Computer program tackles antibiotic resistance

dna computer

A computer program capable of analysing bacterial DNA from patients’ bodies can help choose correct treatment and predict ineffective antibiotics.

Currently trialled at three UK hospitals, the program speeds up diagnoses of antibiotic-resistant infections, which traditionally takes days or even months as bacteria from samples need to be grown in laboratories and tested against every type of antibiotic.

Dubbed the Mykrobe Predictor, the software, developed by a team from the Wellcome Trust Centre for Human Genetics at the University of Oxford, can run on any laptop and tablet.

It can analyse the entire genetic code of a bacterium in less than three minutes, once a bacterial sample has been cultured and its DNA sequenced.

“One of the barriers to making whole genome sequencing a routine part of NHS care is the need for powerful computers and expertise to interpret the masses of complex data, said Zamin Iqbal, senior author of a paper published in the latest issue of Nature Communications.

“Our software manages data quickly and presents the results to doctors and nurses in ways that are easy to understand, so they can instinctively use them to make better treatment decisions.”

In the article in Nature Communications, the researchers described how they used the program to reliably detect antibiotic resistance in more than 4,500 patient samples of the Staphylococcus aureus and tuberculosis infection.

Understanding staphylococcus aureus is particularly important as it can cause lethal MRSA (Methicillin-resistant Staphylococcus aureus) infections for which virtually no cure exists.

Using the software enables doctors to better target the prescription of antibiotics to prevent development of further resistant bacterial strains. Drug resistance, caused by the quick evolution of bacteria, can only be prevented by treating patients promptly and with the correct type of antibiotics. The current procedures, however, are frequently too lengthy as in some cases, such as tuberculosis, it takes weeks to grow the sample.

As a result, infections are springing up that don’t react to any existing antibiotics.

“Drug-resistant infections pose a major threat to global public health. Antibiotics that were once lifesavers are in danger of becoming worthless, and within our lifetime we could see minor infections returning as a major public health concern, explained Stephen Caddick, director of innovations at health research charity Wellcome Trust.

“We urgently need new diagnostic strategies that allow us to better target antibiotic use, and thereby safeguard the effectiveness of our existing antibiotics, and any new drugs that are developed in future.”

The new program identifies mutations in the DNA sequence of the bacteria that are known to cause resistance.

The software uses automated genome analysis to cross-check the bacterium’s DNA sequence with previous strains to look for resistance-causing mutations and presents information about the bug in an easy-to-understand format.

During the trials, the software successfully detected resistance to the five first-line antibiotics in more than 99 per cent of Staphylococcus aureus cases, matching the performance of traditional drug sensitivity testing.

In the case of Tuberculosis, the software was able to identify drug-resistant strains five to 16 weeks faster than tradition lab testing, while successfully detecting almost 83 per cent of resistant infections.

“Genome sequencing has the potential to transform the way we diagnose and treat bacterial infections in NHS hospitals, but one of the main challenges is developing the right tools to enable us to unlock this information quickly and affordably, said Professor Derrick Crook, a consultant microbiologist at the John Radcliffe Hospital, Oxford, and director of the National Infection Service, Public Health England.

“Our ultimate goal is to be able to provide complete information on a pathogen within 24 hours of culture, linking this information to a national surveillance database to enable more timely and better targeted patient treatment.”

The software is being evaluated in hospitals in Oxford, Brighton and Leeds

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