Electrochemical Peptide-Based (E-PB) Sensor for the Detection of Uranium

Wednesday, 31 May 2017: 15:00
Grand Salon A - Section 4 (Hilton New Orleans Riverside)
C. C. Thompson (University of Nebraska-Lincoln) and R. Y. Lai (University of Nebraska - Lincoln Department of Chemistry)
Metal ion sensing attracts significant attention as many metal ions that are introduced into natural waters as water waste from industrial processes are toxic to humans. Uranium is a radioactive heavy metal naturally present in the environment and largely found in its hexavalent oxidation state as the uranyl ion, UO22+. Anthropogenic activities such as mining, milling, and nuclear testing increase the distribution of groundwater contamination and in many regions in the United States contamination exceeds the U.S. Environmental Protection Agency (EPA) Maximum Contamination Level (MCL) of 30 µg/L (126 nM). Therefore, there is a need for developing sensitive, selective, and cost-effective analytical methods capable of identifying and quantifying uranium in environmental samples. In this study, we focus on understanding the interactions between uranium-binding peptides and UO22+ as well as exploiting these interactions in the design of electrochemical peptide-based (E-PB) uranium sensors. We are particularly interested in assessing the effect of threonine phosphorylation on uranium binding affinity of peptides. The peptide probe used in the fabrication of the first generation E-PB uranium sensor is a thiolated 12-amino acid peptide probe modified with methylene blue (MB). In the absence of the target, the probe is flexible and the MB current is high; in the presence of the target, the flexibility of the probe is dampened, resulting in a large reduction in the MB current. Our preliminary results show that the sensor is capable of specific detection of UO22+ at concentrations substantially lower than the EPA MCL (limit of detection = 10 nM). Like most E-PB sensors, it is also reusable and selective enough to be employed in 50% synthetic aquifer samples. With further optimization, this sensor could find applications in real time detection of uranium in complex environmental samples.