Foodborne illnesses result in many hospitalizations worldwide, and rapid detection of causative pathogens is critical for outbreak prevention. Before detection, however, enrichment of pathogens is usually required to increase the minimum bacterial count. To address this, magnetic nanoparticle (MNP)-based extraction methods have often been proposed but have limitations with expenses related to recognition ligands and cold-storage requirements. This study used glycan-coated magnetic nanoparticles (gMNP) for the concentration and extraction of pathogens from various foods. The gMNP were synthesized using a simple one-pot method, lacking expensive recognition moieties, and were found to be stable for over 3 years at room temperature. Transmission electron microscopy and confocal laser microscopy confirmed the binding of gMNP to bacterial cells in buffer solution and food matrices, respectively. The gMNP successfully captured cells in high pH environments where they displayed a net-negative charge showing their binding mechanism extends beyond electrostatic interaction. The successful concentration of S. enterica and E. coli was demonstrated in cucumber, raw chicken, and lettuce samples, with natural microflora being typical among these foods. The extraction was confirmed using qPCR, demonstrating that the gMNP-qPCR system can be used in the rapid assessment of low pathogen contamination in complex food matrices. While gMNP successfully extracted bacterial cells from foods, their rapid and specific detection is critical. To achieve this, near infrared spectroscopy (NIRS) and gold nanoparticle (GNP)-based biosensor were assessed for feasibility. Among the primary obstacles with current detection methods are expenses and complexities related to sample preparation which often require technical skillset. NIRS can provide for sensitive and affordable screening, but its incapacity to identify low bacterial loads and the influence of food debris have prevented its wide application. The gMNP were used to address these drawbacks by concentrating bacterial cells and separating them from the interfering matrix. Following magnetic extraction of E. coli, NIRS was used for bacterial classification, and a classification accuracy of >90% was observed in bacterial samples extracted from a pure culture. At low bacterial loads, the processed spectra in the wavelength range of 1100 nm to 1350 nm showed a clear difference between bacterial samples with gMNP and control lacking gMNP. Serially diluted samples were used to establish a limit of detection with bacterial loads as low as 102 CFU/mL, and an accuracy of 85% was achieved using Support Vector Machine (SVM). Using gMNP allowed for bacterial concentration and resulted in an enhanced signal from the spectrophotometer; their presence did not hinder the spectral acquisition. While the gMNP-NIRS platform offers a reasonable solution for outbreak prevention related to foods contaminated with a single bacterial type, high bacterial load in natural microbiota can present problems. Alternatives that are specific to the pathogen of interest are therefore necessary. Gold nanoparticle (GNPs)-based plasmonic/colorimetric biosensors have recently gained attention owing to their remarkable surface plasmon resonance but have often required long probe-functionalization procedures or genomic amplification prior to detection. In this study, highly stable dextrin-capped GNPs (dGNP) were used for the detection of E. coli targeting the uidA gene and S. enterica targeting the invA gene. The synthesized dGNPs showed a characteristic wavelength peak at 520 nm in the visible spectrum and were <50 nm in diameter, confirmed with TEM and Dynamic Light Scattering. The dGNP biosensor demonstrated a detection limit of 10 ng/μL of DNA (p < 0.05) for E. coli while a limit of 5 ng/μL was achieved for S. enterica. The presence of target DNA was indicated by the stability of dGNPs due to their binding to the target DNA and was confirmed with a shift in peak wavelength away from 520 nm. The biosensor differentiated E. coli from S. enterica, K. pneumoniae, and Enterobacter cloacae in pure culture, followed by successful detection from lettuce and spinach. The biosensor also successfully differentiated S. enterica from E. coli, K. pneumoniae, E. cloacae, L. monocytogenes, and B. cereus in pure culture. Melons and cucumbers contaminated with S. enterica were also successfully detected. The total assay time including gMNP extraction and dGNP detection from foods was <7 h in the presence of natural microflora and food microparticles. Finally, the application of magnetic nanoparticles towards the prevention of counterfeit foods was also tested. Using DNA as an anticounterfeiting tag offers several advantages such as remarkable information density, high level of encryption, and difficulty in replication. However, its association with consumer products has some major obstacles, including the degradation of DNA in tags and time-consuming sequence determination. To address this, magnetic nanoparticles were coated with silica to provide protection to DNA-based anticounterfeiting tags. The DNA on silica-coated magnetic nanoparticles (SCMP) was found to be stable following exposure to temperatures as high as 90 °C and to UV light. The DNA/SCMP conjugate was also found to tolerate the effect of DNase while control samples readily degraded. The dGNP biosensor developed earlier was used for the successful detection of target DNA on SCMP. The DNA-based anticounterfeiting tags were readily extracted and detected from various materials including aluminum, clingwrap, and polystyrene.
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