April 10, 2014
Predicting The Severity Of MRSA
April Flowers for redOrbit.com - Your Universe Online
A new technique to predict the toxicity of a MRSA (methicillin-resistant Staphylococcus aureus) infection from its DNA sequence has been developed by a team of researchers led by the Universities of Bath and Exeter.
Dr. Ruth Massey from the University of Bath's Department of Biology & Biochemistry said, "the standard approach has always been to focus on a single or small number of genes and proteins." This method has had limited success because toxicity is a complex trait encoded by many genetic loci.
The research team studied the whole genome sequences from 91 MRSA isolates. This allowed them to identify 125 genetic mutations that contributed to an individual isolate being either high-or low-toxicity. One surprising find was that isolates from the same clone varied hugely in toxicity.
All of the highly toxic strains shared a common genetic signature that, once recognized, allowed the researchers to predict which isolates were the most toxic and therefore would cause severe disease.
Massey explained, "In the future as the cost and speed of genome sequencing decreases, it will become feasible to take a swab from a patient, sequence the genome of the bacterium causing the infection, and then use this to predict the toxicity of the infection."
"Clinicians will then be able to tailor the treatment to the specific infection – this technique can tell them which combination of antibiotics will be most effective, or tell them which drugs to administer to dampen the toxicity of the infection," she continued. "The standard approach in studying MRSA's toxicity has always been to focus on a single or small number of genes and proteins. However, this has not always been successful because toxicity is a complex trait encoded by many genetic loci. By looking at whole genome sequences we've been able to identify a number of new loci involved in toxicity.
"This work represents a step change in how genome sequencing can help us diagnose and control infections. It has also increased our understanding of how this pathogen causes severe infections by identifying novel regulators of toxicity."
The findings could provide critical insight into the virulence of MRSA, according to Dr. Mario Recker, Associate Professor in Applied Mathematics at the University of Exeter. He said, "We know that many bacterial pathogens, such as MRSA, are so virulent in part because of their ability to damage a host's tissue."
"By using whole genome sequences we have been able to predict which would be most toxic, and so therefore would be more likely to cause severe disease. Having identified these novel genetic loci will also shed more light upon the complex machinery regulating bacterial virulence."
The team is continuing their research by applying their methodology to other bacterial pathogens such as Streptococcus pneumonia, a leading cause of deaths in infants and children under the age of five.