scholarly journals Detection and characterization of apoptotic and necrotic cell death by time-lapse quantitative phase image analysis

2019 ◽  
Author(s):  
Tomas Vicar ◽  
Martina Raudenska ◽  
Jaromir Gumulec ◽  
Michal Masarik ◽  
Jan Balvan
Keyword(s):  
Cell Death ◽  
Cell Density ◽  
Cell Mass ◽  
Time Lapse ◽  
Intensity Change ◽  
Average Intensity ◽  
Label Free ◽  
Quantitative Phase ◽  
Label Free Detection ◽  
Direct Cell

AbstractCell 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. 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.

scholarly journals Cancer Cells Viscoelasticity Measurement by Quantitative Phase and Flow Stress Induction

2021 ◽  
Author(s):  
Tomas Vicar ◽  
Jaromir Gumulec ◽  
Jiri Chmelik ◽  
Jiri Navratil ◽  
Radim Kolar ◽  
...  
Keyword(s):  
Shear Modulus ◽  
Cell Mass ◽  
Time Lapse ◽  
Cytochalasin D ◽  
Phase Imaging ◽  
Label Free ◽  
Height Measurement ◽  
Stress Induction ◽  
Cell Parameters ◽  
Quantitative Phase

Cell viscoelastic properties are affected by the cell cycle, differentiation, pathological processes such as malignant transformation. Therefore, evaluation of the mechanical properties of the cells proved to be an approach to obtaining information on the functional state of the cells. Most of the currently used methods for cell mechanophenotypisation are limited by low robustness or the need for highly expert operation. In this paper, the system and method for viscoelasticity measurement using shear stress induction by fluid flow is described and tested. Quantitative Phase Imaging (QPI) is used for image acquisition because this technique enables to quantify optical path length delays introduced by the sample, thus providing a label-free objective measure of morphology and dynamics. Viscosity and elasticity determination were refined using a new approach based on the linear system model and parametric deconvolution. The proposed method allows high-throughput measurements during live cell experiments and even through a time-lapse, where we demonstrated the possibility of simultaneous extraction of shear modulus, viscosity, cell morphology, and QPI-derived cell parameters like circularity or cell mass. Additionally, the proposed method provides a simple approach to measure cell refractive index with the same setup, which is required for reliable cell height measurement with QPI, an essential parameter for viscoelasticity calculation. Reliability of the proposed viscoelasticity measurement system was tested in several experiments including cell types of different Young/shear modulus and treatment with cytochalasin D or docetaxel, and an agreement with atomic force microscopy was observed. The applicability of the proposed approach was also confirmed by a time-lapse experiment with cytochalasin D washout, where an increase of stiffness corresponded to actin repolymerisation in time.

scholarly journals Rapid, label-free classification of tumor-reactive T cell killing with quantitative phase microscopy and machine learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Diane N. H. Kim ◽  
Alexander A. Lim ◽  
Michael A. Teitell
Keyword(s):  
Machine Learning ◽  
T Cell ◽  
Time Lapse ◽  
Cell Receptor ◽  
Model System ◽  
Cell Killing ◽  
Label Free ◽  
Receptor Model ◽  
Quantitative Phase ◽  
Phase Microscopy

AbstractQuantitative phase microscopy (QPM) enables studies of living biological systems without exogenous labels. To increase the utility of QPM, machine-learning methods have been adapted to extract additional information from the quantitative phase data. Previous QPM approaches focused on fluid flow systems or time-lapse images that provide high throughput data for cells at single time points, or of time-lapse images that require delayed post-experiment analyses, respectively. To date, QPM studies have not imaged specific cells over time with rapid, concurrent analyses during image acquisition. In order to study biological phenomena or cellular interactions over time, efficient time-dependent methods that automatically and rapidly identify events of interest are desirable. Here, we present an approach that combines QPM and machine learning to identify tumor-reactive T cell killing of adherent cancer cells rapidly, which could be used for identifying and isolating novel T cells and/or their T cell receptors for studies in cancer immunotherapy. We demonstrate the utility of this method by machine learning model training and validation studies using one melanoma-cognate T cell receptor model system, followed by high classification accuracy in identifying T cell killing in an additional, independent melanoma-cognate T cell receptor model system. This general approach could be useful for studying additional biological systems under label-free conditions over extended periods of examination.

