Due to a highly homogeneous genetic composition, the subtyping of Salmonella enterica serovar Enteritidis strains to an epidemiologically relevant level remains intangible for pulsed-field gel electrophoresis (PFGE). We reported previously on a highly discriminatory PFGE-based subtyping scheme for S. enterica serovar Enteritidis that relies on a single combined cluster analysis of multiple restriction enzymes. However, the ability of a subtyping method to correctly infer genetic relatedness among outbreak strains is also essential for effective molecular epidemiological traceback. In this study, genetic and phylogenetic analyses were performed to assess whether concatenated enzyme methods can cluster closely related salmonellae into epidemiologically relevant hierarchies. PFGE profiles were generated by use of six restriction enzymes (XbaI, BlnI, SpeI, SfiI, PacI, and NotI) for 74 strains each of S. enterica serovar Enteritidis and S. enterica serovar Typhimurium. Correlation analysis of Dice similarity coefficients for all pairwise strain comparisons underscored the importance of combining multiple enzymes for the accurate assignment of genetic relatedness among Salmonella strains. The mean correlation increased from 81% and 41% for single-enzyme PFGE up to 99% and 96% for five-enzyme combined PFGE for S. enterica serovar Enteritidis and S. enterica serovar Typhimurium strains, respectively. Data regressions approached 100% correlation among Dice similarities for S. enterica serovar Enteritidis and S. enterica serovar Typhimurium strains when a minimum of six enzymes were concatenated. Phylogenetic congruence measures singled out XbaI, BlnI, SfiI, and PacI as most concordant for S. enterica serovar Enteritidis, while XbaI, BlnI, and SpeI were most concordant among S. enterica serovar Typhimurium strains. Together, these data indicate that PFGE coupled with sufficient enzyme numbers and combinations is capable of discerning accurate genetic relationships among Salmonella serovars comprising highly homogeneous strain complexes.
All Science Journal Classification (ASJC) codes
- Microbiology (medical)