alexa Neurite-J: an image-J plug-in for axonal growth analysis in organotypic cultures.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Computer Science & Systems Biology

Author(s): TorresEspn A, Santos D, GonzlezPrez F, del Valle J, Navarro X

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Abstract BACKGROUND: Previous studies in our lab proposed a method of dorsal root ganglia (DRG) and spinal cord slice (SC) organotypic 3D cultures to study motor and sensory axonal regeneration. Although these models are useful to test how different factors affect axonal growth, manual sample analysis can be inaccurate and time-consuming. Thus, we designed and set-up a plug-in to quantify axonal growth in 3D organotypic cultures. NEW METHOD: DRG and SC were cultured in a 3D collagen matrix. Explants were maintained in culture medium (control condition) or in culture medium supplemented with neurotrophins. Neurites were immunolabeled against RT-97 and pictures were obtained using an epifluorescence microscope. To quantify axonal growth we adapted the Sholl method of concentric rings to our cultures and the algorithm was implemented as an ImageJ plug-in. COMPARISON WITH EXISTING METHOD(S): Our method and plug-in was compared with standard Sholl method demonstrating better accuracy. In comparison with Neurite-J, manual measures of axonal growth in organotypic cultures require more time and provide fewer data than our proposed method. RESULTS: Neurite-J gives a reliable quantitative analysis of neurite growth, providing counts of neurite number and neurite area at different distances from the explant. Moreover, this plug-in follows lineal and semi-logarithmic analysis of the Sholl method, yielding a numerical value of neurite outgrowth useful for comparing different experimental conditions. CONCLUSION: Neurite-J provides a quantification method of neurite arbors in 3D organotypic cultures that gives the researcher an easy, fast and reliable tool to study axonal growth. Copyright © 2014 Elsevier B.V. All rights reserved. This article was published in J Neurosci Methods and referenced in Journal of Computer Science & Systems Biology

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