scholarly journals Wide-field Surface-Enhanced Coherent Anti-Stokes Raman Scattering Microscopy

2021 ◽  
Author(s):  
Cheng Zong ◽  
Ran Cheng ◽  
Fukai Chen ◽  
Peng Lin ◽  
Meng Zhang ◽  
...  
Keyword(s):  
Raman Scattering ◽  
Large Scale ◽  
Time Lapse ◽  
Live Cells ◽  
Large Field ◽  
Wide Field ◽  
Label Free ◽  
Label Free Detection ◽  
Surface Enhanced ◽  
Anti Stokes

Surface-enhanced Raman scattering (SERS) spectroscopy has been used extensively to study biology, chemistry, and materials. However, a point-by-point SERS mapping is time-consuming, taking minutes to hours for large-scale imaging. Here, we report a wide-field surface-enhanced coherent anti-Stokes Raman scattering (WISE-CARS) microscopy for monitoring nanotags in live cells and label-free detection of metabolic molecules. The WISE-CARS microscope achieves an imaging speed as fast as 120 frames per second for a large field of view of 130 microns X 130 microns. By spectral focusing of femtosecond lasers, a hyperspectral WISE-CARS stack of 120 frames can be acquired with a spectral resolution of 10 cm-1, where over 1 million Raman spectra are parallelly recorded within 0.5 seconds. As applications, we demonstrate time-lapse, 3D WISE-CARS imaging of nanotags in live cells as well as label-free detection of adenine released from S. aureus.

scholarly journals Towards in-vivo label-free detection of brain tumor margins with epi-illumination tomographic quantitative phase imaging

2021 ◽  
Vol 12 (3) ◽  
pp. 1621
Author(s):  
Paloma Casteleiro Costa ◽  
Zhe Guang ◽  
Patrick Ledwig ◽  
Zhaobin Zhang ◽  
Stewart Neill ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Phase Imaging ◽  
Label Free ◽  
Quantitative Phase Imaging ◽  
Quantitative Phase ◽  
Tumor Margins ◽  
Label Free Detection

scholarly journals Quantitative Phase Dynamics of Cancer Cell Populations Affected by Blue Light

2020 ◽  
Vol 10 (7) ◽  
pp. 2597 ◽  
Author(s):  
Marek Feith ◽  
Tomáš Vičar ◽  
Jaromír Gumulec ◽  
Martina Raudenská ◽  
Anette Gjörloff Wingren ◽  
...  
Keyword(s):  
Cell Death ◽  
Cell Motility ◽  
Cell Line ◽  
Cell Density ◽  
Blue Light ◽  
Cell Lines ◽  
Dry Mass ◽  
Light Dose ◽  
Phase Dynamics ◽  
Quantitative Phase

Increased exposition to blue light may induce many changes in cell behavior and significantly affect the critical characteristics of cells. Here we show that multimodal holographic microscopy (MHM) within advanced image analysis is capable of correctly distinguishing between changes in cell motility, cell dry mass, cell density, and cell death induced by blue light. We focused on the effect of blue light with a wavelength of 485 nm on morphological and dynamical parameters of four cell lines, malignant PC-3, A2780, G361 cell lines, and the benign PNT1A cell line. We used MHM with blue light doses 24 mJ/cm2, 208 mJ/cm2 and two kinds of expositions (500 and 1000 ms) to acquire real-time quantitative phase information about cellular parameters. It has been shown that specific doses of the blue light significantly influence cell motility, cell dry mass and cell density. These changes were often specific for the malignant status of tested cells. Blue light dose 208 mJ/cm2 × 1000 ms affected malignant cell motility but did not change the motility of benign cell line PNT1A. This light dose also significantly decreased proliferation activity in all tested cell lines but was not so deleterious for benign cell line PNT1A as for malignant cells. Light dose 208 mJ/cm2 × 1000 ms oppositely affected cell mass in A2780 and PC-3 cells and induced different types of cell death in A2780 and G361 cell lines. Cells obtained the least damage on lower doses of light with shorter time of exposition.

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