Potent pathogens

But they may have some insight, gained through their research, that could help turn that around.

The team demonstrated that at least 25 percent of antibiotic-resistant pathogenic bacteria in clinical settings can spread their resistance directly to other bacteria, and the use of antibiotics does not meaningfully affect the rate at which the genes responsible for resistance are swapped between bacteria. They used an automated high-throughput method of measuring the rate at which bacteria exchange the packages of DNA that provide resistance in an attempt to determine what variables affect transfer rates to help doctors slow or reverse the spread of resistance in certain human pathogens. The research was supported by the National Institutes of Health, the Army Research Office and the David and Lucile Packard Foundation.

According to Lingchong You, a professor of biomedical engineering at Duke, “Our previous research showed that antibiotics do not affect the rate at which bacteria spread their resistance directly to their community in laboratory strains of E.coli, but we wanted to see if this is also true for clinical strains of pathogens that are actually out there in the world.”

While each antibiotic-resistant pathogen carries a genetic recipe for its resistance, not all recipes are the same, and not all of them are easily taught to others. Resistance to antibiotics is growing, and it may be impossible to eliminate.

As Jonathan Bethke, a Ph.D. student working in You’s laboratory and first author of the paper, explained, “The real problem is the resistance making its way into pathogens that harm humans. We’re looking to gain a good understanding of what factors affect their rate of conjugation, because if you can slow that process down enough, the plasmids carrying the genes for resistance can fall out of a population.”

The classical method of measuring the rate of plasmid conjugation is labor-intensive and requires 16 hours for a new generation of bacteria to grow in Petri dishes. Thus, it is difficult to use when analyzing hundreds of bacterial strains and dozens of variables. Instead, the researchers developed a method using automated machinery and requiring only five hours to deliver results. They mixed two strains of bacteria: a donor strain with resistance to one antibiotic that can be shared through plasmid conjugation, and a recipient strain with resistance to a different antibiotic that cannot be shared. After the strains mingle and the plasmid conjugation takes place, the researchers transferred the bacterial mixture to vials containing nutrients and both antibiotics to promote the growth of the recipient bacteria that have successfully received the donor’s plasmids for resistance while stunting the growth of all the others. The mixture is then monitored to see how long the newly dual-resistant population takes to hit a certain threshold.

“This method opens up the ability to test many more drugs or environmental factors to see how they influence the rate of plasmid conjugation,” said Bethke. “It will also allow us to determine if there’s some sort of genetic determinant that is playing a greater role in terms of the transfer rate.”

The researchers obtained 219 clinical isolates of pathogens from real patients. They carried resistance to beta-lactamase, the most common form of antibiotic currently used. By measuring the rate of plasmid conjugation both with and without beta-lactamase antibiotics present, they demonstrated that antibiotics do not increase the rate of sharing resistance and discovered that more than 25 percent of the strains studied are capable of sharing their resistance at rates fast enough to detect. While antibiotics promote the spread of resistance, the study indicated that it is primarily through selective population dynamics, rather than through an increased rate of plasmid conjugation.

Additionally, the study examined how slight variations in the genetics of the resistance plasmids affect their conjugation rate. Working with Minfeng Xiao’s laboratory at BGI Genomics in Shenzhen, China, the team sequenced the plasmids, analyzed their DNA and categorized the plasmids into “mobility groups” based on how they jump between cells and “incompatibility groups” based on how they replicate. While there were only two mobility groups present in their sample library, neither of which affected the rate of conjugation, there were seven incompatibility groups that did affect the rate of conjugation.

Bethke noted that, “This is a preliminary but potentially big discovery because these two classifications are genetic, which makes them easy to identify. If we can start to build a library of genetic markers that indicate what a pathogen’s ability to spread its resistance directly to its neighbors is likely to be, then we can start to make large predictions about things like horizontal gene transfer networks and maybe start understanding how bacteria are evolving through this process at large.”

“Such a library would also have direct implications for how doctors use antibiotics in the field. This knowledge would help doctors make patient-specific decisions on whether or not to administer antibiotics,” You concluded.