High-throughput engineering of ligand-selective fluorescent biosensors for detecting endogenous and exogenous opioids

项目摘要/摘要 神经肽对神经元回路的调节与许多关键行为密切相关，如 探索、压力、记忆形成、学习和许多病理生理条件。不幸的是， 神经肽是出了名的难以理解，因为许多方法都不适合分离。 神经肽在大脑内准确地在空间和时间上发挥作用。基因编码的荧光蛋白 传感器可以提供高空间和时间分辨率以及细胞类型特异性的精确监测。 然而，神经肽传感器工程中的一个重要障碍是电流的缓慢通过 工程学方法。我们这项提议的中心目标是开发先进的传感器，专门用于 通过实现大信号幅度和生理功能来监测体内阿片神经肽的动态 相关的配体结合亲和力。同时，我们将建立一个有效的神经肽框架 传感器工程。我们将利用我们的新工程平台在几个月内筛选数千个传感器变种 几分钟，而且效率高。我们将快速识别具有所需幅度和灵敏度的传感器 用于体内电路特异性阿片类药物的检测。此外，我们将在诱发的模型中描述所有传感器的特征 行为小鼠脑内内源性阿片类药物释放。我们已经设计了一种阿片类药物传感器 具有改进的生物物理特性的原型，我们将在这些范例中将其用作门槛。我们的目标 是为神经元电路中的高级检测能力生成多个特定的传感器，已知 阿片受体和/或多肽的存在。在目标1中，我们将创建大型传感器变异库以增加 信号幅度，以对抗体内应用中预期的信号衰减。我们将针对特定的目标 带有随机突变的残基，以促进传感器种群向活性构象的转变。 此外，我们将增加阿片感受域和报告结构域之间的变构偶联。在目标2中，我们将 生成具有特定配体选择性特征的传感器，例如脑啡肽胜过内啡肽等。我们将生成 靶向配体结合口袋内或附近残基的文库。我们将在我们的高潮期间应用多个配体- 吞吐量筛选，以识别具有所需配体选择性的传感器。在目标3中，我们将验证我们的传感器 在体内和在引起阿片类药物释放的行为期间。这包括监测内源性阿片肽 使用纤维光度法在具有细胞类型和电路类型特异性的不同脑区中进行动力学分析。这项建议 之所以意义重大，是因为神经肽是神经元活动的关键调节器，但它们的动态行为 由于缺乏适当的体内监测，人们对此还没有很好的了解。我们的项目具有创新性，因为 所提出的方法将在设计高效神经肽传感器蛋白质方面提供最快的吞吐量。 此外，阿片类感受器可能是识别状态依赖增强剂的神经元机制的关键。 压力和焦虑等行为，或在阿片类药物滥用条件下探测大脑回路。

PROJECT SUMMARY / ABSTRACT Neuropeptide modulation of neuronal circuits is strongly linked to many crucial behaviors such as exploration, stress, memory formation, learning, and many pathophysiological conditions. Unfortunately, neuropeptides are notoriously difficult to understand because many methods are not well-positioned to isolate neuropeptide function accurately in space and time within the brain. Genetically-encoded fluorescent protein sensors could provide precise monitoring with high-spatial and temporal resolution and cell-type specificity. However, a significant obstacle in the engineering of neuropeptide sensors is the slow throughput of current engineering approaches. Our central goal in this proposal is to develop advanced sensors specifically for monitoring opioid neuropeptides dynamics in vivo by achieving large signal amplitudes and physiological- relevant ligand binding affinities. At the same time, we will establish an efficient framework for neuropeptide sensor engineering. We will utilize our new engineering platform to screen thousands of sensor variants in a few minutes and with high efficiency. We will rapidly identify sensors with the required amplitudes and sensitivities for circuit-specific opioid detection in vivo. Furthermore, we will characterize all sensors in models of evoked endogenous opioid release in the brain of behaving mice. We have already engineered an opioid sensor prototype with improved biophysical properties that we will use as a threshold in these paradigms. Our objective is to generate multiple, specific sensors for advanced detection capabilities in neuronal circuits with a known presence of opioid receptors and/or peptides. In Aim 1, we will create large sensor variant libraries to increase signal amplitudes to combat the anticipated signal attenuation in in vivo applications. We will target specific residues with randomized mutagenesis to facilitate the transition of sensor populations into active conformations. Additionally, we will increase allosteric coupling between opioid sensing and reporter domains. In Aim 2, we will generate sensors with specific ligand-selectivity profiles, e.g. enkephalin over endorphin, etc. We will generate libraries targeting residues in or near the ligand-binding pocket. We will apply multiple ligands during our high- throughput screens to identify sensors with the desired ligand-selectivity. In Aim 3, we will validate our sensors in vivo and during behaviors that evoke opioid release. That includes monitoring endogenous opioid peptide dynamics using fiber photometry in various brain regions with cell-type and circuit-type specificity. This proposal is significant because neuropeptides are critical modulators of neuronal activity, but their dynamic actions are not well understood due to the lack of appropriate in vivo monitoring. Our project is innovative because the proposed approach will provide the fastest throughput in designing highly efficient neuropeptide sensor proteins. In addition, opioid sensors could be the keys to identify neuronal mechanisms of state-dependent enhancers for behaviors such as stress and anxiety or to probe brain circuits under conditions of opioid abuse.