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

修改项目摘要/摘要部分 活性氧（ROS）水平升高与导致心肌病和神经变性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小信号幅度、慢动力学、低灵敏度、体内不相容性以及细胞和亚细胞靶向限制的限制。因此，实时监测氧化应激的ROS仍然非常有限。 我们在这项提案中的中心目标是解决ROS蛋白传感器的当前限制。我们将结合联合收割机结构化指导的蛋白质设计和高通量筛选的大型变异库的创新方法，工程新的ROS传感器。我们期望显著增加信号幅度、ROS敏感性和对缺氧条件的不敏感性将使我们能够在广泛的疾病模型中监测氧化应激。此外，我们将在干细胞衍生模型中验证新的传感器，用于神经退行性疾病和心肌病的亚细胞精度。我们的目标是进一步最大化ROS传感器功能，用于疾病模型中对急性和慢性应激源的氧化应激的高级监测。在第一个目标中，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这类传感器的色谱。此外，我们还将创造出比荧光蛋白更耐光、对不同氧气水平更不敏感的传感器。在第二个目标中，我们将使用一种新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，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，我们将在几个现实的使用场景中验证我们的传感器，以接收即时反馈，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、干细胞衍生的神经元和心肌细胞中的缺血和再灌注的指标。这一建议是重要的，因为氧化应激是常见的，可以影响每一个器官和细胞类型，导致大量严重的疾病。荧光显微镜的最新进展使我们能够利用特异性探针以越来越高的精度监测生理过程。改进的ROS传感器的工程设计将显着扩大这些方法用于分析细胞信号传导和疾病进展的实用性。我们的项目是创新的，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通量。此外，改进的传感器将能够以显著增加的时间和空间分辨率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。

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.