Nonviral delivery techniques for in vivo prime editing

基因编辑是治疗甚至永久治愈遗传病的一种很有前途的策略。在……里面 特别是，一种名为优质编辑的新技术有可能使小目标 已知疾病的潜在覆盖率非常高的插入、删除和替换- 造成突变，同时将危险的双链DNA断裂降至最低。为了 意识到这一潜力，必须制定强有力的交付战略来交付主要的编辑工具 有效地转移到与疾病相关的器官。一种这样的递送策略是脂纳米粒递送 基于RNA和/或蛋白质的主要编辑组件。LNPs无病毒、无毒，具有临床应用价值 经过验证的交付工具。然而，可能的LNP有一个极其多样化的空间， 数以万计的可能对LNP传递有用的潜在的脂结构。选择 因此，最适合主要编辑应用程序的最佳LNP是具有挑战性的，因为在体外 检测通常是不可靠的，而且一次只检测一个LNP的体内检测的吞吐量极低。 在这里，我们建议结合两种可伸缩的技术来生成和测试安全、有效的LNP 用于执行主要编辑的公式。首先，我们将使用组合化学 生成大量可生物降解的脂类以包含在LNPs中的技术。第二, 我们将引入一种我们称之为pegRNA条形码的新技术来筛选数十个 在一只鼠标中成功编辑数百个LNP。我们将采用这种技术 确定最适合编辑多个器官的可生物降解的LNPs，尤其包括 肺和肝。在确定了最佳候选人后，我们将继续使用我们的LNPs来 应用质数编辑治疗两种不同遗传性疾病的小鼠模型：遗传性 I型酪氨酸血症(HTI)，一种肝脏疾病，以及囊性纤维化(CF)，主要是一种肺部疾病。我们 将评估主要编辑的效率、不受欢迎的编辑事件的级别，以及 这些小鼠的表型校正。这一结果可能会确定有前途的临床前候选人。 用于治疗HTI、CF和许多其他肺和肝脏疾病。

Gene editing is a promising strategy for treating or even permanently curing genetic diseases. In particular, a new technique called prime editing has the potential to make small targeted insertions, deletions, and substitutions with very high potential coverage of known disease- causing mutations, and while minimizing dangerous double-stranded breaks in DNA. In order to realize this potential, robust delivery strategies must be developed to deliver prime editing tools efficiently to disease-relevant organs. One such delivery strategy is lipid nanoparticle delivery of RNA and/or protein-based prime editing components. LNPs are nonviral, nontoxic, and clinically validated delivery tools. However, there is an extremely diverse space of possible LNPs, with tens of thousands of potential lipid structures that may be useful for LNP delivery. Selecting the best possible LNP for a prime editing application, therefore, is challenging because in vitro testing is often unreliable and in vivo testing of one LNP at a time is extremely low throughput. Here, we propose to combine two scalable techniques to generate and test safe, potent LNP formulations for performing prime editing. First, we will employ combinatorial chemistry techniques to generate large libraries of biodegradable lipids for inclusion into LNPs. Second, we will introduce a new technique which we term pegRNA barcoding to screen dozens to hundreds of LNPs for successful prime editing in a single mouse. We will employ this technique to identify the best biodegradable LNPs for editing of multiple organs, including in particular the lung and the liver. Having identified the top candidates, we will proceed to use our LNPs to apply prime editing to treat mouse models of two different inherited genetic diseases: hereditary tyrosinemia type I (HTI), a liver disease, and cystic fibrosis (CF), primarily a lung disease. We will evaluate the efficiency of prime editing, the levels of undesired editing events, and phenotypic correction of these mice. The results may identify promising preclinical candidates for the treatment of HTI, CF, and many other lung and liver diseases.