The Quantitative-Phase Dynamics of Apoptosis and Lytic Cell Death

Abstract

Cell viability and cytotoxicity assays are highly important for drug screening and cytotoxicity tests of antineoplastic or other therapeutic drugs. Even though biochemical-based tests are very helpful to obtain preliminary preview, their results should be confirmed by methods based on direct cell death assessment. In this study, time-dependent changes in quantitative phase-based parameters during cell death were determined and methodology useable for rapid and label-free assessment of direct cell death was introduced. The goal of our study was distinction between apoptosis and primary lytic cell death based on morphologic features. We have distinguished the lytic and non-lytic type of cell death according to their end-point features (Dance of Death typical for apoptosis versus swelling and membrane rupture typical for all kinds of necrosis common for necroptosis, pyroptosis, ferroptosis and accidental cell death). Our method utilizes Quantitative Phase Imaging (QPI) which enables the time-lapse observation of subtle changes in cell mass distribution. According to our results, morphological and dynamical features extracted from QPI micrographs are suitable for cell death detection (76% accuracy in comparison with manual annotation). Furthermore, based on QPI data alone and machine learning, we were able to classify typical dynamical changes of cell morphology during both caspase 3,7-dependent and -independent cell death subroutines. The main parameters used for label-free detection of these cell death modalities were cell density (pg/pixel) and average intensity change of cell pixels further designated as Cell Dynamic Score (CDS). To the best of our knowledge, this is the first study introducing CDS and cell density as a parameter typical for individual cell death subroutines with prediction accuracy 75.4% for caspase 3,7-dependent and -independent cell death.

Quantitative Phase Dynamics of Cancer Cell Populations Affected by Blue Light

“…While cell mass in A2780 decreased quickly after exposure to blue light dose 208 mJ/cm 2 × 1000 ms, the cell mass in PC-3 continually increased ( Figure 5). These changes in cell dry mass (Figure 5a,b) and the decrease of the relative number of A2780 cells (Figure 4) indicate cell death in this cell line [23]. Indeed, a high rate of cell death was shown in the A2780 cell line under these conditions (Supplementary Video S2).…”

“…line [23]. Indeed, a high rate of cell death was shown in the A2780 cell line under these conditions (Supplementary Video S2).…”

“…Sufficiently, precise tracking of individual cells during the whole sequence is a very hard problem [23]; however, for analysis of our dynamical features statistics across the whole-cell set, we require only to correctly cross-connect cells between each two consecutive time frames and larger tracks are not required. This was achieved by searching for the largest overlap with respect to Intersection over Union (IoU) of segmentation masks, where everything with IoU smaller than 0.7 was discarded as segmentation errors or cell divisions and thus these cells were not used for calculation of dynamical features.…”

“…This was achieved by searching for the largest overlap with respect to Intersection over Union (IoU) of segmentation masks, where everything with IoU smaller than 0.7 was discarded as segmentation errors or cell divisions and thus these cells were not used for calculation of dynamical features. As dynamical features describing cell motility, we have extracted cell speed (Euclidian distance between cell centroid in two consecutive frames) and Cell Dynamic Score (CDS) defined in [23] (Euclidean distance of cell pixel values in two consecutive frames). Cell dry mass and cell density are calculated as a sum and a mean of cell pixel values, respectively.…”

“…This approach enables also to measure cell mass and its distribution in cells [19][20][21]. Based on QPI, a new approach of distinction of apoptosis and lytic types of cell death was developed [22,23]. HM also enables effort-less and more accurate tracking of cells and their motility patterns compared to other microscopic techniques [24,25].…”