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Scientists Reverse Bacterial Resistance to Antibiotics

New research mixes antibiotic cycling and mathematics

The rise of antibiotic-resistant bacteria is a growing problem throughout the world. New findings by researchers in evolutionary biology and mathematics could help physicians to better address the problem in a clinical setting.

Biologist Miriam Barlow of the University of California, Merced, and mathematician Kristina Crona of American University have found a way to return bacteria to a pre-resistant state. In research published online in PLoS One, they show how to rewind the evolution of bacteria, and they verify treatment options for a family of 15 antibiotics used to fight common infections, including penicillin.

Their work could have major implications for physicians attempting to keep 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. “The doctors would benefit from a system of rotation that is proven. Our goal was to find a precise, ordered schedule of antibiotics that doctors could rely on and know that in the end, resistance will be reversed, and an antibiotic will work.”

When bacteria grow strong enough that antibiotics are no longer effective, it can be a matter of life and death. Recently, at the Ronald Reagan UCLA Medical Center, two patients died and seven were injured when a medical scope used in patient procedures harbored drug-resistant bacteria. In the U.S., more than 2 million people develop antibiotic-resistant infections each year, and at least 23,000 people die as a result, according to the Centers for Disease Control and Prevention.

Resistance to antibiotics is a natural part of the evolution of bacteria and is unavoidable given the many types of bacteria and the susceptibility of the human host, Barlow said. To compensate for bacterial evolution, a physician fighting infections in an intensive care unit may reduce, rotate, or discontinue different antibiotics to get them to be effective in the short term.

The researchers have uncovered how to reverse bacterial resistance in the drug environment by combining lab work with mathematics and computer technology.

“We have learned so much about the human genome as well as the sequencing of bacteria,” Crona said. “Mathematics helps one to draw interpretations, find patterns, and give insight into medical applications.”

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 their harmless state using the aptly named Time Machine software.

Managing resistance in any drug environment is difficult because bacteria evolve 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 antibiotic cycling works. As a medical application, physicians can take a more strategic approach,” Crona said. “Uncovering optimal plans in antibiotic 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 plan to test the treatment paths in a clinical setting, working with doctors to rotate antibiotics to maximize their efficacy.

“This work shows that there is still hope for antibiotics if we use them intelligently,” Barlow said.

Sources: Medical Xpress; May 6, 2015; and PLoS One; May 6, 2015.

 

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