Scientists

Russell Thomas

Russell Thomas

Education

B.A., chemistry, Tabor College, Hillsboro, Kansas, 1991.
M.S., radioecology, Colorado State University, Fort Collins, Colorado, 1993.
Ph.D., toxicology, Colorado State University, Fort Collins, Colorado, 1998.
Postdoctoral training, McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, Wisconsin, 1998-2000.

Research

With the draft of the human genome completed in 2001 and experimental organisms such as the mouse and rat either completed or near completion, a large volume of sequence information has been generated with only limited understanding of the contents. A functional genomics approach is needed to bridge the gap between the DNA sequence information itself, the genes and regulatory information it contains, and functional roles within the cell.

In toxicology, the application of genomics and associated technology was initially forecast to lead to the rapid identification and mechanistic understanding of physical and chemical agents that result in adverse human or environmental end points. These forecasts have created a wave of excitement within the toxicology community, with an increasing number of researchers applying genomic tools such as microarrays to various research projects. However, with a few notable exceptions, the increasing application of these tools has not resulted in a substantial increase in the mechanistic understanding of how various chemical and physical agents act on a system or improved our ability to predict how these systems behave at low doses. The missing components are a basic understanding of the cause-and-effect relationship contained within these lists of genes and the underlying logic of the signaling network involved in producing the toxicological effect at environmentally relevant doses.

To delineate the signaling network involved in the toxicological effect and the cause-and-effect relationships among the altered transcripts, new approaches specifically designed to address the functional aspects of these genomic alterations are necessary. Notably, no single technology can be relied on to accomplish these goals. A functional genomics approach that combines a variety of disciplines and utilizes broad-coverage experimental and computational methods holds promise for addressing these needs. The research program in my laboratory is focused in three primary areas.

Functional genomic screens to dissect upstream cellular signaling pathways:

Dissecting the upstream cellular signaling pathway is important to understand the potential targets of toxicity, identify key nodal points in the signaling pathway, and identify potential cross-talk among pathways known to be involved in other biological end points (e.g., development or inflammation).

Functional genomic screens to identify genes involved in susceptibility:

Applying gain-of-function and loss-of-function screens in cells exposed to a marginally toxic or subtoxic dose can identify potential modifiers of susceptibility. For example, some people may express more or less of a certain gene than others in the general population. The reasons for this difference in expression are numerous and can include nutritional state, physiological state (e.g., inflammation), and genetic polymorphisms.

A combination of gene expression analysis and functional genomic tools to map downstream gene expression trees:

Identifying the upstream cellular signaling pathway is only part of the overall picture. The event initiated by the chemical may not necessarily be directly responsible for the toxic end point but instead may be driven by downstream (i.e., secondary and tertiary) alterations in gene expression. In other words, what branch on the tree representing the time-course changes in gene expression following exposure to a toxic chemical is responsible? In addition, the specific gene expression tree can vary significantly among species, resulting in cross-species differences in toxicity. For example, what if the gene upstream of the node responsible for toxicity is missing or has evolutionarily acquired a different function in humans but not in rats or mice? The ultimate biological response would also be different. Comparisons of these gene expression trees are important both for understanding the mechanism of toxicity and for the cross-species scaling of the toxic end point.

Selected Publications

Clewell, H. J., Thomas, R. S., Gentry, P. R., Crump, K. S., Kenyon, E. M., El-Masri, H. A., and Yager, J. W. (2007). Research toward the development of a biologically based dose response assessment for inorganic arsenic carcinogenicity: A progress report. Toxicol. Appl. Pharmacol. doi:10.1016/j.taap.2007.03.021. In press.

Halsey, T. A., Yang, L., Walker, J. R., Hogenesch, J. B., and Thomas, R. S. (2007). A functional map of NF?B signaling identifies novel modulators and multiple system controls. Genome Biol. In press.

Roberts, E., Struve, M., Thomas, R. S., and Dorman, D. (2007) Basal gene expression in male and female Sprague-Dawley rat nasal respiratory and olfactory epithelium. Inhal. Toxicol. In press.

Thomas, R. S., Allen, B. C., Nong, A., Yang, L., Bermudez, E., Clewell, H. J., and Andersen, M. E. (2007). A method to integrate benchmark dose estimates with genomic data to assess the functional effects of chemical exposure. Toxicol. Sci. doi: 10.1093/toxsci/kfm092. In press.

Conolly, R. B. and Thomas, R. S. (2007). Biologically motivated approaches to extrapolation from high to low doses and the advent of systems biology: The road to toxicological safety assessment. Human Ecol. Risk Assessment, 13, 52-56.

Ingram, J. L., Antao-Menezes, A., Turpin, E. A., Wallace, D. G., Mangum, J. B., Pluta, L. J., Thomas, R. S., and Bonner, J. C. (2007). Genomic analysis of human lung fibroblasts exposed to vanadium pentoxide to identify candidate genes for occupational bronchitis. Respir. Res. 8, 34.

Thomas, R. S., O'Connell, T. M., Pluta, L., Wolfinger, R. D., Yang, L. and Page, T. J. (2007). A comparison of transcriptomic and metabonomic technologies for identifying biomarkers predictive of two-year rodent cancer bioassays. Toxicol. Sci. 96(1), 40-46.

Thomas, R. S., Pluta, L., Yang, L., and Halsey, T. A. (2007) Application of genomic biomarkers to predict increased lung tumor incidence in two-year rodent cancer bioassays. Toxicol. Sci. 97(1), 55-64.

Page, T. J., Sikder, D., Yang, L., Pluta, L., Wolfinger, R. D., Kodadek, T., and Thomas, R. S. (2006). Genome-wide analysis of human HSF1 signaling reveals a transcriptional program linked to cellular adaptation and survival. Mol. Biosystems. 2, 627-639.

