Abstract
We describe the use of pattern recognition and multivariate regression in the assessment of complex mixtures by correlating chemical fingerprints to the mutagenicity of the mixtures. Mixtures were 20 organic extracts of exhaust particles, each containing 102-170 individual compounds such as polycyclic aromatic hydrocarbons (PAHs), nitro-PAHs, oxy-PAHs, and saturated hydrocarbons. Mixtures were characterized by full-scan GC-MS (gas chromatography-mass spectrometry). Data were resolved into peaks and spectra for individual compounds by an automated curve resolution procedure. Resolved chromatograms were integrated, resulting in a predictor matrix that was used as input to a principal component analysis to evaluate similarities between mixtures (i.e., classification). Furthermore, partial least-squares projections to latent structures were used to correlate the GC-MS data to mutagenicity, as measured in the Ames Salmonella assay (i.e., calibration). The best model (high r2 and Q2) identifies the variables that co-vary with the observed mutagenicity. These variables may subsequently be identified in more detail. Furthermore, the regression model can be used to predict mutagenicity from GC-MS chromatograms of other organic extracts. We emphasize that both chemical fingerprints as well as detailed data on composition can be used in pattern recognition.
Full Text
The Full Text of this article is available as a PDF (159.0 KB).
Selected References
These references are in PubMed. This may not be the complete list of references from this article.
- Bostrøm E., Engen S., Eide I. Mutagenicity testing of organic extracts of diesel exhaust particles after spiking with polycyclic aromatic hydrocarbons (PAH). Arch Toxicol. 1998 Oct;72(10):645–649. doi: 10.1007/s002040050555. [DOI] [PubMed] [Google Scholar]
- Eide I., Johnsen H. G. Mixture design and multivariate analysis in mixture research. Environ Health Perspect. 1998 Dec;106 (Suppl 6):1373–1376. doi: 10.1289/ehp.98106s61373. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Eide I., Neverdal G., Thorvaldsen B., Shen H., Grung B., Kvalheim O. Resolution of GC-MS data of complex PAC mixtures and regression modeling of mutagenicity by PLS. Environ Sci Technol. 2001 Jun 1;35(11):2314–2318. doi: 10.1021/es000154e. [DOI] [PubMed] [Google Scholar]
- Feron V. J., Cassee F. R., Groten J. P. Toxicology of chemical mixtures: international perspective. Environ Health Perspect. 1998 Dec;106 (Suppl 6):1281–1289. doi: 10.1289/ehp.98106s61281. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Feron V. J., Groten J. P., Jonker D., Cassee F. R., van Bladeren P. J. Toxicology of chemical mixtures: challenges for today and the future. Toxicology. 1995 Dec 28;105(2-3):415–427. doi: 10.1016/0300-483x(95)03239-c. [DOI] [PubMed] [Google Scholar]
- Maron D. M., Ames B. N. Revised methods for the Salmonella mutagenicity test. Mutat Res. 1983 May;113(3-4):173–215. doi: 10.1016/0165-1161(83)90010-9. [DOI] [PubMed] [Google Scholar]
- Ostby L., Engen S., Melbye A., Eide I. Mutagenicity testing of organic extracts of diesel exhaust particles after fractionation and recombination. Arch Toxicol. 1997;71(5):314–319. doi: 10.1007/s002040050392. [DOI] [PubMed] [Google Scholar]
- Pennie W. D., Tugwood J. D., Oliver G. J., Kimber I. The principles and practice of toxigenomics: applications and opportunities. Toxicol Sci. 2000 Apr;54(2):277–283. doi: 10.1093/toxsci/54.2.277. [DOI] [PubMed] [Google Scholar]
- Schuetzle D., Lewtas J. Bioassay-directed chemical analysis in environmental research. Anal Chem. 1986 Sep;58(11):1060A–1075A. doi: 10.1021/ac00124a001. [DOI] [PubMed] [Google Scholar]
- Verhaar H. J., Morroni J. R., Reardon K. F., Hays S. M., Gaver D. P., Jr, Carpenter R. L., Yang R. S. A proposed approach to study the toxicology of complex mixtures of petroleum products: the integrated use of QSAR, lumping analysis and PBPK/PD modeling. Environ Health Perspect. 1997 Feb;105 (Suppl 1):179–195. doi: 10.1289/ehp.97105s1179. [DOI] [PMC free article] [PubMed] [Google Scholar]