Allergen identification in genetically modified maize by multiplex PCR for neuropathy prevention

Tata Ninidze1,2, Kakha Bitskinashvili2, Tamara Kutateladze2, Boris Vishnepolsky2, Nelly Datukishvili1,2

1 Ilia State University, Tbilisi, Georgia

2 I.Beritashvili Center of Experimental Biomedicine, Tbilisi, Georgia

Analysis of food allergens is of particular interest for health protection including neuropathy prevention. The allergenicity assessment of genetically modified (GM) plants and products derived thereof is important for food quality and safety, labeling regulation and consumer information. GM foods may contain both species-specific and GMO-specific allergens. This study aimed to develop new effective multi-allergen diagnostic approach for transgenic maize. To this purpose multiplex polymerase chain reaction (PCR) technology was applied. Maize (corn) is often used in food production whereas it belongs to the important GM crops as well as food allergens. The investigation was focused on the insect resistant GM maize event MON 810. The set of certified reference materials consisting of 0 – 5% MON810 were used for the optimization of the PCR systems. The analytical procedure includes several steps such as identification of allergen-specific DNA sequences by in silico genome data analysis, design of PCR primers, genomic DNA extraction, development and optimization of uniplex and multiplex PCR systems, evaluation of genomic DNAs and PCR products by agarose gel electrophoresis, analysis of allergens in food products. The results showed that new effective DNA markers were identified for three maize allergens, namely Zea m 8 (chitinase), Zea m 14 (phospholipid transfer protein 1) and zein as well as GMO-specific Cry1Ab delta-endotoxin expressed in the insect resistant GMOs. The multiplex PCRs were developed for simultaneous identification of these allergens. The analysis of different food products revealed the effective PCR-based procedure for reliable and fast testing of GM maize allergens. 

Acknowledgments

This work was supported by Shota Rustaveli National Science Foundation of Georgia (SRNSFG) under GENIE project (grant number № CARYS-19-2035)