Effect of nanoparticles on our health is still poorly understood, with research indicating correlation between exposure to nanoparticles and different diseases. One of the possible entry ways into the human body is trough the respiratory system, which highlights the importance to understand the interaction between nanoparticles and lung epithelial cells - one of the building blocks of the air-blood barrier. Recent studies show that cells exposed to nanoparticels increase the production of cholesterol, which increases lipid ordering in the cell membrane, so nanoparticles could also affect the mobility of molecules in the membrane.
In this master’s thesis we use fluorescent correlation spectroscopy (FCS) to measure the diffusion rate of lipids in lung epithelial cell membrane after exposure to TiO$_2$ nanoparticles. We varied the dose of nanoparticles and the length of the exposure. We found that the effect is largest 24 h after exposure to nanoparticles, when the lipid diffusion slows down. This suggests a decrease in membrane fluidity, which could result from the cell defense against nanoparticle intrusion. After 48 h we did not observe any difference in the diffusion rate between lipids in membranes of cells exposed to nanoparticles and the ones without added nanoparticles. Interestingly, the higher concentration of nanoparticles did not result in a greater change of lipid diffusion rate.
We also developed an algorithm that allows us to automatically acquire the FCS data. The two main objectives of the program are maintaining the sample in the focal plane between consecutive measurements, and determining suitable areas of interest within the cells for data acquisition. With the introduced automation we can acquire the necessary measurements faster and without bias of the experimenter. The basic concepts of this method are transferable and therefore enable us to automate other experiments as well.
More generally, this work contributes towards better understanding of the effect of nanoparticles on cells, and further to understanding of the effect of nanoparticles on our health. With a better understanding of the interaction at all levels, we will be able to predict possible complications in the entire organism after nanoparticle exposure.
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