A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry
Publication year
2016Source
Plos Computational Biology, 12, 3, (2016), pp. 1-25, article e1004823ISSN
Publication type
Article / Letter to editor
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Organization
Human Genetics
Cell Biology (UMC)
Medical Imaging
Pathology
Journal title
Plos Computational Biology
Volume
vol. 12
Issue
iss. 3
Page start
p. 1
Page end
p. 25
Subject
Radboudumc 17: Women's cancers RIHS: Radboud Institute for Health Sciences; Radboudumc 19: Nanomedicine RIMLS: Radboud Institute for Molecular Life Sciences; Radboudumc 7: Neurodevelopmental disorders DCMN: Donders Center for Medical Neuroscience; Radboudumc 7: Neurodevelopmental disorders RIMLS: Radboud Institute for Molecular Life SciencesAbstract
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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- Academic publications [246515]
- Electronic publications [134157]
- Faculty of Medical Sciences [93308]
- Open Access publications [107688]
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