Single Cell Profiling To Define Biomarkers Of Photoreceptor Dysfunction After Gene Editing Within PSC-Derived Organoids

项目总结 基因组编辑对基因组进行有针对性的改变，并在基础和翻译方面都有很大的希望 研究。不幸的是，它们经常产生有害的副作用，包括遗传毒性、免疫反应、 以及细胞功能的降低。因此，对不良事件的筛查对于发展 安全的基因组编辑疗法。 在这里，我们建议开发一种可推广和可扩展的方法来定义不良事件的生物标记物 在一个基因组编辑交付之后。我们的策略结合了最先进的、无标记的光学代谢成像 (OMI)用单细胞测量生理、功能和高含量的形态状态 转录图谱(scRNA-seq)和基于调控网络的方法来分析单细胞数据。这个 推断的基因调控网络可以用来开发一小组(~50)不良事件的生物标记物 在功能细胞内。概念验证研究将集中在视网膜，特别是视杆细胞和视锥细胞。 人多能干细胞来源的三维视泡有机体内的光感受器 (PSCS)。该数据集的创建和该方法的验证将利用这些生物工程技术 更安全的基因组编辑疗法的发展。 在目标1中，我们将调整现有的成像和培养平台，以将Cas9基因组编辑管理到OV中。 细胞将用重要的PR主调节器进行编辑，并受到光和化学扰动的挑战 测试基因组编辑后的功能性光转导。在目标2中，我们将发现基因调控网络和 与正常和功能失调的基因编辑OV的代谢异常相关的生物标记物。我们会 对代谢不同的、基因编辑的OV进行scRNA-seq和OMI，然后绘制基因调控图 与公关内不良事件相关的网络。我们计划通过以下方式验证生物标记物小组 QPCR/免疫细胞化学(ICC)和电生理学。在目标3中，我们将以新颖的方式对平台进行测试和优化 SCGE工具包中的sgRNAs和基因组编辑。最后，在目标4中，我们将扩展该平台以检测 仅在视锥PR中发生的不良事件，在视网膜内仅占PR的少数，但却是严重的 为了人类的视觉。 通过处理3D、不同种类的有机培养，我们的方法将扩展到更复杂的培养。因此， 这项工作的影响可能是广泛的，有可能推动基因组编辑的发展 用在任何组织上。

PROJECT SUMMARY Genome editors make targeted changes in the genome and hold great promise in both basic and translational research. Unfortunately, they often produce unwanted adverse effects, including genotoxicity, immune response, and reductions in cellular function. Therefore, screening for adverse events is essential for the development of safe genome editing therapies. Here we propose to develop a generalizable and scalable approach to define biomarkers for adverse events after delivery of a genome editor. Our strategy combines state-of-the-art, label-free optical metabolic imaging (OMI) to measure the physiological, functional, and high-content morphological status, with single cell transcriptomic profiling (scRNA-seq) and regulatory network-based methods to analyze single cell data. The inferred gene regulatory networks can be used to develop a small (~50) set of biomarkers for adverse events within functional cells. Proof-of-concept studies will focus on the retina, specifically on rod and cone photoreceptors (PR) within 3D optic vesicle (OV) organoids derived from human pluripotent stem cells (PSCs). Creation of this dataset and validation of this approach will leverage these bioengineering technologies toward the development of safer genome editing therapeutics. In Aim 1, we will adapt an existing imaging and culture platform to administer Cas9 genome editors into OVs. Cells will be edited with important PR master regulators and challenged with light and chemical perturbations to test functional phototransduction post genome editing. In Aim 2, we will discover gene regulatory networks and biomarkers associated with abnormal metabolism within normal and dysfunctional gene-edited OVs. We will perform scRNA-seq and OMI on metabolically-distinct, gene-edited OVs, and then map the gene regulatory network associated with adverse events within PRs. We plan to validate the biomarker panel with qPCR/immunocytochemistry (ICC) and electrophysiology. In Aim 3, we will test and refine the platform with novel sgRNAs and genome editors within the SCGE toolkit. And finally, in Aim 4, we will expand the platform to detect adverse events that occur only in cone PRs, which constitute a minority of PRs within the retina, yet are critical for human vision. By tackling a 3D, heterogeneous organoid culture, our approach will extend to more complex cultures. Thus, the impact of this work could be broad, with the potential to advance the development of genome editors administered to any tissue.