MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells.
We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip.
Dublin Institute of Technology, Kevin St, Dublin, Ireland.
Jane
J
Courtney
UCD Centre for Research in Infectious Diseases, School of Medicine and Medical Science, University College Dublin (UCD), Dublin, Ireland.
Elena
E
Woods
UCD Conway Institute of Biomolecular & Biomedical Research, School of Medicine and Biomedical Science University College Dublin (UCD), Dublin, Ireland.
Dimitri
D
Scholz
UCD Centre for Research in Infectious Diseases, School of Medicine and Medical Science, University College Dublin (UCD), Dublin, Ireland.
William W
WW
Hall
UCD Centre for Research in Infectious Diseases, School of Medicine and Medical Science, University College Dublin (UCD), Dublin, Ireland.
Virginie W
VW
Gautier
D000465:Algorithms; D002465:Cell Movement; D058948:Cell Tracking / Q000295:instrumentation / Q000379:methods; D002868:Chromosomal Proteins, Non-Histone / Q000235:genetics / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D006367:HeLa Cells; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D020407:Internet; D008164:Luminescent Proteins / Q000235:genetics / Q000378:metabolism; D018613:Microscopy, Confocal; D011993:Recombinant Fusion Proteins / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results; D012984:Software; D059008:Time-Lapse Imaging / Q000379:methods
D002868:Chromosomal Proteins, Non-Histone; C583169:Dendra2 protein, Dendronephthya; D008164:Luminescent Proteins; D011993:Recombinant Fusion Proteins; C047458:fibrillarin