Within each grid, they sampled five different natural areas spaced at least 20 miles apart. Altogether, project cooperators collected 1,004 samples that resulted in 1,854 isolates.
Of those, 594 isolates were characterized using whole genome sequencing. Among the isolates were L. monocytogenes as well as 18 other Listeria species. Broken down further, 13 were existing species and five were new species.
Overall, 11.8% of the samples tested positive for L. monocytogenes and 31% were positive for Listeria species.
While some species and subtypes were distributed across much of the country, others were more regional. For example, a L. monocytogenes subgroup designated lineage III was found concentrated in the eastern United States.
"Not all Listeria is found everywhere," Wiedmann said. "We found some regional differences. In general, the likelihood of finding Listeria wasn't the same across the United States. In some areas, you were more likely to find it, which will help the industry to identify high-risk areas. It was geographical, but there were also climate factors and soil factors associated.
Sometimes knowing which of these are found in the environment and in which environment can help if you find
in a processing facility. Is it more likely to come in with the raw material or is it living in my facility?"
As part of the project, Wiedmann and his team also performed WGS of Listeria isolated from the produce chain and from preexisting collections.
They then performed a comprehensive analysis of the WGS data to identify genetic differences or epidemiological links among the different organisms.
The results were something akin to an ancestral tree showing likely recent common ancestors that could be used to help interpret WGS data.
A processing facility, for example, may have isolated closely related Listeria species nine months apart. By delving deeper into the genetics of the two samples, the facility could determine whether persistence was likely an issue and whether the two shared a common ancestor years ago.