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  • Title: Determination of ochratoxin A by polyclonal antibodies based sensitive time-resolved fluoroimmunoassay.
    Author: Huang B, Tao W, Shi J, Tang L, Jin J.
    Journal: Arch Toxicol; 2006 Aug; 80(8):481-5. PubMed ID: 16688427.
    Abstract:
    Using indirect competitive time-resolved fluoroimmunoassay (TRFIA), a rapid, highly selective and extremely sensitive method has been established for the determination of ochratoxin A (OA). Tests can be performed in a 96-well microplate using the toxin-specific polyclonal antibodies, obtained from rabbits immunized with ochratoxin A-keyhole limpet's hemocyanin (OA-KLH). In indirect TRFIA format, ochratoxin A-bovine serum albumin conjugate (OA-BSA) is coated onto the microtitre plate and incubated with standard toxin (samples) and anti-OA antibody. A goat anti-rabbit IgG Eu(3+) conjugate is used to enable the detection. The suitability of the assay for quantification of OA is also studied and samples are determined by OA-TRFIA using autoDELFIA1235 system. The results show that the polyclonal antibodies can be used at a dilution exceeding 1:8,000 and the OA detection limit is 0.02 microg/l for indirect competitive TRFIA formats. The 80, 50, and 20% inhibition binding effect dose (ED80, ED50, ED20) of OA were 0.195, 1.018, and 5.314 microg/l, respectively. The assay ranges from 0.02 to 400 microg/l. The cross reactivity with ochratoxin B is 5.6% and antibodies do not react with aflatoxin B1, phenylalanine and BSA. The within-run and between-run CVs of the OA-TRFIA are 2.6 and 5.2%, respectively. The mean recoveries from the OA-free cereals spiked with 1-200 microg of OA/kg of cereals sample were 95.8%. Both OA-TRFIA and OA-ELISA tests are applied for the quantitative measurement of OA in the same cereals, and the coefficient of correlation is 0.912. The results show that the novel TRFIA method can be applied to detect the OA contamination in cereals. It provides very high sensitivity and optimal range and will be useful to screen OA contamination easily, simply, and economically when the number of samples is large.
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