Using Mouse Pain Scales to Discover Unusual Pain Sensitivity and New Pain Targets

项目摘要 急性和慢性疼痛存在巨大的个体间差异，遗传结构是其中之一 形成我们对疼痛的独特反应的主要因素。伤害性感受器中基因的错误表达可以促进 从急性疼痛到慢性疼痛的过渡，因此靶向外周伤害性感受器基因是一个重要的 通向非上瘾的止痛药之路。如果我们试图发现人类基因组的多样性可能会导致 病理性痛感，这是我们在临床前研究中对一种典型的野生型小鼠品系的狭隘关注， C57BL/6J，是不够的。此外，为了充分利用疼痛小鼠模型的翻译潜力， 先决条件是能够准确地测量疼痛，这是一种内在的主观感觉，它成为 在非语言动物身上得分就更难了。在我的实验室最近发表的文章中，我们开发了自动化 使用高速摄像、机器学习和定制软件的鼠标“疼痛刻度”，捕捉 以定量的方式描述疼痛的感觉--反射维度。在正在进行的研究中，我们使用无监督学习 这些平台可以自动捕捉疼痛的自发信号。因此，我们现在可以很好地使用 我们的自动疼痛行为评估平台可测试新的疼痛目标基因并从基因上识别 具有非典型疼痛敏感性的发散小鼠。 我们在这个新创新者奖项目中有三个主要目标。首先，我们的目标是从基因上识别 独特的小鼠品系，对急性和慢性疼痛有不寻常的反应，使用诱发和自发疼痛 测量，测试数百只老鼠。在此应用程序中测试的无法正常响应的鼠标行 对疼痛的反应或疼痛反应增强，可能是揭示人群如何 病理性疼痛敏感。这一点很重要，因为对疼痛过敏的人似乎有 患慢性疼痛的风险增加。这些小鼠品系的遗传结构也有助于 绘制分析图，将基因与疼痛特征联系起来，从而确定潜在的新疼痛靶点。第二，我们将 在我的实验室已经发表的一种小鼠品系中研究疼痛敏感的生物学基础， 机械性疼痛过敏。我们的目标是确定允许这种过敏性的原因变化，从而 解锁一个新的痛苦目标。最后，我们将使用小鼠基因打靶来消融小鼠的一个候选疼痛靶点 使用我们的自动化行为流水线测试伤害性感受器和功能后果。这个新的候选基因 最近从人类伤害性感受器的单细胞RNA测序中出现了。总而言之，我们正在利用 我的实验室开发了工具，并将资源提供给整个社区，以制作一份超级疼痛地图集- 以及低敏感的小鼠品系，以及在功能上识别新的疼痛治疗靶点。

Project Summary There is vast inter-individual variability to acute and chronic pain, and genetic architecture is one of the major factors that shape our unique responses to pain. The misexpression of genes in nociceptors can facilitate the transition from acute to chronic pain, and thus targeting nociceptor genes in the periphery is an important route towards non-addictive pain therapeutics. If we seek to uncover how diverse human genomes may give rise to pathological pain sensation, a narrow focus in our preclinical studies on one canonical wildtype mouse line, C57BL/6J, is insufficient. Moreover, to harness the full translational potential of mouse models of pain, a prerequisite is being able to accurately measure pain, which is an inherently subjective sensation that becomes even harder to score in nonverbal animals. In recent publications from my lab, we have developed automated mouse “pain scales” using high-speed videography, machine learning, and custom software, to capture the sensory-reflexive dimensions of pain in a quantitative manner. In ongoing studies, we use unsupervised learning platforms to automatically capture spontaneous signatures of pain. Therefore, we are now well-positioned to use our automated pain behavior assessment platforms to test new pain target genes and identify genetically divergent mice with atypical pain sensitivity. We have three major goals in this New Innovator Award program. First, we aim to identify genetically unique mouse lines that have unusual responses to acute and chronic pain, using evoked and spontaneous pain measurements, testing hundreds of mice. The mouse lines tested in this application that fail to respond normally to pain, or have heightened pain responses, may hold the keys to uncovering how populations of people have pathological pain sensitivity. This is significant because individuals with hypersensitivity to pain, appear to have an increased risk of developing chronic pain. The genetic construction of these mouse lines also facilitates mapping analyses to connect genes to pain traits, thus identifying potential new pain targets. Second, we will investigate the biological basis of pain sensitivity in a mouse line that my lab already published on, as having mechanical pain hypersensitivity. We aim to identify causative changes that permit this hypersensitivity, and thus unlock a new pain target. Finally, we will use mouse genetic targeting to ablate a candidate pain target in mouse nociceptors and test functional consequences with our automated behavioral pipelines. This new candidate gene recently emerged from single-cell RNA sequencing of human nociceptors. Taken together, we are levering the tools my lab developed and resources made available to the entire community, to produce an atlas of pain hyper- and hypo-sensitive mouse lines, as well as functionally identifying new pain therapeutic targets.