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

用于检测内源性和外源性阿片类药物的配体选择性荧光生物传感器的高通量工程

• 批准号: 10635413
• 负责人: Andre Berndt
• 金额: $ 251.02万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-15 至 2026-04-14
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10635413
• 关键词: Acceleration; Adaptive Behaviors; Address; Affinity; Anxiety; Area; BRAIN initiative; Behavior; Behavioral; Benchmarking; Biology; Biosensor; Brain; Brain region; Cells; Chimeric Proteins; Coupling; Data; Detection; Development; Disease; Drug Screening; Endorphins; Engineering; Enhancers; Enkephalins; Ensure; Fiber; Fluorescence Microscopy; Future; Genetic; Goals; Green Fluorescent Proteins; In Vitro; Invertebrates; Knock-out; Learning; Libraries; Ligand Binding; Ligands; Link; Location; Measurement; Memory; Methods; Modeling; Molecular; Molecular Conformation; Monitor; Mus; Mutagenesis; Neurons; Neuropeptides; Neurosciences Research; Nucleus Accumbens; Opioid; Opioid Peptide; Opioid Receptor; Optics; Organism; Pain; Partner in relationship; Pathologic; Performance; Photometry; Physiological; Population; Positioning Attribute; Property; Protein Engineering; Proteins; Randomized; Reporter; Research; Research Personnel; Signal Transduction; Slice; Specificity; Speed; Stress; Structure of nucleus infundibularis hypothalami; Testing; Time; Variant; Vertebrates; Work; attenuation; biophysical properties; cell type; combat; delta opioid receptor; design; endogenous opioids; experimental study; feeding; high throughput screening; improved; in vivo; in vivo monitoring; innovation; innovative technologies; mu opioid receptors; neuronal circuitry; neurotransmission; next generation; novel; novel therapeutic intervention; opioid abuse; opioid withdrawal; optogenetics; pharmacologic; prototype; receptor; sensor; temporal measurement; tool development; two-photon

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.

项目总结/摘要 神经元回路的神经肽调节与许多关键行为密切相关， 探索、压力、记忆形成、学习和许多病理生理条件。不幸的是， 众所周知，神经肽很难理解，因为许多方法都不能很好地分离 神经肽在脑内的空间和时间中准确地起作用。基因编码荧光蛋白 传感器可以提供具有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显著障碍是电流的缓慢通过量。 工程方法。我们在这项提案中的中心目标是开发专门用于 通过实现大信号幅度和生理- 相关配体结合亲和力。同时，我们将建立一个高效的神经肽框架 传感器工程我们将利用我们新的工程平台，在几分钟内筛选数千种传感器变体。 分钟，效率高。我们将快速识别具有所需振幅和灵敏度的传感器 用于体内回路特异性阿片样物质检测。此外，我们将在诱发模型中描述所有传感器的特征。 内源性阿片样物质释放的行为小鼠的大脑。我们已经设计了一种阿片类物质传感器 具有改进的生物物理特性的原型，我们将在这些范例中用作阈值。我们的目标 是产生多个，特定的传感器，用于神经元回路中的高级检测能力， 阿片受体和/或肽的存在。在目标1中，我们将创建大型传感器变体库， 信号幅度，以对抗体内应用中预期的信号衰减。我们将针对具体 残基进行随机突变，以促进传感器群体转变为活性构象。 此外，我们将增加阿片类物质传感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，例如脑啡肽超过内啡肽等。 靶向配体结合口袋中或附近的残基的文库。我们将在我们的高- 通量筛选以鉴定具有所需配体选择性的传感器。在目标3中，我们将验证传感器 在体内和在诱发阿片样物质释放的行为期间。这包括监测内源性阿片肽 在具有细胞类型和回路类型特异性的各种脑区域中使用纤维光度法进行动力学分析。这项建议 是重要的，因为神经肽是神经元活动的关键调节剂，但它们的动力学作用 由于缺乏适当的体内监测，尚未充分了解。我们的项目是创新的，因为 所提出的方法将提供最快的吞吐量在设计高效的神经肽传感器蛋白。 此外，阿片受体可能是识别状态依赖性增强剂的神经机制的关键， 行为，如压力和焦虑，或探测阿片类药物滥用条件下的大脑回路。