1. Automated analysis of neuronal morphology, synapse number and synaptic recruitment.
- Author
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Schmitz SK, Hjorth JJ, Joemai RM, Wijntjes R, Eijgenraam S, de Bruijn P, Georgiou C, de Jong AP, van Ooyen A, Verhage M, Cornelisse LN, Toonen RF, and Veldkamp WJ
- Subjects
- Animals, Cells, Cultured, Dendrites metabolism, Diagnostic Imaging, Disks Large Homolog 4 Protein, Guanylate Kinases, Hippocampus cytology, Intracellular Signaling Peptides and Proteins metabolism, Lysine analogs & derivatives, Lysine metabolism, Lysosomal Membrane Proteins metabolism, Membrane Proteins metabolism, Mice, Mice, Mutant Strains, Microtubule-Associated Proteins metabolism, Munc18 Proteins genetics, Neurites metabolism, Neuropeptide Y metabolism, Receptors, Transferrin metabolism, Synaptic Vesicles metabolism, Time Factors, Vesicle-Associated Membrane Protein 2 metabolism, Electronic Data Processing methods, Neurons cytology, Neurons physiology, Software, Synapses physiology
- Abstract
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., (© 2010 Elsevier B.V. All rights reserved.)
- Published
- 2011
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