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Yersinia pestis: New Evidence for an Old Infection

Overview of attention for article published in PLOS ONE, November 2012
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Title
Yersinia pestis: New Evidence for an Old Infection
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0049803
Pubmed ID
Authors

Kirsten I. Bos, Philip Stevens, Kay Nieselt, Hendrik N. Poinar, Sharon N. DeWitte, Johannes Krause

Abstract

The successful reconstruction of an ancient bacterial genome from archaeological material presents an important methodological advancement for infectious disease research. The reliability of evolutionary histories inferred by the incorporation of ancient data, however, are highly contingent upon the level of genetic diversity represented in modern genomic sequences that are publicly accessible, and the paucity of available complete genomes restricts the level of phylogenetic resolution that can be obtained. Here we add to our original analysis of the Yersinia pestis strain implicated in the Black Death by consolidating our dataset for 18 modern genomes with single nucleotide polymorphism (SNP) data for an additional 289 strains at over 600 positions. The inclusion of this additional data reveals a cluster of Y. pestis strains that diverge at a time significantly in advance of the Black Death, with divergence dates roughly coincident with the Plague of Justinian (6(th) to 8(th) century AD). In addition, the analysis reveals further clues regarding potential radiation events that occurred immediately preceding the Black Death, and the legacy it may have left in modern Y. pestis populations. This work reiterates the need for more publicly available complete genomes, both modern and ancient, to achieve an accurate understanding of the history of this bacterium.

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Geographical breakdown

Country Count As %
United States 3 3%
Germany 2 2%
Norway 1 <1%
Panama 1 <1%
France 1 <1%
United Kingdom 1 <1%
Sweden 1 <1%
Denmark 1 <1%
Guatemala 1 <1%
Other 0 0%
Unknown 89 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 24%
Researcher 21 21%
Student > Bachelor 15 15%
Student > Master 8 8%
Student > Doctoral Student 7 7%
Other 15 15%
Unknown 11 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 47%
Biochemistry, Genetics and Molecular Biology 13 13%
Social Sciences 11 11%
Medicine and Dentistry 8 8%
Immunology and Microbiology 2 2%
Other 8 8%
Unknown 12 12%