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A method for estimating relative changes in the synaptic density in Drosophila central nervous system

BACKGROUND: Synapse density is an essential indicator of development and functioning of the central nervous system. It is estimated indirectly through the accumulation of pre and postsynaptic proteins in tissue sections. 3D reconstruction of the electron microscopic images in serial sections is one...

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Autores principales: Rai, Dipti, Dey, Swagata, Ray, Krishanu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5956817/
https://www.ncbi.nlm.nih.gov/pubmed/29769037
http://dx.doi.org/10.1186/s12868-018-0430-3
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author Rai, Dipti
Dey, Swagata
Ray, Krishanu
author_facet Rai, Dipti
Dey, Swagata
Ray, Krishanu
author_sort Rai, Dipti
collection PubMed
description BACKGROUND: Synapse density is an essential indicator of development and functioning of the central nervous system. It is estimated indirectly through the accumulation of pre and postsynaptic proteins in tissue sections. 3D reconstruction of the electron microscopic images in serial sections is one of the most definitive means of estimating the formation of active synapses in the brain. It is tedious and highly skill-dependent. Confocal imaging of whole mounts or thick sections of the brain provides a natural alternative for rapid gross estimation of the synapse density in large areas. The optical resolution and other deep-tissue imaging aberrations limit the quantitative scope of this technique. RESULTS: Here we demonstrate a simple sample preparation method that could enhance the clarity of the confocal images of the neuropil regions of the ventral nerve cord of Drosophila larvae, providing a clear view of synapse distributions. We estimated the gross volume occupied by the synaptic junctions using 3D object counter plug-in of Fiji/ImageJ(®). It gave us a proportional estimate of the number of synaptic junctions in the neuropil region. The method is corroborated by correlated super-resolution imaging analysis and through genetic perturbation of synaptogenesis in the larval brain. CONCLUSIONS: The method provides a significant improvement in the relative estimate of region-specific synapse density in the central nervous system. Also, it reduced artifacts in the super-resolution images obtained using the stimulated emission depletion microscopy technique. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12868-018-0430-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-59568172018-05-24 A method for estimating relative changes in the synaptic density in Drosophila central nervous system Rai, Dipti Dey, Swagata Ray, Krishanu BMC Neurosci Methodology Article BACKGROUND: Synapse density is an essential indicator of development and functioning of the central nervous system. It is estimated indirectly through the accumulation of pre and postsynaptic proteins in tissue sections. 3D reconstruction of the electron microscopic images in serial sections is one of the most definitive means of estimating the formation of active synapses in the brain. It is tedious and highly skill-dependent. Confocal imaging of whole mounts or thick sections of the brain provides a natural alternative for rapid gross estimation of the synapse density in large areas. The optical resolution and other deep-tissue imaging aberrations limit the quantitative scope of this technique. RESULTS: Here we demonstrate a simple sample preparation method that could enhance the clarity of the confocal images of the neuropil regions of the ventral nerve cord of Drosophila larvae, providing a clear view of synapse distributions. We estimated the gross volume occupied by the synaptic junctions using 3D object counter plug-in of Fiji/ImageJ(®). It gave us a proportional estimate of the number of synaptic junctions in the neuropil region. The method is corroborated by correlated super-resolution imaging analysis and through genetic perturbation of synaptogenesis in the larval brain. CONCLUSIONS: The method provides a significant improvement in the relative estimate of region-specific synapse density in the central nervous system. Also, it reduced artifacts in the super-resolution images obtained using the stimulated emission depletion microscopy technique. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12868-018-0430-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-05-16 /pmc/articles/PMC5956817/ /pubmed/29769037 http://dx.doi.org/10.1186/s12868-018-0430-3 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Rai, Dipti
Dey, Swagata
Ray, Krishanu
A method for estimating relative changes in the synaptic density in Drosophila central nervous system
title A method for estimating relative changes in the synaptic density in Drosophila central nervous system
title_full A method for estimating relative changes in the synaptic density in Drosophila central nervous system
title_fullStr A method for estimating relative changes in the synaptic density in Drosophila central nervous system
title_full_unstemmed A method for estimating relative changes in the synaptic density in Drosophila central nervous system
title_short A method for estimating relative changes in the synaptic density in Drosophila central nervous system
title_sort method for estimating relative changes in the synaptic density in drosophila central nervous system
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5956817/
https://www.ncbi.nlm.nih.gov/pubmed/29769037
http://dx.doi.org/10.1186/s12868-018-0430-3
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