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Quantitative characterisation of ipRGCs in retinal degeneration using a computation platform for extracting and reconstructing single neurons in 3D from a multi-colour labeled population

Light has a profound impact on mammalian physiology and behavior. Intrinsically photosensitive retinal ganglion cells (ipRGCs) express the photopigment melanopsin, rendering them sensitive to light, and are involved in both image-forming vision and non-image forming responses to light such as circad...

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Autores principales: Procyk, Christopher A., Rodgers, Jessica, Zindy, Egor, Lucas, Robert J., Milosavljevic, Nina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9664085/
https://www.ncbi.nlm.nih.gov/pubmed/36385954
http://dx.doi.org/10.3389/fncel.2022.1009321
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author Procyk, Christopher A.
Rodgers, Jessica
Zindy, Egor
Lucas, Robert J.
Milosavljevic, Nina
author_facet Procyk, Christopher A.
Rodgers, Jessica
Zindy, Egor
Lucas, Robert J.
Milosavljevic, Nina
author_sort Procyk, Christopher A.
collection PubMed
description Light has a profound impact on mammalian physiology and behavior. Intrinsically photosensitive retinal ganglion cells (ipRGCs) express the photopigment melanopsin, rendering them sensitive to light, and are involved in both image-forming vision and non-image forming responses to light such as circadian photo-entrainment and the pupillary light reflex. Following outer photoreceptor degeneration, the death of rod and cone photoreceptors results in global re-modeling of the remnant neural retina. Although ipRGCs can continue signaling light information to the brain even in advanced stages of degeneration, it is unknown if all six morphologically distinct subtypes survive, or how their dendritic architecture may be affected. To answer these questions, we generated a computational platform−BRIAN (Brainbow Analysis of individual Neurons) to analyze Brainbow labeled tissues by allowing objective identification of voxels clusters in Principal Component Space, and their subsequent extraction to produce 3D images of single neurons suitable for analysis with existing tracing technology. We show that BRIAN can efficiently recreate single neurons or individual axonal projections from densely labeled tissue with sufficient anatomical resolution for subtype quantitative classification. We apply this tool to generate quantitative morphological information about ipRGCs in the degenerate retina including soma size, dendritic field size, dendritic complexity, and stratification. Using this information, we were able to identify cells whose characteristics match those reported for all six defined subtypes of ipRGC in the wildtype mouse retina (M1−M6), including the rare and complex M3 and M6 subtypes. This indicates that ipRGCs survive outer retinal degeneration with broadly normal morphology. We additionally describe one cell in the degenerate retina which matches the description of the Gigantic M1 cell in Humans which has not been previously identified in rodent.
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spelling pubmed-96640852022-11-15 Quantitative characterisation of ipRGCs in retinal degeneration using a computation platform for extracting and reconstructing single neurons in 3D from a multi-colour labeled population Procyk, Christopher A. Rodgers, Jessica Zindy, Egor Lucas, Robert J. Milosavljevic, Nina Front Cell Neurosci Neuroscience Light has a profound impact on mammalian physiology and behavior. Intrinsically photosensitive retinal ganglion cells (ipRGCs) express the photopigment melanopsin, rendering them sensitive to light, and are involved in both image-forming vision and non-image forming responses to light such as circadian photo-entrainment and the pupillary light reflex. Following outer photoreceptor degeneration, the death of rod and cone photoreceptors results in global re-modeling of the remnant neural retina. Although ipRGCs can continue signaling light information to the brain even in advanced stages of degeneration, it is unknown if all six morphologically distinct subtypes survive, or how their dendritic architecture may be affected. To answer these questions, we generated a computational platform−BRIAN (Brainbow Analysis of individual Neurons) to analyze Brainbow labeled tissues by allowing objective identification of voxels clusters in Principal Component Space, and their subsequent extraction to produce 3D images of single neurons suitable for analysis with existing tracing technology. We show that BRIAN can efficiently recreate single neurons or individual axonal projections from densely labeled tissue with sufficient anatomical resolution for subtype quantitative classification. We apply this tool to generate quantitative morphological information about ipRGCs in the degenerate retina including soma size, dendritic field size, dendritic complexity, and stratification. Using this information, we were able to identify cells whose characteristics match those reported for all six defined subtypes of ipRGC in the wildtype mouse retina (M1−M6), including the rare and complex M3 and M6 subtypes. This indicates that ipRGCs survive outer retinal degeneration with broadly normal morphology. We additionally describe one cell in the degenerate retina which matches the description of the Gigantic M1 cell in Humans which has not been previously identified in rodent. Frontiers Media S.A. 2022-11-01 /pmc/articles/PMC9664085/ /pubmed/36385954 http://dx.doi.org/10.3389/fncel.2022.1009321 Text en Copyright © 2022 Procyk, Rodgers, Zindy, Lucas and Milosavljevic. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Procyk, Christopher A.
Rodgers, Jessica
Zindy, Egor
Lucas, Robert J.
Milosavljevic, Nina
Quantitative characterisation of ipRGCs in retinal degeneration using a computation platform for extracting and reconstructing single neurons in 3D from a multi-colour labeled population
title Quantitative characterisation of ipRGCs in retinal degeneration using a computation platform for extracting and reconstructing single neurons in 3D from a multi-colour labeled population
title_full Quantitative characterisation of ipRGCs in retinal degeneration using a computation platform for extracting and reconstructing single neurons in 3D from a multi-colour labeled population
title_fullStr Quantitative characterisation of ipRGCs in retinal degeneration using a computation platform for extracting and reconstructing single neurons in 3D from a multi-colour labeled population
title_full_unstemmed Quantitative characterisation of ipRGCs in retinal degeneration using a computation platform for extracting and reconstructing single neurons in 3D from a multi-colour labeled population
title_short Quantitative characterisation of ipRGCs in retinal degeneration using a computation platform for extracting and reconstructing single neurons in 3D from a multi-colour labeled population
title_sort quantitative characterisation of iprgcs in retinal degeneration using a computation platform for extracting and reconstructing single neurons in 3d from a multi-colour labeled population
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9664085/
https://www.ncbi.nlm.nih.gov/pubmed/36385954
http://dx.doi.org/10.3389/fncel.2022.1009321
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