4.5 Article

Characterization and identification of cell death dynamics by quantitative phase imaging

Journal

JOURNAL OF BIOMEDICAL OPTICS
Volume 27, Issue 4, Pages -

Publisher

SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
DOI: 10.1117/1.JBO.27.4.046502

Keywords

quantitative phase imaging; cell death; morphology; time-series analysis

Funding

  1. Ministry of Science and Technology, Taiwan [108-2221-E-002-081-MY3]

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Investigating the dynamics of cell death at the single-cell level is crucial in biological research. This study developed a label-free technique called quantitative phase imaging (QPI) to quantify the cellular morphology and intracellular mass distribution of cells undergoing apoptosis and necrosis. The results showed that apoptotic and necrotic cells differ from normal cells in terms of phase and nuclear boundary. This method can be applied to studying cells undergoing state transitions such as drug response.
Significance: Investigating cell death dynamics at the single-cell level plays an essential role in biological research. Quantitative phase imaging (QPI), a label-free method without adverse effects of exogenous labels, has been widely used to image many types of cells under various conditions. However, the dynamics of QPI features during cell death have not been thoroughly characterized. Aim: We aim to develop a label-free technique to quantitatively characterize single-cell dynamics of cellular morphology and intracellular mass distribution of cells undergoing apoptosis and necrosis. Approach: QPI was used to capture time-lapse phase images of apoptotic, necrotic, and normal cells. The dynamics of morphological and QPI features during cell death were fitted by a sigmoid function to quantify both the extent and rate of changes. Results: The two types of cell death mainly differed from normal cells in the lower phase of the central region and differed from each other in the sharp nuclear boundary shown in apoptotic cells. Conclusions: The proposed method characterizes the dynamics of cellular morphology and intracellular mass distributions, which could be applied to studying cells undergoing state transition such as drug response. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License.

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