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Quantitative imaging of cell membrane-associated effective mass density using Photonic Crystal Enhanced Microscopy (PCEM)

期刊

PROGRESS IN QUANTUM ELECTRONICS
卷 50, 期 -, 页码 1-18

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.pquantelec.2016.10.001

关键词

Photonic Crystal Enhanced Microscopy (PCEM); Photonic Crystal (PC); Photonic Crystal Slab; Photonic Crystal Biosensor; Live Cell Imaging; Label-free Imaging; Stem Cell; Cancer Cell; Refractive Index (RI); Peak Wavelength Value (PWV); Peak Wavelength Shift (PWS); Mass Density (MD); Cell Membrane -associated Effective Mass; Density

资金

  1. National Science Foundation (NSF) [CBET 11-32301]
  2. National Institutes of Health (NIH) [R01 DK099528]
  3. NIH [R21 EB018481]
  4. Center for Innovative Instrumentation Technology (CiiT) at UIUC

向作者/读者索取更多资源

Adhesion is a critical cellular process that contributes to migration, apoptosis, differentiation, and division. It is followed by the redistribution of cellular materials at the cell membrane or at the cell-surface interface for cells interacting with surfaces, such as basement membranes. Dynamic and quantitative tracking of changes in cell adhesion mass redistribution is challenging because cells are rapidly moving, inhomogeneous, and nonequilibrium objects, whose physical and mechanical properties are difficult to measure or predict. Here, we report a novel biosensor based microscopy approach termed Photonic Crystal Enhanced Microscopy (PCEM) that enables the movement of cellular materials at the plasma membrane of individual live cells to be dynamically monitored and quantitatively imaged. PCEM utilizes a photonic crystal biosensor surface, which can be coated with arbitrary extracellular matrix materials to facilitate cellular interactions, within a modified brightfield microscope with a low intensity non-coherent light source. Benefiting from the high sensitivity, narrow resonance peak, and tight spatial confinement of the evanescent field atop the photonic crystal biosensor, PCEM enables label-free live cell imaging with high sensitivity and high lateral and axial spatial-resolution, thereby allowing dynamic adhesion phenotyping of single cells without the use of fluorescent tags or stains. We apply PCEM to investigate adhesion and the early stage migration of different types of stem cells and cancer cells. By applying image processing algorithms to analyze the complex spatiotemporal information generated by PCEM, we offer insight into how the plasma membrane of anchorage dependent cells is dynamically organized during cell adhesion. The imaging and analysis results presented here provide a new tool for biologists to gain a deeper understanding of the fundamental mechanisms involved with cell adhesion and concurrent or subsequent migration events.

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