Automated analysis of neuronal morphology, synapse number and synaptic recruitment

• Published in: Journal of neuroscience methods Vol. 195; no. 2; pp. 185 - 193
• Main Authors: Schmitz, Sabine K., 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
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.02.2011
• Subjects: Animals; Cells, Cultured; Dendrites; Dendrites - metabolism; Diagnostic Imaging; Disks Large Homolog 4 Protein; Electronic Data Processing - methods; Guanylate Kinases; Hippocampus - cytology; Image analysis; Immuno-fluorescence; 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; Neuronal morphology; Neurons - cytology; Neurons - physiology; Neuropeptide Y - metabolism; Receptors, Transferrin - metabolism; Software; Synapses; Synapses - physiology; Synaptic Vesicles - metabolism; Synaptopathies; Time Factors; Vesicle-Associated Membrane Protein 2 - metabolism; Immuno-fluorescence; Image analysis; Neuronal morphology; Dendrites; Synaptopathies; Synapses
• ISSN: 0165-0270; 1872-678X
• DOI: 10.1016/j.jneumeth.2010.12.011

[Display omitted] ▶ SynD reliably analyzes dendrite length and synapse number. ▶ SynD automatically quantifies dendritic branching and synaptic localization. ▶ SynD measures synapse intensity and synaptic localization of proteins. ▶ Image analysis in SynD is time-efficient. ▶ SynD is not limited to synapse detection in cultured neurons. 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.