Whole Genome Sequencing data has enhanced Salmonella Enteritidis investigations in Minnesota and become an integral part of the surveillance process, according to a study.

Clusters of Salmonella Enteritidis cases were identified by the Minnesota Department of Health Public Health Laboratory with pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) single nucleotide polymorphism (SNP) analysis from January 2015 through December 2017.

Researchers said the new study in the journal Epidemiology and Infection demonstrated WGS is a more discriminatory and useful subtyping method than PFGE for detection and investigation of Salmonella Enteritidis outbreaks.

From January 2015 to December 2017, the Minnesota Department of Health Public Health Lab received or recovered 660 Salmonella Enteritidis clinical isolates from residents.

Receiving actionable results
Turnaround times for PFGE and WGS were calculated for 624 samples. The median time for getting PFGE cluster results from isolate recovery was one day with a range from one to seven days.

Time for WGS cluster results was 12 days with a range from four to 57. It was nine days for isolate sequencing and three for SNP analysis and cluster determination.

Researchers said national transition of Salmonella outbreak surveillance to WGS has allowed more resources toward it, which has increased timeliness in Minnesota since the study timeframe.

“Turnaround times will not be fully optimized until the volume of samples is consistently high enough to sequence isolates immediately upon submission, or until the adoption of a sequencing platform capable of handling smaller numbers of samples with reduced cost detriment,” according to the researchers.

PFGE clusters
During 2015 to 2017, there were 39 Salmonella Enteritidis PFGE clusters with 538 isolates. The median number of cases in each cluster was four with a range of two to 99 and the median duration of each was 56 days ranging from two to 1,043 days.

A confirmed source was found in 18 clusters including eight foodborne outbreaks, eight international travel-associated outbreaks in which multiple cases stayed at the same resort, and two associated with live poultry contact. For the 10 foodborne and poultry contact outbreaks, a median of 46 percent of cases in the clusters reported the outbreak vehicle or exposure of interest.

The probability of identifying a confirmed source for a PFGE cluster rose as the number of cases increased. Eighty-eight percent of clusters of five or more cases had a confirmed source compared to no clusters of four cases, 50 percent of those with three cases, and 7 percent with two cases.

WGS results
In 2015 to 2017, there were 92 Salmonella Enteritidis WGS clusters comprising 356 isolates. The median number of cases in each cluster was two with a range of two to 18. The median duration of each cluster was 29 days ranging from zero to 247 days.

A confirmed source was identified in 29 clusters including 15 international travel-associated outbreaks wher multiple cases reported staying at the same resort, nine foodborne outbreaks, and five linked to live poultry contact.

Probability of identifying a confirmed source for a WGS cluster also increased as the number of cluster cases went up. Eighty-nine percent of WGS clusters of five or more patients had a confirmed source compared to 30 percent of those with four cases, 20 percent of clusters of three cases, and 13 percent of clusters of two cases.

The 48 percent of WGS clusters that had a confirmed or probable source identified was lower than for PFGE clusters at 59 percent. However, WGS detected more than twice as many clusters, and this translated into 44 WGS clusters that had a confirmed or probable source identified compared to 23 for PFGE. The benefit of WGS in solving additional outbreaks was seen mostly with clusters of less than five cases, according to the study.

WGS reduced the number of cases included in clusters by 34 percent, and clusters were smaller on average. Median duration of WGS clusters was shorter than PFGE ones, decreasing the likelihood of drawn-out investigations with no source ever identified.

“The greatest value of WGS was that it identified smaller groups of related outbreak cases within a background sea of unrelated sporadic cases that had the same clonal PFGE pattern combinations, and that coincidentally clustered in time because they occurred so commonly,” said researchers.