Structure-guided and high-throughput engineering of genetically encoded sensors for reactive oxygen species

修改后的项目摘要/摘要部分 活性氧（ROS）水平升高与导致心肌病和神经退行性变的严重病理状况密切相关。今天，我们可以利用荧光探针来检测细胞生理学和病理生理学中ROS水平的动态变化。然而，许多ROS传感器的能力目前仍然受到信号幅度小、动力学慢、灵敏度低、体内不相容以及细胞和亚细胞靶向的限制等限制。因此，实时监测氧化应激的ROS仍然受到很大限制。 我们此提案的中心目标是解决 ROS 蛋白质传感器的当前限制。我们将采用创新方法将结构化引导的蛋白质设计和大型变异库的高通量筛选结合起来，设计新型 ROS 传感器。我们期望显着增加信号幅度、ROS 敏感性和对缺氧条件的不敏感性将使我们能够监测各种疾病模型中的氧化应激。此外，我们将在干细胞衍生模型中以亚细胞精度验证神经退行性疾病和心肌病的新传感器。我们的目标是进一步最大化 ROS 传感器功能，以对疾病模型中的氧化应激进行高级监测，以应对急性和慢性应激源。第一个目标是，我们将通过将绿色、黄色和红色荧光蛋白融合到 ROS 敏感蛋白结构域来拓宽此类传感器的色谱。此外，与荧光蛋白相比，我们将创建更光稳定且对变化的氧气水平不敏感的传感器。在第二个目标中，我们将使用一种新颖的荧光传感器工程平台，使我们能够筛选大型随机变体库。快速的迭代过程有可能显着加速目标 1 中建立的传感器框架的优化。在第三个目标中，我们将在几个实际使用场景中验证我们的传感器，以接收即时反馈，以进一步完善传感器功能。这包括监测氧化应激作为阿尔茨海默病、干细胞衍生神经元和心肌细胞缺血和再灌注的指标。这一提议意义重大，因为氧化应激很常见，可以影响每个器官和细胞类型，导致大量严重疾病。荧光显微镜的最新进展使我们能够利用特定的探针以更高的精度监测生理过程。改进的 ROS 传感器的工程将显着扩展这些方法在细胞信号传导和疾病进展分析中的效用。我们的项目具有创新性，因为所提出的方法将为高效 ROS 传感器蛋白的设计提供最快的吞吐量。此外，改进的传感器将能够将疾病表型与氧化应激的急性和慢性应激源因果联系起来，并显着提高时间和空间分辨率。

Modified Project Summary/Abstract Section Elevated levels of reactive oxygen species (ROS) are strongly linked to severe pathological conditions causing cardiomyopathies and neurodegeneration. Today we can utilize fluorescent probes to detect dynamic changes in ROS levels in cell physiology and pathophysiology. However, the capabilities of many ROS sensors are currently still limited by small signal amplitudes, slow kinetics, low sensitivity, in vivo incompatibility, and restraints in cellular and subcellular targeting. Thus, monitoring ROS of oxidative stress in real-time is still very restricted. Our central goal in this proposal is to resolve current limitations in ROS protein sensors. We will combine structured-guided protein design and high-throughput screening of large variant libraries in an innovative approach to engineer novel ROS sensors. We expect that significantly increasing signal amplitudes, ROS sensitivity, and insensitivity to hypoxic conditions will enable us to monitor oxidative stress in a wide range of disease models. Furthermore, we will validate new sensors in stem-cell derived models for neurodegeneration and cardiomyopathies with subcellular precision. Our objective is to further maximize ROS sensor function for advanced monitoring of oxidative stress in disease models in response to acute and chronic stressors. In the first aim, we will broaden the color spectrum of this class of sensors by fusing green, yellow, and red fluorescent proteins to a ROS sensitive protein domain . Furthermore, we will create sensors that are more photostable and insensitive to varying oxygen levels compared to fluorescent proteins. In the second aim, we will use a novel engineering platform for fluorescent sensors that allows us to screen large libraries of randomized variants. The fast, iterative process has the potential to significantly accelerate the optimization of sensor frameworks established in Aim 1. In the third aim, we will validate our sensors in several realistic use scenarios to receive immediate feedback for further refinement of sensor function. This includes the monitoring of oxidative stress as an indicator for Alzheimer’s disease, ischemia and reperfusion in stem-cell-derived neurons and cardiomyocytes. This proposal is significant because oxidative stress is common and can affect every organ and cell type resulting in a large number of severe diseases. Recent progress in fluorescent microscopy allows us to utilize specific probes to monitoring physiological processes with increasing precision. The engineering of improved ROS sensors will significantly expand the utility of those methods for the analysis of cell signaling and disease progression. Our project is innovative because the proposed approach will provide the fastest throughput for the design of highly efficient ROS sensor proteins. Furthermore, the improved sensors will be able to causally link disease phenotypes to acute and chronic stressors of oxidative stress with significantly increased temporal and spatial resolution.