Astrocytic Gi-GPCR activation enhances stimulus-evoked extracellular glutamate
Description
Astrocytes perform critical functions in the nervous system, many of which are dependent on neurotransmitter-sensing through G protein-coupled receptors (GPCRs). However, whether specific astrocytic outputs follow specific GPCR activity remains unclear, and exploring this question is critical for understanding how astrocytes ultimately influence brain function and behavior. Here, we investigate the outputs of astrocytic Gi-GPCRs, a family of GPCRs which we previously showed is sufficient to increase slow-wave neural activity (SWA) during sleep when activated in cortical astrocytes1. We focus on two putative outputs by astrocytes in vivo, the regulation of extracellular glutamate and GABA, by combining fiber photometry recordings of the extracellular indicators iGluSnFR and iGABASnFR with astrocyte-specific chemogenetic Gi-GPCR activation. We find that Gi-GPCR activation does not change spontaneous dynamics of extracellular glutamate or GABA. However, Gi-GPCR activation does specifically increase visual stimulus-evoked extracellular glutamate. Together, these data point towards a complex relationship between astrocytic inputs and outputs in vivo that may depend on behavioral context. Further, they suggest an extracellular glutamate-specific mechanism underlying some astrocytic Gi-GPCR-dependent behaviors, including the regulation of sleep SWA.
Notes
This dataset is split into two parts: SnFR data (GluSnFR and GABASnFR photometry data) and GCaMP data. Each part is saved as a MAT file containing a single matlab structure array. For SnFR data, the strucutre array contains N rows where each row corresponds to an individual photometry recording. For GCaMP data, the structure array contains N rows where each row corresponds to a mouse and contains individual photometry recordings for that mouse as separate fields within the row. Each structure array contains many different fields that include metadata for the animal, recording information, as well as the raw data. A description of each field is found in the ReadMe file that is attached. In the code provided, the code relies on using the raw data in the structure array as well as saving new fields into the structure for processed data of various stages. All data for all animals and recordings are included. In any instance where duplicate data exists or animals are excluded, it is referenced in the code.
Funding provided by: National Institutes of Health
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000002
Award Number: R01NS099254, R01MH121446
Funding provided by: National Science Foundation
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000001
Award Number: CAREER 1942360
Funding provided by: Chan Zuckerberg Initiative
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100014989
Award Number:
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Additional details
Related works
- Is cited by
- 10.7554/eLife.63329 (DOI)
- Is source of
- 10.5061/dryad.h70rxwdmd (DOI)