Phase Correlation Imaging of Unlabeled Cell Dynamics

Lihong Ma, Gannavarpu Rajshekhar, Ru Wang, Basanta Bhaduri, Shamira Sridharan, Mustafa Mir, Arindam Chakraborty, Rajashekar Iyer, Supriya Prasanth, Larry Millet, Martha U. Gillette, and Gabriel Popescu
Nature Scientific Reports 2016 6 32702 https://doi.org/10.1038/srep32702

We present phase correlation imaging (PCI) as a novel approach to study cell dynamics in a spatially resolved manner. PCI relies on quantitative phase imaging time-lapse data and, as such, functions in label-free mode, without the limitations associated with exogenous markers. The correlation time map outputted in PCI informs on the dynamics of the intracellular mass transport. Specifically, we show that PCI can extract quantitatively the diffusion coefficient map associated with live cells, as well as standard Brownian particles. Due to its high sensitivity to mass transport, PCI can be applied to studying the integrity of actin polymerization dynamics. Our results indicate that the cyto-D treatment blocking the actin polymerization has a dominant effect at the large spatial scales, in the region surrounding the cell. We found that PCI can distinguish between senescent and quiescent cells, which is extremely difficult without using specific markers currently. We anticipate that PCI will be used alongside established, fluorescence-based techniques to enable valuable new studies of cell function.