A real-time antibody-based field assay to predict containment bioavailability in

一种基于实时抗体的现场测定，用于预测药物中的遏制生物利用度

• 批准号: 8402397
• 负责人: STEPHEN L KAATTARI
• 金额: $ 27.62万
• 依托单位: VIRGINIA INSTITUTE OF MARINE SCIENCE
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-12-12 至 2014-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8402397
• 关键词: Adult; Alkylation; Antibodies; Antibody Specificity; Antigens; Aromatic Polycyclic Hydrocarbons; Beds; Biological Assay; Biological Availability; Biosensor; Biota; Carbon; Characteristics; Chemicals; Containment; Creosote; Detection; Development; Dose; Effectiveness; Environment; Environmental Risk Factor; Evaluation; Exposure to; Food Webs; Habitats; Health; Heterogeneity; Human; Laboratories; Lipids; Measurement; Measures; Methods; Modeling; Monitor; Monoclonal Antibodies; National Institute of Environmental Health Sciences; Oysters; Petroleum; Phase; Proteins; Relative (related person); Research Project Grants; Risk; Risk Assessment; Rivers; Route; Sampling; Seafood; Shellfish; Signal Recognition Particle; Silicon Dioxide; Site; Specificity; Surface; System; Technology; Testing; Time; Tissues; Variant; Virginia; Water; aqueous; base; bioaccumulation; chemical property; cost effective; physical property; remediation; sensor; superfund site; uptake

DESCRIPTION (provided by applicant): 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.

描述（由申请人提供）：该NIEHS-SRP研究项目将使用新开发的生物传感器技术来迅速预测多环芳烃如何在暴露于受污染沉积物的海鲜中积累的多环芳烃（PAH）。 PAH等疏水污染物很容易积聚在贝类中，在那里消耗时会造成严重的人类健康风险。脂质分配驱动贝类中的生物积累，但多种化学，物理和环境因素会影响动态天然系统的生物利用度和组织浓度。由于测量生物群中的污染物吸收既耗时又昂贵，因此已经开发出模型来预测污染物的命运和处置。但是，自然栖息地的时间变异性和异质性使得很难可靠地预测来自测量沉积物浓度的风险评估的生物积累。最终，特定地点测量对于准确预测污染物的生物利用度至关重要，并评估沉积物修复工作的有效性。现在，生物传感器技术的最新进展允许在数十亿浓度的一部分中几乎实时测量污染物。该项目将评估，完善和验证基于自动化的，定量的，单克隆抗体的传感器，以测量与沉积物相关水中的PAH。我们将验证生物传感器作为贝类中PAH组织负担的预测因子，这是PAH从受污染的沉积物中暴露于人类的重要途径。这将通过牡蛎的受控实验室剂量来实现。然后，将在弗吉尼亚州诺福克市高度污染的伊丽莎白河中应用生物传感器，以评估采用正在进行的补救策略的有效性，以减少通过食品网络暴露与PAH相关的人类健康风险。假设1。在水性样品（沉积物孔隙水，地表水）中迅速预测居住在PAH污染位点的天然牡蛎组织中的脂质差异PAH浓度的PAH浓度的实时生物传感器估计值。 2。pAH浓度的生物传感器测量是特异性的，剂量响应性，与剂量牡蛎中的PAH组织浓度直接相关，因此是组织生物蓄能的预测替代物。 3。将混合分析物床具有不同PAH类别的差异性抗体特异性的结合，将提供更准确的辨别于田间和实验室中这些不同PAH的相对贡献。