|Title:||Development of Monte Carlo simulations for characterization and optimization of TOCCSL experiments||Other Titles:||Entwicklung von Monte Carlo Simulationen zur Charakterisierung und Optimierung von TOCCSL Experimenten||Language:||English||Authors:||Kiesenhofer, Dominik||Qualification level:||Diploma||Advisor:||Schütz, Gerhard||Assisting Advisor:||Brameshuber, Mario||Issue Date:||2017||Citation:||
Kiesenhofer, D. (2017). Development of Monte Carlo simulations for characterization and optimization of TOCCSL experiments [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2017.50432
|Number of Pages:||75||Qualification level:||Diploma||Abstract:||
A previously developed single-molecule microscopy technique termed TOCCSL (thinning out clusters while conserving stoichiometry of labeling) allows for direct imaging and stoichiometric analysis of molecular aggregates diffusing in the plasma membrane at high surface densities. The method is based on photobleaching of a confned area and subsequent imaging at the onset of the recovery process. Brightness analysis of individual diffraction-limited spots reveals the distribution of oligomeric fractions. In the present work, Monte Carlo-based computer simulations of TOCCSL experiments were developed to study the influence of three major sources of error on the experimental outcome: incomplete photobleaching of aggregates, oligomerization state-dependent mobility differences and false-positive oligomer detection due to random encounters. Trajectories of randomly diffusing particles are implemented as a Gaussian random walk. The photobleaching probability for individual particles is stochastically determined according to measured photobleaching curves of GPI-anchored monomeric GFP in the plasma membrane of CHO cells. TOCCSL simulations with varying parameters were performed to characterize individual and combined error sources. With regard to these simulations, strategies are discussed in order to optimize the accuracy of measurements by adjustment of experimental parameters and data post-processing.
|Keywords:||Single Molecule Microscopy; Monte Carlo Simulations; Protein-Protein Interactions||URI:||https://doi.org/10.34726/hss.2017.50432
|DOI:||10.34726/hss.2017.50432||Library ID:||AC14483872||Organisation:||E134 - Institut für Angewandte Physik||Publication Type:||Thesis
|Appears in Collections:||Thesis|
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checked on May 11, 2022
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