hill
    Profluent Bio, Berkeley, CA, USA.
  • Martin Pačesa
    Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland. m.pacesa@bioc.uzh.ch.
  • Alexander J Meeske
    Profluent Bio, Berkeley, CA, USA.
  • Peter Cameron
    Profluent Bio, Berkeley, CA, USA.
  • Ali Madani
    Molecular Cell Biomechanics Laboratory, Departments of Bioengineering and Mechanical Engineering, University of California, 208A Stanley Hall #1762, Berkeley, CA, 94720-1762, USA.

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