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SynapseJ: An Automated, Synapse Identification Macro for ImageJ

While electron microscopy represents the gold standard for detection of synapses, a number of limitations prevent its broad applicability. A key method for detecting synapses is immunostaining for markers of pre- and post-synaptic proteins, which can infer a synapse based upon the apposition of the...

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Autores principales: Moreno Manrique, Juan Felipe, Voit, Parker R., Windsor, Kathryn E., Karla, Aamuktha R., Rodriguez, Sierra R., Beaudoin, Gerard M. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524137/
https://www.ncbi.nlm.nih.gov/pubmed/34675779
http://dx.doi.org/10.3389/fncir.2021.731333
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author Moreno Manrique, Juan Felipe
Voit, Parker R.
Windsor, Kathryn E.
Karla, Aamuktha R.
Rodriguez, Sierra R.
Beaudoin, Gerard M. J.
author_facet Moreno Manrique, Juan Felipe
Voit, Parker R.
Windsor, Kathryn E.
Karla, Aamuktha R.
Rodriguez, Sierra R.
Beaudoin, Gerard M. J.
author_sort Moreno Manrique, Juan Felipe
collection PubMed
description While electron microscopy represents the gold standard for detection of synapses, a number of limitations prevent its broad applicability. A key method for detecting synapses is immunostaining for markers of pre- and post-synaptic proteins, which can infer a synapse based upon the apposition of the two markers. While immunostaining and imaging techniques have improved to allow for identification of synapses in tissue, analysis and identification of these appositions are not facile, and there has been a lack of tools to accurately identify these appositions. Here, we delineate a macro that uses open-source and freely available ImageJ or FIJI for analysis of multichannel, z-stack confocal images. With use of a high magnification with a high NA objective, we outline two methods to identify puncta in either sparsely or densely labeled images. Puncta from each channel are used to eliminate non-apposed puncta and are subsequently linked with their cognate from the other channel. These methods are applied to analysis of a pre-synaptic marker, bassoon, with two different post-synaptic markers, gephyrin and N-methyl-d-aspartate (NMDA) receptor subunit 1 (NR1). Using gephyrin as an inhibitory, post-synaptic scaffolding protein, we identify inhibitory synapses in basolateral amygdala, central amygdala, arcuate and the ventromedial hypothalamus. Systematic variation of the settings identify the parameters most critical for this analysis. Identification of specifically overlapping puncta allows for correlation of morphometry data between each channel. Finally, we extend the analysis to only examine puncta overlapping with a cytoplasmic marker of specific cell types, a distinct advantage beyond electron microscopy. Bassoon puncta are restricted to virally transduced, pedunculopontine tegmental nucleus (PPN) axons expressing yellow fluorescent protein. NR1 puncta are restricted to tyrosine hydroxylase labeled dopaminergic neurons of the substantia nigra pars compacta (SNc). The macro identifies bassoon-NR1 overlap throughout the image, or those only restricted to the PPN-SNc connections. Thus, we have extended the available analysis tools that can be used to study synapses in situ. Our analysis code is freely available and open-source allowing for further innovation.
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spelling pubmed-85241372021-10-20 SynapseJ: An Automated, Synapse Identification Macro for ImageJ Moreno Manrique, Juan Felipe Voit, Parker R. Windsor, Kathryn E. Karla, Aamuktha R. Rodriguez, Sierra R. Beaudoin, Gerard M. J. Front Neural Circuits Neural Circuits While electron microscopy represents the gold standard for detection of synapses, a number of limitations prevent its broad applicability. A key method for detecting synapses is immunostaining for markers of pre- and post-synaptic proteins, which can infer a synapse based upon the apposition of the two markers. While immunostaining and imaging techniques have improved to allow for identification of synapses in tissue, analysis and identification of these appositions are not facile, and there has been a lack of tools to accurately identify these appositions. Here, we delineate a macro that uses open-source and freely available ImageJ or FIJI for analysis of multichannel, z-stack confocal images. With use of a high magnification with a high NA objective, we outline two methods to identify puncta in either sparsely or densely labeled images. Puncta from each channel are used to eliminate non-apposed puncta and are subsequently linked with their cognate from the other channel. These methods are applied to analysis of a pre-synaptic marker, bassoon, with two different post-synaptic markers, gephyrin and N-methyl-d-aspartate (NMDA) receptor subunit 1 (NR1). Using gephyrin as an inhibitory, post-synaptic scaffolding protein, we identify inhibitory synapses in basolateral amygdala, central amygdala, arcuate and the ventromedial hypothalamus. Systematic variation of the settings identify the parameters most critical for this analysis. Identification of specifically overlapping puncta allows for correlation of morphometry data between each channel. Finally, we extend the analysis to only examine puncta overlapping with a cytoplasmic marker of specific cell types, a distinct advantage beyond electron microscopy. Bassoon puncta are restricted to virally transduced, pedunculopontine tegmental nucleus (PPN) axons expressing yellow fluorescent protein. NR1 puncta are restricted to tyrosine hydroxylase labeled dopaminergic neurons of the substantia nigra pars compacta (SNc). The macro identifies bassoon-NR1 overlap throughout the image, or those only restricted to the PPN-SNc connections. Thus, we have extended the available analysis tools that can be used to study synapses in situ. Our analysis code is freely available and open-source allowing for further innovation. Frontiers Media S.A. 2021-10-04 /pmc/articles/PMC8524137/ /pubmed/34675779 http://dx.doi.org/10.3389/fncir.2021.731333 Text en Copyright © 2021 Moreno Manrique, Voit, Windsor, Karla, Rodriguez and Beaudoin. 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 Neural Circuits
Moreno Manrique, Juan Felipe
Voit, Parker R.
Windsor, Kathryn E.
Karla, Aamuktha R.
Rodriguez, Sierra R.
Beaudoin, Gerard M. J.
SynapseJ: An Automated, Synapse Identification Macro for ImageJ
title SynapseJ: An Automated, Synapse Identification Macro for ImageJ
title_full SynapseJ: An Automated, Synapse Identification Macro for ImageJ
title_fullStr SynapseJ: An Automated, Synapse Identification Macro for ImageJ
title_full_unstemmed SynapseJ: An Automated, Synapse Identification Macro for ImageJ
title_short SynapseJ: An Automated, Synapse Identification Macro for ImageJ
title_sort synapsej: an automated, synapse identification macro for imagej
topic Neural Circuits
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524137/
https://www.ncbi.nlm.nih.gov/pubmed/34675779
http://dx.doi.org/10.3389/fncir.2021.731333
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