Antibiotic resistance of bacteria can be reversed: new research

Efficient cycling of antibiotics can help doctors deal with resistant bacteria in a clinical setting

By DTE Staff
Published: Thursday 07 May 2015

Photo: NOAA

Recent findings by researchers could help the world fight the problem of rise of antibiotic-resistant bacteria. Increasing prevalence of such bacteria is a growing problem in the United States and a few other countries.

According to a latest study published in the open-access journal PLOS ONE, there is a way to return bacteria to a pre-resistant state. This can help doctors better address the problem in a clinical setting.

The research was conducted by a group of by researchers in evolutionary biology and mathematics. Biologist Miriam Barlow of the University of California, Merced, and mathematician Kristina Crona of American University tested and found a way to rewind the evolution of bacteria and verify treatment options for a family of 15 antibiotics used to fight common infections. The tested antibiotics include medicines like penicillin.

Their work could have major implications for doctors attempting to keep patient infections at bay using "antibiotic cycling", in which a handful of different antibiotics are used on a rotating basis. "Doctors don't take an ordered approach when they rotate antibiotics," Barlow said.

Dangers of antibiotic resistance

“When bacteria grow powerful enough that antibiotics no longer work, it can be a matter of life and death,” says a press release by the American University. It further states that at the Ronald Reagan UCLA Medical Center, two people recently died and seven were injured when a medical scope used in patient procedures harboured drug-resistant bacteria. According to the Centers for Disease Control and Prevention, in the US, annually, more than two million people get infections that are resistant to antibiotics and at least 23,000 people die as a result.

How the results were achieved

After creating bacteria in a lab, the researchers exposed them to 15 different antibiotics and measured their growth rates. From there, they computed the probability of mutations to return the bacteria to its harmless state using the aptly named "Time Machine" software.

Managing resistance in any drug environment is extremely difficult, because bacteria evolve so quickly, becoming highly resistant after many mutations. To find optimal cycling strategies, the researchers tested up to six drugs in rotation at a time and found optimal plans for reversing the evolution of drug-resistant bacteria.

"This shows antibiotics cycling works. As a medical application, physicians can take a more strategic approach," Crona said. "Uncovering optimal plans in antibiotics cycling presents a mathematical challenge. Mathematicians will need to create algorithms that can deliver optimal plans for a greater amount of antibiotics and bacteria."

The researchers hope to next test the treatment paths in a clinical setting, working with doctors to rotate antibiotics to maximise their efficacy.

"This work shows that there is still hope for antibiotics if we use them intelligently," Barlow said. "More research in this area and more research funding would make it possible to explore the options more comprehensively."

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