Quantifying Cell-to-Cell Variation in Power-Law Rheology
Among individual cells of the same source and type, the complex shear modulus G[subscript ∗] exhibits a large log-normal distribution that is the result of spatial, temporal, and intrinsic variations. Such large distributions complicate the statistical evaluation of pharmacological treatments and th...
Main Authors: | , , , , , , , , |
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Other Authors: | , |
Format: | Article |
Language: | English |
Published: |
Elsevier,
2014-12-18T16:39:13Z.
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Subjects: | |
Online Access: | Get fulltext |
Summary: | Among individual cells of the same source and type, the complex shear modulus G[subscript ∗] exhibits a large log-normal distribution that is the result of spatial, temporal, and intrinsic variations. Such large distributions complicate the statistical evaluation of pharmacological treatments and the comparison of different cell states. However, little is known about the characteristic features of cell-to-cell variation. In this study, we investigated how this variation depends on the spatial location within the cell and on the actin filament cytoskeleton, the organization of which strongly influences cell mechanics. By mechanically probing fibroblasts arranged on a microarray, via atomic force microscopy, we observed that the standard deviation σ of G[subscript ∗] was significantly reduced among cells in which actin filaments were depolymerized. The parameter σ also exhibited a subcellular spatial dependence. Based on our findings regarding the frequency dependence of σ of the storage modulus G[subscript '], we proposed two types of cell-to-cell variation in G[subscript '] that arise from the purely elastic and the frequency-dependent components in terms of the soft glassy rheology model of cell deformability. We concluded that the latter inherent cell-to-cell variation can be reduced greatly by disrupting actin networks, by probing at locations within the cell nucleus boundaries distant from the cell center, and by measuring at high loading frequencies. Singapore. National Research Foundation National Science Foundation (U.S.) (CAREER CBET-0644846) National Institutes of Health (U.S.) (National Institute for Biomedical Imaging and Bioengineering (U.S.) Training Grant EB006348) |
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