Design of genetically encoded sensors for detecting endogenous opioid peptides

检测内源性阿片肽的基因编码传感器的设计 靶向Mu阿片受体(MOR)的阿片类药物仍然是最有效的止痛药，但 有严重的副作用，如上瘾、便秘和呼吸抑制。副作用 这是由于目前可用的阿片类药物在痛觉调制回路中缺乏MOR的特异性所致。 由于内源性阿片肽不会导致这种不良反应，了解它们在不同的 神经元回路可以促进我们对阿片肽如何不同地发挥作用的了解，并可能促进 副作用减少的新型止痛药的设计。研究内源性阿片肽是如何 在不同的神经回路中发挥作用，我们需要检测内源性阿片类药物何时何地 多肽在大脑中以高时空分辨率和电路水平释放。微透析， 检测小鼠大脑中阿片肽的最佳方法，可以用 空间分辨率为~400微米，时间分辨率为~20分钟。然而，神经元SoMAS是~ 20微米和神经调节肽通常被释放，并在几秒钟到几分钟的数量级起作用。 需要一种具有较高时空分辨率的内源性阿片肽释放检测方法 决议。因此，我们建议设计两类阿片类传感器：1)转录报告 这将使以细胞分辨率检测内源性阿片肽成为可能 研究内源性阿片肽如何在脑回路发挥作用的脑组织体积 水平；2)实时荧光传感器，能够检测内源性阿片肽 具有亚细胞空间分辨率和数秒量级的时间分辨率。这两个传感器 将相辅相成，解决有关内源性阿片类药物的长期悬而未决的问题 多肽调节和信号转导。例如，什么样的疼痛和奖赏刺激会刺激阿片类药物 释放多肽？阿片肽到底在哪里以细胞或亚细胞分辨率释放 对不同的疼痛和奖励刺激的反应？疼痛或奖励刺激后多久是内源性阿片类药物 多肽释放了吗？这项建议的完成将有助于我们设计工具以实现以下长期目标 提高我们对内源性阿片信号转导用于设计迷你-阿片类止痛药的理解 妈妈的副作用。

Design of genetically encoded sensors for detecting endogenous opioid peptides Opioids that target the mu-opioid receptors (MOR) remain the most effective pain medication but with severe side effects, such as addiction, constipation and respiratory suppression. The side effects result from a lack of specificity for the MOR in the pain modulation circuit by currently available opioids. Since endogenous opioid peptides do not lead to such adverse effects, understanding their role in different neuronal circuits could advance our knowledge of how opioid peptides act differently, and possibly facilitate the design of novel pain medications with reduced side effects. To study how endogenous opioid peptides exert their effects on different neural circuits, we need to detect when and where the endogenous opioid peptides are released in the brain at a high spatiotemporal resolution and at the circuit level. Microdialysis, the best available method for detecting opioid peptides in the mouse brain, can detect opioid peptides with a spatial resolution of ~ 400 µm and a temporal resolution of ~20 minutes. However, neuron somas are ~ 20 µm and neuromodulating peptides are usually released and function on the order of seconds to minutes. There is a need of methods to detect the endogenous opioid peptide release with higher spatiotemporal resolution. Therefore, we propose to design two classes of opioid sensors: 1) A transcriptional reporter that will enable the detection of the endogenous opioid peptides at a cellular resolution across a large volume of the brain tissue for studying how endogenous opioid peptides exert their effects at the circuit level; 2) Real time fluorescent sensors that will enable the detection of the endogenous opioid peptides with subcellular spatial resolution and a temporal resolution on the order of seconds. These two sensors will complement each other to address the long unanswered questions regarding the endogenous opioid peptide regulation and signaling. For example, what kind of pain and reward stimuli will stimulate the opioid peptide release? Where exactly are the opioid peptides released at a cellular or sub-cellular resolution in response to different pain and reward stimuli? How soon after pain or reward stimuli are endogenous opioid peptides released? Completion of this proposal will contribute to our long-term goal of designing tools to advance our understanding of the endogenous opioid signaling for designing pain medications with mini- mum side effects.