Development of electrochemical sensors for the detection of mycotoxins in food matrices using functionalised nanocomposites

Abstract

The analysis of pathogens in foods is of critical importance to ensure consumer safety and quality assurance, as contaminants pose serious risks to public health. Mycotoxins are naturally occurring carcinogenic toxins that arise from specific strains of fungi as they contaminate food. They are found in a wide variety of grains, cereals, and dairy products, causing cancer in both humans and animals. Thus, there is a growing demand for simple, sensitive and inexpensive sensors for mycotoxin detection in lieu of conventionally employed large-scale instrumentation. In this study, the development of electrochemical sensors for the detection of aflatoxin B1 (AFB1), zearalenone (ZEN) and ochratoxin A (OTA) in foods was investigated and presented as three case studies, respectively. In the first case study, an ultrasensitive aptasensor was developed for the indirect detection of AFB1 in the presence of a ferri/ferrocyanide ([Fe(CN)6]3-/4-) redox probe solution. The sensor was constructed by immobilizing an anti-AFB1 aptamer (Apt) to a carboxylated multiwalled carbon nanotube (cMWCNT) and iron oxide (Fe3O4) nanoparticle (NP) composite using a glassy carbon electrode (GCE). This resulted in the development of the GCE/cMWCNTsFe3O4 NP/Apt sensor. An electrochemical response was exhibited from AFB1 applying cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and differential pulse voltammetry (DPV), respectively, utilizing a [Fe(CN)6]3-/4- redox probe prepared in phosphatebuffered saline (PBS) solution with reference to the Ag/AgCl reference electrode under optimized conditions. DPV findings reported very low limits of detection (LOD) and quantification (LOQ) of 0.43 fg mL-1 and 1.44 fg mL-1 respectively in comparison to current literature, over a calibration range of 0.50 fg mL-1 to 5.00 fg mL-1. For real sample analysis, excellent spike recoveries from 95% to 105% were obtained for corn and rice flour. Density functional theory (DFT) was used to propose a reaction scheme by ascertaining the electronic properties of the redox-active functional groups of AFB1. This supported the experimental anodic response findings of DPV. The second case study focused on how PEGylated Fe3O4 NPs and cMWCNTs fabricated on a GCE could be used for the design of an electrochemical sensor for ZEN analysis. The qualitative and quantitative analyses of ZEN were completed using CV, EIS and DPV, respectively, under optimized conditions in a sodium phosphate buffer solution. The developed sensor reported significantly low LODs and LOQs of 0.34 fg mL-1 and 1.12 fg mL-1 respectively, over a calibration range of 1.00 fg mL-1 to 10.00 fg mL-1 by DPV. Excellent spike recoveries ranging from 92% to 106% were obtained for rice and corn flour. The Monte Carlo (MC) adsorption simulation studies predicted the strong interaction of ZEN with the constructed sensor. In the final case study, an OTA electrochemical sensor was designed using a nickel metalorganic framework (Ni-MOF) and carboxylated reduced graphene oxide (cRGO) on a GCE. The detection of OTA was achieved under optimized conditions in PBS solution with the developed GCE/Ni-MOF/cRGO electrode, employing CV, EIS and DPV as electrochemical tools. Applying DPV, the sensor reported very low LODs and LOQs of 3.29 fg mL-1 and 10.97 fg mL-1 respectively, over a calibration range of 10.00 fg mL-1 to 90.00 fg mL-1. Regarding real sample analysis, excellent spike recoveries from 95% to 105% were obtained for corn and rice flour. Molecular dynamics (MD) studies predicted that the Ni-MOF exhibited a strong electrostatic interaction with the OTA analyte, in agreement with the experimental findings. The synthesized nanomaterials (cMWCNTs-Fe3O4 NP, PEG-Fe3O4 NPs/cMWCNTs, and NiMOF/cRGO) utilized in this study were characterized by an array of techniques, including single particle inductively coupled plasma-mass spectrometry (spICP-MS), transmission electron microscopy (TEM), X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDS), scanning electron microscopy (SEM), multidetector asymmetrical flow field-flow fractionation (AF4), and Fourier transform infrared spectroscopy (FTIR). Finally, computational modelling studies were undertaken to establish a synergy with the experimental approaches employed in each case study. These methodologies included DFT, docking studies, MC adsorption and MD simulations, which were aimed at predicting and assessing the atomic and molecular interactions between the mycotoxins and their respective electrode systems.