Rapid Real-Time Polymerase Chain Reaction for Salmonella Serotyping Based on Novel Unique Gene Markers by Pangenome Analysis

Abstract

An accurate diagnostic method for Salmonella serovars is fundamental to preventing the spread of associated diseases. A diagnostic polymerase chain reaction (PCR)-based method has proven to be an effective tool for detecting pathogenic bacteria. However, the gene markers currently used in real-time PCR to detect Salmonella serovars have low specificity and are developed for only a few serovars. Therefore, in this study, we explored the novel unique gene markers for 60 serovars that share similar antigenic formulas and show high prevalence using pangenome analysis and developed a real-time PCR to detect them. Before exploring gene markers, the 535 Salmonella genomes were evaluated, and some genomes had serovars different from the designated serovar information. Based on these analyses, serovar-specific gene markers were explored. These markers were identified as genes present in all strains of target serovar genomes but absent in strains of other serovar genomes. Serovar-specific primer pairs were designed from the gene markers, and a real-time PCR method that can distinguish between 60 of the most common Salmonella serovars in a single 96-well plate assay was developed. As a result, real-time PCR showed 100% specificity for 199 Salmonella and 29 non-Salmonella strains. Subsequently, the method developed was applied successfully to both strains with identified serovars and an unknown strain, demonstrating that real-time PCR can accurately detect serovars of strains compared with traditional serotyping methods, such as antisera agglutination. Therefore, our method enables rapid and economical Salmonella serotyping compared with the traditional serotyping method.

Keywords: Salmonella; detection; gene marker; pangenome analysis; real-time PCR; serotyping.

FIGURE 1

Pangenome distribution of the 535 Salmonella genomes. The red letters in the circular dendrogram indicates the strains predicted by the incorrect serovars. The orange, purple, blue, green, and yellow backgrounds represent Typhimurium, I 4,[5],12:i:-, Enteritidis, Agona, and Tennessee, respectively.

FIGURE 2

Evaluation of specificity unique gene markers. The figure shows the presence or absence of unique gene markers in 535 genomes. The number of analyzed genomes for each serovar is shown in the green bar, and the number of genomes with gene marker corresponding to that serovar is shown in the red bar.

FIGURE 3

The specificity of serovar-specific primers. (A) Specificity of Bareilly primer pair, amplification curve: Bareilly MFDS 1007637; (B) Specificity of Enteritidis primer pair, amplification curve: Enteritidis MFDS 1010897; (C) I 4,[5],12:i:- primer pair, amplification curve: MFDS 1004858; (D) Specificity of Montevideo specific primer pair, amplification curve: CCARM 8189; (E) Specificity of Typhi primer pair, amplification curve: ATCC 33459; (F) Specificity of Typhimurium primer pair, amplification curve: ATCC 19585. ΔRn value means Rn (fluorescent signal from SYBR Green) value of an experimental response minus the Rn value of the baseline signal.

FIGURE 4

Real-time PCR standard curve. (A) Bareilly MFDS 1007637 standard curve (y = –3.58 x + 29.779, R² = 0.998); (B) Enteritidis MFDS 1010897 standard curve (y = –3.39 x + 19.106, R² = 0.999); (C) I 4,[5],12:i:- MFDS 1004858 standard curve (y = –3.66 x + 18.591, R² = 0.997); (D) Montevideo CCARM 8189 standard curve (y = –3.45 x + 19.009, R² = 0.999); (E) Typhi ATCC 33459 standard curve (y = –3.67 x + 21.768, R² = 0.999); (F) Typhimurium ATCC 19585 standard curve (y = –3.61 x + 19.372, R² = 0.999).