Conditional protein tagging methods reveal highly specific subcellular distribution of ion channels in motion-sensing neurons
Neurotransmitter receptors and ion channels shape the biophysical properties of neurons, from the sign of the response mediated by neurotransmitter receptors to the dynamics shaped by voltage-gated ion channels. Therefore, knowing the localizations and types of receptors and channels present in neurons is fundamental to our understanding of neural computation. Here, we developed two approaches to visualize the subcellular localization of specific proteins in Drosophila: The flippase-dependent expression of GFP-tagged receptor subunits in single neurons and 'FlpTag', a versatile new tool for the conditional labelling of endogenous proteins. Using these methods, we investigated the subcellular distribution of the receptors GluClα, Rdl, and Dα7 and the ion channels para and Ih in motion-sensing T4/T5 neurons of the Drosophila visual system. We discovered a strictly segregated subcellular distribution of these proteins and a sequential spatial arrangement of glutamate, acetylcholine, and GABA receptors along the dendrite that matched the previously reported EM-reconstructed synapse distributions.
All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 2, 3 and 4. Previously Published Datasets: Seven medulla column connectome: Kazunori Shinomiya, 2019, http://emdata.janelia.org/#/repo/medulla7column, #3b548
Article and author information
- Sandra Fendl
- Renee Marie Vieira
- Alexander Borst
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Claude Desplan, New York University, United States
- Received: September 10, 2020
- Accepted: October 14, 2020
- Accepted Manuscript published: October 20, 2020 (version 1)
- Accepted Manuscript updated: October 21, 2020 (version 2)
- Version of Record published: November 10, 2020 (version 3)
© 2020, Fendl et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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