Engineered gene circuits for basic science and biotechnology

项目摘要 我们将继续设计、建造和表征基因电路。我们将使用微电子工具 在精确控制的环境条件下生长和观察单个细胞和克隆，我们将 在动物模型中测试一组工程细菌菌株作为治疗方法。单细胞和集落 动力学将为数学模型提供信息，这些模型将用于确定关键的设计特征，其中 然后将使用先前建立的分子生物学技术进行严格的测试。八名毕业生 学生和博士后将致力于该项目的多个方面，同时保持对 用于监测细菌或活体表征的建模或技术开发。我们的过往记录 展示我们以多学科方法培训人员的能力，这种方法已为 合成生物学，以及对基因和信号网络的普遍了解的增加。 我们最近在动物模型中对细菌回路的表征突出了这种需求 对于在治疗相关的时间范围内稳定和安全的有益菌株。因此，我们的 特定目标侧重于稳定性(目标1)、传递(目标2)、安全性(目标3)和体内试验(目标4)。 基因电路不可避免地会产生突变，这些突变是为了减少额外的负担而选择的 通过植入的基因机器。我们的首要目标是制定延长生命周期的策略 在选择性压力使细菌的预期功能失效之前，细菌中的基因回路。我们将发展 计算模型和实验量化电路冗余如何提高电路寿命。我们 将使用我们的实验平台来监控从单细胞培养到批量培养的各种功能 环境。我们的第二个目标将主要集中在设计小型细菌生态系统上。在这里我们 将使用建模来指导最多三个相互作用的菌株的设计，这些菌株可以在 预先确定的顺序。在第三个目标中，我们将建立一个触发死亡的安全电路 所有细菌在给定的门槛种群密度下。我们的目标是创造一个不可逆转的细胞内 在突变可能危及安全策略之前，这种开关可以迅速而特别地杀死所有细胞。在……里面 最后，我们将在动物模型上测试第一个三个目标中设计的电路。我们将进行工程设计 能够表征体内细菌菌落动态和肿瘤大小的光学标记。 重要的是，细菌克隆的相对容易和低成本将不可避免地导致 合成生物学，因为治疗性菌株的产生速度将远远超过 来测试他们。这突显了对经过彻底验证的量化模型的迫切需求 使用体外技术。因此，只有一小部分在AIMS 1-3建造的赛道将被视为 值得进行体内试验。更广泛地说，我们预计由此产生的计算模型 这些研究将普遍适用于使用细菌的各种新兴应用。

Project Summary We will continue to design, construct and characterize genetic circuits. We will use micro uidic tools to grow and observe single cells and colonies in precisely controlled environmental conditions, and we will test a subset of the engineered bacterial strains as therapies in animal models. Single cell and colony dynamics will inform mathematical models that will be used to identify key design characteristics, which will then be rigorously tested using previously established molecular biology techniques. Eight graduate students and postdocs will work on multiple aspects of the project, while maintaining a particular focus on modeling or technology development for monitoring bacteria or in vivo characterization. Our track record demonstrates our ability to train personnel in a multi-disciplinary approach that has led to new tools for Synthetic Biology, along with an increased understanding of gene and signaling networks generally. Our recent characterization of bacterial circuits in animal models has served to highlight the need for bene cial strains that are stable and safe over therapeutically relevant timescales. Accordingly, our Speci c Aims focus on stability (Aim 1), delivery (Aim 2), safety (Aim 3), and in vivo testing (Aim 4). Gene circuits inevitably generate mutations that are selected to decrease the additional burden created by the inserted genetic machinery. Our rst aim will develop strategies for extending the \lifetime" of gene circuits in bacteria before selective pressure disables their desired functionality. We will develop computational models and experimentally quantify how circuit redundancy increases circuit lifetime. We will use our experimental platform to monitor functionality across scales from single-cell to batch culture environments. Our second aim will primarily focus on engineering small bacterial ecologies. Here we will use modeling to guide the design of up to three interacting strains that can deliver therapies in a pre-determinted sequential order. In the third aim, we will build a safety circuit that triggers the death of all bacteria at a given threshold population density. The goal is to create an irreversible intracellular switch that rapidly and eciently kills all cells before mutations can compromise the safety strategy. In the nal aim, we will test the circuits designed in the rst three aims in animal models. We will engineer optical markers that enable characterization of the dynamics of bacterial colonies and tumor size in vivo. Importantly, the relative ease and low cost of bacterial cloning will inevitably lead to a bottleneck for the eld of Synthetic Biology, as therapeutic strains can be created at a rate that will far exceed the ability to test them. This highlights an acute need for quantitative models that have been thoroughly validated using in vitro technologies. Consequently, only a fraction of the circuits built in Aims 1-3 will be deemed worthy of in vivo testing. More generally, we anticipate that the computational models arising from these studies will be generally applicable across a wide range of emerging applications that employ bacteria.