Tracing neuronal circuits in transgenic animals by transneuronal control of transcription (TRACT)
Abstract
Understanding the computations that take place in brain circuits requires identifying how neurons in those circuits are connected to one another. We describe a technique called TRACT (TRAnsneuronal Control of Transcription) based on ligand-induced intramembrane proteolysis to reveal monosynaptic connections arising from genetically labeled neurons of interest. In this strategy, neurons expressing an artificial ligand ('donor' neurons) bind to and activate a genetically-engineered artificial receptor on their synaptic partners ('receiver' neurons). Upon ligand-receptor binding at synapses the receptor is cleaved in its transmembrane domain and releases a protein fragment that activates transcription in the synaptic partners. Using TRACT in Drosophila we have confirmed the connectivity between olfactory receptor neurons and their postsynaptic targets, and have discovered potential new connections between neurons in the circadian circuit. Our results demonstrate that the TRACT method can be used to investigate the connectivity of neuronal circuits in the brain.
Additional Information
© 2017 Huang 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. Received: 15 September 2017; Accepted: 02 December 2017; Published: 12 December 2017. Supported by NIH grant UO1109147 from the BRAIN initiative. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. Author contributions: Ting-hao Huang, Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing; Peter Niesman, Formal analysis, Validation, Investigation, Visualization, Writing—review and editing; Deepshika Arasu, Donghyung Lee, Antuca Callejas, Validation, Investigation, Visualization; Aubrie L De La Cruz, Data curation, Validation, Investigation, Visualization, Writing—original draft, Writing—review and editing; Elizabeth J Hong, Experimental design, Analysis and data interpretation, Funding; Carlos Lois, Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing. Competing interests: None.Attached Files
Published - elife-32027-v2.pdf
Supplemental Material - elife-32027-supp1-v2.docx
Supplemental Material - elife-32027-supp2-v2.docx
Supplemental Material - elife-32027-transrepform-v2.pdf
Files
Additional details
- PMCID
- PMC5777821
- Eprint ID
- 83961
- Resolver ID
- CaltechAUTHORS:20171219-101419416
- NIH
- U01MH109147
- Created
-
2017-12-19Created from EPrint's datestamp field
- Updated
-
2023-06-02Created from EPrint's last_modified field
- Caltech groups
- Tianqiao and Chrissy Chen Institute for Neuroscience