4.6 Article

Automated tracking of gene expression in individual cells and cell compartments

Journal

JOURNAL OF THE ROYAL SOCIETY INTERFACE
Volume 3, Issue 11, Pages 787-794

Publisher

ROYAL SOC
DOI: 10.1098/rsif.2006.0137

Keywords

high-content screening; image analysis; image processing; single-cell analysis; NF-kappa B signalling

Funding

  1. Medical Research Council [G0500346] Funding Source: Medline
  2. MRC [G0500346] Funding Source: UKRI
  3. Medical Research Council [G0500346] Funding Source: researchfish

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Many intracellular signal transduction processes involve the reversible translocation from the cytoplasm to the nucleus of transcription factors. The advent of fluorescently tagged protein derivatives has revolutionized cell biology, such that it is now possible to follow the location of such protein molecules in individual cells in real time. However, the quantitative analysis of the location of such proteins in microscopic images is very time consuming. We describe CellTracker, a software tool designed for the automated measurement of the cellular location and intensity of fluorescently tagged proteins. CellTracker runs in the MS Windows environment, is freely available (at http://www.dbkgroup.org/celltracker/), and combines automated cell tracking methods with powerful image-processing algorithms that are optimized for these applications. When tested in an application involving the nuclear transcription factor NF-kappa B, CellTracker is competitive in accuracy with the manual human analysis of such images but is more than 20 times faster, even on a small task where human fatigue is not an issue. This will lead to substantial benefits for time-lapse-based high-content screening.

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