PLoS ONE (Jan 2014)

Insights to genetic characterization tools for epidemiological tracking of Francisella tularensis in Sweden.

  • Tara Wahab,
  • Dawn N Birdsell,
  • Marika Hjertqvist,
  • Cedar L Mitchell,
  • David M Wagner,
  • Paul S Keim,
  • Ingela Hedenström,
  • Sven Löfdahl

DOI
https://doi.org/10.1371/journal.pone.0112167
Journal volume & issue
Vol. 9, no. 11
p. e112167

Abstract

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Tularaemia, caused by the bacterium Francisella tularensis, is endemic in Sweden and is poorly understood. The aim of this study was to evaluate the effectiveness of three different genetic typing systems to link a genetic type to the source and place of tularemia infection in Sweden. Canonical single nucleotide polymorphisms (canSNPs), MLVA including five variable number of tandem repeat loci and PmeI-PFGE were tested on 127 F. tularensis positive specimens collected from Swedish case-patients. All three typing methods identified two major genetic groups with near-perfect agreement. Higher genetic resolution was obtained with canSNP and MLVA compared to PFGE; F. tularensis samples were first assigned into ten phylogroups based on canSNPs followed by 33 unique MLVA types. Phylogroups were geographically analysed to reveal complex phylogeographic patterns in Sweden. The extensive phylogenetic diversity found within individual counties posed a challenge to linking specific genetic types with specific geographic locations. Despite this, a single phylogroup (B.22), defined by a SNP marker specific to a lone Swedish sequenced strain, did link genetic type with a likely geographic place. This result suggests that SNP markers, highly specific to a particular reference genome, may be found most frequently among samples recovered from the same location where the reference genome originated. This insight compels us to consider whole-genome sequencing (WGS) as the appropriate tool for effectively linking specific genetic type to geography. Comparing the WGS of an unknown sample to WGS databases of archived Swedish strains maximizes the likelihood of revealing those rare geographically informative SNPs.