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ToxSci Advance Access originally published online on October 20, 2007
Toxicological Sciences 2008 101(2):206-214; doi:10.1093/toxsci/kfm262
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© The Author 2007. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Mode of Action Clustering of Chemicals and Environmental Samples on the Bases of Bacterial Stress Gene Inductions

Freddy Dardenne*,1, Stefan Van Dongen*, Ingrid Nobels*, Roel Smolders{dagger}, Wim De Coen* and Ronny Blust*

* University of Antwerp, Department of Biology, Ecophysiology, Biochemistry and Toxicology Group, B-2020 Antwerp, Belgium {dagger} VITO, Environmental Toxicology Group, B-2400 Mol, Belgium

1 To whom correspondence should be addressed at University of Antwerp, Department of Biology, Ecophysiology, Biochemistry and Toxicology Group, Groenenborgerlaan 171/U7, B-2020 Antwerp, Belgium. Fax: +32-32-65-04-97. E-mail: gosia.freddy{at}scarlet.be.

Received August 7, 2007; accepted September 26, 2007


   Abstract

Over the years, environment and the human population have seen an increasing exposure to both existing and newly developed chemicals. It is generally accepted that at least some of those are toxic, albeit as pure compound or in combination with others. In response to a growing public awareness and scientific data, the new European chemicals legislation (Registration, Evaluation and Authorization of Chemicals) is under implementation at the moment. As a consequence, during the coming years about 30,000 chemicals have to be assessed on their potential hazard for man and biota. Part of this assessment will be done using existing and new in vitro tests offering insight into the toxicity of chemicals and into their toxicological mode of action. This study presents data on a battery of 14 bacterial reporter gene assay allowing mode of action determination and statistical grouping of chemicals based on their induction profile. Gene induction results are used to group reference chemicals in a statistical cascade employing hierarchical tree and k-means clustering for initial grouping. Both complementary, yet mathematically different, algorithms are consequently confirmed by principal component analysis (PCA). The gene induction profiles of an environmental extract with documented in vivo effects and a chemical with limited toxicological are data available and projected in the PCA vector space. The projection allows correct mode of action grouping and indicates that effect predictions based on the known toxicological effects of the reference compounds can be made.

Key Words: alternatives to animal testing; in vitro and alternatives; biomonitoring; risk assessment; dose–response; risk assessment; gene expression/regulation; predictive toxicology; toxicogenomics; methods.


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