Track Membrane Proteins of Plant Cells |
Posted: October 24, 2016 |
In recent years, with the development of life science, fluorescence microscopic imaging technology has become an indispensable tool in the research of modern cell biology. However, due to the limitation of the optical diffraction limit, the resolution ratio of traditional optical microscope can only reach 200 nm, which can not meet the needs of biological research. In 1976, scientists first tried to use the total internal reflection fluorescence method to realize the single molecule fluorescence detection. From then on, the technology had been paid great attention in the field of analytical chemistry, life science and so on. Especially in recent years, with the emergence of a variety of new fluorescent probes and imaging theories, single molecule detection technology (SMD) broke the optical diffraction limit. The resolution was increased to dozens of nanometer level, and by its high sensitivity, rapid detection, and accurate observatio, it greatly promoted the study of interactions between molecules and reaction kinetics in live cells. However, in the field of plant cell research, this technology has been limited by the cell wall. On this issue, the researchers constructed a single molecule detection platform for analysis of plant cell integral membrane proteins, to overcome the interference of cell wall on protein dynamic analysis. They set up a total internal reflection fluorescence microscopy (TIRFM), achieving the real time imaging for single vesicle movement. On this basis, they also put forward an improved multiple hypothesis tracking algorithm for multiple hypothesis tracking (MHT) algorithm. This algorithm creatively uses the "single particle tracking" method to predict the trajectory of a single membrane transporter protein in plant cells. Trajectory prediction in single particle tracking is a linear, unbiased and minimum variance statistical estimation method. The researchers used MATLAB algorithm to simplify the operation to improve the speed of operation by modifying the hypothesis generation, hypothesis deletion, new target initialization, cross target association, combined with the characteristics of plant cell fluorescence imaging. This algorithm will improve the accuracy of single membrane protein motion analysis parameters to nanometer and millisecond level, which lays the foundation for the further exploration of the mechanism of plant cell membrane protein and membrane protein expression by different polymerization methods and the lateral movement of self realization activity regulation.
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