High throughput sample processing and automated scoring.
The comet assay is a sensitive and versatile method for assessing DNA damage in cells. In the traditional version of the assay, there are many manual steps involved and few samples can be treated in one experiment. High throughput (HT) modifications have been developed during recent years, and they are reviewed and discussed. These modifications include accelerated scoring of comets; other important elements that have been studied and adapted to HT are cultivation and manipulation of cells or tissues before and after exposure, and freezing of treated samples until comet analysis and scoring. HT methods save time and money but they are useful also for other reasons: large-scale experiments may be performed which are otherwise not practicable (e.g., analysis of many organs from exposed animals, and human biomonitoring studies), and automation gives more uniform sample treatment and less dependence on operator performance. The HT modifications now available vary largely in their versatility, capacity, complexity, and costs. The bottleneck for further increase of throughput appears to be the scoring.
Department of Chemicals and Radiation, Division of Environmental Medicine, Norwegian Institute of Public Health Oslo, Norway.
Gunnar
G
Brunborg
National Research Centre for the Working Environment Copenhagen, Denmark.
Petra
P
Jackson
Department of Nutrition, University of Oslo Oslo, Norway ; NorGenoTech AS, Skreia Norway.
Sergey
S
Shaposhnikov
Department of Chemicals and Radiation, Division of Environmental Medicine, Norwegian Institute of Public Health Oslo, Norway.
Hildegunn
H
Dahl
Department of Pharmacology and Toxicology, University of Navarra Pamplona, Spain.
Amaya
A
Azqueta
Department of Nutrition, University of Oslo Oslo, Norway.
Andrew R
AR
Collins
Department of Chemicals and Radiation, Division of Environmental Medicine, Norwegian Institute of Public Health Oslo, Norway.
Kristine B
KB
Gutzkow
automated scoring; comet assay; genotoxicity; high throughput; in vivo sample processing