PgmNr D1269: Receptor-based Mapping Reveals the Architecture of a Neural Circuit that Governs a Behavioral Sequence in Drosophila.

Authors:
F. Diao; Amicia Elliott; Fengqiu Diao; Sarav Shah; Benjamin White


Institutes
national institute of mental health, Bethesda, MD.


Keyword: neuropeptides

Abstract:

Studies in both vertebrates and invertebrates have shown that neuromodulators can reconfigure the output of multifunctional neural networks to generate multiple motor patterns. However, very few such networks have been characterized in detail and knowledge of how modulators act at different levels within a network remains poorly understood. Progress has been impeded both by the lack of complete maps of most neural networks and by incomplete knowledge of how network-wide activity translates into behavior in intact animals.  Here we address these issues, using the pupal ecdysis sequence of Drosophila as a model, taking advantage of its essential dependence on neuromodulatory inputs and its well-defined behavioral components. Pupal ecdysis consists of three, sequentially executed motor rhythms and is governed by multiple neuroactive factors, among which Ecdysis Triggering Hormone (ETH), CCAP, and Bursicon have well-characterized roles. By manipulating neurons that express the receptors of these factors, we have succeeded in mapping the hierarchical organization of the ecdysis network. We find that three distinct subsets of ETH receptor-expressing neurons comprise individual input modules, each one essential for a different behavioral phase. Bursicon receptor-expressing interneurons form a multi-functional central pattern generator (CPG) targeted by the ETHR-expressing modules. Downstream of this CPG are CCAP receptor-expressing motor neurons, which are responsible for generating the ecdysis motor rhythms. The expression patterns of the receptors of key modulators governing the ecdysis sequence thus define the hierarchical architecture of the ecdysis network.  Our results provide an example of how receptor mapping can be used to identify functional nodes in a neural circuit and characterize their organization. In addition, our work serves as an entry point to investigating the mechanisms underlying multi-level control of behavioral state by neuromodulators in a neuronal circuit.