Publication details
Enzymatic Precipitation Enhanced Surface Plasmon Resonance Immunosensor for the Detection of Salmonella in Powdered Milk
| Authors | |
|---|---|
| Year of publication | 2016 |
| Type | Article in Periodical |
| Magazine / Source | Analytical Chemistry |
| MU Faculty or unit | |
| Citation | |
| Web | http://pubs.acs.org/doi/abs/10.1021/acs.analchem.6b03511 |
| Doi | http://dx.doi.org/10.1021/acs.analchem.6b03511 |
| Field | Analytic chemistry |
| Keywords | Surface plasmon resonance biosensor; Biocatalyzed precipitation; Food safety; Bacterial pathogen; Salmonella Typhimurium; Atomic force microscopy |
| Description | Contamination of food by pathogenic bacteria has always been a serious threat for human health. The amount of food exports and imports has been increasing in recent years which requires precise food quality control with short analysis time and simplified sample treatment. Surface plasmon resonance (SPR) immunosensor enhanced by biocatalyzed precipitation was developed for the analysis of Salmonella in dairy products. The specific capture antibody was immobilized on the SPR chip which allowed a direct label-free detection of Salmonella Typhimurium with the limit of detection (LOD) of 104 CFU·mL–1 and the analysis time of 10 min. Alternatively, the secondary detection antibody was conjugated with horseradish peroxidase to provide a signal enhancement by the biocatalyzed conversion of 4-chloro-1-naphthol to insoluble benzo-4-chlorocyclohexadienone. The formation of precipitate was studied in detail by atomic force microscopy (AFM). The sensitivity was increased 40 times in case of the precipitation-enhanced detection compared to the label-free approach. The optimized method provided LOD of 100 CFU·mL–1 with linear range up to 106 CFU·mL–1. The total time of analysis including bacteria binding and enhancement step was below 60 min. The capability to analyze real samples with complex matrices was demonstrated on the detection of Salmonella in powdered milk. The developed sensor represents simple and robust approach for routine monitoring of food contamination. |
| Related projects: |