Public health and regulatory agencies worldwide sequence all Listeria monocytogenes (Lm) isolates obtained as part of routine surveillance and outbreak investigations. Many of these entities submit the sequences to the NCBI Pathogen Detection (NCBI PD) database, which groups the Lm isolates into SNP clusters based on a pairwise SNP difference threshold of 50 SNPs. Our goal was to assess if isolates with metadata suggesting different sources or locations could show evidence for close genetic relatedness indicating a recent common ancestor and a possible unknown common source. We compared the WGS data of 249 Lm isolates sequenced here, which have detailed metadata, to WGS data of non-clinical isolates on NCBI PD. The 249 Lm isolates originated from natural environments (n = 91) as well as smoked fish (n = 62), dairy (n = 56), and deli-meat (n = 40) operations in the US. Using a combination of subtyping by cgMLST and hqSNP, we observed 5 SNP clusters where study isolates and SNP cluster isolates seemed to be closely related and either (i) share the same geolocation, but show different source types (1 SNP cluster); (ii) share the same source type, but show different geolocations (2 SNP clusters); or (iii) shared neither source type nor geolocation (2 SNP clusters). For one of the two clusters under (iii), there however was no strong bootstrap support for a common ancestor shared between the study isolates and SNP cluster isolates, indicating the value of in-depth evolutionary analyses when WGS data are used for traceback and epidemiological investigations. Overall, our results demonstrate that some Lm subtypes may be associated with specific locations or commodities; these associations can help in investigations involving multi-ingredient foods such as sandwiches. However, at least some Lm subtypes can be widespread geographically and be associated with different sources, which may present a challenge to traceback investigations involving these subtypes.

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