Improving biosensors by the use of different nanomaterials: Case study with microcystins as target analytes

Abstract

The eutrophication of lakes and rivers without adequate rainfall leads to excessive growth of cyanobacterial harmful algal blooms (CyanoHABs) that produce toxicants, green tides, and unpleasant odors. The rapid growth of CyanoHABs owing to global warming, climate change, and the development of rainforests and dams without considering the environmental concern towards lakes and rivers is a serious issue. Humans and livestock consuming the toxicant-contaminated water that originated from CyanoHABs suffer severe health problems. Among the various toxicants produced by CyanoHABs, microcystins (MCs) are the most harmful. Excess accumulation of MC within living organisms can result in liver failure and hepatocirrhosis, eventually leading to death. Therefore, it is essential to precisely detect MCs in water samples. To date, the liquid chromatography– mass spectrometry (LC–MS) and enzyme-linked immunosorbent assay (ELISA) have been the standard methods for the detection of MC and provide precise results with high reliability. However, these methods require heavy instruments and complicated operation steps that could hamper the portability and field-readiness of the detection system. Therefore, in order for this goal to be achieved, the biosensor has been attracted to a powerful alternative for MC detection. Thus far, several types of MC biosensor have been proposed to detect MC in freshwater sample. The introduction of material is a useful option in order to improve the biosensor performance and construct new types of biosensors. Introducing nanomaterials to the biosensor interface provides new phenomena or enhances the sensitivity. In recent times, different types of nanomaterials, such as metallic, carbon-based, and transition metal dichalcogenide-based nanomaterials, have been developed and used to fabricate biosensors for MC detection. This study reviews the recent advancements in different nanomaterial-based MC biosensors.