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Predicting the virulence of MRSA from its genome sequence
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, in...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4009613/ https://www.ncbi.nlm.nih.gov/pubmed/24717264 http://dx.doi.org/10.1101/gr.165415.113 |
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author | 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. |
author_facet | 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. |
author_sort | Laabei, Maisem |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4009613 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-40096132014-05-06 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. Genome Res Research 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. Cold Spring Harbor Laboratory Press 2014-05 /pmc/articles/PMC4009613/ /pubmed/24717264 http://dx.doi.org/10.1101/gr.165415.113 Text en © 2014 Laabei et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by/4.0/ This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0. |
spellingShingle | Research 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 |
title | Predicting the virulence of MRSA from its genome sequence |
title_full | Predicting the virulence of MRSA from its genome sequence |
title_fullStr | Predicting the virulence of MRSA from its genome sequence |
title_full_unstemmed | Predicting the virulence of MRSA from its genome sequence |
title_short | Predicting the virulence of MRSA from its genome sequence |
title_sort | predicting the virulence of mrsa from its genome sequence |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4009613/ https://www.ncbi.nlm.nih.gov/pubmed/24717264 http://dx.doi.org/10.1101/gr.165415.113 |
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