The introduction of genome engineering technology has transformed biomedical research, making it possible to make precise changes to genetic information. However, creating an efficient gene-editing system requires a deep understanding of CRISPR technology, and the complex experimental systems under investigation. While Large Language Models (LLMs) have shown promise in various tasks, they often lack specific knowledge and struggle to accurately solve biological design problems. In this work, we introduce CRISPR-GPT, an LLM agent augmented with domain knowledge and external tools to automate and enhance the design process of CRISPR-based gene-editing experiments. CRISPR-GPT leverages the reasoning ability of LLMs to facilitate the process of selecting CRISPR systems, designing guide RNAs, recommending cellular delivery methods, drafting protocols, and designing validation experiments to confirm editing outcomes. We showcase the potential of CRISPR-GPT for assisting non-expert researchers with gene-editing experiments from scratch and validate the agent's effectiveness in a real-world use case. Furthermore, we explore the ethical and regulatory considerations associated with automated gene-editing design, highlighting the need for responsible and transparent use of these tools. Our work aims to bridge the gap between beginner biological researchers and CRISPR genome engineering techniques, and demonstrate the potential of LLM agents in facilitating complex biological discovery tasks.

翻译：基因组工程技术的引入彻底改变了生物医学研究，使精准修改遗传信息成为可能。然而，设计高效的基因编辑系统需要对CRISPR技术及所研究的复杂实验体系有深入理解。尽管大语言模型在多种任务中展现出潜力，但它们通常缺乏特定领域知识，难以准确解决生物学设计问题。本研究提出CRISPR-GPT——一种融合领域知识与外部工具的大语言模型智能体，用于自动化和增强基于CRISPR的基因编辑实验设计流程。CRISPR-GPT利用大语言模型的推理能力，促进CRISPR系统选择、导向RNA设计、细胞递送方法推荐、实验方案拟定以及验证编辑效果的验证实验设计等环节。我们展示了CRISPR-GPT帮助非专业研究人员从零开始开展基因编辑实验的潜力，并通过实际案例验证了该智能体的有效性。此外，我们探讨了与自动化基因编辑设计相关的伦理和监管考量，强调了这些工具负责任和透明使用的必要性。本研究旨在弥合生物研究初学者与CRISPR基因组工程技术之间的鸿沟，并展现大语言模型智能体在促进复杂生物学发现任务中的潜力。