A team of UCLA biologists has been exploring possible ways to defeat life-threatening antibiotic-resistant bacteria.

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Two combinations of drugs that are unexpectedly successful in reducing the growth of E. coli bacteria have been identified by researchers.
Their latest work, which is published online and appears in the current print edition of the Journal of the Royal Society Interface, extends their understanding of that phenomenon and identifies two combinations of drugs that are unexpectedly successful in reducing the growth of E. coli bacteria.
A key to the study is an understanding that using two, three or more antibiotics in combination does not necessarily make the drugs more effective in combating bacteria - in fact, in many cases, their effectiveness is actually reduced when drugs are used together - so the combinations must be chosen carefully and systematically. The new paper also provides the first detailed explanation of how the scientists created a mathematical formula that can help predict which combinations of drugs will be most effective.
The scientists tested every possible combination of a group of six antibiotics, including 20 different combinations of three antibiotics at a time.
Among the three-drug combinations, the researchers found two that were noticeably more effective than they had expected. Those groupings used treatments from three different classes of antibiotics, so the combinations used a wide range of mechanisms to fight the bacteria. (Five of the three-drug combinations were less effective than they expected, and the other 13 groupings performed as they predicted.)
The researchers have identified cases where the effects of the interactions are larger than the sum of the parts.
For the current study, the scientists evaluated the drug combinations on plates in a lab. Beppler said a next step will be to test the most effective combinations in mice.
In addition to reporting on how well various combinations of antibiotics worked, the paper also presents a mathematical formula the biologists developed for analyzing how three or more factors interact and of explaining complex, unexpected interactions. The framework would be useful for solving other questions in the sciences and social sciences in which researchers analyze how three or more components might interact - for example, how climate is affected by the interplay among temperature, rainfall, humidity and ocean acidity.
The biologists are gaining a deep understanding of why certain groups of three antibiotics interact well together, and others don't, said Van Savage, a co-author of the paper and a UCLA professor of ecology and evolutionary biology and of biomathematics.
Beppler said more research is needed to determine which combinations are optimal for specific diseases and for specific parts of the body. And the researchers now are using the mathematical formula to test combinations of four antibiotics.
Source-Eurekalert
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