National Center for Computational Toxicology

Key Contact: James Samet, Ph.D., HSD, NHEERL, samet.jim@epa.gov, tel: 919-966-0665

Diesel exhaust particulate matter (DEP) is a ubiquitous ambient air contaminant derived from mobile and stationary diesel fuel combustion. Exposure to DEP is associated with carcinogenic and immunotoxic effects in humans and experimental animals. At the cellular level, these health effects are underlain by genotoxic and inflammatory properties of chemical compounds present in DEP. DEP is composed of elemental, inorganic and organic compounds that vary widely in composition with the source of the fuel, engine operating conditions, sampling methods and other parameters. The genotoxic and inflammatory potencies of DEP also vary with its physicochemical properties, and these differences along with multiple health effects impede the development of targeted regulatory strategies for mitigating the impact of DEP exposure on human health. While traditional reductive toxicology approaches are not likely to succeed in quantifying relationships between DEP composition and its numerous health effects, generating a database for modeling the toxicological effects of DEP would provide a framework for quantitative hazard identification. This project proposes a systems approach to developing and applying predictive computational models that quantitatively describe relationships between the composition of DEP and its genotoxic and inflammogenic potencies. This objective will be met in three phases. In phase 1 (Specific Aim 1), 16 distinct DEP will be generated using a combination of fuels, engine types, engine loads and collection temperatures. These DEP will then be characterized through extensive chemical and physical analyses. In phase 2 (Specific Aims 2 and 3), the inflammogenic and genotoxic potencies of each of the 16 DEP will be determined quantitatively. Specific bioassays will measure the expression of the pivotal inflammatory mediator IL-8/MIP-2 in cultured human and mouse lung cells in response to DEP exposure. Signaling mechanisms that regulate the expression of IL-8/MIP-2 in response to DEP exposure will also be examined in order to provide mechanistic insight and support for the models. The genotoxicity of the 16 DEP will be assayed using bacterial mutagenicity assays. Human, mouse and bacterial gene expression arrays will be used to provide additional mechanistic insights on patterns of gene expression induced by DEP. Phase 3 (Specific Aim 4) will utilize the generated data to construct a series of statistical and mathematical models that quantitatively relate DEP composition, its inflammogenic and mutagenic effects and the relevant intracellular signaling mechanisms. These models will have practical application in offices responsible for DEP assessment and regulatory programs including the Office of Air and Radiation (OAR) and the National Center for Environmental Assessment (NCEA).

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