Harnessing Calcium Influx to Visualize and Regulate Seizure Networks

项目总结。癫痫在美国的患病率为每1000人中有7人，是第四大 常见的神经性疾病。虽然许多患者通过药物治疗可以缓解癫痫发作， 大约三分之一的癫痫病例是耐药的。对于许多这些医学上难以治愈的病例，外科手术 虽然这些患者中多达四分之三的患者获得了癫痫发作自由， 外科手术方法有很大的局限性和缺点。开放切除和消融是破坏性的。 而永久性和神经刺激，需要植入硬件，对硬件来说是一个风险 故障和感染。此外，这些缺乏细胞类型特异性的方法会影响该区域的所有组织。 有针对性的，有偏离目标效果的风险。因此，需要一种专门针对癫痫的治疗方法 启动或传播病理性神经元活动的神经元。这种疗法的开发将是 通过更好地了解癫痫发作活动动力学，特别是在细胞分辨率下，大大了解了这一点。这个 目前对癫痫发作动力学的大部分了解来自电生理学，包括脑电，它 仅提供活动和单个单元记录的总体分辨率。而单个单元记录来自 单个神经元记录的神经元密度很稀疏，很难知道是什么亚型 正在被记录下来。基因编码的钙指示剂(GECI)可以绕过其中的许多 缺点，并允许通过使用双光子来观察单个神经元的活动 动物模型中的显微镜。虽然这种方法已经被用来在啮齿动物模型中可视化急性癫痫发作， 这项工作还没有捕捉到自发发作模型中的癫痫发作，这更接近于癫痫。因此， 我们首先旨在研究癫痫网络中神经元的时空放电在慢性癫痫小鼠模型中的作用。 新皮质癫痫发作，并按神经元亚型分析其活动(目标1)。在本练习中发出的光将 然后被利用来开发一种活动响应性神经调节剂，使网络能够自我调节。 我们的实验室开发了光化学发生剂，发光素，我们已经用于细胞亚型特异性， 硬件不依赖于体外和体内的神经调节。具体地说，发光素是光响应离子。 通道或泵与它们自己的光源融合在一起，光源是一种生物发光酶。我们的目标是修改发光体 构建，将生物发光酶与生物发光Geci交换，这将导致发光素 它的功能取决于细胞内有足够的钙，从而具有活性。钙离子结合 这些响应性发光素的亲和力将被选择为仅对细胞内高水平的发光蛋白做出反应 钙的水平，例如在癫痫发作期间经历的水平，这将允许保存非 病理性神经元活动。反应灵敏的发光素随后将在自发性发作中被引入体内。 模型以观察它们是否能够使这些网络自我调节(目标2)。归根结底发展 这方面的知识和工具可用于为癫痫的未来治疗方法的发展提供信息。

PROJECT SUMMARY. Epilepsy, with a prevalence in the United States of 7 per 1000 people, is the fourth most common neurological disorder. While many patients achieve relief from disabling seizures through medication, about one third of epilepsy cases are pharmacoresistant. For many of these medically intractable cases, surgical intervention is indicated and while seizure freedom is obtained in as many as three quarters of these patients, the surgical approaches have substantial limitations and drawbacks. Open resection and ablation are destructive and permanent, and neurostimulation, necessitating implanted hardware, presents a risk for hardware malfunction and infection. Furthermore, these methods lacking cell-type specificity impact all tissue in the region targeted, carrying a risk for off target effects. Hence there is a need for an epilepsy treatment that is specific to the neurons initiating or propagating the pathologic neuronal activity. Development of such a treatment would be greatly informed by a better understanding of seizure activity dynamics, especially at a cellular resolution. The majority of the current understanding of seizure dynamics come from electrophysiology, including EEG, which only offers population resolution of activity, and single unit recordings. While single units record activity from individual neurons the density of neurons recorded is sparse and it is exceedingly difficult to know what subtype of neuron is being recorded. Genetically encoded calcium indicators (GECI) circumvent many of these drawbacks and allow for observation of the activity of individual neurons through the use of two-photon microscopy in animal models. While this approach has been taken to visualize acute seizures in a rodent model, this work has yet to capture seizures in spontaneous seizure models, which better approximate epilepsy. Thus, we first aim to examine spatiotemporal firing of neurons within seizure networks in a chronic mouse model of neocortical seizures and parse the activity by neuronal subtype (Aim 1). The light emitted during this activity will then be harnessed to develop an activity responsive neuromodulatory agent to allow networks to self-regulate. Our lab developed opto-chemogenetic agents, luminopsins, which we have used for cell subtype specific, hardware independent in vitro and in vivo neuromodulation. Specifically, luminopsins are light responsive ion channels or pumps fused with their own light source, a bioluminescent enzyme. We aim to modify the luminopsin construct, exchanging the bioluminescent enzyme with a bioluminescent GECI, which will result in a luminopsin whose functionality is contingent upon sufficient intracellular calcium and thus activity. The calcium binding affinity for these responsive luminopsins will be selected such that they are only responsive to high intracellular levels of calcium, such as those experienced during seizures, which would allow for preservation of non- pathologic neuronal activity. Responsive luminopsins will then be introduced in vivo in a spontaneous seizure model to observe if they are able to enable these networks to self-regulate (Aim 2). Ultimately the development of such knowledge and tools could be used to inform development of future treatments for epilepsy.