MXene-based aptasensor for the detection of aflatoxin in food and agricultural products

The detection of toxins that contaminate food needs highly sensitive and selective techniques to prevent substantial monitory loss. In this regard, various nanostructured material-enabled biosensors, have recently been developed to improve the detection of food toxins among them aflatoxin is the prevalent one. The biosensor-based detection of aflatoxin is quick, cheaper, and needs less skilled personnel, therefore overcoming the shortcomings of conventional techniques such as LC/MS-MS, HPLC, and ELISA assays. 2D MXenes manifest as an efficient material for biosensing due to their desirable biocompatibility, magnificent mechanical strength, easiness of surface functionalization, and tuneable optical and electronic features. Contrary to this, aptamers as biorecognition elements (BREs) possess high selectivity, sensitivity, and ease of synthesis when compared to conventional BREs. In this review, we explored the most cutting-edge aptamer-based MXene-enabled biosensing technologies for the detection of the most poisonous mycotoxins (i.e., Aflatoxins) in food and environmental matrices. The discussion begins with the synthesis processes and surface functionalization/modification of MXenes. Computational approaches for designing aptasensors and advanced data analysis based on artificial intelligence and machine learning with special emphasis over Internet-of-Thing integrated biosensing devices has been presented. Besides, the advantages of aptasensors over conventional methods along with their limitations have been briefed. Their benefits, drawbacks, and future potential are discussed concerning their analytical performance, utility, and on-site adaptability. Additionally, next-generation MXene-enabled biosensing technologies that provide end users with simple handling and improved sensitivity and selectivity have been emphasized. Owing to massive applicability, economic/commercial potential of MXene in current and future perspective have been highlighted. Finally, the existing difficulties are scrutinized and a roadmap for developing sophisticated biosensing technologies to detect toxins in various samples in the future is projected.