Core genome and whole genome multi-locus sequence typing of Cronobacter isolates

Cronobacter species, especially C. sakazakii and C. malonaticus, are opportunistic pathogens that are linked to severe infections in infants with high case fatality rates. In this study, we investigated whole genome sequencing (WGS) analysis approaches, specifically 7-gene multi-locus sequence typing (7-gene MLST), core genome MLST (cgMLST), and whole genome MLST (wgMLST) to subtype Cronobacter isolates. We analyzed a comprehensive set of 743 Cronobacter isolates derived from clinical, food, and environmental sources. We also evaluated high-quality single nucleotide polymorphism (hqSNP), cgMLST, and wgMLST to cluster epidemiologically related and differentiate sporadic C. sakazakii isolates. Our results indicate that both cgMLST and wgMLST accurately identify closely related isolates and are consistent with epidemiological findings. The allele-based analyses were also comparable with hqSNP analyses, the current gold standard. Our workflow also outputs 7-gene MLST allele calls, Cronobacter sequence types, and clonal complexes, which may be useful for historic comparisons during outbreak investigations. Following the recent classification of Cronobacter infections as nationally notifiable in the United States, our findings demonstrate the efficacy of WGS-based approaches within the PulseNet framework to improve outbreak detection and response strategies for Cronobacter .

IMPORTANCE

Cronobacter species, specifically C. sakazakii and C. malonaticus , are opportunistic pathogens linked to severe infections in infants with high case fatality rates. This study highlights the critical importance of advanced molecular techniques in public health surveillance, using whole genome sequencing (WGS) methodologies such as multi-locus sequence typing (7-gene MLST), core genome MLST (cgMLST), and whole genome MLST (wgMLST). The validation of these WGS-based approaches within the PulseNet framework is timely, especially following the recent classification of Cronobacter infections as nationally notifiable in the United States. WGS methods not only enhance outbreak detection but can also inform public health guidance aimed at preventing infections and reducing mortality in vulnerable populations, especially infants. Our research supports implementation of cgMLST as a standardized approach for routine PulseNet surveillance of Cronobacter , with wgMLST and hqSNP analyses providing additional discriminatory power for outbreak investigations and high resolution phylogenetic analysis.