Heavy metals in the environment are harmful both to human beings and the environment. In the past, heavy metal contamination was detected using traditional analytical methods that were time-consuming, costly, and required complex equipment. In recent years, several different types of biosensors based upon the programmable use of nucleic acids have been developed. The focus of this review is to cover the architecture, principles of operation, and performance characteristics of CRISPR-based biosensors for detection of heavy metals. CRISPR-Cas12 and Cas13 nucleases enable programmable biosensors through collateral trans-cleavage of single-stranded DNA and RNA, respectively. The review further explores the conversion of specific heavy metal binding events into nucleic acid signals and their subsequent integration with CRISPR based molecular system. In addition, many different types of signal transduction modalities), and the use of nanomaterials for signal enhancement for heavy metals are also analysed. Presently, the available technologies demonstrates good recovery rates and comparable performance to ICP-MS for metal detection in complex matrix. Nonetheless, substantial challenges persists, including matrix interference from organic matter and competing ions, component stability and scalability, and regulatory standardisation. Future efforts are likely to include the development of portable devices integrated with smartphones, multiplex detection, microfluidic lab-on-a-chip integration, and the implementation of artificial intelligence to assist in data analysis. This article presents a thorough roadmap for converting laboratory advances into dependable technology capable of providing comprehensive monitoring of heavy metals for use in the field while stressing the need for ongoing optimisation with real-world sample matrices.
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Kulabhusan et al. (2026) studied this question.
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