Harnessing Calcium Influx to Visualize and Regulate Seizure Networks

项目摘要。癫痫在美国的患病率为每1000人中有7人，是第四大 常见的神经系统疾病虽然许多患者通过药物治疗缓解了致残性癫痫发作， 大约三分之一的癫痫病例具有抗药性。对于许多这些医学上难以治愈的病例， 需要进行干预并且虽然在多达四分之三的这些患者中获得了癫痫发作自由， 外科手术方法具有相当大的局限性和缺点。开放切除和消融是破坏性的 和永久性，神经刺激，需要植入硬件，对硬件构成风险 故障和感染。此外，这些缺乏细胞类型特异性的方法影响该区域的所有组织。 有针对性的，带有脱靶效应的风险。因此，需要一种癫痫治疗， 神经元启动或传播病理性神经元活动。开发这种治疗方法将是 通过更好地理解癫痫发作活动动力学，特别是在细胞分辨率下，的 目前对癫痫发作动力学的大多数理解来自电生理学，包括EEG， 仅提供活动的群体分辨率和单个单元记录。虽然单个单位记录活动， 单个神经元记录的神经元的密度是稀疏的，并且极难知道什么亚型 的神经元被记录下来。遗传编码钙指标（GECI）规避了许多这些 并且允许通过使用双光子成像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于在啮齿动物模型中可视化急性癫痫发作， 这项工作还没有在自发性发作模型中捕获发作，这更接近癫痫。因此，在本发明中， 我们的目的首先是检查癫痫发作网络中神经元的时空放电，在慢性小鼠模型中， 新皮质癫痫发作，并通过神经元亚型解析活动（Aim 1）。在此活动期间发出的光将 然后被用来开发一种活动响应神经调节剂，使网络能够自我调节。 我们的实验室开发了光化学发生剂，发光蛋白，我们已经用于细胞亚型特异性， 硬件独立的体外和体内神经调节。具体地，发光蛋白是光响应离子， 通道或泵与它们自己的光源，一种生物发光酶融合。我们的目标是修饰发光蛋白 构建体，用生物发光GECI交换生物发光酶，这将产生发光蛋白 其功能取决于足够的细胞内钙并因此取决于活性。钙结合 将选择对这些响应性发光蛋白的亲和力，使得它们仅响应于高细胞内活性。 钙的水平，如癫痫发作期间所经历的，这将允许保存非- 病理性神经元活动然后在自发性癫痫发作中将响应性发光蛋白引入体内 模型来观察他们是否能够使这些网络自我调节（目标2）。最终，发展 这些知识和工具可以用来为未来癫痫治疗的发展提供信息。

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.