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A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry

The morphology of synapses is of central interest in neuroscience because of the intimate relation with synaptic efficacy. Two decades of gene manipulation studies in different animal models have revealed a repertoire of molecules that contribute to synapse development. However, since such studies o...

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Autores principales: Nijhof, Bonnie, Castells-Nobau, Anna, Wolf, Louis, Scheffer-de Gooyert, Jolanda M., Monedero, Ignacio, Torroja, Laura, Coromina, Lluis, van der Laak, Jeroen A. W. M., Schenck, Annette
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4801422/
https://www.ncbi.nlm.nih.gov/pubmed/26998933
http://dx.doi.org/10.1371/journal.pcbi.1004823
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author Nijhof, Bonnie
Castells-Nobau, Anna
Wolf, Louis
Scheffer-de Gooyert, Jolanda M.
Monedero, Ignacio
Torroja, Laura
Coromina, Lluis
van der Laak, Jeroen A. W. M.
Schenck, Annette
author_facet Nijhof, Bonnie
Castells-Nobau, Anna
Wolf, Louis
Scheffer-de Gooyert, Jolanda M.
Monedero, Ignacio
Torroja, Laura
Coromina, Lluis
van der Laak, Jeroen A. W. M.
Schenck, Annette
author_sort Nijhof, Bonnie
collection PubMed
description The morphology of synapses is of central interest in neuroscience because of the intimate relation with synaptic efficacy. Two decades of gene manipulation studies in different animal models have revealed a repertoire of molecules that contribute to synapse development. However, since such studies often assessed only one, or at best a few, morphological features at a given synapse, it remained unaddressed how different structural aspects relate to one another. Furthermore, such focused and sometimes only qualitative approaches likely left many of the more subtle players unnoticed. Here, we present the image analysis algorithm ‘Drosophila_NMJ_Morphometrics’, available as a Fiji-compatible macro, for quantitative, accurate and objective synapse morphometry of the Drosophila larval neuromuscular junction (NMJ), a well-established glutamatergic model synapse. We developed this methodology for semi-automated multiparametric analyses of NMJ terminals immunolabeled for the commonly used markers Dlg1 and Brp and showed that it also works for Hrp, Csp and Syt. We demonstrate that gender, genetic background and identity of abdominal body segment consistently and significantly contribute to variability in our data, suggesting that controlling for these parameters is important to minimize variability in quantitative analyses. Correlation and principal component analyses (PCA) were performed to investigate which morphometric parameters are inter-dependent and which ones are regulated rather independently. Based on nine acquired parameters, we identified five morphometric groups: NMJ size, geometry, muscle size, number of NMJ islands and number of active zones. Based on our finding that the parameters of the first two principal components hardly correlated with each other, we suggest that different molecular processes underlie these two morphometric groups. Our study sets the stage for systems morphometry approaches at the well-studied Drosophila NMJ.
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spelling pubmed-48014222016-03-23 A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry Nijhof, Bonnie Castells-Nobau, Anna Wolf, Louis Scheffer-de Gooyert, Jolanda M. Monedero, Ignacio Torroja, Laura Coromina, Lluis van der Laak, Jeroen A. W. M. Schenck, Annette PLoS Comput Biol Research Article The morphology of synapses is of central interest in neuroscience because of the intimate relation with synaptic efficacy. Two decades of gene manipulation studies in different animal models have revealed a repertoire of molecules that contribute to synapse development. However, since such studies often assessed only one, or at best a few, morphological features at a given synapse, it remained unaddressed how different structural aspects relate to one another. Furthermore, such focused and sometimes only qualitative approaches likely left many of the more subtle players unnoticed. Here, we present the image analysis algorithm ‘Drosophila_NMJ_Morphometrics’, available as a Fiji-compatible macro, for quantitative, accurate and objective synapse morphometry of the Drosophila larval neuromuscular junction (NMJ), a well-established glutamatergic model synapse. We developed this methodology for semi-automated multiparametric analyses of NMJ terminals immunolabeled for the commonly used markers Dlg1 and Brp and showed that it also works for Hrp, Csp and Syt. We demonstrate that gender, genetic background and identity of abdominal body segment consistently and significantly contribute to variability in our data, suggesting that controlling for these parameters is important to minimize variability in quantitative analyses. Correlation and principal component analyses (PCA) were performed to investigate which morphometric parameters are inter-dependent and which ones are regulated rather independently. Based on nine acquired parameters, we identified five morphometric groups: NMJ size, geometry, muscle size, number of NMJ islands and number of active zones. Based on our finding that the parameters of the first two principal components hardly correlated with each other, we suggest that different molecular processes underlie these two morphometric groups. Our study sets the stage for systems morphometry approaches at the well-studied Drosophila NMJ. Public Library of Science 2016-03-21 /pmc/articles/PMC4801422/ /pubmed/26998933 http://dx.doi.org/10.1371/journal.pcbi.1004823 Text en © 2016 Nijhof et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Nijhof, Bonnie
Castells-Nobau, Anna
Wolf, Louis
Scheffer-de Gooyert, Jolanda M.
Monedero, Ignacio
Torroja, Laura
Coromina, Lluis
van der Laak, Jeroen A. W. M.
Schenck, Annette
A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry
title A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry
title_full A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry
title_fullStr A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry
title_full_unstemmed A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry
title_short A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry
title_sort new fiji-based algorithm that systematically quantifies nine synaptic parameters provides insights into drosophila nmj morphometry
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4801422/
https://www.ncbi.nlm.nih.gov/pubmed/26998933
http://dx.doi.org/10.1371/journal.pcbi.1004823
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