Analysis of multiple physical parameters for mechanical phenotyping of living cells
Analysis of multiple physical parameters for mechanical phenotyping of living cells
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DOI：
10.1007/s00249-013-0888-y
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发表时间：
2013-05-01
影响因子：
2
通讯作者：
Losert, W.
中科院分区：
文献类型：
--
作者：
Kiessling, T. R.;Herrera, M.;Losert, W.
由于细胞骨架是已知的调节许多细胞功能，越来越多的努力来表征细胞的机械性能已经发生。尽管多组分细胞骨架的结构复杂性和动力学，单细胞上的机械测量通常适合于具有两到三个参数的简单模型，并且记录和报告这些参数。然而，可能需要不同的简单模型来捕获不同的机械细胞状态，并且可能需要额外的参数来捕获细胞主动变形的能力。我们的新方法是使用多个流变模型以及动态变形和图像数据从细胞的力学测量中捕获更大的可能冗余的参数集。主成分分析和基于网络的方法被用来分组参数，以减少冗余和发展强大的生物力学表型。参数的网络表示允许对细胞复杂的机械系统进行可视化探索，并突出显示参数之间的意外连接。为了证明我们的生物力学表型分析方法可以检测到细微的机械差异，我们使用微流体光学细胞拉伸器来机械拉伸循环的人乳腺肿瘤细胞，这些细胞具有c-src酪氨酸激酶激活的基因工程改变，已知其会影响转移过程中的再附着和侵袭。
Since the cytoskeleton is known to regulate many cell functions, an increasing amount of effort to characterize cells by their mechanical properties has occured. Despite the structural complexity and dynamics of the multicomponent cytoskeleton, mechanical measurements on single cells are often fit to simple models with two to three parameters, and those parameters are recorded and reported. However, different simple models are likely needed to capture the distinct mechanical cell states, and additional parameters may be needed to capture the ability of cells to actively deform. Our new approach is to capture a much larger set of possibly redundant parameters from cells' mechanical measurement using multiple rheological models as well as dynamic deformation and image data. Principal component analysis and network-based approaches are used to group parameters to reduce redundancies and develop robust biomechanical phenotyping. Network representation of parameters allows for visual exploration of cells' complex mechanical system, and highlights unexpected connections between parameters. To demonstrate that our biomechanical phenotyping approach can detect subtle mechanical differences, we used a Microfluidic Optical Cell Stretcher to mechanically stretch circulating human breast tumor cells bearing genetically-engineered alterations in c-src tyrosine kinase activation, which is known to influence reattachment and invasion during metastasis.