Current PCR-based methods for the detection of mycotoxigenic fungi in complex food and feed matrices

Abstract

Mycotoxins are toxic secondary fungal metabolites produced by certain types of filamentous fungi, such as Aspergillus, Fusarium, and Penicillium spp. Mycotoxigenic fungi and their produced mycotoxins are considered to be an important issue in food and feed safety due to their toxic effects like carcinogenicity, immunosuppression, neurotoxicity, nephrotoxicity, and hepatotoxicity on humans and animals. To boost the safety level of food and feedstuff, detection and identification of toxins are essential at critical control points across food and feed chains. Zero-tolerance policies by the European Union and other organizations about the extreme low level of tolerance of mycotoxins contamination in food and feed matrices have led to an increasing interest to design more sensitive, specific, rapid, cost-effective, and safer to use mycotoxigenic fungi detection technologies. Hence, many mycotoxigenic fungi detection technologies have been applied to measure and control toxins contamination in food and feed substrates. PCR-based mycotoxigenic fungi detection technologies, such as conventional PCR, real-time PCR, nested PCR, reverse transcriptase (RT)-PCR, loop-mediated isothermal amplification (LAMP), in situ PCR, polymerase chain reaction-denaturing gradient gel electrophoresis (PCR DGGE), co-operational PCR, multiplex PCR, DNA arrays, magnetic capture-hybridization (MCH)-PCR and restriction fragment length polymorphism (RFLP), would contribute to our understanding about different mycotoxigenic fungi detection approaches and will enhance our capability about mycotoxigenic fungi identification, isolation and characterization at critical control points across food and feed chains. We have assessed the principles, results, the limit of detection, and application of these PCR-based detection technologies to alleviate mycotoxins contamination problem in complex food and feed substrates. The potential application of these detection technologies can reduce mycotoxins in complex food and feed matrices.