Application of Bayesian Model Selection in Fluorescence Correlation Spectroscopy (FCS) to WNT3EGFP Secretion and Diffusion in Zebrafish Embryos

Abstract

Fluorescence Correlation Spectroscopy (FCS) is a powerful technique to address molecular dynamics with single molecule sensitivity. In this study, a Bayesian model selection approach has been applied to evaluate FCS data of fluorescent proteins in vitro and in vivo to address the issues of competing fitting models. This approach has also been applied in the model determination of EGFP labeled proteins in zebrafish embryos. FCS has then been employed to investigate in vivo Wnt3EGFP secretion and diffusion patterns during zebrafish neural development. Wnt3 is a secreted lipid modified signaling protein important in animal development and disease. However, its mode of transport during signaling is not known. Experiments in this thesis show that despite the lipid modifications at least some of Wnt3EGFP freely diffuses from the producing cells and may traverse a significant distance in intercellular space, possibly explaining how it can produce effects far away from the source of expression.