Abstract
This thesis focused on the, thus far, underdeveloped area of SPR cytometry. We have successfully established that SPR can be used to give added value to cell analysis by being multiplex and being able to measure viable cells label free. In addition, we have also established that SPR has the potential to be much quicker for multiplex cell analysis compared to the golden standard of flow cytometry.
We have also explored more unusual potential applications of SPR cytometry by monitoring cellular excretion of antibodies by hybridoma cells. We have successfully quantified the production rates of these antibodies by single cells. In order to further fortify our findings, we have created a simulation model using Comsol Multiphysics modelling software in order to model the production process of these antibodies on top of an SPR sensor. The model indeed showed that the SPRi output can be used as a reliable method for quantifying single cell antibody excretion and therefore in theory could be used for high producing cell selection.
In addition, we have proven to be able to detect apoptosis in cells while being monitored in real time. We have first captured the cells on top of the sensor surface based on their cell surface maker expression and have then treated the cells with paclitaxel, after a few hours we were able to detect a binding signal of cytochrome C (an apoptosis marker) on the attached cells.
In order to further prove the usefulness of SPRi we have investigated if we can use SPRi in more specific applications, such as the detection of bispecific antibodies generated by CHO cells. We found that SPR was able to detect both the recognition sites that are intended to be expressed by the bispecific antibody, but we did not have a high enough concentration of bispecific antibody to accurately determine the limits of detection of SPRi in this application field. It currently is the intention to optimize the bispecific antibody detection method in the near future.
Lastly, we also showed that SPRi can be used to analyze samples that instead of containing whole tumor cells contain tumor derived micro vesicles. SPRi is capable of detecting cell surface markers expressed by these vesicles while analysis using flow cytometry showed low to negative expression of these same markers on the same vesicles.
Original language | English |
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Qualification | Doctor of Philosophy |
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Award date | 20 Oct 2016 |
Place of Publication | Enschede |
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Publication status | Published - 20 Oct 2016 |