ViaFuse: Fiji macros to calculate skeletal muscle cell viability and fusion index.

IF 5.3 2区 医学 Q2 CELL BIOLOGY
Emma Rose Hinkle, Tasneem Omar Essader, Gabrielle Marie Gentile, Jimena Giudice
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引用次数: 7

Abstract

Background: Measuring biological features of skeletal muscle cells is difficult because of their unique morphology and multinucleate nature upon differentiation. Here, we developed a new Fiji macro package called ViaFuse (that stands for viability and fusion) to measure skeletal muscle cell viability and differentiation. To test ViaFuse, we utilized immunofluorescence images of differentiated myotubes where the capping actin protein of muscle z-line subunit beta (CAPZB) was depleted in comparison with control cells.

Results: We compared the values achieved using the ViaFuse macros first with manual quantification performed by researchers and second with those obtained utilizing the MATLAB muscle-centric software MyoCount. We observed a high degree of correlation between all methods of quantification.

Conclusions: ViaFuse can detect the borders of myotubes and identify nuclear clumps which have been limitations of previous muscle-centric imaging software. The ViaFuse macros require little computer power or space to run and user inputs to the ViaFuse macros are minimal, thereby automating the analysis process in a quick, easy, and accurate fashion. Additionally, the ViaFuse macros work with Fiji, an existing imaging software widely used by skeletal muscle researchers. Furthermore, ViaFuse is compatible with many computer systems, has a very intuitive interface, and does not require prior complex mathematical knowledge. Therefore, we propose ViaFuse as a robust and meticulous method to quantify skeletal muscle cell viability and differentiation.

Abstract Image

Abstract Image

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ViaFuse:斐济宏计算骨骼肌细胞活力和融合指数。
背景:由于骨骼肌细胞在分化过程中具有独特的形态和多核性质,测量骨骼肌细胞的生物学特性是困难的。在这里,我们开发了一个新的斐济宏包称为ViaFuse(代表活力和融合)来测量骨骼肌细胞的活力和分化。为了测试ViaFuse,我们使用了分化肌管的免疫荧光图像,其中与对照细胞相比,肌肉z线亚单位β (CAPZB)的封顶肌动蛋白被耗尽。结果:我们首先将使用ViaFuse宏获得的值与研究人员进行的手动量化进行了比较,然后与使用MATLAB肌肉中心软件MyoCount获得的值进行了比较。我们观察到所有量化方法之间的高度相关性。结论:ViaFuse可以检测肌管边界,识别核团块,这是以往肌肉中心成像软件的局限性。ViaFuse宏需要很少的计算机功率或空间来运行,并且用户对ViaFuse宏的输入最少,从而以快速,简单和准确的方式自动化分析过程。此外,ViaFuse宏与Fiji(骨骼肌研究人员广泛使用的现有成像软件)一起工作。此外,ViaFuse与许多计算机系统兼容,具有非常直观的界面,并且不需要事先具备复杂的数学知识。因此,我们提出ViaFuse作为一种稳健而细致的方法来量化骨骼肌细胞的活力和分化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Skeletal Muscle
Skeletal Muscle CELL BIOLOGY-
CiteScore
9.10
自引率
0.00%
发文量
25
审稿时长
12 weeks
期刊介绍: The only open access journal in its field, Skeletal Muscle publishes novel, cutting-edge research and technological advancements that investigate the molecular mechanisms underlying the biology of skeletal muscle. Reflecting the breadth of research in this area, the journal welcomes manuscripts about the development, metabolism, the regulation of mass and function, aging, degeneration, dystrophy and regeneration of skeletal muscle, with an emphasis on understanding adult skeletal muscle, its maintenance, and its interactions with non-muscle cell types and regulatory modulators. Main areas of interest include: -differentiation of skeletal muscle- atrophy and hypertrophy of skeletal muscle- aging of skeletal muscle- regeneration and degeneration of skeletal muscle- biology of satellite and satellite-like cells- dystrophic degeneration of skeletal muscle- energy and glucose homeostasis in skeletal muscle- non-dystrophic genetic diseases of skeletal muscle, such as Spinal Muscular Atrophy and myopathies- maintenance of neuromuscular junctions- roles of ryanodine receptors and calcium signaling in skeletal muscle- roles of nuclear receptors in skeletal muscle- roles of GPCRs and GPCR signaling in skeletal muscle- other relevant aspects of skeletal muscle biology. In addition, articles on translational clinical studies that address molecular and cellular mechanisms of skeletal muscle will be published. Case reports are also encouraged for submission. Skeletal Muscle reflects the breadth of research on skeletal muscle and bridges gaps between diverse areas of science for example cardiac cell biology and neurobiology, which share common features with respect to cell differentiation, excitatory membranes, cell-cell communication, and maintenance. Suitable articles are model and mechanism-driven, and apply statistical principles where appropriate; purely descriptive studies are of lesser interest.
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