小柯机器人

2022年2月14日，美国威尔康奈尔医学院Lukas E. Dow研究团队在《自然—生物技术》杂志发表论文。该研究报道了用于癌症相关单核苷酸变体的高通量工程化和功能分析的碱基编辑传感器库。

研究人员描述了模块化的碱基编辑活性"传感器"，它将单向导RNA（sgRNA）和同源的目标位点顺式连接起来，并利用它们来系统地测量成千上万的sgRNA与功能不同碱基编辑器配对的编辑效率和精度。通过量化超过200,000个编辑器-sgRNA组合的传感器编辑，研究人员提供了一个全面的sgRNA资源，用于在多个模型系统中引入和研究癌症相关的单核苷酸变异。

研究人员证明，经过传感器验证的工具可以简化体内癌症模型的产生，并且在集合的sgRNA库中整合传感器模块可以帮助解释高通量碱基编辑筛选。使用这种方法，研究人员确定了几个以前未被描述的突变TP53等位基因作为癌细胞增殖和体内肿瘤发展的驱动因素。研究人员预计，该框架将有助于在细胞和动物模型中对癌症变体进行功能研究。

据悉，碱基编辑可用于表征功能未知的单核苷酸变体，但定义sgRNA和碱基编辑的有效组合仍然具有挑战性。

附：英文原文

Title: Base editing sensor libraries for high-throughput engineering and functional analysis of cancer-associated single nucleotide variants

Author: Snchez-Rivera, Francisco J., Diaz, Bianca J., Kastenhuber, Edward R., Schmidt, Henri, Katti, Alyna, Kennedy, Margaret, Tem, Vincent, Ho, Yu-Jui, Leibold, Josef, Paffenholz, Stella V., Barriga, Francisco M., Chu, Kevan, Goswami, Sukanya, Wuest, Alexandra N., Simon, Janelle M., Tsanov, Kaloyan M., Chakravarty, Debyani, Zhang, Hongxin, Leslie, Christina S., Lowe, Scott W., Dow, Lukas E.

Issue&Volume: 2022-02-14

Abstract: Base editing can be applied to characterize single nucleotide variants of unknown function, yet defining effective combinations of single guide RNAs (sgRNAs) and base editors remains challenging. Here, we describe modular base-editing-activity ‘sensors’ that link sgRNAs and cognate target sites in cis and use them to systematically measure the editing efficiency and precision of thousands of sgRNAs paired with functionally distinct base editors. By quantifying sensor editing across >200,000 editor-sgRNA combinations, we provide a comprehensive resource of sgRNAs for introducing and interrogating cancer-associated single nucleotide variants in multiple model systems. We demonstrate that sensor-validated tools streamline production of in vivo cancer models and that integrating sensor modules in pooled sgRNA libraries can aid interpretation of high-throughput base editing screens. Using this approach, we identify several previously uncharacterized mutant TP53 alleles as drivers of cancer cell proliferation and in vivo tumor development. We anticipate that the framework described here will facilitate the functional interrogation of cancer variants in cell and animal models.

DOI: 10.1038/s41587-021-01172-3

Source: https://www.nature.com/articles/s41587-021-01172-3

Nature Biotechnology：《自然—生物技术》，创刊于1996年。隶属于施普林格·自然出版集团，最新IF：68.164
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投稿链接：https://mts-nbt.nature.com/cgi-bin/main.plex