马萨诸塞州总医院Benjamin P. Kleinstiver研究团队报道了通过可扩展的工程和机器学习定制CRISPR-Cas9 PAM变体。这一研究成果发表在2025年4月22日出版的国际学术期刊《自然》上。

为了实现Cas9酶的可扩展重编程，该研究团队将高通量蛋白质工程与机器学习（ML）相结合，以获得更适合特定目标的定制编辑器。通过结构/功能饱和诱变和细菌选择，研究人员获得了近1000个工程SpCas9酶，并表征了它们对原间隔物邻近基序7 （protospaco -邻基序7，PAM）的需求，以训练一个神经网络，将氨基酸序列与PAM特异性联系起来。通过利用所得到的PAM ML算法（PAMmla）预测6400万种SpCas9酶的PAM，课题组研究人员确定了在人类细胞中作为核酸酶和碱基编辑器，同时减少脱靶的有效性和特异性酶，优于基于进化和工程的SpCas9酶。一种硅定向进化方法可以实现热定向Cas9酶设计，包括在人类细胞和小鼠中对RHO P23H等位基因进行等位基因选择性靶向。总之，PAMmla将ML和蛋白质工程结合起来，编制了具有不同PAM要求的SpCas9酶目录，并激发了高效和安全定制Cas9酶的主题，而不是用于各种应用的通用酶。

据了解，工程和表征蛋白质可能是耗时和繁琐的，这促使开发通用CRISPR-Cas酶1 - 4，以实现多种基因组编辑应用。然而，这种酶也有一些缺点，比如脱靶编辑的风险增加。

附：英文原文

Title: Custom CRISPR—Cas9 PAM variants via scalable engineering and machine learning

Author: Silverstein, Rachel A., Kim, Nahye, Kroell, Ann-Sophie, Walton, Russell T., Delano, Justin, Butcher, Rossano M., Pacesa, Martin, Smith, Blaire K., Christie, Kathleen A., Ha, Leillani L., Meis, Ronald J., Clark, Aaron B., Spinner, Aviv D., Lazzarotto, Cicera R., Li, Yichao, Matsubara, Azusa, Urbina, Elizabeth O., Dahl, Gary A., Correia, Bruno E., Marks, Debora S., Tsai, Shengdar Q., Pinello, Luca, De Ravin, Suk See, Liu, Qin, Kleinstiver, Benjamin P.

Issue&Volume: 2025-04-22

Abstract: Engineering and characterizing proteins can be time-consuming and cumbersome, motivating the development of generalist CRISPR-Cas enzymes1–4 to enable diverse genome editing applications. However, such enzymes have caveats such as an increased risk of off-target editing3,5,6. To enable scalable reprogramming of Cas9 enzymes, here we combined high-throughput protein engineering with machine learning (ML) to derive bespoke editors more uniquely suited to specific targets. Via structure/function-informed saturation mutagenesis and bacterial selections, we obtained nearly 1,000 engineered SpCas9 enzymes and characterized their protospacer-adjacent motif7 (PAM) requirements to train a neural network that relates amino acid sequence to PAM specificity. By utilizing the resulting PAM ML algorithm (PAMmla) to predict the PAMs of 64 million SpCas9 enzymes, we identified efficacious and specific enzymes that outperform evolution-based and engineered SpCas9 enzymes as nucleases and base editors in human cells while reducing off-targets. An in silico directed evolution method enables user-directed Cas9 enzyme design, including for allele-selective targeting of the RHO P23H allele in human cells and mice. Together, PAMmla integrates ML and protein engineering to curate a catalog of SpCas9 enzymes with distinct PAM requirements, and motivates the use of efficient and safe bespoke Cas9 enzymes instead of generalist enzymes for various applications.

DOI: 10.1038/s41586-025-09021-y

Source: https://www.nature.com/articles/s41586-025-09021-y