Design-driven engineering of robust mammalian sense-and-respond functions: from parts to programs

项目摘要 该项目的总体目标是使工程细胞疗法的使用能够安全和有效地 治疗各种疾病，包括癌症、自身免疫性疾病和再生医学。工程细胞 治疗是一个令人兴奋的前沿，癌症治疗的早期成功证明了 这种方法的潜力。定制的细胞疗法可以为许多人提供安全有效的治疗 癌症以外的应用，但实现这一潜力受到以下事实的限制：评估一种潜在的治疗方法 战略需要大量的时间和资源来实施。这个项目的目标是颠覆这一范式-- 以减少构建时间，从而专注于评估潜在有用的策略。 该项目将开发最先进的细胞工程技术，并使它们的应用能够解决 三个开放的、互补的、临床激励的挑战。第一个目标是开发这项技术， 理解，以及构建使用自然机制的遗传程序所需的计算工具 实现长寿命内存。自然系统使用遗传记忆来驱动过程，如 通过在基因组中添加和删除稳定的标记来实现分化和发育。尽管研究表明 生物工程师已经对如何推动这些变化有了深刻的见解，但他们还没有能力利用这些 为了有用的目的而构建实现这些效果的程序的见解。该项目将满足这一需求 通过开发表现出稳定行为的遗传程序，包括可诱导和自主状态 正在切换。第二个目标将产生治疗癌症的新的候选细胞疗法， 工程细胞评估和响应外部提示的基础进展(例如， 肿瘤部位)以诱导所需的治疗行为。这项工作将制定计划，以改善 这些方法的安全性和有效性。这项工作的一个关键方面是使用模型制导设计来 评估和改进遗传程序，以授予所需的行为。第三个目标是开发一种计算性的 使计算机辅助设计遗传程序成为可能的框架。目前的设计受到想象力的限制 设计师--一个人必须提出一个设计方案，然后进行评估。这一目标将使 实现向半自动设计的转型飞跃，建立可自由访问的工作流程和工具 支持图形的开放软件框架中的研究人员。

Project Summary The overarching goal of this project is to enable the use of engineered cell therapies to safely and effectively treat conditions ranging across cancer, autoimmune disease, and regenerative medicine. Engineered cell therapies are an exciting frontier, with early successes in cancer treatment demonstrating the transformative potential of this approach. Customized cell therapies could yield safe and effective treatments for many applications beyond cancer, but realizing this potential is limited by the fact that evaluating a potential therapeutic strategy requires extensive time and resources to implement it. The goal of this project is to flip this paradigm— to enable spending less time building and thus focus on evaluating potentially useful strategies. This project will develop state-of-the-art technologies for cell engineering and enable their application to solve three open, complementary, clinically motivated challenges. The first aim is to develop the technology, understanding, and computational tools required to build genetic programs that employ natural mechanisms for implementing long-lived memory. Natural systems employ genetic memory to drive processes such as differentiation and development by adding and removing stable marks to the genome. Although research has yielded insights into how to drive such changes, bioengineers do not yet have the ability to leverage those insights to build programs that implement these effects for useful purposes. This project will address this need by developing genetic programs that exhibit stable behaviors including inducible and autonomous state switching. The second aim will generate novel candidate cell therapies for treating cancer that leverage foundational advances for engineering cells to evaluate and respond to external cues (e.g., unique markers of the tumor site) to induce desired therapeutic behaviors. This work will develop programs hypothesized to improve both safety and efficacy of these approaches. A key aspect of this work is employing model-guided design to evaluate and refine genetic programs to confer desired behaviors. The third aim will develop a computational framework enabling computer-assisted design of genetic programs. Current design is limited by the imagination of the designer—a human must propose a design which is subsequently evaluated. This aim will make the transformative leap to semi-automated design, establishing workflows and tools that are freely accessible to researchers in a graphics-enabled open software framework.