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MRSA DNA Sequencing Predicts Patient Survival

NEW YORK (GenomeWeb) – Researchers at the Milner Center for Evolution at the University of Bath have developed a technique to accurately predict an individual's chance of survival against methicillin-resistant Staphylococcus aureus (MRSA) by sequencing the superbug's DNA.

As they explained in their study, published yesterday in Nature Microbiology, the researchers examined blood samples from 300 patients with septicemia, looking at how the different MRSA strains behaved and evaluating their lethality.

"For the first time we've been able to predict which strains are most virulent, or likely to cause disease, and the outcomes of infection," senior author and University of Bath researcher Ruth Massey said in a statement.

To investigate the role of bacterial factors in causing bacteremia-associated deaths, Massey and her team phenotyped a portion of the sequenced Staphylococcus aureus isolates from patients with bloodstream infections, representing the CC22 and CC30 strains. They identified and verified several genetic loci that affect the expression of the bacterium's cytolytic toxicity and biofilm information.

The team then coupled this information with individual risk factors for each patient — including age and presence of any other illnesses — and noted whether the patient was still living after 30 days of the infection. If the patient had passed away, the researchers noted whether MRSA contributed to the individual's death.

"We've combined information from real people with phenotypic and DNA sequence data from the bacteria causing the infection," Massey noted.

Putting the information together allowed the team to create a predictive model that would be able to prognosticate with high accuracy an individual's chances of surviving a MRSA infection.

The researchers also found that different strains of MRSA may have adopted different strategies to overcome host responses and cause varying levels of health issues. The toxicity and biofilm forming abilities for the CC22 strain played a significant role in whether affected patients survived infection, whereas they did not play a significant role in CC30 strain-related deaths.

"Our study demonstrates the use of a combined genomics and and an analytic approach to enhance our understanding of bacterial pathogenesis at the individual level, which will be an important step towards personalized medicine and infectious disease management," the authors wrote.