Parametric design software for nanostructured CRISPR payloads

项目摘要 全世界有3亿多人受到遗传健康状况的影响。超过4,400个基因 疾病已经被确定;几乎所有这些都被认为是罕见的，这限制了研究的数量 每个人都收到。基因治疗是治疗遗传性疾病的一种有吸引力的方法，因为它具有广泛的 适用性CRISPR-Cas9基因组编辑系统（CRISPR）彻底改变了基因治疗研究， 然而，在生命科学的其他领域，还没有基于CRISPR的治疗方法进入市场和临床 应用仍面临重大挑战。 在这个项目中，我们的目标是开发设计自动化软件，以帮助改善遗传供体模板是如何 通过CRISPR进行基因组整合，从而提高CRISPR编辑效率。而这些 模板通常以非结构化（线性）单链DNA的形式提供，最近的研究表明， 当模板被折叠成紧凑的形状时， DNA纳米技术。这种用于CRISPR的纳米结构遗传有效载荷（NGP）具有 有可能成为基因治疗和个性化医疗的重要组成部分。远景目标 该项目的目的是为研究人员提供设计更有效的CRISPR治疗方法的软件， 改善有遗传健康问题的人的生活。我们的解决方案也将推动其他应用 DNA纳米技术正在使用的领域，如纳米医学，纳米传感和 生物相容性纳米材料，从而支持国家综合医学研究所的使命 科学（NIGMS）：提高生物医学研究中计算方法的有效性。 存在学术软件来促进DNA纳米结构的设计，然而，这些应用或者需要 广泛的专业知识或仅限于3D线框设计。一种新型DNA纳米结构的设计 不属于一小部分简单设计的复杂性可能需要数百小时的专业劳动。 此外，由于NGP对科学来说是新的，目前还没有软件可以自动生成DNA 图4示出了用于给定的NGP设计参数集的纳米结构。在本项目的目标1中，我们将采用迭代 设计-构建-测试开发周期，我们已经将其他软件产品推向市场，以开发新的 参数化设计软件（PDS）能够为给定的遗传模板和一组 设计参数在目标2中，我们将模拟和合成八种NGP，并通过分子表征它们， 建模和原子力显微镜，以确认它们符合设计规范。然后我们将测试这些 NGP用于体外针对非结构化有效载荷对照的CRISPR编辑效率。在第二阶段，我们将加强 PDS并使用它来探索NGP设计的巨大空间，以优化CRISPR性能， 跨多个细胞系、模板和插入靶标的组合测试。最终，我们的目标是 将NGP软件和设计服务商业化，以加速CRISPR研究。

PROJECT SUMMARY More than 300 million people worldwide are affected by a genetic health condition. Over 4,400 genetic diseases have been identified; nearly all of which are considered rare, which limits the amount of research each receives. Gene therapy is an attractive approach for treatment of genetic disease because of its broad applicability. CRISPR-Cas9 genome editing systems (CRISPR) have revolutionized gene therapy research and other fields of life science, however, no CRISPR-based treatments have reached the market and clinical application still faces important challenges. In this project, we aim to develop design automation software to help improve how genetic donor templates are packaged for genomic integration via CRISPR, thereby increasing CRISPR editing efficiency. Whereas such templates are usually delivered as unstructured (linear) single-stranded DNA, recent studies indicate genome integration efficiency is significantly improved when templates are folded into compact shapes using techniques from DNA nanotechnology. Such nanostructured genetic payloads (NGPs) for CRISPR have the potential to become an essential component of genetic therapy and personalized medicine. The long-term goal of the project is to provide researchers with software for designing more effective CRISPR treatments to improve the lives of people with genetic health problems. Our solution will also advance other application domains where DNA nanotechnology is being employed, such as nanomedicine, nanosensing and biocompatible nanomaterials, thereby supporting the mission of the National Institute of General Medical Sciences (NIGMS): improving the effectiveness of computational approaches in biomedical research. Academic software exists to facilitate design of DNA nanostructures, however, these applications either require extensive expertise or are limited to 3D wireframe designs. Design of a novel DNA nanostructure of modest complexity that is not among a small set of simple designs can require hundreds of hours of expert labor. Moreover, because NGPs are new to science, no software currently exists to automatically generate DNA nanostructures for a given set of NGP design parameters. In Aim 1 of this project, we will employ an iterative design-build-test development cycle we have used to bring other software products to market to develop novel parametric design software (PDS) able to create NGPs automatically for a given genetic template and set of design parameters. In Aim 2, we will simulate and synthesize eight NGPs and characterize them via molecular modeling and atomic force microscopy to confirm they meet design specifications. We will then test these NGPs for CRISPR editing efficiency against unstructured payload controls in vitro. In Phase II, we will enhance the PDS and use it to explore the vast space of NGP designs for those that optimize CRISPR performance via combinatorial testing across multiple cell lines, templates and insertion targets. Ultimately, we aim to commercialize NGP software and design services to accelerate CRISPR research.