April 9, 2014 -The spread of the antibiotic-resistant pathogen MRSA (methicillin-resistant Staphylococcus aureus) remains a concerning public health problem, especially among doctors trying to determine appropriate treatment options for infected patients. Bacterial pathogens, such as MRSA, cause disease in part due to toxicity, or the bacterium's ability to damage a host's tissue. In a study published online today in Genome Research, researchers used the genome sequence of MRSA to predict which isolates were highly toxic, thus potentially personalizing the treatment of individual MRSA infections.
To study MRSA's toxicity, "the standard approach has always been to focus on a single or small number of genes and proteins," said lead author Ruth Massey, from the University of Bath. However, this has not always been successful because toxicity is a complex trait encoded by many genetic loci.
In this new study, the authors used whole genome sequences from 90 MRSA isolates to identify over 100 genetic loci associated with toxicity. Despite belonging to the same ST239 clone, the isolates varied greatly in toxicity.
Importantly, the highly toxic isolates shared a common genetic signature. By looking for this signature in the MRSA genome, the researchers were able to predict which isolates were the most toxic and thus more likely to cause severe disease when used to infect mice.
"As the cost and speed of genome sequencing decreases, it is becoming increasingly feasible to sequence the genome of an infecting organism," said Massey. In a clinical setting, sequencing may be useful for deciding the course of MRSA treatment. For example, a clinician may treat a highly toxic infection more aggressively, including prescribing certain antibiotics known to reduce toxin expression. The patient also may be monitored more closely for complications and isolated from others to help control the spread of infection.
Although many novel genetic loci involved in MRSA toxicity were identified in this study, it remains to be determined how each influences disease. In addition to examining genomes of other MRSA strains, such as the particularly antibiotic-resistant USA300 strain, the authors are working to apply their methodology to other bacterial pathogens, such as Streptococcus pneumonia, a leading cause of deaths in infants and children under the age of five.
Scientists from University of Bath, University of Exeter, Dokuz Eylul University, University of Nottingham, University of Nebraska Medical Center, University of Cambridge, Wellcome Trust Sanger Institute, Emory University, and University of Gothenburg contributed to this study.
This work was supported by funding from the European Commission, the BBSRC, and a Royal Society University Research Fellowship.
The authors are available for more information by contacting:
Vicky Just, University of Bath Press Office (email@example.com, +44 (0)1225 386 883 or +44 (0)7966 341 357)
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Prior to the embargo date, interested reporters may obtain copies of the manuscript via email from Laura DeMare, Assistant Editor, Genome Research (email@example.com, +1-516-422-4012).
About the article:
The manuscript will be published online ahead of print on 9 April 2014. Its full citation is as follows: Laabei M, Recker M, Rudkin JK, Aldeljawi M, Gulay Z, Sloan TJ, Williams P, Endres JL, Bayles KW, Fey PD, Kumar Yajjala V, 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. Predicting the virulence of MRSA from its genome sequence. Genome Res doi: 10.1101/gr.165415.113
About Genome Research:
Launched in 1995, Genome Research is an international, continuously published, peer-reviewed journal that focuses on research that provides novel insights into the genome biology of all organisms, including advances in genomic medicine. Among the topics considered by the journal are genome structure and function, comparative genomics, molecular evolution, genome-scale quantitative and population genetics, proteomics, epigenomics, and systems biology. The journal also features exciting gene discoveries and reports of cutting-edge computational biology and high-throughput methodologies.
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