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

在果蝇睡眠稳态系统级模型中建立分子联系

基本信息

  • 批准号:
    1656603
  • 负责人:
  • 金额:
    $ 55.79万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-05-15 至 2022-04-30
  • 项目状态:
    已结题

项目摘要

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.
非技术性摘要许多人都很熟悉一夜失眠后第二天的强烈睡眠需求。这种需求的建立往往是紧迫的,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,大概是由一组通过复杂的电信号和生化信号相互连接的神经元产生的。这个神经元连接系统被统称为睡眠稳态器。但是,尽管体内平衡器在控制睡眠中起着核心作用,但人们对其结构、组成和工作原理知之甚少。这项研究将利用果蝇来构建稳态器的功能架构,果蝇像人类一样表现出睡眠,但由于其相对简单,提供了一个易于处理的系统来解剖稳态器。拟议的研究将开发一系列新的遗传工具,这些工具将允许精确和可控地操纵神经元和被怀疑形成睡眠稳态的互连通路。实验将由PI开发的新型计算模型指导。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验证假设。该项目中数学建模和遗传学的相互作用将为本科生和研究生提供跨学科研究和课程的独特机会,特别强调传统上在科学领域代表性不足的成员。 技术摘要这项工作将建立一个模型的睡眠稳态,一个反馈系统,调整未来的睡眠需求的基础上过去的睡眠,这是既数学上严格和分子上听话。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描述这些途径。结合行为,遗传和计算的方法将被用来连接的理论参数的神经调质,从而建立了第一个定量模型的睡眠稳态与明确的分子身份。目的1将检查睡眠-觉醒动力学过表达或表达不足的候选神经调质,以快速生成神经调质通路的短名单。然后,目标2将使用Gal 4/UAS系统靶向产生神经调节剂的神经元,通过改变入围底物的丰度来生物化学地干扰它们。目标3将过表达离子通道,以电干扰特定的神经调节剂表达神经元,并作为第三个独立的测试,在识别神经调节剂,苍蝇睡眠稳态的基础。总之,这些研究将导致一个统一的,计算分子模型的稳态,并在这样做,大大拓宽了我们的理解的神经机制管理睡眠。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经验,从而培养未来的科学家如何将数学和分子方法整合到神经系统功能的研究中。

项目成果

期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Daytime colour preference in Drosophila depends on the circadian clock and TRP channels
  • DOI:
    10.1038/s41586-019-1571-y
  • 发表时间:
    2019-10-03
  • 期刊:
  • 影响因子:
    64.8
  • 作者:
    Lazopulo, Stanislav;Lazopulo, Andrey;Syed, Sheyum
  • 通讯作者:
    Syed, Sheyum
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Sheyum Syed其他文献

A Computational Method to Quantify Fly Circadian Activity.
量化苍蝇昼夜节律活动的计算方法。
Real time, in vivo measurement of neuronal and peripheral clocks in Drosophila melanogaster
果蝇神经元和外周时钟的实时体内测量
  • DOI:
    10.1101/2022.01.12.476067
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    7.7
  • 作者:
    Peter S. Johnstone;Maite Ogueta;Inan Top;Sheyum Syed;R. Stanewsky;Deniz Top
  • 通讯作者:
    Deniz Top
Automated analysis of internally programmed grooming behavior in Drosophila using a k-nearest neighbors classifier
使用 k 最近邻分类器自动分析果蝇内部编程的梳理行为
  • DOI:
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Bing Qiao;Chiyuan Li;V. W. Allen;M. Shirasu;Sheyum Syed
  • 通讯作者:
    Sheyum Syed
Synthesis in living cells with the assistance of supramolecular nanocarriers
借助超分子纳米载体在活细胞中合成
  • DOI:
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    S. Ragab;Ek Raj Thapaliya;Yang Zhang;Sicheng Tang;Jeffrey B McMahan;Sheyum Syed;B. Captain;F. Raymo
  • 通讯作者:
    F. Raymo

Sheyum Syed的其他文献

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{{ truncateString('Sheyum Syed', 18)}}的其他基金

Circuit Mechansims of Color Preference
颜色偏好的电路机制
  • 批准号:
    2131037
  • 财政年份:
    2022
  • 资助金额:
    $ 55.79万
  • 项目类别:
    Continuing Grant

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