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 活性氧簇(ROS)水平的升高与导致心肌病和神经退行性变的严重病理条件密切相关。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，目前许多ROS传感器的能力仍然受到信号幅度小、动力学速度慢、灵敏度低、体内不相容以及细胞和亚细胞靶向的限制。因此，实时监测氧化应激的ROS仍然是非常有限的。 我们在这项提案中的中心目标是解决目前ROS蛋白质传感器的局限性。我们将结合结构引导蛋白质设计和高通量筛选大型变异库，以一种创新的方法来设计新型的ROS传感器。我们预计，显著增加的信号幅度、ROS敏感性和对低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的神经变性和心肌病模型中验证新的传感器，并以亚细胞精度进行验证。我们的目标是进一步最大限度地发挥ROS传感器的功能，以高级监测疾病模型中对急性和慢性应激源的氧化应激。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敏感的蛋白结构域来拓宽这类传感器的颜色光谱。此外，与荧光蛋白质相比，我们将创造出更具光稳定性和对氧气水平变化不敏感的传感器。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异文库。快速、迭代的过程有可能显著加快目标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，以获得即时反馈，以进一步完善传感器功能。这包括监测氧化应激，将其作为阿尔茨海默病、干细胞来源的神经元和心肌细胞的缺血和再灌注的指标。这一建议意义重大，因为氧化应激很常见，可以影响到每一个器官和细胞类型，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来更精确地监测生理过程。改良的ROS传感器的工程将极大地扩展这些方法在细胞信号和疾病进展分析中的应用。我们的项目是创新的，因为所提出的方法将为设计高效的ROS传感器蛋白提供最快的吞吐量。此外，改进后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，并显著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.