Predicting the virulence of MRSA from its genome sequence

M. Laabei, M. Recker, J. K. Rudkin, M. Aldeljawi, Z. Gulay, T. J. Sloan, P. Williams, J. L. Endres, K. W. Bayles, P. D. Fey, V. K. Yajjala, T. Widhelm, E. Hawkins, K. Lewis, S. Parfett, L. Scowen, S. J. Peacock, M. Holden, D. Wilson, T. D. ReadJ. Van Den Elsen, N. K. Priest, E. J. Feil, L. D. Hurst, E. Josefsson, R. C. Massey

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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
Pages (from-to)839-849
Number of pages11
JournalGenome Research
Volume24
Issue number5
Early online date9 Apr 2014
DOIs
Publication statusPublished - 1 May 2014

Cite this

Laabei, M., Recker, M., Rudkin, J. K., Aldeljawi, M., Gulay, Z., Sloan, T. J., Williams, P., Endres, J. L., Bayles, K. W., Fey, P. D., Yajjala, V. K., Widhelm, T., Hawkins, E., Lewis, K., Parfett, S., Scowen, L., Peacock, S. J., Holden, M., Wilson, D., ... 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