We apply label-free imaging using digital holographic microscopy to analyze different cancer cell lines. Separation of cell lines based on extraction of amplitude and phase map variations along with post-processed, population specific parameters, was accomplished using machine learning. These data are used to train a neural network algorithm that attains accurate discrimination of non-adherent cancer cells.
In order to advance quantitative phase microscopy as a significant clinical tool, we have implemented a new modality, holographic cytometry, which provides high resolution phase maps at high frame rates using several novel advances such as high speed line scan cameras integrated with microfluidic and illuminated with pulsed light source. The system is used to examine carcinogenic changes in epithelial cells which have been exposed to heavy metals in population sizes that are diagnostically relevant.
Cellular viscoelasticity is a biomarker for cancer type and toxin exposure. Current standard methods for probing cellular stiffness are slow, laborious, and utilize complex or indirect detection. These limitations prevent effective study of changes to viscoelasticity over time as well as longitudinal study of single cells. To enable direct and non-contact measurement of stiffness, we developed a quantitative phase imaging (QPI) based method to directly measure mechanical displacement in living cells in response to static loading. We calculated mechanical parameters, including shear stiffness, to discriminate between different cancer types and cell types that were exposed to varied levels of environmental and pharmacological toxins. We also demonstrated a correlation between our shear stiffness parameter and disorder strength, a measure of cellular refractive index homogeneity acquired via a single QPI image, showing the feasibility of high-throughput, nondestructive mechanical measurements.
Now, we compare our methods to atomic force microscopy (AFM), the gold standard for measuring cellular viscoelastic characteristics. We evaluate multiple breast cancer cell lines that are dosed with varying concentrations of cytochalasin B, an actin network-disrupting toxin. Each group is characterized by a commercial AFM to measure Young’s modulus and indentation stiffness. The same groups are analyzed using our QPI system to simultaneously measure shear stiffness and disorder strength. Relationships between all four measurements are analyzed to determine the correlation between the QPI derived parameters and those found using the commercial AFM, and to explore the feasibility of using QPI as a high-throughput alternative to AFM for measurements of cellular viscoelasticity.
Spatiotemporal patterns of intracellular transport are very difficult to quantify and, consequently, continue to be insufficiently understood. While it is well documented that mass trafficking inside living cells consists of both random and deterministic motions, quantitative data over broad spatiotemporal scales are lacking. We studied the intracellular transport in live cells using spatial light interference microscopy, a high spatiotemporal resolution quantitative phase imaging tool. The results indicate that in the cytoplasm, the intracellular transport is mainly active (directed, deterministic), while inside the nucleus it is both active and passive (diffusive, random). Furthermore, we studied the behavior of the two-dimensional mass density over 30 h in HeLa cells and focused on the active component. We determined the standard deviation of the velocity distribution at the point of cell division for each cell and compared the standard deviation velocity inside the cytoplasm and the nucleus. We found that the velocity distribution in the cytoplasm is consistently broader than in the nucleus, suggesting mechanisms for faster transport in the cytosol versus the nucleus. Future studies will focus on improving phase measurements by applying a fluorescent tag to understand how particular proteins are transported inside the cell.
We used a new quantitative high spatiotemporal resolution phase imaging tool to explore the nuclear structure and dynamics of individual cells. We used a novel analysis tool to quantify the diffusion outside and inside the nucleus of live cells. We also obtained information about the nuclear spatio temporal mass density in metastatic cells. The results indicate that in the cytoplasm, the intracellular transport is mainly active (direct, deterministic), while inside the nucleus it is both active and passive (diffusive, random). We calculated the standard deviation of velocities in active transport and the diffusion coefficient for passive transport.
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