Development, Optimization and Validation of LC-MS/MS Method for Multi-Mycotoxin Detection in Cereals

Mycotoxins are fungal natural metabolites that have a wide range of toxic effects. Among hundreds of mycotoxins, aflatoxins (AFs) (AFB1, AFB2, AFG1, and AFG2), ochratoxin A (OTA), zearalenone (ZEA), deoxynivalenol (DON), fumonisins (FB1 and FB2,), T2 and HT2-toxins are the major health concerns for humans and domestic animals. First, an HPLC method has been developed to investigate the separation of mycotoxins in liquid chromatography. Two derivatization systems, photochemical and chemical methods were applied for derivatization of AFB1 and AFG1, as well as FB1 and FB2, respectively. Then, a LC-MS/MS method has been developed by evaluating the effect of LC column (50 and 150 mm), organic modifier (methanol and acetonitrile) ionization process (ESI, APCI) and ionization mode (positive and negative) on separation and determination of mycotoxins. Then the developed method was optimized for simultaneous determination of the 11 mycotoxins. Response surface methodology (RSM) was used to optimize the LC conditions. The effect of organic solvent percentage at the beginning (0-20%) and end (75-95%) of gradient mobile phase, acid concentration in aqueous phase (0-1%), and flow rate (100-300 μl/min) have been investigated for optimization of LC responses peak area and signal to noise ratio (S/N). The optimized responses obtained using following conditions: organic solvent of 5% at start and 95% at the end of gradient mobile phase, 0.1% acid concentration, and 250 μl/min flow rate. In addition, best sample preparation procedure have been selected by evaluating the effects of two different common types of solvent extraction methods (one step and two step extraction) and four types of clean-up methods including Oasis HLB, MycoSep, immunoaffinity column (IAC) and no clean-up on mycotoxins recoveries. The results of the study showed that the best recoveries (79-109%) for all mycotoxins would be obtained by using one step extraction with no clean up. Finally, the optimized LC-MS/MS method was validated by measuring the selectivity, sensitivity, linearity, accuracy and precision. Limit of Detection (LOD) for AFB1, AFB2, AFG1, AFG2, DON, T2-Toxin, HT2-Toxin, FB1, FB2, OTA and ZEA was 0.05, 0.25, 0.05, 0.5, 5, 2, 2, 10, 10, 0.01, and 0.1, whereas the Limit of Quantification (LOQ) was 0.1, 0.5, 0.1, 1, 10, 4, 4, 20, 20, 0.02, and 0.2 ppb, respectively. Finally, the optimized and validated LC-MS/MS method was applied on real cereal samples (rice, barley, oat, wheat and maize) collected from Malaysian markets. The results showed applicability of the aforementioned method for being used as fast routine method with high accuracy and precision for simultaneous determination of mycotoxins in cereal

Simultaneous detection of 12 mycotoxins in cereals using RP-HPLC-PDA-FLD with PHRED and a post-column derivatization system.

A new method for the simultaneous quantification of 12 mycotoxins was developed and optimized using reverse phase high performance liquid chromatography (RP-HPLC) with a photodiode array (PDA) and fluorescence detector (FLD), a photochemical reactor for enhanced detection (PHRED) and post-column derivatization. The mycotoxins included aflatoxins (AFB1, AFB2, AFG1, and AFG2), ochratoxin A (OTA), zearalenone (ZEA), deoxynivalenol (DON), fumonisins (FB1, FB2, and FB3), T-2 and HT-2 toxins. A double sample extraction with a phosphate-buffered saline solution (PBS) and methanol was used for co-extraction of mycotoxins, and a multifunctional immunoaffinity column was used for cleanup. Optimum conditions for separation of the mycotoxins were obtained to separate 12 mycotoxins in FLD and PDA chromatograms with a high resolution. The method gave recoveries in the range 72-111% when applied to spiked corn samples. The limits of detection (LOD) were 0.025 ng/g for AFB1 and AFG1, 0.012 ng/g for AFB2 and AFG2, 0.2 ng/g for OTA, 1.5 ng/g for ZEA, 6.2 ng/g for FB1, FB3 and HT-2 toxin, 9.4 ng/g for FB2 and T-2 toxin, and 18.7 ng/g for DON. In addition, the limits of quantification (LOQ) ranged from 0.04 ng/g for AFB2 and AFG2 to 62 ng/g for DON. The method was successfully applied to the determination of these mycotoxins in 45 cereal samples obtained from the Malaysian market. The results indicated that the method can be applied for the multi-mycotoxin determination of cereals

Sample preparation optimization for the simultaneous determination of mycotoxins in cereals.

The efficiency of three extraction solvents and three clean-up procedures was compared for simultaneous extraction and purification of aflatoxins (AFB1, AFB2, AFG1 and AFG2), ochratoxin A (OTA), and zearalenone (ZEA) from spiked cereal samples. The best recovery rates for all mycotoxins were achieved using methanol: water (80:20) as the extraction solvent and AOZ multi-functional immunoaffinity column (IAC), as clean up method with recovery values of 61-89%, while that of Oasis HLB and MycoSep 226 were 37-67% and 44-78%, respectively. Then, five variables in the IAC clean-up conditions, including primary conditioning with phosphate buffer saline (PBS) (0-10 mL) (X1), extract load up volume (10-20 mL) (X2), washing volume with PBS (10-20 mL) (X3), and eluting solution volumes with methanol (1-3 mL) (X4) and acetic acid (0-1.5 mL) (X5), were optimized for the specific purification and enrichment of the mycotoxins. Results showed that primary conditioning and PBS washing did not have a significant effect on the recovery responses of mycotoxins. Optimized conditions were selected as 0, 15, 10, 1.3, and 1.5 mL for X1-X5, respectively. The recovery rates of AFB1, AFB2, AFG1, AFG2, OTA and ZEA were within 93-104% in spiked rice, under optimal conditions. LOD and LOQ were 0.0125 and 0.05 ng/g for AFB1 and AFG1, 0.0037 and 0.015 ng/g for AFB2 and AFG2, 0.05 and 0.2 ng/g for OTA, and 0.5 and 2 ng/g for ZEA, respectively. Extraction of spiked cereal samples with methanol: water (80:20) and clean up using AOZ IAC column in optimal condition provided recovery range of 77-104% for all targeted mycotoxins