Establishing Molecular Links Within a Systems-level Model of the Drosophila Sleep Homeostat

非技术摘要许多人都很熟悉在一夜失眠后的第二天所感受到的强烈睡眠需求。这种需求的积累往往是紧迫的，因为睡眠对许多基本的生理过程至关重要，包括学习、记忆形成和组织修复。增加的睡眠需求是在大脑中产生的，可能是通过复杂的电信号和生化信号相互连接的神经元集合。这个相互连接的神经元系统统称为睡眠恒定器。但是，尽管恒态器在控制睡眠方面起着核心作用，人们对它的结构、组成和工作原理知之甚少。这项研究将通过利用果蝇的优势来构建稳态的功能架构，果蝇像人类一样表现出睡眠，但由于其相对简单，提供了一个容易处理的系统来剖析稳态。拟议中的研究将开发一系列新的基因工具，使人们能够精确和可控地操纵神经元和疑似形成睡眠稳态的相互连接的通路。实验将由PI开发的一种新的计算模型指导。这些研究的结果将构成睡眠稳态的第一个计算分子模型，并可能产生关于睡眠-觉醒周期调节的新的可检验的假说。数学建模和遗传学在该项目中的相互作用将为本科生和研究生在跨学科研究和课程工作中提供独特的机会，特别强调让传统上在科学界代表性较低的成员参与进来。技术摘要这项工作将建立一个睡眠稳态的模型，这是一个反馈系统，根据过去的睡眠调整未来的睡眠需求，这在数学上是严格的，在分子上也是容易处理的。该项目将利用果蝇来建立一个最近开发的理论模型，该模型表明四个核心生化途径构成了这种昆虫的稳态。该模型的参数预测，神经调节剂如多巴胺和短神经肽F描述了这些通路。将结合行为、遗传和计算方法将理论参数与神经调节剂联系起来，从而建立第一个具有明确分子同一性的睡眠稳态的定量模型。目标1将检查睡眠-觉醒动态过度或表达不足的候选神经调节剂，以快速生成神经调节剂途径的短列表。然后，目标2将使用Gal4/UAS系统来靶向神经调节剂产生神经元，通过改变入围底物的丰度来生化干扰它们。目标3将过度表达离子通道，以电扰乱特定神经调节剂表达的神经元，并作为第三个独立测试，以确定苍蝇睡眠稳态的神经调节剂。总而言之，这些研究将导致一个统一的计算分子模型的稳态，这样做，这样做，大大拓宽了我们对控制睡眠的神经机制的理解。此外，研究中采用的计算和分子方法将被纳入学生的实验室体验，从而培训未来的科学家如何在神经系统功能研究中整合数学和分子方法。

Non-technical abstractThe intense sleep need felt the day following a night of sleeplessness is familiar to many. The build-up of this need is often urgent because sleep is crucial to many essential physiological processes including learning, memory formation and tissue repair. The increased sleep need is generated in the brain, presumably by a collection of neurons inter-connected via complex electrical and biochemical signals. This system of connected neurons is collectively known as the sleep homeostat. But despite the homeostat's central role in controlling sleep, very little is known about its structure, composition, and principles of operation. This research will construct a functional architecture of the homeostat by taking advantage of the fruit fly that, like humans, exhibits sleep but, owing to its relative simplicity offers a tractable system in which to dissect the homeostat. The proposed studies will develop a new series of genetic tools that will allow precise and controllable manipulations of the neurons and the interconnecting pathways suspected of forming the sleep homeostat. The experiments will be guided by a novel computational model developed by the PI. Results from the studies will constitute the first computational-molecular model of the sleep homeostat and will likely give rise to new testable hypotheses about the regulation of sleep-wake cycles. The interplay of mathematical modeling and genetics in the project will offer unique opportunities in interdisciplinary research and coursework for undergraduate and graduate students, with particular emphasis on involving members traditionally underrepresented in the sciences. Technical abstractThis work will establish a model of the sleep homeostat, a feedback system that adjusts future sleep need based on past sleep, which is both mathematically rigorous and molecularly tractable. The project will exploit the fruit fly to build upon a recently developed theoretical model that suggests that four core biochemical pathways constitute the homeostat of the insect. Parameters of the model predict that neuromodulators such as dopamine and short neuropeptide F describe these pathways. A combination of behavioral, genetic and computational approaches will be employed to link the theoretical parameters to the neuromodulators, thus establishing the first quantitative model of the sleep homeostat with well-defined molecular identities. Objective 1 will examine the sleep-wake dynamics over- or under-expressing candidate neuromodulators to rapidly generate a short-list of neuromodulator pathways. Objective 2 will then use the Gal4/UAS system to target the neuromodulator-producing neurons, biochemically perturbing them by altering the abundance of the short-listed substrates. Objective 3 will overexpress ion channels to electrically perturb specific neuromodulator-expressing neurons and serve as a third independent test in the identification of neuromodulators that underlie fly sleep homeostasis. Together, these studies will lead to a unified, computational-molecular model of the homeostat and, in so doing, substantially broaden our understanding of the neural mechanisms governing sleep. Additionally, the computational and molecular approaches taken in the research will be incorporated into laboratory experiences for students, thus training future scientists in how to integrate mathematical and molecular approaches in the study of nervous system functions.