Recent Advances in Nanotechnology-Based Biosensors Development for Detection of Arsenic, Lead, Mercury, and Cadmium.

Heavy metals cause considerable environmental pollution due to their extent and non-degradability in the environment. Analysis and trace levels of arsenic, lead, mercury, and cadmium as the most toxic heavy metals show that they can cause various hazards in humans' health. To achieve rapid, high-sensitivity methods for analyzing ultra-trace amounts of heavy metals in different environmental and biological samples, novel biosensors have been designed with the participation of strategies applied in nanotechnology. This review attempted to investigate the novel, sensitive, efficient, cost-benefit, point of care, and user-friendly biosensors designed to detect these heavy metals based on functional mechanisms. The study's search strategies included examining the primary databases from 2015 onwards and various keywords focusing on heavy metal biosensors' performance and toxicity mechanisms. The use of aptamers and whole cells as two important bio-functional nanomaterials is remarkable in heavy metal diagnostic biosensors' bioreceptor design. The application of hybridized nanomaterials containing a specific physicochemical function in the presence of a suitable transducer can improve the sensing performance to achieve an integrated detection system. Our study showed that in addition to both labeled and label-free detection strategies, a wide range of nanoparticles and nanocomposites were used to modify the biosensor surface platform in the detection of heavy metals. The detection limit and linear dynamic range as an essential characteristic of superior biosensors for the primary toxic metals are studied. Furthermore, the perspectives and challenges facing the design of heavy metal biosensors are outlined. The development of novel biosensors and the application of nanotechnology, especially in real samples, face challenges such as the capability to simultaneously detect multiple heavy metals, the interference process in complex matrices, the efficiency and stability of nanomaterials implemented in various laboratory conditions.