Food poisoning and infectious diseases caused by pathogenic bacteria such as Staphylococcus aureus (SA) are serious public health concerns. A method of specific, sensitive, and rapid detection of such bacteria is essential and important. This study presents a strategy that combines aptamer and antibiotic-based dual recognition units with magnetic enrichment and fluorescent detection to achieve specific and sensitive quantification of SA in authentic specimens and in the presence of much higher concentrations of other bacteria. Aptamer-coated magnetic beads (Apt-MB) were employed for specific capture of SA. Vancomycin-stabilized fluorescent gold nanoclusters (AuNCs@Van) were prepared by a simple one-step process and used for sensitive quantification of SA in the range of 32-10(8) cfu/mL with the detection limit of 16 cfu/mL via a fluorescence intensity measurement. And using this strategy, about 70 cfu/mL of SA in complex samples (containing 3 × 10(8) cfu/mL of other different contaminated bacteria) could be successfully detected. In comparison to prior studies, the developed strategy here not only simplifies the preparation procedure of the fluorescent probes (AuNCs@Van) to a great extent but also could sensitively quantify SA in the presence of much higher concentrations of other bacteria directly with good accuracy. Moreover, the aptamer and antibiotic used in this strategy are much less expensive and widely available compared to common-used antibodies, making it cost-effective. This general aptamer- and antibiotic-based dual recognition strategy, combined with magnetic enrichment and fluorescent detection of trace bacteria, shows great potential application in monitoring bacterial food contamination and infectious diseases.

The effective monitoring, identification, and quantification of pathogenic bacteria is essential for addressing serious public health issues. In this study, we present a universal and facile one-step strategy for sensitive and selective detection of pathogenic bacteria using a dual-molecular affinity-based Förster (fluorescence) resonance energy transfer (FRET) platform based on the recognition of bacterial cell walls by antibiotic and aptamer molecules, respectively. As a proof of concept, Vancomycin (Van) and a nucleic acid aptamer were employed in a model dual-recognition scheme for detecting Staphylococcus aureus (Staph. aureus). Within 30 min, by using Van-functionalized gold nanoclusters and aptamer-modified gold nanoparticles as the energy donor and acceptor, respectively, the FRET signal shows a linear variation with the concentration of Staph. aureus in the range from 20 to 10 cfu/mL with a detection limit of 10 cfu/mL. Other nontarget bacteria showed negative results, demonstrating the good specificity of the approach. When employed to assay Staph. aureus in real samples, the dual-recognition FRET strategy showed recoveries from 99.00% to the 109.75% with relative standard derivations (RSDs) less than 4%. This establishes a universal detection platform for sensitive, specific, and simple pathogenic bacteria detection, which could have great impact in the fields of food/public safety monitoring and infectious disease diagnosis.

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The simple, economic, rapid, and sensitive detection of lysozyme has an important significance for disease diagnosis since it is a potential biomarker. In this work, a new detection strategy for lysozyme was developed based on the change of the plasmon resonance light scattering (PRLS) signal of peptidoglycan stabilized gold nanoparticles (PGN-AuNPs). Peptidoglycan (PGN) was employed as a stabilizer to prepare PGN-AuNPs which have the properties of a uniform particle size, good stability, and a specific biological function. Due to the specific cleavage of lysozyme to PGN, a very simple specific and sensitive detection method for lysozyme was developed based on the PRLS signal of PGN-AuNPs after mixing with lysozyme for 1.5 h. The enhanced PRLS signals (ΔI, at 560 nm) increased linearly with increasing lysozyme in the range 5 nM to 1600 nM with the detection limit down to 2.32 nM (ΔI = 41.6397 + 0.5332c, R = 0.9961). When the PGN-AuNP based method was applied to assay lysozyme in authentic human serum samples, the recovery efficiency was 106.76-119.32% with the relative standard deviations in the range of 0.14-3.11%, showing good feasibility. The PGN-AuNP based method for lysozyme assay developed here is simple, rapid, selective, and sensitive, which is expected to provide a feasible new method for the diagnosis or prognosis of lysozyme-related diseases in a clinical setting.

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