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Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip
Published on: February 7, 2017
Simple, high efficiency detection of microcystins and nodularin-R in water by fluorescence polarization immunoassay
Huiyan Zhang1, Shupeng Yang2, Ross C Beier3
1Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Veterinary Medicine, China Agricultural University, Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, Beijing Laboratory for Food Quality and Safety, Beijing 100193, People's Republic of China.
Abstract:
This manuscript describes the development of a sensitive, fast and easily-performed fluorescence polarization immunoassay (FPIA) for detection of microcystins (MCs) and nodularin-R (NOD) in water. MCs and NOD, the most widespread cyanobacterial toxin are hepatotoxins and tumor promoters, and their acute exposure may result in severe health problems in animals and humans. The fluorescein-based tracers were synthesized, and for the first time preparative high performance liquid chromatography (HPLC) was employed for their purification. Optimal tracers for the analysis were selected by evaluating the immunochemical activity. Under the optimal conditions, the achieved limits of detection (LODs) for MC-LR and NOD were 0.86 and 0.95 μg L-1, respectively, providing a sufficient sensitivity to meet the provisional guideline value recommended by the World Health Organization (WHO). An ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed to confirm the accuracy and precision of the FPIA, and no obvious difference in recovery between these two methods was found. The correlation coefficients (R2) were higher than 0.968. The developed FPIA was easy-to-operate and could be completed within 10 min after simple filtration and adjustment of pH for water samples. The method can be easily extended for screening of other cyanotoxins, representing a versatile strategy for environmental sample analysis.

