A serious public health threat to Native American communities in the Four Corners region of the US is chemical toxicity arising from exposure to uranium through water resources contaminated by abandoned mines. Chronic environmental exposure to uranium, a documented nephrotoxin, negatively impacts DNA repair, disrupts regulation of transcription factors and gene expression, and promotes apoptosis thus increasing the risk of cancer and other health problems. Effective risk management for uranium contamination requires reliable exposure assessment and biomonitoring tools for these impacted populations; however, the current analytical ?gold standards? require laborious pretreatment steps and data collection and interpretation can be time-consuming, particularly in complex matrices such as urine and surface or ground water. As a result, the goal of this project is to reduce public health risks and negative side effects of uranium exposure for at risk populations through the development of enabling technology for the near real-time and trace detection of total uranium concentration in media relevant to exposure mechanisms and biomonitoring so that contamination threats can be dealt with in a timely manner. The innovation of this proposal is derived from our ability to confront the analytical challenge of uranium speciation, which often hinders the efficacy of standard detection and quantification methods with improved detection selectivity through functionalized electrospun polymer mats with detection sensitivity using surface enhanced Raman scattering (SERS). By using equilibrium speciation modeling to predict most probable uranium complexes in environmentally and biologically relevant media, we can guide the design of selective, high capacity sorbent materials that can be easily integrated into sensing platforms harnessing the sensitivity of SERS, which notably produces distinct signatures for different bound uranium species. Importantly, selectivity of uranium detection in synthetic urine has been demonstrated using the sorbent materials and SERS. This total systems approach allows for a highly sensitive and rapid approach for measuring not only total uranium in a sample but also the potential to distinguish distinct chemical forms using portable Raman spectrometers and simple barcode outputs will provide ease of use. While standard techniques provide isotopic signatures, aqueous speciation that is crucial for environmental remediation, chelation therapies and improved risk assessment cannot be attained. We anticipate the development of this novel sensing platform will produce empowering technologies that improve the health and overall quality of life of a currently overlooked and underserved population, the Navajo Nation and other neighboring communities.

Public Health Relevance

The objective of this proposal is to develop a near real-time, field deployable detection system for trace- level uranium present in aqueous systems and biological fluids using a platform that couples selective capture of diverse uranium species on a porous membrane with subsequent detection of uranium complexes by surface enhanced Raman spectroscopy (SERS). Our hypothesis is that concentrating various uranium complexes on chemically functionalized, nanostructured filter surfaces should concentrate uranium by 10-106-fold while SERS will further improve detectability by 103 ? 108 thus facilitating trace-level uranium concentrations. The long-term outcomes of this proposal could enable the Native American communities at risk of uranium exposure through contaminated water to use this sensing device; thus, empowering the community to improve their environmental health and overall quality of life.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Research Project (R01)
Project #
5R01ES027145-02
Application #
9419298
Study Section
Instrumentation and Systems Development Study Section (ISD)
Program Officer
Balshaw, David M
Project Start
2017-02-01
Project End
2021-01-31
Budget Start
2018-02-01
Budget End
2019-01-31
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Iowa
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
062761671
City
Iowa City
State
IA
Country
United States
Zip Code
52242
Xi, Wenjing; Phan, Hoa T; Haes, Amanda J (2018) How to accurately predict solution-phase gold nanostar stability. Anal Bioanal Chem 410:6113-6123
Lu, Grace; Johns, Adam J; Neupane, Binita et al. (2018) Matrix-Independent Surface-Enhanced Raman Scattering Detection of Uranyl Using Electrospun Amidoximated Polyacrylonitrile Mats and Gold Nanostars. Anal Chem 90:6766-6772