Uranium is an environmental pollutant with severe health and ecological consequences since it has radioactive and chemical toxicity affecting mammalian reproduction and development. Therefore, the environmental detection of this element is essential, to prevent deleterious effects on the ecosystems.
The development of a portable and simple detection technique is not easy since traditional methods, including mass spectrometry, energy dispersive X-ray fluorescence spectrometry, laser-induced kinetic phosphorimetry and laser-atomic absorption spectrometry, require extensive and complicated protocols, and specialized equipment and facilities. This makes it impossible to detect uranium pollutants on-site and in a manageable time frame, which limits their use.
The development of a new technique by Zhang and colleagues provides a time and cost effective way to measure uranium in the environment. This method is based on DNAzymes, with specificity for metal ions, and on the coupling of these enzymes with magnetic beads. The DNAzymes are easy to synthesize, thermally stable and economic, making them highly suitable for a widespread application. The magnetic beads allow the rapid recovery and separation of uranium ions from solution without any previous sample enrichment. These unique characteristics make the conjugation of DNAzymes and magnetic beads highly suitable for use in the development of biosensors based on electrochemical or colorimetric assays. The authors developed a colorimetric biosensor that is highly specific and sensitive for the detection of uranium ions. Using this sensor is easy since the enzymatic reaction with a TMB substrate allows immediate visual detection in the field even when uranium ions are present in trace amounts (limit of detection of 0.02ppb(74pM)). The magnetic beads make the isolation of pollutants and operation of the device easy.
Magnetic beads-based DNAzyme recognition and AuNPs-based enzymatic catalysis amplification for visual detection of trace uranyl ion in aqueous environment. Zhang, H., Lin, L., Zeng, X., Ruan, Y., Wu, Y., Lin, M., Fu, F. (2016). Biosensors and Bioelectronics, 78, 73–79. doi:10.1016/j.bios.2015.11.024
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