Evidence map›Paper›PMID 26998933›Full record

ArticlePLoS computational biology2016

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

Bonnie Nijhof, Anna Castells-Nobau, Louis Wolf, Jolanda M Scheffer-de Gooyert, Ignacio Monedero, Laura Torroja, Lluis Coromina, Jeroen A W M van der Laak, Annette Schenck

Abstract read
In one paragraph

Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

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  15. Vps54 regulatesBiology open · 2020
    Article
  16. The Journal of biological chemistry · 2020
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Bonnie NijhofDepartment of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
Anna Castells-NobauDepartment of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
Louis WolfMicroscopical Imaging Centre (MIC), Radboud University Medical Center, Nijmegen, the Netherlands.
Jolanda M Scheffer-de GooyertDepartment of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
Ignacio MonederoDepartment of Biology, Universidad Autónoma de Madrid, Madrid, Spain.
Laura TorrojaDepartment of Biology, Universidad Autónoma de Madrid, Madrid, Spain.
Lluis CorominaResearch Group on Statistics, Econometrics and Health (GRECS) and CIBER of Epidemiology and Public Health (CIBERESP), University of Girona, Girona, Spain.
Jeroen A W M van der LaakDepartment of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands.
Annette SchenckDepartment of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.

Funding

Resource Component: Acquisition, maintenance and distribution of Drosophila stocksP40OD018537 · OD · TRUSTEES OF INDIANA UNIVERSITY · PI Annette L. Parks · 2014 to 2026
$13.5M
NIH HHS P40 OD018537
6 · The paper itself

Abstract

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.

Indexed as

AlgorithmsDatabases, FactualModels, NeurologicalAnimalsData MiningDrosophilaImage Interpretation, Computer-AssistedModels, AnatomicNeuromuscular Junction

Identifiers

PMID26998933
PMCPMC4801422

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.