Andersen, M. E., Dennison, J. E., Thomas, R. S., and Conolly, R. B. (2005). New directions in incidence-dose modeling. Trends Biotechnol. 23, 122-127.

Andersen, M. E., Thomas, R. S., Gaido, K. W., and Conolly, R. B. (2005). Dose-response modeling in reproductive toxicology in the systems biology era. Reprod. Toxicol. 19, 327-337.

Hayes, K. R., Vollrath, A. L., Zastrow, G. M., McMillan, B. J., Craven, M., Jovanovich, S., Rank, D. R., Penn, S., Walisser, J. A., Reddy, J. K., Thomas, R. S., and Bradfield, C. A. (2005). EDGE: A Centralized resource for the comparison, analysis and distribution of toxicogenomic information. Mol. Pharmacol. 67, 1360-1368.

Yang, R. S. H., El-Masri, H. A., Thomas, R. S., Dobrev, I. D., Dennison Jr., J. E., Bae, D.-S., Campain, J. A., Liaon, K. H., Reisfeld, B., Andersen, M. E., and Mumtaz, M. (2004). Chemical mixture toxicology: from descriptive to mechanistic, and going on to in silico toxicology. Environ. Toxicol. Pharmacol. 18, 65-81.

Chanda, S. K., White, S., Orth, A. P., Reisdorph, R., Miraglia, L., Thomas, R. S., DeJesus, P., Mason, D. E., Huang, Q., Vega, R., Yu, D.-H., Nelson, C. G., Smith, B. M., Terry, R., Linford, A. S., Yu, Y., Chirn, G. W., Song, C., Labow, M. A., Cohen, D., King, F. J., Peters, E. C., Schultz, P. G., Vogt, P. K., Hogenesch, J. B., and Caldwell, J. S. (2003). Genome-scale functional profiling of the mammalian AP-1 signaling pathway. Proc. Natl. Acad. Sci. U.S.A. 100 (21), 12153-12158.

Ou, Y. C., Conolly, R. B., Thomas, R. S., Gustafson, D. L., Long, M. E., Dobrev, I. D., Chubb, L. S., Xu, Y., Lapidot, S. A., Andersen, M. E., and Yang, R. S. (2003). Stochastic simulation of hepatic preneoplastic foci development for four chlorobenzene congeners in a medium-term bioassay. Toxicol. Sci. 73 (2), 301-314.

Rank, D. R., Hanzel, D. K., Jenkins, D., Thomas, R. S., Shannon, M., Guo, J., Corrigan, A., Zhang, J., Gu, Y., Chen, W., Ji, Y., Hu, T., Barker, D. L., and Penn, S. G. (2003). Microarrays: use in gene identification. In Encyclopedia of the Human Genome (van Ommen, G. J. and Cooper, D. N., editors). Macmillan & Nature Publishing Group, London.

Love, B., Rank, D. R., Penn, S. G., Jenkins, D. A., and Thomas, R. S. (2002). A conditional density error model for the statistical analysis of microarray data. Bioinformatics 18 (8), 1064-1072.

Thomas, R. S., Hayes, K. R., Zastrow, G. M., Tran, K., Penn, S. G., Rank, D. R., and Bradfield, C. A. (2002). Application of DNA microarrays for predicting toxicity and evaluating cross-species extrapolation. In Toxicogenomics (Inoue, T. and Pennie, W. D., editors), pp. 31-38. Springer-Verlag, Tokyo.

Thomas, R. S., Penn, S. G., Holden, K., Bradfield, C. A., and Rank, D. R. (2002). Sequence variation and phylogenetic history of the mouse Ahr gene. Pharmacogenetics 12, 151-163.

Thomas, R. S., Rank, D. R., Penn, S. G., Zastrow, G. M., Hayes, K. R., Hu, T., Pande, K., Lewis, M., Jovanovich, S. B., Bradfield, C. A. (2002). Application of genomics to toxicology research. Environ. Health Perspect. 110 (Suppl. 6), 919-923.

Thomas, R. S., Rank, D. R., Penn, S. G., Craven, M. W., Drinkwater, N. R., and Bradfield, C. A. (2002). Developing toxicologically predictive gene sets using cDNA microarrays and Bayesian classification. Methods Enzymol. 357, 198-205.

Ou, Y., Conolly, R. B., Thomas, R. S., Gustafson, D. L., Benjamin, S. A., and Yang, R. S. H. (2001). A comparison of GST-P hepatic foci induction among chlorobenzene isomers using biologically-based clonal growth modeling. Cancer Res. 61 (5), 1879-1889.

Thomas, R. S., Rank, D. R., Penn, S. G., Zastrow, G. M., Hayes, K. R., Pande, K., Glover, E., Silander, T., Craven, M. W., Reddy, J. K., Jovanovich, S. B., and Bradfield, C. A. (2001). Identification of toxicologically predictive gene sets using cDNA microarrays. Mol. Pharmacol. 60 (6), 1189-1194.

Lahvis, G. P., Lindell, S. L., Thomas, R. S., McCuskey, R. S., Murphy, C., Glover, E., Bentz, M., Southard, J., and Bradfield, C. A. (2000). Portosystemic shunting and persistent fetal vascular structures in aryl hydrocarbon receptor-deficient mice. Proc. Nat. Acad. Sci. 97 (19), 10442-10447.

Thomas, R. S., Conolly, R. B., Gustafson, D. L., Long, M. E., Benjamin, S. A., and Yang, R. S. H. (2000). A physiologically-based pharmacodynamic analysis of hepatic foci within a medium-term liver bioassay using pentachlorobenzene as a promoter and diethylnitrosamine as an initiator. Toxicol. Appl. Pharmacol. 166 (2), 128-137.