Automatic cell segmentation is a powerful method for quantifying signaling dynamics at single-cell resolution in live cell fluorescence imaging. Segmentation methods for mononuclear and round shape cells have been developed extensively. However, a segmentation method for elongated polynuclear cells, such as differentiated C2C12 myotubes, has yet to be developed. In addition, myotubes are surrounded by undifferentiated reserve cells, making it difficult to identify background regions and subsequent quantification. Here we developed an automatic quantitative segmentation method for myotubes using watershed segmentation of summed binary images and a two-component Gaussian mixture model. We used time-lapse fluorescence images of differentiated C2C12 cells stably expressing Eevee-S6K, a fluorescence resonance energy transfer (FRET) biosensor of S6 kinase (S6K). Summation of binary images enhanced the contrast between myotubes and reserve cells, permitting detection of a myotube and a myotube center. Using a myotube center instead of a nucleus, individual myotubes could be detected automatically by watershed segmentation. In addition, a background correction using the two-component Gaussian mixture model permitted automatic signal intensity quantification in individual myotubes. Thus, we provide an automatic quantitative segmentation method by combining automatic myotube detection and background correction. Furthermore, this method allowed us to quantify S6K activity in individual myotubes, demonstrating that some of the temporal properties of S6K activity such as peak time and half-life of adaptation show different dose-dependent changes of insulin between cell population and individuals.Key words: time lapse images, cell segmentation, fluorescence resonance energy transfer, C2C12, myotube.

中文翻译：

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肌管的自动定量分段揭示了S6激酶激活的单细胞动力学。

自动细胞分割是在活细胞荧光成像中以单细胞分辨率定量信号传导动态的强大方法。单核细胞和圆形细胞的分割方法已经得到了广泛的发展。但是，尚未开发出用于细长的多核细胞（例如分化的C2C12肌管）的分割方法。另外，肌管被未分化的储备细胞包围，这使得难以鉴定背景区域和随后的定量。在这里，我们使用求和后的二值图像的分水岭分割和两成分高斯混合模型，开发了一种用于肌管的自动定量分割方法。我们使用了稳定表达Eevee-S6K的分化C2C12细胞的延时荧光图像，S6激酶（S6K）的荧光共振能量转移（FRET）生物传感器。二值图像的求和增强了肌管和储备细胞之间的对比度，从而允许检测肌管和肌管中心。使用肌管中心而不是细胞核，可以通过分水岭分割自动检测单个肌管。另外，使用两组分高斯混合模型进行背景校正可以在单个肌管中自动进行信号强度定量。因此，我们通过结合自动肌管检测和背景校正提供了一种自动定量分割方法。此外，这种方法使我们能够量化单个肌管中的S6K活性，