Abstract
It is often desirable to characterise the morphology of myogenic cultures. To achieve this, the surface area of myotubes is often quantified, along with the nuclear fusion index (NFI). Existing methods of such quantification are time-consuming and subject to error-prone human input. We have developed MyoCount, an open-source program that runs via the freely available MATLAB Runtime and quantifies myotube surface area and NFI. MyoCount allows the user to adjust its parameters to account for differences in image quality, magnification and the colour channels used in generating the image. MyoCount measures of myotube surface area and NFI were compared to the mean of measures performed by two blinded investigators using ImageJ software (surface area R 2 = 0.89, NFI R 2 =0.87). For NFI, the mean coefficient of variation (CV) between two investigators (17.6 ± 2.3%) was significantly higher than that between the investigator mean and MyoCount (13.5 ± 1.4%). For measurements of myotube area, the CV did not differ between both analysis methods. Given these results and the advantages of applying the same image analysis method uniformly across all images in an experiment, we suggest that MyoCount will be a useful research tool and we publish its source code and instructions for its use alongside this article.
Highlights
Myogenic cell cultures are commonly used for the investigation of skeletal muscle physiology[1,2,3,4,5]
We describe the development of MyoCount[11], an opensource program for the automatic quantification of myotube surface area and nuclear fusion index (NFI)
Here we describe the development of MyoCount[11], a software tool for the automated and reproducible quantification of myotube surface area and NFI in immunofluorescence-stained myotubes
Summary
Myogenic cell cultures are commonly used for the investigation of skeletal muscle physiology[1,2,3,4,5]. Myotubes formed by such cultures represent useful surrogates for skeletal muscle fibres. The Photoshop method of myotube surface area measurement developed by Agley et al has considerable merits, its ability to quantify the surface area of individual myotubes[10]. It requires the purchase of software and relies upon time-consuming and error-prone manual input
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