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Complete Genome Sequence of a Pantón-Valentine Leukocidin-Negative Community-Associated Methicillin-Resistant Staphylococcus aureus Strain of Sequence type 72 from Korea

Overview of attention for article published in PLOS ONE, August 2013
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Title
Complete Genome Sequence of a Pantón-Valentine Leukocidin-Negative Community-Associated Methicillin-Resistant Staphylococcus aureus Strain of Sequence type 72 from Korea
Published in
PLOS ONE, August 2013
DOI 10.1371/journal.pone.0072803
Pubmed ID
Authors

Yan Chen, Som S. Chatterjee, Stephen F. Porcella, Yun-Song Yu, Michael Otto

Abstract

In the past decade, community-associated (CA-) infections with methicillin-resistant Staphylococcus aureus (MRSA) have emerged throughout the world. Different CA-MRSA strains dominate in different geographical locations. Many CA-MRSA lineages contain genes coding for the Pantón-Valentine leukocidin. However, the role of this leukotoxin in CA-MRSA pathogenesis is still controversial. The genome sequences of two key PVL-positive CA-MRSA strains (USA300, USA400) have been reported, but we lack information on the more recently found PVL-negative CA-MRSA strains. One such strain is the PVL-negative ST72, the main cause of CA-MRSA infections in Korea. Here, we report the entire genome sequence of CA-MRSA ST72 and analyze its gene content with a focus on virulence factors. Our results show that this strain does not have considerable differences in virulence factor content compared to other CA-MRSA strains (USA300, USA400), indicating that other toxins do not substitute for the lack of PVL in ST72. This finding is in accordance with the notion that differential expression of widespread virulence determinants, rather than the acquisition of additional virulence factors on mobile genetic elements, such as PVL, is responsible for the increased virulence of CA- compared to hospital-associated MRSA.

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Geographical breakdown

Country Count As %
Netherlands 1 3%
India 1 3%
Unknown 34 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 28%
Student > Ph. D. Student 9 25%
Student > Bachelor 5 14%
Student > Master 3 8%
Student > Doctoral Student 2 6%
Other 4 11%
Unknown 3 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 44%
Biochemistry, Genetics and Molecular Biology 5 14%
Medicine and Dentistry 5 14%
Environmental Science 2 6%
Computer Science 1 3%
Other 3 8%
Unknown 4 11%