An evaluation of the species and subspecies of the genus Salmonella with whole genome sequence data: Proposal of type strains and epithets for novel S. enterica subspecies VII, VIII, IX, X and XI.

Species and subspecies within the Salmonella genus have been defined for public health purposes by biochemical properties; however, reference laboratories have increasingly adopted sequence-based, and especially whole genome sequence (WGS), methods for surveillance and routine identification. This leads to potential disparities in subspecies definitions, routine typing, and the ability to detect novel subspecies. A large-scale analysis of WGS data from the routine sequencing of clinical isolates was employed to define and characterise Salmonella subspecies population structure, demonstrating that the Salmonella species and subspecies were genetically distinct, including those previously identified through phylogenetic approaches, namely: S. enterica subspecies londinensis (VII), subspecies brasiliensis (VIII), subspecies hibernicus (IX) and subspecies essexiensis (X). The analysis also identified an additional novel subspecies, reptilium (XI). Further, these analyses indicated that S. enterica subspecies arizonae (IIIa) isolates were divergent from the other S. enterica subspecies, which clustered together and, on the basis of ANI analysis, subspecies IIIa was sufficiently distinct to be classified as a separate species, S. arizonae. Multiple phylogenetic and statistical approaches generated congruent results, suggesting that the proposed species and subspecies structure was sufficiently biologically robust for routine application. Biochemical analyses demonstrated that not all subspecies were distinguishable by these means and that biochemical approaches did not capture the genomic diversity of the genus. We recommend the adoption of standardised genomic definitions of species and subspecies and a genome sequence-based approach to routine typing for the identification and definition of novel subspecies.

A proposed core genome scheme for analyses of the Salmonella genus.

The salmonellae are found in a wide range of animal hosts and many food products for human consumption. Most cases of human disease are caused by S. enterica subspecies I; however as opportunistic pathogens the other subspecies (II-VI) and S. bongori are capable of causing disease. Loci that were not consistently present in all of the species and subspecies were removed from a previously proposed core genome scheme (EBcgMLSTv2.0), the removal of these 252 loci resulted in a core genus scheme (SalmcgMLSTv1.0). SalmcgMLSTv1.0 clustered isolates from the same subspecies more rapidly and more accurately grouped isolates from different subspecies when compared with EBcgMLSTv2.0. All loci within the EBcgMLSTv2.0 scheme were present in over 98% of S. enterica subspecies I isolates and should, therefore, continue to be used for subspecies I analyses, while the SalmcgMLSTv1.0 scheme is more appropriate for cross genus investigations.

Comparative analysis of core genome MLST and SNP typing within a European Salmonella serovar Enteritidis outbreak.

Multi-country outbreaks of foodborne bacterial disease present challenges in their detection, tracking, and notification. As food is increasingly distributed across borders, such outbreaks are becoming more common. This increases the need for high-resolution, accessible, and replicable isolate typing schemes. Here we evaluate a core genome multilocus typing (cgMLST) scheme for the high-resolution reproducible typing of Salmonella enterica (S. enterica) isolates, by its application to a large European outbreak of S. enterica serovar Enteritidis. This outbreak had been extensively characterised using single nucleotide polymorphism (SNP)-based approaches. The cgMLST analysis was congruent with the original SNP-based analysis, the epidemiological data, and whole genome MLST (wgMLST) analysis. Combination of the cgMLST and epidemiological data confirmed that the genetic diversity among the isolates predated the outbreak, and was likely present at the infection source. There was consequently no link between country of isolation and genetic diversity, but the cgMLST clusters were congruent with date of isolation. Furthermore, comparison with publicly available Enteritidis isolate data demonstrated that the cgMLST scheme presented is highly scalable, enabling outbreaks to be contextualised within the Salmonella genus. The cgMLST scheme is therefore shown to be a standardised and scalable typing method, which allows Salmonella outbreaks to be analysed and compared across laboratories and jurisdictions.