This NIEHS-SRP research project will use newly developed biosensor technology to rapidly predict how polycyclic aromatic hydrocarbons (PAH) accumulate in seafood exposed to contaminated sediments. Hydrophobic contaminants such as PAH readily accumulate in shellfish, where they pose a significant human health risk when consumed. Lipid partitioning drives bioaccumulation in shellfish but multiple chemical, physical and environmental factors influence bioavailability and tissue concentrations in dynamic natural systems. Because measuring contaminant uptake in biota is time consuming and expensive, models have been developed to predict contaminant fate and disposition. However, temporal variability and heterogeneity of natural habitats make it difficult to reliably predict bioaccumulation for risk assessments from measured sediment concentrations. Ultimately, site-specific measurements are vital to accurately predict contaminant bioavailability and to evaluate the effectiveness of sediment remediation efforts. Recent advances in biosensor technology now allow near real-time measurement of contaminants at sub part per billion concentrations. This project will evaluate, refine and validate an automated, quantitative, monoclonal antibody-based sensor to measure PAH in sediment-associated water. We will validate the biosensor as a predictor of PAH tissue burdens in shellfish, an important route for PAH exposure to humans from contaminated sediments. This will be accomplished through controlled laboratory dosing of oysters. The biosensor will be then be applied in the highly contaminated Elizabeth River, Norfolk, Virginia to assess the effectiveness of ongoing remediation strategies being employed to reduce the human health risks associated with PAH exposure through the food web. Hypotheses 1. Real-time bio-sensor estimates of PAH concentration in aqueous samples (sediment pore water, surface water) rapidly and specifically predict lipid-normalized PAH concentrations in the tissues of native oysters inhabiting PAH-contaminated sites. 2. Biosensor measurements of aqueous PAH concentrations are specific, dose-responsive, correlate directly with tissue concentrations of PAH in dosed oysters and are therefore predictive surrogates of tissue bioaccumulation. 3. Incorporation of mixed analyte beds with differentative antibody specificities for different PAH classes will provide for more accurate discernment of the relative contribution of these different PAHs in the field and laboratory.

Public Health Relevance

Polycyclic aromatic hydrocarbons (PAH) are formed by the combustion of organic matter and they enter the aquatic environment via natural seeps, atmospheric inputs or through spills of petroleum and creosote. Because of their physical properties, PAHs will accumulate in sediments and seafood such as oysters. This research project will develop new antibody-based biosensors to rapidly measure PAHs in the aquatic environment so we can evaluate methods to remediate PAH-contaminated sediments to protect the public from the potential health risks associated with consuming contaminated seafood.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Research Project (R01)
Project #
5R01ES020949-02
Application #
8402397
Study Section
Special Emphasis Panel (ZES1-SET-D (SF))
Program Officer
Henry, Heather F
Project Start
2011-12-12
Project End
2014-10-31
Budget Start
2012-11-01
Budget End
2013-10-31
Support Year
2
Fiscal Year
2013
Total Cost
$276,184
Indirect Cost
$86,184
Name
Virginia Institute of Marine Science
Department
Type
DUNS #
169516213
City
Gloucester Point
State
VA
Country
United States
Zip Code
23062
Li, Xin; Kaattari, Stephen L; Vogelbein, Mary Ann et al. (2016) Evaluation of a time efficient immunization strategy for anti-PAH antibody development. J Immunoassay Immunochem 37:671-83
Li, Xin; Kaattari, Stephen L; Vogelbein, Mary A et al. (2016) A highly sensitive monoclonal antibody based biosensor for quantifying 3-5 ring polycyclic aromatic hydrocarbons (PAHs) in aqueous environmental samples. Sens Biosensing Res 7:115-120