Coagulase-positive Staphylococcus aureus is a foodborne pathogen considered one of the causes of food-related disease outbreaks. Like S. aureus, Staphylococcus capitis, Staphylococcus caprae, and S. epidermidis are opportunistic pathogens causing clinical infections and food contamination. The objective of our study was to develop a rapid, accurate, and monitoring technique to detect four Staphylococcus species in food. Four novel molecular targets (GntR family transcriptional regulator for S. aureus, phosphomannomutase for S. epidermidis, FAD-dependent urate hydroxylase for S. capitis, and Gram-positive signal peptide protein for S. caprae) were mined based on pan-genome analysis. Primers targeting molecular target genes showed 100% specificity for 100 non-target reference strains. The detection limit in pure cultures and artificially contaminated food samples was 10² colony-forming unit/mL for S. aureus, S. capitis, S. caprae, and S. epidermidis. Moreover, real-time polymerase chain reaction successfully detected strains isolated from various food matrices. Thus, our method allows an accurate and rapid monitoring of Staphylococcus species and may help control staphylococcal contamination of food.

Rapid detection of Salmonella serovars is important for the effective control and monitoring of food industries. In this study, we evaluate the application of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry for the rapid detection of three serovars, Enteritidis, Typhimurium, and Thompson, that are epidemiologically important in Korea. All strains were identified at the genus level, with a mean score of 2.319 using the BioTyper database, and their protein patterns were confirmed to be similar by principal component analysis and main spectrum profile dendrograms. Specific peaks for the three serovars were identified by analyzing 65 reference strains representing 56 different serovars. Specific mass peaks at 3018 ± 1 and 6037 ± 1, 7184 ± 1, and 4925 ± 1 m/z were uniquely found in the reference strains of serovars Enteritidis, Typhimurium, and Thompson, respectively, and they showed that the three serovars can be differentiated from each other and 53 other serovars. We verified the reproducibility of these mass peaks in 132 isolates, and serovar classification was achieved with 100% accuracy when compared with conventional serotyping through antisera agglutination. Our method can rapidly detect a large number of strains; hence, it will be useful for the high-throughput screening of Salmonella serovars.