Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro (UFRJ), RJ, Brazil; Instituto de Educação Médica (IDOMED), Campus Vista Carioca, Universidade Estácio de Sá (UNESA), RJ, Brazil.
Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro (UFRJ), RJ, Brazil.
Comput Methods Programs Biomed. 2023 Mar;230:107354. doi: 10.1016/j.cmpb.2023.107354. Epub 2023 Jan 13.
The culture of skeletal muscle cells is particularly relevant to basic biomedical research and translational medicine. The incubation of dissociated cells under controlled conditions has helped to dissect several molecular mechanisms associated with muscle cell differentiation, in addition to contributing for the evaluation of drug effects and prospective cell therapies for patients with degenerative muscle pathologies. The formation of mature multinucleated myotubes is a stepwise process involving well defined events of cell proliferation, commitment, migration, and fusion easily identified through optical microscopy methods including immunofluorescence and live cell imaging. The characterization of each step is usually based on muscle cell morphology and nuclei number, as well as the presence and intracellular location of specific cell markers. However, manual quantification of these parameters in large datasets of images is work-intensive and prone to researcher's subjectivity, mostly because of the extremely elongated cell shape of large myotubes and because myotubes are multinucleated.
Here we provide two semi-automated ImageJ macros aimed to measure the width of myotubes and the nuclear/cytoplasmic localization of molecules in fluorescence images. The width measuring macro automatically determines the best angle, perpendicular to most cells, to draw a profile plot and identify and measure individual myotubes. The nuclear/cytoplasmic ratio macro compares the intensity values along lines, drawn by the user, over cytoplasm and nucleus.
We show that the macro measurements are more consistent than manual measurements by comparing with our own results and with the literature.
By relying on semi-automated muscle specific ImageJ macros, we seek to improve measurement accuracy and to alleviate the laborious routine of counting and measuring muscle cell features.
骨骼肌细胞培养对于基础生物医学研究和转化医学具有特别重要的意义。在受控条件下培养分离细胞有助于剖析与肌细胞分化相关的多个分子机制，同时有助于评估药物效应以及针对退行性肌肉病理患者的潜在细胞疗法。成熟多核肌管的形成是一个逐步的过程，涉及到细胞增殖、分化、迁移和融合等明确的事件，这些事件可以通过光学显微镜方法（包括免疫荧光和活细胞成像）轻易地识别。每个步骤的特征通常基于肌细胞形态和细胞核数量，以及特定细胞标志物的存在和细胞内定位。然而，在大量图像数据集上手动量化这些参数既繁琐又容易受研究人员主观性的影响，主要是因为大肌管的细胞形状极其细长，而且肌管是多核的。
本文提供了两个用于测量荧光图像中肌管宽度和分子核质定位的半自动 ImageJ 宏。宽度测量宏自动确定最佳角度，垂直于大多数细胞，以绘制轮廓图并识别和测量单个肌管。核质比宏比较用户绘制的线在细胞质和细胞核上的强度值。
我们通过与我们自己的结果和文献进行比较，证明了宏测量比手动测量更一致。
通过依赖于半自动的肌肉特异性 ImageJ 宏，我们旨在提高测量精度，并减轻计数和测量肌细胞特征的繁琐工作。
