We have employed a differential detector combined with dielectrophoretic (DEP) translation
in a microfluidic channel to monitor dielectric response of single cells and particularly
to track phenomenon related to apoptosis. Two different cell lines were studied; Chinese
hamster ovary cells (CHO) and MRC5 cells. Dielectric response was quantified by a factor
called Force Index. Force Index was studied statistically to identify apoptotic subpopulations.
Another direction of this work was to monitor changes in the cytoplasm conductivity following
inhibition of mitochondrial ATP production by Oligomycin. To make the DEP response
mostly sensitive to the cytoplasm conductivity, medium conductivity and DEP frequency
were adjusted such that Clausius Mossotti factor and hence DEP response become less sensitive
to cell radius.
Chinese hamster ovary cells were used in this work and the impact of different concentrations
of Oligomycin has been studied. We show that following exposure to Oligomycin at
8 μg/ml, cytoplasm conductivity drops. The majority of the changes takes place within one
hour of exposure to the drug. Furthermore, double shell models has been used to estimate
cytoplasm conductivity in a medium with conductivity of 0.42 S/m and the drop in the cytoplasm
conductivity following treatment with Oligomycin was estimated to be ≈ 0.16 S/m.
The magnitude of the decrease in the cytoplasm conductivity is evidence that Glycolysis is
active as an energy production pathway within the cell. This approach can be used to quantify
Glycolysis versus mitochondria ATP production which has an application in Warburg
effect in cancer cells and monitoring bioprocesses.
| Identifer | oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/24054 |
| Date | 17 September 2014 |
| Creators | Saboktakin Rizi, Bahareh |
| Contributors | Thomson, Douglas (Electrical and Computer Engineering), Bridges, Gregory (Electrical and Computer Engineering) Xing, Malcolm (Mechanical Engineering) |
| Source Sets | University of Manitoba Canada |
| Detected Language | English |
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