In the past decade, single molecule imaging has advanced our understanding of processes at the molecular scale. Total internal reflection fluorescence (TIRF) microscopy is one implementation in particular that has been extensively applied in the study of protein adsorption to surfaces. The spatial and temporal resolution provided by TIRF has enabled dynamic measurements of individual proteins in solution, where previously only bulk measurements or static electron microscopy observations were possible. The ability to study individual proteins has revealed and sometimes clarified the complex interactions at their interfaces. Here, the utility of TIRF is expanded to introduce a new model of protein adsorption to the suface and to study the protein interface in contact with solution.
Protein adsorption to surfaces has implications in surface biocompatibility, protein separation, and pharmaceutical nanoparticle development. For this reason, the phenomenon has been quantitatively by a variety of techniques, including single molecule imaging. The key data are the protein lifetimes on the surface, which have been shown to be broadly distributed and well-approximated by the sum of several exponential functions. The determined desorption rate constants are thought to reflect different interaction types between surface and protein, but the rates are not typically linked to a specific physical interaction. In the first part of this thesis, we establish appropriate imaging conditions and analysis methods for TIRF. A robust survival analysis technique is applied to capture the range of protein adsorption kinetics. In the second part, we utilize single molecule lifetime data from the adsorption of fibrinogen and bovine serum albumin (BSA) to glass surfaces and discover a heavy-tailed distribution: a very small fraction of proteins adsorbs effectively permanently, while the majority of proteins adsorb for a very short time. We then demonstrate that this characteristic power law behavior is well described by a model with a novel interpretation of the complex protein adsorption process.
The second half of the thesis extends TIRF to study the solution-facing interface of the protein as opposed to the surface facing interface by establishing the parameters for a super-resolution imaging technique. Point accumulation for imaging nanoscale topography (PAINT) generates high-resolution images of the sample of interest through the positional tracking of many temporally-distinct instances of a fluorescent probe binding to the sample. Previously, this technique has been applied in the mapping of DNA nanostructures. Here, in the third part, we apply PAINT to the study of proteins. First, a workstream is established for a model system of Nile red and BSA. The kinetic parameters for the system are established to allow rational design of PAINT experiments with this system. The on-rate and off-rate for Nile red are determined. Additionally, the binding model between the two components is tested by studying how the presence of an inhibitor effects the parameters.
In the final part, TIRF is used to study the protein-solution interface to examine the glycosylation of immunoglobulin A 1 (IgA1). Over 50% of eukaryotic proteins are glycosylated, and the glycan sequence is simultaneously difficult to study and crucial in the many functional roles proteins play. The glycosylation of IgA1, for example, plays a key role in the pathophysiology of IgA1 nephropathy. Lectins are proteins that bind to specifc glycan sequences and are often used to isolate glycosylated proteins. In this study, the appropriate surface conditions are established to allow specific binding between lectins and IgA1 glycans. The association and dissociation rate between lectins specific for the glycans on IgA1 are measured and affinity constants calculated. These efforts will help to rationally design experiments in the future to elucidate unknown glycan sequences on proteins.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-gmas-yr65 |
| Date | January 2019 |
| Creators | Armstrong, Megan Julia |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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