A team of University of Oxford
researchers has developed easy-to-use software that's able to quickly
predict which antibiotics will work for a patient by analyzing DNA
from their infection. The program is currently being trialed in three
Just like every other species on the planet, bacteria are constantly evolving. As time goes on, some of the changes that occur in their DNA makes them resistant to drugs that we use to treat them. Treatment-resistant bacteria are more likely to survive and pass on their traits to other bacteria, creating an escalating problem, and one that could one day pose a huge risk to global health.
The best way to tackle the problem is to treat patients with the right antibiotic as quickly as possible, but that's not always easy to achieve. Doctors first have to identify the bacteria that's infecting the patient, then find out whether it's resistant to certain drugs. This is usually done by applying different antibiotics to the bacteria in a petri dish and watching to see which drug kills it off – a process that can take days, weeks or even months in certain cases.
So, how can we speed up the process? Well, scientists think that it's possible to identify bacterias' drug resistance by searching their DNA for particular mutations that are known to cause drug immunity. There are problems here too, however, with typical methods requiring a lot of computing power and the presence of an expert.
The University of Oxford researchers decided to tackle the issue head-on, developing a computer program known as Mykrobe Predictor, that aims to make the entire process much more straightforward. It allows for automated genome processing, checking bacteria DNA sequences against previously-analyzed strains, to quickly search for the mutations that cause resistance. Once the analysis is complete, the information is presented in an easy-to-understand manner that negates the need to have an expert on hand.
The results were impressive, with the Mykrobe detecting resistance to five first-line antibiotics in more than 99 percent of Staphylococcus aureus cases – equaling the performance of traditional methods. When testing TB samples, the software was able to detect resistance in 82.6 percent of cases between five and 16 weeks quicker than conventional testing.
Unlike existing methods, the new software can be updated as new resistance mutations are discovered, meaning it'll keep getting better as time goes on. It's also able to identify infections even when a there are a mixture of drug-susceptible and drug-resistant bacteria present in a patient's system.
"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," said paper lead author Dr. Zamin Iqbal.
The software is currently being trialed in hospitals in Leeds, Brighton and Oxford, while a paper discussing it was recently published in the journal Nature Communications.
For a look at the program, you can check out the video below.
Source: University of Oxford
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