Reference : Automated analysis of neuronal morphology, synapse number and synaptic recruitment.
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/16130
Automated analysis of neuronal morphology, synapse number and synaptic recruitment.
English
Schmitz, Sabine* mailto [Vrije Universiteit Amsterdam - VU > Functional Genomics]
Hjorth, J. J. Johannes* [> >]
Joemai, Raoul M. S. [> >]
Wijntjes, Rick [> >]
Eijgenraam, Susanne [> >]
de Bruijn, Petra [> >]
Georgiou, Christina [> >]
de Jong, Arthur P. H. [> >]
van Ooyen, Arjen [> >]
Verhage, Matthijs [> >]
Cornelisse, L. Niels [> >]
Toonen, Ruud F. [> >]
Veldkamp, Wouter J. H. [> >]
* These authors have contributed equally to this work.
2011
Journal of neuroscience methods
195
2
185-93
Yes (verified by ORBilu)
International
0165-0270
1872-678X
Netherlands
[en] Automatic Data Processing/methods ; Cells, Cultured ; Dendrites/metabolism ; Diagnostic Imaging ; Hippocampus/cytology ; Intracellular Signaling Peptides and Proteins/metabolism ; Lysosome-Associated Membrane Glycoproteins/metabolism ; Membrane Proteins/metabolism ; Mice ; Mice, Mutant Strains ; Microtubule-Associated Proteins/metabolism ; Munc18 Proteins/genetics ; Neurites/metabolism ; Neurons/cytology/physiology ; Neuropeptide Y/metabolism ; Receptors, Transferrin/metabolism ; Software ; Synapses/physiology ; Synaptic Vesicles/metabolism ; Time Factors ; Vesicle-Associated Membrane Protein 2/metabolism
[en] The shape, structure and connectivity of nerve cells are important aspects of neuronal function. Genetic and epigenetic factors that alter neuronal morphology or synaptic localization of pre- and post-synaptic proteins contribute significantly to neuronal output and may underlie clinical states. To assess the impact of individual genes and disease-causing mutations on neuronal morphology, reliable methods are needed. Unfortunately, manual analysis of immuno-fluorescence images of neurons to quantify neuronal shape and synapse number, size and distribution is labor-intensive, time-consuming and subject to human bias and error. We have developed an automated image analysis routine using steerable filters and deconvolutions to automatically analyze dendrite and synapse characteristics in immuno-fluorescence images. Our approach reports dendrite morphology, synapse size and number but also synaptic vesicle density and synaptic accumulation of proteins as a function of distance from the soma as consistent as expert observers while reducing analysis time considerably. In addition, the routine can be used to detect and quantify a wide range of neuronal organelles and is capable of batch analysis of a large number of images enabling high-throughput analysis.
http://hdl.handle.net/10993/16130
(c) 2010 Elsevier B.V. All rights reserved.

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