title: An automated tracking system to measure the dynamic properties of vesicles in living cells.
abstract: Recent technological improvements have made it possible to examine the dynamics of individual vesicles at a very high temporal and spatial resolution. Quantification of the dynamic properties of secretory vesicles is labor-intensive and therefore it is crucial to develop software to automate the process of analyzing vesicle dynamics. Dual-threshold and binary image conversion were applied to enhance images and define the areas of objects of interest that were to be tracked. The movements, changes in fluorescence intensity, and changes in the area of each tracked object were measured using a new software system named the Protein Tracking system (PTrack). Simulations revealed that the system accurately recognized tracked objects and measured their dynamic properties. Comparison of the results from tracking real time-lapsed images manually with those automatically obtained using PTrack revealed similar patterns for changes in fluorescence intensity and a high accuracy (<89%). According to tracking results, PTrack can distinguish different vesicular organelles that are similar in shape, based on their unique dynamic properties. In conclusion, the novel tracking system, PTrack, should facilitate automated quantification of the dynamic properties of vesicles that are important when classifying vesicular protein locations.
authors.affiliation: Department of Biomedical Engineering, Chung Yuan Christian University, Jhongli, Taiwan.
authors.forename: Tien-Chuan
authors.initials: TC
authors.lastname: Ku
authors.forename: Yun-Nih
authors.initials: YN
authors.lastname: Huang
authors.forename: Chien-Chang
authors.initials: CC
authors.lastname: Huang
authors.forename: De-Ming
authors.initials: DM
authors.lastname: Yang
authors.forename: Lung-Sen
authors.initials: LS
authors.lastname: Kao
authors.forename: Tai-Yu
authors.initials: TY
authors.lastname: Chiu
authors.forename: Chung-Fan
authors.initials: CF
authors.lastname: Hsieh
authors.forename: Pei-Yo
authors.initials: PY
authors.lastname: Wu
authors.forename: Yuh-Show
authors.initials: YS
authors.lastname: Tsai
authors.forename: Chung-Chih
authors.initials: CC
authors.lastname: Lin
mesh_terms: D000818:Animals; D001693:Biological Transport, Active; D005089:Exocytosis / Q000502:physiology*; D049452:Green Fluorescent Proteins / Q000378:metabolism; D007091:Image Processing, Computer-Assisted; D008856:Microscopy, Fluorescence / Q000295:instrumentation / Q000379:methods; D009478:Neuropeptide Y / Q000378:metabolism; D016716:PC12 Cells; D020675:Peroxisomes / Q000502:physiology; D051381:Rats; D011993:Recombinant Fusion Proteins / Q000378:metabolism; D022142:Secretory Vesicles / Q000502:physiology* / Q000648:ultrastructure; D020826:rab3A GTP-Binding Protein / Q000378:metabolism
chemical_list: D009478:Neuropeptide Y; D011993:Recombinant Fusion Proteins; C485184:enhanced green fluorescent protein; C514578:synaptopHIuorin; D049452:Green Fluorescent Proteins; D020826:rab3A GTP-Binding Protein