Deciphering Biologically Relevant Processes from Single-Molecule Trajectories of Protein in vitro and in Live Cells with Time-Resolved Light-Sheet Microscopy

• Main Authors: Lin, Chien Yu, 林建佑
• Other Authors: Huang, Jung Y.
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/00941969895949511429

博士 === 國立交通大學 === 光電工程研究所 === 104 === The composition of a biological system contains a wide scale of components, ranging from hydrogen bonds to complex protein-protein interaction networks. A biological system can robustly perform biochemical functions to accomplish stable growth and differentiation. Recent research has indicated that the energy landscapes of local transitions in a biological system confront with several random perturbations, which is referred to as "intrinsic noise". The complex interactions between a biological system and its surroundings influence the system's dynamics. However, how a biological system robustly performs biochemical functions under such random perturbations remains unclear. To address this question, in this thesis study, the complex interactions of a biological system were divided into three levels of research: (1) the influence of hydrogen-bonding networks on protein dynamics; (2) the influence of conformational changes on the function of a protein; and (3) the effect of protein-protein interaction on cellular signal transduction. To investigate the influence of intrinsic noise on the dynamics of a biological system, we employed single-molecule microscopy to record protein dynamics in a biological system. We developed a theoretical model for deciphering the underlying mechanism that generates the dynamical processes recorded on the trajectories of a reporting protein. In summary, this thesis study aims to offer some useful guidelines for the implementation of single-molecule microscopy methodology accompanying with mathematical tools needed for analyzing datasets of single-molecule trajectories. The integration of single-molecule experimental techniques and theoretical models entails unravelling the hidden dynamics of a biological system and providing an in-depth mechanistic understanding of biological processes under varying environmental perturbations.