Predicting the virulence of MRSA from its genome sequence

Maisem Laabei, Mario Recker, Justine K. Rudkin, Mona Aldeljawi, Zeynep Gulay, Tim J. Sloan, Paul Williams, Jennifer L. Endres, Kenneth W Bayles, Paul D Fey, Vijaya Kumar Yajjala, Todd Widhelm, Erica Hawkins, Katie Lewis, Sara Parfett, Lucy Scowen, Sharon J. Peacock, Matthew Holden, Daniel Wilson, Timothy D. ReadJean Van Den Elsen, Nicholas K. Priest, Edward J. Feil, Laurence D. Hurst, Elisabet Josefsson, Ruth C. Massey

Research output: Contribution to journalArticle

76 Citations (Scopus)

Abstract

Microbial virulence is a complex and often multifactorial phenotype, intricately linked to a pathogen's evolutionary trajectory. Toxicity, the ability to destroy host cell membranes, and adhesion, the ability to adhere to human tissues, are the major virulence factors of many bacterial pathogens, including Staphylococcus aureus. Here, we assayed the toxicity and adhesiveness of 90 MRSA (methicillin resistant S. aureus) isolates and found that while there was remarkably little variation in adhesion, toxicity varied by over an order of magnitude between isolates, suggesting different evolutionary selection pressures acting on these two traits. We performed a genome-wide association study (GWAS) and identified a large number of loci, as well as a putative network of epistatically interacting loci, that significantly associated with toxicity. Despite this apparent complexity in toxicity regulation, a predictive model based on a set of significant single nucleotide polymorphisms (SNPs) and insertion and deletions events (indels) showed a high degree of accuracy in predicting an isolate's toxicity solely from the genetic signature at these sites.Our results thus highlight the potential of using sequence data to determine clinically relevant parameters and have further implications for understanding the microbial virulence of this opportunistic pathogen.

Original languageEnglish (US)
Pages (from-to)839-849
Number of pages11
JournalGenome Research
Volume24
Issue number5
DOIs
StatePublished - May 2014

Fingerprint

Methicillin-Resistant Staphylococcus aureus
Virulence
Genome
Adhesiveness
Genome-Wide Association Study
Virulence Factors
Cell Adhesion
Single Nucleotide Polymorphism
Staphylococcus aureus
Cell Membrane
Phenotype
Pressure

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Cite this

Laabei, M., Recker, M., Rudkin, J. K., Aldeljawi, M., Gulay, Z., Sloan, T. J., ... Massey, R. C. (2014). Predicting the virulence of MRSA from its genome sequence. Genome Research, 24(5), 839-849. https://doi.org/10.1101/gr.165415.113

Predicting the virulence of MRSA from its genome sequence. / Laabei, Maisem; Recker, Mario; Rudkin, Justine K.; Aldeljawi, Mona; Gulay, Zeynep; Sloan, Tim J.; Williams, Paul; Endres, Jennifer L.; Bayles, Kenneth W; Fey, Paul D; Yajjala, Vijaya Kumar; Widhelm, Todd; Hawkins, Erica; Lewis, Katie; Parfett, Sara; Scowen, Lucy; Peacock, Sharon J.; Holden, Matthew; Wilson, Daniel; Read, Timothy D.; Van Den Elsen, Jean; Priest, Nicholas K.; Feil, Edward J.; Hurst, Laurence D.; Josefsson, Elisabet; Massey, Ruth C.

In: Genome Research, Vol. 24, No. 5, 05.2014, p. 839-849.

Research output: Contribution to journalArticle

Laabei, M, Recker, M, Rudkin, JK, Aldeljawi, M, Gulay, Z, Sloan, TJ, Williams, P, Endres, JL, Bayles, KW, Fey, PD, Yajjala, VK, Widhelm, T, Hawkins, E, Lewis, K, Parfett, S, Scowen, L, Peacock, SJ, Holden, M, Wilson, D, Read, TD, Van Den Elsen, J, Priest, NK, Feil, EJ, Hurst, LD, Josefsson, E & Massey, RC 2014, 'Predicting the virulence of MRSA from its genome sequence', Genome Research, vol. 24, no. 5, pp. 839-849. https://doi.org/10.1101/gr.165415.113
Laabei M, Recker M, Rudkin JK, Aldeljawi M, Gulay Z, Sloan TJ et al. Predicting the virulence of MRSA from its genome sequence. Genome Research. 2014 May;24(5):839-849. https://doi.org/10.1101/gr.165415.113
Laabei, Maisem ; Recker, Mario ; Rudkin, Justine K. ; Aldeljawi, Mona ; Gulay, Zeynep ; Sloan, Tim J. ; Williams, Paul ; Endres, Jennifer L. ; Bayles, Kenneth W ; Fey, Paul D ; Yajjala, Vijaya Kumar ; Widhelm, Todd ; Hawkins, Erica ; Lewis, Katie ; Parfett, Sara ; Scowen, Lucy ; Peacock, Sharon J. ; Holden, Matthew ; Wilson, Daniel ; Read, Timothy D. ; Van Den Elsen, Jean ; Priest, Nicholas K. ; Feil, Edward J. ; Hurst, Laurence D. ; Josefsson, Elisabet ; Massey, Ruth C. / Predicting the virulence of MRSA from its genome sequence. In: Genome Research. 2014 ; Vol. 24, No. 5. pp. 839-849.
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