Automated tracking of gene expression in individual cells and cell compartments

Author:

Shen Hailin12,Nelson Glyn3,Nelson David E3,Kennedy Stephnie3,Spiller David G3,Griffiths Tony4,Paton Norman4,Oliver Stephen G5,White Michael R.H3,Kell Douglas B12

Affiliation:

1. School of Chemistry, The University of ManchesterFaraday Building, Sackville Street, PO Box 88, Manchester M60 1QD, UK

2. Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, The University of Manchester131 Princess Street, Manchester M1 7DN, UK

3. Centre for Cell Imaging, School of Biological Sciences, University of LiverpoolBiosciences Building, Crown Street, Liverpool L69 7ZB, UK

4. School of Computer Science, The University of ManchesterOxford Road, Manchester M13 9PL, UK

5. Faculty of Life Sciences, The University of ManchesterMichael Smith Building, Oxford Road, Manchester M13 9PT, UK

Abstract

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 (athttp://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-κB, 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.

Publisher

The Royal Society

Subject

Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology

Reference27 articles.

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4. Systematic genome-wide screens of gene function

5. Flow cytometry and cell sorting of heterogeneous microbial populations: the importance of single-cell analysis;Davey H.M;Microbiol. Rev,1996

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