Whole-genome sequencing of the rare Salmonella enterica serovar Anfo isolated from food handlers.

Field investigations were conducted after a small cluster of food poisoning involving six cases was reported. While no stool samples were available from the cases for microbiological testing, Salmonella species was found to be present in the stools of food handlers with gastroenteritis symptoms. Four Salmonella isolates recovered from the food handlers were retrospectively investigated at the genome level using whole-genome sequencing (WGS). WGS showed that S. Anfo (antigenic formulae 39:y:1,2), a rarely isolated serovar, caused infections in the food handlers. S. Anfo analysed in this study contained virulence factors required for causing disease. They did not contain any antibiotic resistance genes or plasmid. The epidemiologically related isolates differed to each other by a maximum of one single nucleotide polymorphism. WGS was useful in identifying rare Salmonella serovars and it is potentially more cost-effective than traditional serotyping methods. It can also confidently group epidemiologically related isolates belonging to S. Anfo.

Retrospective genome-wide comparisons of Salmonella enterica serovar Enteritidis from suspected outbreaks in Singapore.

The number of salmonellosis cases in Singapore has increased over the years. Salmonella enterica serovar Enteritidis has always been the most predominant serovar in the last five years. The National Public Health Laboratory assisted outbreak investigations by performing multilocus variable number tandem repeat analysis (MLVA) on isolates that were collected at the time of the investigations. Isolates were defined as belonging to a particular cluster if they had identical MLVA patterns. Whilst MLVA has been instrumental in outbreak investigations, it may not be useful when outbreaks are caused by an endemic MLVA type. In this study, we analysed 67 isolates from 12 suspected outbreaks with known epidemiological links to explore the use of next-generation sequencing (NGS) for defining outbreaks. We found that NGS can confidently group isolates into their respective outbreaks. The isolates from each suspected outbreak were closely related and differed by a maximum of 3 single nucleotide polymorphisms (SNPs). They were also clearly separated from isolates that belonged to different suspected outbreaks. This study provides an important insight and further evidence on the value of NGS for routine surveillance and outbreak detection of S. Enteritidis.