A sensitive fluorometric bio-barcodes immunoassay for detection of triazophos residue in agricultural products and water samples by iterative cycles of DNA-RNA hybridization and dissociation of fluorophores by Ribonuclease H

Although the toxicity of triazophos is high and it has been pulled from the market in many countries; it is still widely used and frequently detected in agricultural products. While conventional analyses have been routinely used for the quantification and monitoring of triazophos residues, those for detecting low residual levels are deemed necessary. Therefore, we developed a novel and sensitive fluorometric signal amplification immunoassay employing bio-barcodes for the quantitative analysis of triazophos residues in foodstuffs and surface water. Herein, monoclonal antibodies (mAbs) attached to gold nanoparticles (AuNPs) were coated with DNA oligonucleotides (used as a signal generator), and a complementary fluorogenic RNA was used for signal amplification. The system generated detection signals through DNA-RNA hybridization and subsequent dissociation of fluorophores by Ribonuclease H (RNase H). It has to be noted that RNase H can only disintegrate the RNA in DNA-RNA duplex, but not cleave single or double-stranded DNA. Hence, with iterative cycles of DNA-RNA hybridization, sufficient strong signal was obtained for reliable detection of residues. Furthermore, this method enables quantitative detection of triazophos residues through fluorescence intensity measurements. The competitive immunoassay shows a wide linear range of 0.01–100 ng/mL with a limit of detection (LOD) of 0.0032 ng/mL. The assay substantially meets the demand for the low residue detection of triazophos residues in agricultural products and water samples. Accuracy (expressed as spiked recovery %) and coefficient of variation (CV) were ranged from 73.4% to 116% and 7.04% to 17.4%, respectively. The proposed bio-barcodes immunoassay has the advantages of being stable, reproducible, and reliable for residue detection. In sum, the present study provides a novel approach for detection of small molecules in various sample matrices.