Analyzing the Nanomechanical Oscillations of Brain Tumor Cells using Optical Tweezers
Date
2019-01-02
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Abstract
Under the microscope, cells manifest nanomechanical oscillations (also known as vibrations and fluctuations). While the exact source of these oscillations is unknown, they may reflect the numerous inherent active processes of living cells. The sum of these active processes of cell characterizes its phenotype and function. Therefore, we hypothesize that the oscillation spectrum is unique for each cell type, and reflective of its functional state, allowing phenotypically-different cell types to be differentiated and functional changes in the cells to be followed. To test this hypothesis, we employed a novel, highly sensitive tool, optical tweezers, to record the oscillations of two brain tumor cells and applied advanced multivariate analysis to statistically evaluate the difference between the oscillation spectra. Two main sub aims were addressed; (1) To find optimal conditions for the optical tweezers setup for single cell oscillation measurements, and (2) To establish statistical methods to differentiate cells based on their oscillation patterns. Our results showed feature-rich spectra of different cell types over a frequency range from a few Hertz (Hz) to 50 kHz. The multivariate analysis generated two separate clusters for each cell type. The analysis also allowed evaluation of the spectra for features that are strongly associated with differences and the features that are common among cells. My thesis expands the current knowledge of cellular oscillations. While previous studies demonstrated a correlation between the metabolic activity of cells and overall magnitude of oscillations, spectral decomposition was either not reported or showed few, if any, cell-specific frequencies. In conclusion, the recording of oscillation spectra of single cells using optical tweezers, followed by multivariate statistical analysis is a promising method to differentiate cell types and follow cellular functions in real-time.
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Keywords
cancer diagnosis, brain tumor, method development, gliblastoma, cell oscillations
Citation
Ghandorah, S. (2019). Analyzing the Nanomechanical Oscillations of Brain Tumor Cells using Optical Tweezers (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.