A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry
Entity
UAM. Departamento de BiologíaPublisher
Public Library of ScienceDate
2016-03-21Citation
10.1371/journal.pcbi.1004823
PLoS Computational Biology 12.3 (2016): e1004823
ISSN
1553-734X (print); 1553-7358 (online)DOI
10.1371/journal.pcbi.1004823Funded by
This study was supported by VIDI and TOP grants (917-96-346, 912-12-109) from the Netherlands Organization for Scientific Research (NWO), by a DCN/Radboud University Medical Center PhD fellowship, by the German Mental Retardation Network funded by the NGFN+ program of the German Federal Ministry of Education and Research (BMBF) and by the European Union's FP7 large scale integrated network Gencodys (HEALTH-241995) to ASProject
info:eu-repo/grantAgreement/EC/FP7/241995Editor's Version
http://dx.doi.org/10.1371/journal.pcbi.1004823Subjects
Drosophila; Fiji; Gender; Genetic background; Geometry; Biología y Biomedicina / BiologíaRights
© 2016 Nijhof et alAbstract
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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Google Scholar:Nijhof, B.
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Castells-Nobau, A.
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Wolf, L.
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Scheffer-de Gooyert, J.M.
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Monedero Cobeta, Ignacio
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Torroja Fungairiño, Laura
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Coromina, L.
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Van der Laak, J.A.W.M.
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Schenck, A.
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