Changes in the biomechanical properties of cells accompanying the development of various pathological conditions have been increasingly reported as biomarkers for various diseases and as a predictor of disease progression stages. For instance, cancer cells have been found to be less stiff compared to their healthy counterparts due to the proteomic and lipidomic dysregulations conferred by the underlying pathology. The separation and selective recovery of cells or extracellular vesicles secreted from such cells that have undergone these changes have been suggested to be of diagnostic and prognostic value.
This dissertation first describes the implementation of a stiffness-based separation of phosphatidylcholine-based vesicles using a method first introduced based on the research in this work and was dubbed thermally-assisted acoustophoresis, or thermo-acoustophoresis. By tuning the temperature, we achieved the separation of vesicles of the same size, shape, and charge but with different stiffness values. It was observed that at a specific transition point, the acoustic contrast factor of vesicles changed sign from positive to negative. This change was mainly due to change in the compressibility of the vesicles, which is inversely proportional to stiffness. The acoustic contrast temperature (Tϕ), corresponding to the temperature at which the contrast factor switches sign, was determined to be unique to the composition of the vesicles. This unique temperature signature allowed us to develop this separation method of vesicles with distinct membrane stiffness with target outlet purities exceeding 95%.
We have further explored the functionality of this method by experimenting with cholesterol-containing vesicles. In cells, the cholesterol content plays a crucial role in determining stiffness. Changes in the cholesterol content in cellular membranes can be an indication of pathological disorders. We evaluated the Tϕ of vesicles at different cholesterol molar ratios (Xchol) and developed a multi-stage lab-on-a-chip method to accomplish for the first time the separation of a three-vesicle mixture. Using Xchol = 0.1, 0.2, and 0.3 vesicles, we obtained efficiencies exceeding 93%. The simplicity, rapidity, and label-free nature of this approach holds promise as a diagnostic and separation tool for cells affected by diseases that affect the stiffness and extracellular vesicles such as exosomes and microvesicles.
Identifer | oai:union.ndltd.org:fiu.edu/oai:digitalcommons.fiu.edu:etd-4335 |
Date | 09 June 2017 |
Creators | Dolatmoradi, Ata |
Publisher | FIU Digital Commons |
Source Sets | Florida International University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | FIU Electronic Theses and Dissertations |
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