Bergmeister Konstantin D, Gröger Marion, Aman Martin, Willensdorfer Anna, Manzano-Szalai Krisztina, Salminger Stefan, Aszmann Oskar C
CD Laboratory for the Restoration of Extremity Function, Division of Plastic and Reconstructive Surgery, Department of Surgery, Medical University of Vienna; Department of Hand, Plastic and Reconstructive Surgery, Burn Center, BG Trauma Center Ludwigshafen, Plastic and Hand Surgery, University of Heidelberg.
Core Facility Imaging, Core Facilities, Medical University Vienna.
J Vis Exp. 2017 Mar 28(121):55441. doi: 10.3791/55441.
Quantification of muscle fiber populations provides a deeper insight into the effects of disease, trauma, and various other influences on skeletal muscle composition. Various time-consuming methods have traditionally been used to study fiber populations in many fields of research. However, recently developed immunohistochemical methods based on myosin heavy chain protein expression provide a quick alternative to identify multiple fiber types in a single section. Here, we present a rapid, reliable and reproducible protocol for improved staining quality, allowing automatic acquisition of whole cross sections and automatic quantification of fiber populations with ImageJ. For this purpose, embedded skeletal muscles are cut in cross sections, stained using myosin heavy chains antibodies with secondary fluorescent antibodies and DAPI for cell nuclei staining. Whole cross sections are then scanned automatically using a slide scanner to obtain high-resolution composite pictures of the entire specimen. Fiber population analyses are subsequently performed to quantify slow, intermediate and fast fibers using an automated macro for ImageJ. We have previously shown that this method can identify fiber populations reliably to a degree of ±4%. In addition, this method reduces inter-user variability and time per analyses significantly using the open source platform ImageJ.
肌肉纤维群体的定量分析能更深入地了解疾病、创伤以及其他各种因素对骨骼肌组成的影响。在许多研究领域，传统上一直采用各种耗时的方法来研究纤维群体。然而，最近基于肌球蛋白重链蛋白表达开发的免疫组织化学方法，为在单个切片中识别多种纤维类型提供了一种快速的替代方法。在此，我们提出一种快速、可靠且可重复的方案，以提高染色质量，实现对整个横截面的自动采集，并使用ImageJ对纤维群体进行自动定量分析。为此，将包埋的骨骼肌切成横截面，使用肌球蛋白重链抗体与二级荧光抗体以及用于细胞核染色的DAPI进行染色。然后使用载玻片扫描仪自动扫描整个横截面，以获得整个标本的高分辨率合成图片。随后使用ImageJ的自动宏程序对纤维群体进行分析，以量化慢肌纤维、中间肌纤维和快肌纤维。我们之前已经表明，该方法能够可靠地识别纤维群体，误差在±4%以内。此外，该方法使用开源平台ImageJ显著降低了用户间的变异性以及每次分析所需的时间。
