It selects the cells containing a single nucleus from the binarized neurons image and produces images of single neurons and their skeleton. The second part of the macro allows the creation of single neuron images from the segmented images obtained in part I ( Fig 2C). Part II: Creation of individual neuron images and skeletization. For a better segmentation of thin cellular processes, AutoNeuriteJ requires well-contrasted images of fluorescent cells and images of nuclei stained with DAPI or Hoechst, used to locate cell bodies and remove touching neurons. At the end of the text file a summary indicates the number of neurons that have been measured, the percentage of polarization (neurons with an axon), the mean primary neurite length (neurite that initiate form the cell body) and mean primary neurite number per neuron.ĪutoNeuriteJ can be used to process a single file or multiple large images obtained from mosaic images recorded from slide scanners ( Fig 2A). It also gives measurements of the axon length, number of branches and total axonal tree length, if any. It gives, in a text file for each neuron, the length and order (primary, secondary etc…) of each neurite. AutoNeuriteJ was created to characterize a neuronal population in culture on a cell-based basis, with large numbers of neurons analyzed allowing an accurate estimation of the whole distribution of the population.ĪutoNeuriteJ, a plugin set to measure and classify neuritic extensionsĪutoNeuriteJ has been designed to describe the neuritic arborescence of isolated neurons in cultures of different conditions or genotypes. NeuronJ), or population-based, where whole neuritic lengths are measured with no neuron individualization or neuritic assignment (axon, dendrite, order), thus losing information of the number and classification of neurites. Some of plugins are neuron-based, allowing for the semi-automatic tracing of neurite extension (e.g. The use of image analysis software should overcome these problems and several plugins have been developed to help in this task. Moreover, visual selection of neurons by the investigator may lead to selection bias. The morphometric description of cell cultures is tedious when done by hand, confining analysis to a number of cells that may not be representative of the whole neuronal culture. Eventually, one neurite acquires enhanced growth capabilities and becomes an axon (Stage 3). These protrusions undergo successive elongation and retraction phases with no net outgrowth. Few hours later the neurites sprouting begins (Stage 2). Hippocampal neurons begin to form lamellipodia right after adhesion to the substrate (Stage 1). Stages of early development of hippocampal neurons in culture. (2017-CE11-0026 MAMAs).Ĭompeting interests: The authors have declared that no competing interests exist.įig 1. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the manuscript and its Supporting Information files.įunding: This work was supported by Institut National de la Santé et de la recherche Médicale, Commissariat à l'Energie Atiomique et aux Energies Alternatives, Université Grenoble Alpes and by awards from the French Agence Nationale de la Recherche to A.A. Received: Accepted: JPublished: July 16, 2020Ĭopyright: © 2020 Boulan et al. Gilestro, Imperial College London, UNITED KINGDOM (2020) AutoNeuriteJ: An ImageJ plugin for measurement and classification of neuritic extensions. Overall the use of AutoNeuriteJ will provide rapid, unbiased and accurate measurement of neuron morphologies.Ĭitation: Boulan B, Beghin A, Ravanello C, Deloulme J-C, Gory-Fauré S, Andrieux A, et al. Moreover, by analyzing mouse neurons deficient for the microtubule associated protein 6 (MAP6) and wild type neurons we illustrate that AutoNeuriteJ is capable to detect subtle phenotypic difference in axonal length. In these experiments measurement of more than 5000 mouse neurons per conditions was obtained within a few hours. We showed that AutoNeuriteJ is able to detect variations of neuritic growth induced by several compounds known to affect the neuronal growth. To automate these measurements, we wrote AutoNeuriteJ, an imageJ/Fiji plugin that measures and classifies neurites from a very large number of neurons. This task usually requires labor-intensive measurements and the classification of numerous neurites from large numbers of neurons in culture. Morphometry characterization is an important procedure in describing neuronal cultures and identifying phenotypic differences.
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