<P> A great number of cellular processes can lead to local changes in proton
concentration and temperature. So, it is desirable to be able to measure pH and
temperature with non-invasive and spatially resolved methods. In this thesis, I
describe two unique methods to measure pH and temperature using the
environmental sensitivity of the proton transfer of fluorescent molecules. The first
method is based on the detection of the temperature and pH dependent parameters
associated with the blinking of fluorophores by fluorescence correlation
spectroscopy (FCS). Employing EGFP as the probe, I used this method to
characterize temperature increase at a laser focus due to light absorption in a thin
liquid sample. Using pyranine as a probe, I extended the applicability of this
method to a range of pH including physiological pH. Also, I investigated in
details the effect of buffer composition on the blinking of the fluorophores. Then,
I concluded that one limitation of this method is its strong dependence on buffer
conditions, which are not well characterized in vivo. The second approach is a pH
measurement method based on ratiometric imaging. This method is not as
dependent on buffer condition. We improved on current ratiometric imaging
techniques by demonstrating the possibility of using two-photon excitation. This
method was used to measure pH in pyranine loaded vesicles created during
receptor-mediated endocytosis of ยต-Opioid receptors expressed in HEK 293 cells.
Preliminary results showed that the pH in the endocytic vesicles dropped to a
value similar to those measurements in late endosomes roughly~ 10 minutes after
triggering the endocytosis, and eventually, the pH reading reached a value similar
to that of the pH oflysosomes. </p> / Thesis / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/19199 |
| Date | 03 1900 |
| Creators | Wong, Felix |
| Contributors | Fradin, Cecile, Physics and Astronomy |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
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