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Lookup NU author(s): Dr Gerrit Hilgen, Jenny Kartsaki, Viktoriia Kartysh, Professor Evelyne SernagorORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Retinal neurons are remarkedly diverse based on structure, function and genetic identity. Classifying these cells is a challenging task, requiring multimodal methodology. Here, we introduce a novel approach for retinal ganglion cell (RGC) classification, based on pharmacogenetics combined with immunohistochemistry and large-scale retinal electrophysiology. Our novel strategy allows grouping of cells sharing gene expression and understanding how these cell classes respond to basic and complex visual scenes. Our approach consists of several consecutive steps. First, the spike firing frequency is increased in RGCs co-expressing a certain gene (Scnn1a or Grik4) using excitatory DREADDs (designer receptors exclusively activated by designer drugs) in order to single out activity originating specifically from these cells. Their spike location is then combined with post hoc immunostaining, to unequivocally characterize their anatomical and functional features. We grouped these isolated RGCs into multiple clusters based on spike train similarities. Using this novel approach, we were able to extend the pre-existing list of Grik4-expressing RGC types to a total of eight and, for the first time, we provide a phenotypical description of 13 Scnn1a-expressing RGCs. The insights and methods gained here can guide not only RGC classification but neuronal classification challenges in other brain regions as well.
Author(s): Hilgen G, Kartsaki E, Kartysh V, Cessac B, Sernagor E
Publication type: Article
Publication status: Published
Journal: Open biology
Year: 2022
Volume: 12
Issue: 3
Online publication date: 09/03/2022
Acceptance date: 17/01/2022
Date deposited: 21/03/2022
ISSN (electronic): 2046-2441
Publisher: The Royal Society Publishing
URL: https://doi.org/10.1080/0267257X.2021.1908399
DOI: 10.1098/rsob.210367
PubMed id: 35259949
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