Researchers used a newly-developed software to predict how infectious bacteria will evolve to become drug resistant before the treatments that trigger these changes are even introduced.

The algorithm technique could show how methicillin-resistant Staphylococcus aureus (MRSA) will develop to fight new potential therapies that show promise against the deadly infection, Duke University reported. When the researchers treated bacteria with the new drug, they found two generic changes occurred that had been predicted by their algorithm.

Since antibiotics were first developed in the 1940s, bacteria have developed to resist almost every single one of them. This process is believed to be accelerated by antibiotics used in livestock for weight gain.

"My kids are now 15 and 13, and some of the antibiotics they were given when they were little aren't given anymore because they aren't as effective," said co-author Bruce Donald, a professor of computer science and biochemistry at Duke.

In the past, researchers looked at "libraries" of resistance mutations that had occurred to predict resistance and combat it, but this technique was less than efficient. To get around this, researchers developed a protein design algorithm, dubbed OSPREY, to identify DNA sequence changes in bacteria that would lead to drug resistance.

"We wanted to find out what countermoves the bacteria are likely to employ against these novel compounds. Will they be the same old mutations we've seen before, or might the bacteria do new things instead?" Donald said.

The researchers picked out four tiny mutation differences called nucleotide polymorphisms (SNPs) out of ranked possible mutations. None of the mutations they pinpointed had been seen in the past; lab experiments proved them to be correct. The researchers are now using this algorithm to predict resistance mutations in other drugs designed to fight pathogens such as E. coli and Enterococcus.

"We might even be able to coax a pathogen into developing mutations that enable it to evade one drug, but that then makes it particularly susceptible to a second drug, like a one-two punch," Donald said.

The findings were published in a recent edition of the journal Proceedings of the National Academy of Sciences.