During the bioprocessing of therapeutics, proteins may become damaged leading to modifications and changes in stability. This may, as a consequence, cause serious and potentially fatal side effects when administered to patients making damage assessment crucial. High throughput determination of protein stability has become an important factor in many different areas such as protein engineering, formulation and manufacturing. Microfluidics, defined as micro-scale fluid flow systems, can be used to create high throughput methods to monitor these effects, while reducing reagent consumption without compromising sensitivity. Protein denaturation can be measured in many ways however, fluorescence spectroscopy is thought to be the most adaptable to use with microfluidics. In this thesis the feasibility of using microfluidics to detect protein denaturation using this fluorescence method of analysis adapted from a microplate format assay is examined. Protein unfolding transitions were monitored by detecting tryptophan fluorescence at 340nm upon excitation at 266nm. A laser-excited detection system was optimised to detect minimum concentrations of protein, in both the native and denatured states. The range and limitations of this system were assessed and compared to that of the established microplate reader method. The minimum protein concentration detectable in microfluidics was higher than that of the microplate reader, with a reduction in volume leading to a reduction in reagent consumption (105 molecules) while increasing throughput by 50%. Three representative proteins were assessed in an array of process relevant conditions. The 3D protein response surfaces obtained were characterized by global fitting to provide parameters for assessment of protein stability and assist in the determination of processing conditions.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:565003 |
| Date | January 2010 |
| Creators | Remtulla, N. |
| Publisher | University College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://discovery.ucl.ac.uk/20306/ |
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