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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.
Afiliação
  • Nijhof B; Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
  • Castells-Nobau A; Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
  • Wolf L; Microscopical Imaging Centre (MIC), Radboud University Medical Center, Nijmegen, the Netherlands.
  • Scheffer-de Gooyert JM; Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
  • Monedero I; Department of Biology, Universidad Autónoma de Madrid, Madrid, Spain.
  • Torroja L; Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
  • Coromina L; Department of Biology, Universidad Autónoma de Madrid, Madrid, Spain.
  • van der Laak JA; Research Group on Statistics, Econometrics and Health (GRECS) and CIBER of Epidemiology and Public Health (CIBERESP), University of Girona, Girona, Spain.
  • Schenck A; Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands.
PLoS Comput Biol ; 12(3): e1004823, 2016 Mar.
Article em En | MEDLINE | ID: mdl-26998933
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Interpretação de Imagem Assistida por Computador / Bases de Dados Factuais / Drosophila / Modelos Neurológicos / Junção Neuromuscular Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Animals Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Interpretação de Imagem Assistida por Computador / Bases de Dados Factuais / Drosophila / Modelos Neurológicos / Junção Neuromuscular Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Animals Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Holanda