Towards online specific recognition and sensitive analysis of bisphenol A by using AuNPs@aptamer hybrid-silica affinity monolithic column with LC-MS

Abstract

Highly specific sample pretreatment for the sensitive detection of trace bisphenol A (BPA) in compliacted samples is critical. Herein, a new protocol towards online specific recognition and sensitive detection of BPA was proposed by using Aptamer@AuNPs-modified affinity monolith coupled with LC-MS. Optimization of polymerization conditions and characterization such as the morphology, energy spectrum, mechanical stability, aptamer coverage density and specific performance of the affinity monolith were studied. Nano-gold particles (AuNPs) densely distributed on the rigid hybrid-silica substrates, and an unusually high aptamer coverage density reached 3388 pmol/μL, which was favorable to fulfill the effective identification of BPA with high selectivity and inhibit the interference of analogs including BPB and BPC. A highly sensitive recognition of BPA was obtained with the limit of detection (LOD) as low as 0.02 ng/mL. Applied to dairy milk products and serum samples, trace BPA could be sensitive detected by this strategy, while the poor response was achieved by using traditional non-specific SPE column for sample pretreatment. Satisfactory recoveries of fortified BPA were measured as 97.45 ± 2.24%–98.03 ± 4.36% (n = 3) in powdered infant formulas, 96.64 ± 3.37% ~ 99.42 ± 3.22% (n = 3) in bottled milk, 94.69 ± 2.15% ~ 100.96 ± 1.94% (n = 3) in boxed milk, and 93.71 ± 1.53% ~ 96.73 ± 2.56% (n = 3) in children serum samples, respectively. This protocol lights a new access to online specific identification of trace BPA from complex matrix with good detection sensitivity by using aptamer-affinity monolithic column.