Newswise — In the war on antibiotic-resistant bacteria, it’s not just the antibiotics that are making the enemy stronger but also how they are prescribed. A new study suggests that to win against antibiotic resistance, doctors can keep using the same drugs but in a very targeted manner and in combination with other health strategies.
The current broad application of antibiotics helps resistant bacterial strains propagate, but using data about bacteria’s resistance when prescribing those same drugs more precisely can help reverse the spread of resistant strains, according to researchers from the Georgia Institute of Technology, Duke University, and Harvard University who conducted the study.
One researcher cautioned that time is pressing: New antibiotic strategies need introducing before bacteria resistant to most every known antibiotic become too widespread, rendering antibiotics ineffective. It has been widely reported that this could happen by mid-century, making many more bacterial infections lethal.
“Once you get to that pan-resistant state, it’s over,” said Sam Brown, who co-led the study and is an associate professor in Georgia Tech’s School of Biological Sciences. “Timing is, unfortunately, an issue in tackling antibiotic resistance.”
The new study, which was co-led by David McAdams, a professor of business administration and economics at Duke University, delivers a mathematical model to help clinical and public health researchers devise new concrete prescription strategies and supporting measures that would center on analyzing bacterial strains to determine what drugs they are resistant to.
Some medical labs already scan human genomes for hereditary predispositions to certain medical conditions. Bacterial genomes are much easier to analyze, and though the technology is currently not standard equipment in doctors’ offices or medical labs they routinely work with, the researchers think this could change in a reasonable amount of time, which would enable the study’s approach.
The researchers published their study in the journal PLOS Biology on May 16, 2019. The work was funded by the Centers for Disease Control and Prevention, the National Institute of General Medical Sciences, the Simons Foundation, the Human Frontier Science Program, the Wenner-Gren Foundations, and the Royal Physiographic Society of Lund.
Here are some questions and answers to aid understanding of how the study’s approach could beat back antibiotic resistance.
Isn’t prescribing antibiotics the problem? How can it fight resistance?
Currently, the broad application of antibiotics to treat disease in humans and farm animals is killing off a lot of non-resistant bacteria but sparing resistant bacteria. The resistant strains can then reproduce much more and dominate bacterial communities in the host.
They get passed to other hosts and become more prevalent in the world altogether. New prescription strategies would outsmart that evolutionary scenario by exposing through genomic (or other) analysis bacteria’s resistance but also their vulnerabilities.
“Right now, there are rapid tests for the pathogen. If you’ve got strep throat, the clinic swabs the bacteria and does a rapid assay that says yes, that’s streptococcus,” Brown said. “But it won’t tell you if it’s resistant to the drug usually prescribed against it. In the future, diagnostics at the point-of-care could find out what strain you’ve got and if it’s resistant.”
Then clinicians would kill the infectors with antibiotics that the bacteria are not resistant to, thus stopping them from spreading their antibiotic resistant genes. Identifying an infector’s resistance would also help clinicians fight it effectively with antibiotics the bacteria will succumb to.
“It’s great for fighting antibiotic resistance, but it’s also good for patients because we’ll always use the correct antibiotic,” Brown said.
Are there enough effective antibiotics left to do this with?
Plenty. Antibiotics still work as a rule.
In addition, the envisioned approach could help refresh antibiotics’ effectiveness by searching out and destroying resistant bacteria.
“The idea is prevalent that we will use antibiotics up, and then they’re gone,” Brown said. “It doesn’t have to be that way. This study introduces the concept that antibiotics could become a renewable resource.”
As mentioned above, prescription strategies by themselves won’t beat resistance, right?
Correct. Unfortunately, resistance evolution is more complicated.
“A lot of bacteria with the potential to make us sick like E. coli spend most of their time just lurking peacefully in our bodies. These are bystander bacteria, and they are exposed to lots of antibiotics that we take for other things like sore throats or ear aches,” Brown said. “This frequent exposure is probably the major driver of resistance evolution.”
If this isn’t dealt with, too, the antibiotic prescription strategy alone will not win the war on resistance. That requires additional measures.
What are those additional measures?
Diagnostics need to apply to bystander bacteria, too. E. coli in the intestine or Strep pneumoniae living peacefully in nostrils would be sampled for resistance, say, during annual checkups.
“If the patient is carrying a resistant strain, you work to beat it back before it can break out,” Brown said. “There could be non-antibiotic treatments that do this like bacteria replacement.”
Bacteria replacement therapy could involve introducing new bacteria into part of the patient’s body so that it outcompetes the undesirable antibiotic-resistant bacteria and displaces it. Also, people would stay home from school and work for a few days so as not to spread the bad bacteria to other people while their immune systems and alternative therapies, such as bacteriophages or non-antibiotic drugs, do their work.
Are there any other important considerations?
“The study’s mathematical models are broad simplifications of real life,” Brown said. “They don’t take into account that pathogens spend a lot of time in other antibiotic-exposed environments such as farms. That would be a worthy topic for further research and also needs to be dealt with.”
The study also purposely leaves out polymicrobial infections, which are infections by multiple kinds of bacteria at the same time, but the study’s models could still be relevant to them.
“We expect the logic of combatting drug resistance to still hold in these more complex scenarios, but diagnostics and treatment rules will have to be honed for them specifically,” Brown said.
These researchers coauthored the study: David McAdams from Duke University, Kristofer Wollein Waldetoft from Georgia Tech, and Christine Tedijanto and Marc Lipsitch from Harvard University. The research was funded by the Centers for Disease Control and Prevention (grant OADS BAA 2016-N-17812), the National Institute of General Medical Sciences at the National Institutes of Health (grant U54GM088558), the Simons Foundation (grant 396001), the Human Frontier Science Program (grant RGP0011/2014), the Wenner-Gren Foundations, and the Royal Physiographic Society of Lund.
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OADS BAA 2016-N-17812; U54GM088558; 396001; RGP0011/2014; PLOS Biology