Video image-based analysis of single human induced pluripotent stem cell derived cardiomyocyte beating dynamics using digital image correlation.
Video image-based analysis of single human induced pluripotent stem cell derived cardiomyocyte beating dynamics using digital image correlation.
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DOI：
10.1186/1475-925x-13-39
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发表时间：
2014-04-07
影响因子：
3.9
通讯作者：
Hyttinen J
中科院分区：
文献类型：
--
作者：
Ahola A;Kiviaho AL;Larsson K;Honkanen M;Aalto-Setälä K;Hyttinen J
心肌细胞的功能主要通过分析细胞的电生理特性来测量。分析单个心肌细胞的搏动行为，特别是来自干细胞的心肌细胞，是具有挑战性的，但很有必要。在这项研究中，一个基于视频的方法，这是非侵入性和无标记的介绍和应用于研究单个人心肌细胞来源于诱导多能干细胞。用显微镜观察分离的干细胞衍生的心肌细胞的搏动，并记录运动。最小二次差，数字图像相关方法，用于跳动分析与几何扇形细胞分裂和径向/切向方向。从视频数据中计算单个心肌细胞的时间位移矢量场的时间序列。处理矢量场数据以获得细胞特异性收缩-松弛动力学信号。以模拟心肌细胞搏动为参照，采用真实的心肌细胞电流钳技术分析搏动心肌细胞的电功能。我们的研究结果表明，我们的扇形图像相关方法是能够提取单细胞跳动的特征，从视频数据的诱导多能干细胞来源的心肌细胞，没有明确的运动轴，该方法可以准确地识别跳动的相位和时间参数。我们对单个人类心肌细胞跳动运动的视频分析提供了一种强大的，非侵入性的和无标记的方法来分析来自诱导多能干细胞的心肌细胞的机械生物学功能。因此，我们的方法具有潜力的心肌细胞功能的高通量分析。
The functionality of a cardiomyocyte is primarily measured by analyzing the electrophysiological properties of the cell. The analysis of the beating behavior of single cardiomyocytes, especially ones derived from stem cells, is challenging but well warranted. In this study, a video-based method that is non-invasive and label-free is introduced and applied for the study of single human cardiomyocytes derived from induced pluripotent stem cells. The beating of dissociated stem cell-derived cardiomyocytes was visualized with a microscope and the motion was video-recorded. Minimum quadratic difference, a digital image correlation method, was used for beating analysis with geometrical sectorial cell division and radial/tangential directions. The time series of the temporal displacement vector fields of a single cardiomyocyte was computed from video data. The vector field data was processed to obtain cell-specific, contraction-relaxation dynamics signals. Simulated cardiomyocyte beating was used as a reference and the current clamp of real cardiomyocytes was used to analyze the electrical functionality of the beating cardiomyocytes. Our results demonstrate that our sectorized image correlation method is capable of extracting single cell beating characteristics from the video data of induced pluripotent stem cell-derived cardiomyocytes that have no clear movement axis, and that the method can accurately identify beating phases and time parameters. Our video analysis of the beating motion of single human cardiomyocytes provides a robust, non-invasive and label-free method to analyze the mechanobiological functionality of cardiomyocytes derived from induced pluripotent stem cells. Thus, our method has potential for the high-throughput analysis of cardiomyocyte functions.