Lipid dynamics in model lipid bilayers analysed by tirf-based single molecule tracking

• Main Author: Matysik, Artur
• Other Authors: -
• Format: Theses and Dissertations
• Language: English
• Published: Nanyang Technological University 2015
• Subjects: DRNTU::Science::Biological sciences::Biophysics
• Online Access: http://hdl.handle.net/10356/65401
• Institution: Nanyang Technological University

Analysis of the dynamic behavior of membrane components in lipid membranes is essential for understanding plasma membrane structure. Single molecule tracking (SMT) can provide direct insight into diffusion characteristics of membrane probes, supplementing data acquired by ensemble averaging techniques. The effective use of SMT however requires not only careful data acquisition but also unbiased analysis to avoid artifacts and spurious or misleading results. Currently, such analysis can not be easily done by a non-expert due to a dearth in software availability. Many methods and algorithms have been described to deal with each level of SMT data processing, such as particle recognition and linking, data filtering, fitting using various methods, uncertainty calculation and data presentation. All of them however require implementation in the particular programming environment of choice prior to use. This complicated task is often circumvented by using archaic but readily available analysis methods, leading to unreliable, inadequate, biased, and/or non-quantitative results. In the course of our study of lipid bilayer dynamics, using a variety of membrane-integrating or –interacting probes with different lipid mixtures, TrackArt was designed to overcome these problems and integrate SMT data analysis methodology into one software ensemble. The resulting software package was then applied to the analysis of different membrane compositional scenarios and methods of bilayer preparation, where complex diffusion behavior was observed or influenced by experimental perturbation. This study presents major TrackArt features, which include not only data analysis, but also simulations of complex diffusion behavior in lipid bilayers. TrackArt functionality was demonstrated on in silico examples and real membranes, using a variety of different lipid mixtures and lipid and non-lipid probes of diffusion behavior. SMT on lipid bilayers supported on glass and mica revealed the single-molecule behavioral origins of diffusion differences between these substrates that have been previously reported by other (ensemble averaging) methods. Specific examples of diffusion applications where TrackArt was used to detect complex behaviors of membrane-interacting domain tracer molecules, or domain-disrupting molecules were 1) diffusion of the Alzheimer’s Aβ-derived sphingolipid binding domain (SBD) peptide, which was shown to be dependent on lipid bilayer composition, favoring sphingolipids and gangliosides. Here, a faster diffusion was seen in the presence of its characterized lipid targets in the membrane. 2) one of the membrane insertion molecules of the class polyphenylenevinylenes called COE1-5C, was shown by TrackArt analysis of SMT, to stabilize (de-fluidize) lipid bilayers composed of total E.coli lipid extract, and subjected to high butanol concentrations. Using these examples of practical applications, we demonstrate the effectiveness of the sufficiently complex, but user-friendly TrackArt software graphic user interface, where unbiased yet selective analysis of large data sets of individual molecule behavior are needed to gain an overall picture of the origins of different characteristic membrane dynamics and diffusion.