Journal
JOURNAL OF NEUROSCIENCE METHODS
Volume 199, Issue 2, Pages 192-198Publisher
ELSEVIER
DOI: 10.1016/j.jneumeth.2011.04.033
Keywords
MetaMorph; Neuron; Development; Morphology; Image processing
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Funding
- NIH [K08 EB003996]
- Paralyzed Veterans of America Research Foundation [2573]
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Following plating in vitro, neurons pass through a series of morphological stages as they adhere and mature. These morphological stage transitions can be monitored as a function of time to evaluate the relative health and development of neuronal cultures under different conditions. While morphological development is usually quite obvious to the experienced eye, it can often be difficult to quantify in a meaningful way. Morphology quantification typically relies on manual image measurement and can therefore be tedious, time consuming and prone to human error. Here we report the successful development of an automated process using the commercially available image analysis program MetaMorph (R) to analyze the morphology and quantify the growth of embryonic spinal motor neurons in vitro. Our process relied on the Neurite Outgrowth and Cell Scoring modules included in MetaMorph (R) and on analyzing the exported data with an algorithm written in MATLAB (R). We first adopted a series of stages of motor neuron development in vitro. Neurons were classified into these stages directly from the available output of MetaMorph (R) using the algorithm written in MATLAB (R). We validated the results of the automated analysis against a manual analysis of the same images and found no statistically significant difference between the two methods. When properly configured, automated image analysis with MetaMorph (R) is a rapid and reliable alternative to manual measurement and has the potential to accelerate the research process. Published by Elsevier B.V.
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