Genetic dissection of locomotion

描述(申请人提供)：所有动物物种的运动都依赖于精确的协调：动物必须以刻板的和有节奏的方式同步无数的肌肉屈曲和伸展活动。运动协调的核心是中枢模式发生器(CPG)，这是一种神经电路，具有从相对简单的非节奏输入产生节奏输出的能力。虽然已经有大量的运动性和非运动性CPG的功能证据，但在更复杂的系统中调节协调运动的CPG的细胞成分在很大程度上仍然不确定。此外，在细胞水平上，运动CPG活动如何相互整合并被下行和感觉输入所改变也在很大程度上是未知的。我们知识中的这些差距可能不仅是由于神经电路的复杂性，也是正在研究的行为的复杂性的结果。为了应对这些挑战，这个项目的长期目标是补充和扩展其他系统中现有的努力，利用果蝇中可用的强大遗传工具来表征运动神经回路， 黑腹果蝇。在这项提议中，将使用一种新的高分辨率测试来定量测量果蝇模型中的数十个行走参数，以筛选由于激活和/或抑制神经元亚群中的神经活动而发生的特定突变表型。建议进行后续实验，以确定导致这些突变表型的神经元。

DESCRIPTION (provided by applicant): Locomotion in all animal species relies on precise coordination: animals must synchronize a myriad of muscle flexion and extension events in a stereotyped and rhythmic manner. At the core of motor coordination are central pattern generators (CPGs), neural circuits that have the capacity to produce rhythmic outputs from relatively simple, non-rhythmic inputs. Although there exists a large amount of functional evidence for both locomotor and non-locomotor CPGs, the cellular components of CPGs that mediate coordinated locomotion in more complex systems remain largely undefined. Further, how locomotor CPG activities are integrated with each other and modified by descending and sensory inputs is also largely unknown at the cellular level. These gaps in our knowledge may be due not only to the complexity of the neural circuitry, but also a consequence of the complexity of the behaviors under investigation. To address these challenges, the long-term goal for this project is to complement and expand upon existing efforts in other systems to characterize locomotor neural circuits using the powerful genetic tools available in the fruit fly, Drosophila melanogaster. In this proposal, a novel, high-resolution assay that quantitatively measures dozens of walking parameters in the fruit fly model will be used to screen for specific mutant phenotypes that occur as a consequence of activating and/or suppressing neural activity in subsets of neurons. Follow-up experiments are proposed to identify the neurons that are responsible for these mutant phenotypes.