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Updated: Aug 29, 2026

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Published on: November 15, 2017
Quantitation of Bt-176 maize genomic sequences by surface plasmon resonance-based biospecific interaction analysis of
Giordana Feriotto1, Sara Gardenghi, Nicoletta Bianchi
1Biotechnology Center, Ferrara University, Ferrara, Italy.
Abstract:
Surface plasmon resonance (SPR) based biosensors have been described for the identification of genetically modified organisms (GMO) by biospecific interaction analysis (BIA). This paper describes the design and testing of an SPR-based BIA protocol for quantitative determinations of GMOs. Biotinylated multiplex Polymerase Chain Reaction (PCR) products from nontransgenic maize as well as maize powders containing 0.5 and 2% genetically modified Bt-176 sequences were immobilized on different flow cells of a sensor chip. After immobilization, different oligonucleotide probes recognizing maize zein and Bt-176 sequences were injected. The results obtained were compared with Southern blot analysis and with quantitative real-time PCR assays. It was demonstrated that sequential injections of Bt-176 and zein probes to sensor chip flow cells containing multiplex PCR products allow discrimination between PCR performed using maize genomic DNA containing 0.5% Bt-176 sequences and that performed using maize genomic DNA containing 2% Bt-176 sequences. The efficiency of SPR-based BIA in discriminating material containing different amounts of Bt-176 maize is comparable to real-time quantitative PCR and much more reliable than Southern blotting, which in the past has been used for semiquantitative purposes. Furthermore, the approach allows the BIA assay to be repeated several times on the same multiplex PCR product immobilized on the sensor chip, after washing and regeneration of the flow cell. Finally, it is emphasized that the presented strategy to quantify GMOs could be proposed for all of the SPR-based, commercially available biosensors. Some of these optical SPR-based biosensors use, instead of flow-based sensor chips, stirred microcuvettes, reducing the costs of the experimentation.
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