Amy M Hopkins1, Brandon Wheeler2, Cristian Staii3, David L Kaplan4, Timothy J Atherton5. 1. Department of Biomedical Engineering, Tufts University Science & Technology Center, 4 Colby Street, Medford, MA 02155, USA. Electronic address: Amy.Hopkins@Tufts.edu. 2. Department of Biomedical Engineering, Tufts University Science & Technology Center, 4 Colby Street, Medford, MA 02155, USA. Electronic address: Brandon.Wheeler@Tufts.edu. 3. Department of Physics and Astronomy, and Center for Nanoscopic Physics, Tufts University Science & Technology Center, 4 Colby Street, Medford, MA 02155, USA. Electronic address: Cristian.Staii@Tufts.edu. 4. Department of Biomedical Engineering, Tufts University Science & Technology Center, 4 Colby Street, Medford, MA 02155, USA. Electronic address: David.Kaplan@Tufts.edu. 5. Department of Physics and Astronomy, and Center for Nanoscopic Physics, Tufts University Science & Technology Center, 4 Colby Street, Medford, MA 02155, USA. Electronic address: Timothy.Atherton@Tufts.edu.
Abstract
BACKGROUND: Bundling of neurite extensions occur during nerve development and regeneration. Understanding the factors that drive neurite bundling is important for designing biomaterials for nerve regeneration toward the innervation target and preventing nociceptive collateral sprouting. High-density neuron cultures including dorsal root ganglia explants are employed for in vitro screening of biomaterials designed to control directional outgrowth. Although some semi-automated image processing methods exist for quantification of neurite outgrowth, methods to quantify axonal fasciculation in terms of direction of neurite outgrowth are lacking. NEW METHOD: This work presents a semi-automated program to analyze micrographs of high-density neurites; the program aims to quantify axonal fasciculation by determining the orientational distribution function of the tangent vectors of the neurites and calculating its Fourier series coefficients ('c' values). RESULTS: We found that neurite directional distribution analysis (NDDA) of fasciculated neurites yielded 'c' values of ≥∼0.25 whereas branched outgrowth led to statistically significant lesser values of <∼0.2. The 'c' values correlated directly to the width of neurite bundles and indirectly to the number of branching points. COMPARISON WITH EXISTING METHODS: Information about the directional distribution of outgrowth is lost in simple counting methods or achieved laboriously through manual analysis. The NDDA supplements previous quantitative analyses of axonal bundling using a vector-based approach that captures new information about the directionality of outgrowth. CONCLUSION: The NDDA is a valuable addition to open source image processing tools available to biomedical researchers offering a robust, precise approach to quantification of imaged features important in tissue development, disease, and repair.
BACKGROUND: Bundling of neurite extensions occur during nerve development and regeneration. Understanding the factors that drive neurite bundling is important for designing biomaterials for nerve regeneration toward the innervation target and preventing nociceptive collateral sprouting. High-density neuron cultures including dorsal root ganglia explants are employed for in vitro screening of biomaterials designed to control directional outgrowth. Although some semi-automated image processing methods exist for quantification of neurite outgrowth, methods to quantify axonal fasciculation in terms of direction of neurite outgrowth are lacking. NEW METHOD: This work presents a semi-automated program to analyze micrographs of high-density neurites; the program aims to quantify axonal fasciculation by determining the orientational distribution function of the tangent vectors of the neurites and calculating its Fourier series coefficients ('c' values). RESULTS: We found that neurite directional distribution analysis (NDDA) of fasciculated neurites yielded 'c' values of ≥∼0.25 whereas branched outgrowth led to statistically significant lesser values of <∼0.2. The 'c' values correlated directly to the width of neurite bundles and indirectly to the number of branching points. COMPARISON WITH EXISTING METHODS: Information about the directional distribution of outgrowth is lost in simple counting methods or achieved laboriously through manual analysis. The NDDA supplements previous quantitative analyses of axonal bundling using a vector-based approach that captures new information about the directionality of outgrowth. CONCLUSION: The NDDA is a valuable addition to open source image processing tools available to biomedical researchers offering a robust, precise approach to quantification of imaged features important in tissue development, disease, and repair.
Authors: Pablo de Gracia; Beatriz I Gallego; Blanca Rojas; Ana I Ramírez; Rosa de Hoz; Juan J Salazar; Alberto Triviño; José M Ramírez Journal: PLoS One Date: 2015-11-18 Impact factor: 3.240