The average lifespan for a patient with cystic fibrosis (CF) in the United States is 40 years old. This has improved from years ago due to aggressive treatments with antibiotics. Yet, Ryan Hunter, PhD, assistant professor for the Department of Microbiology and Immunology, and his colleagues noticed inconsistencies among how effective antibiotics are in treating patients with CF and began studying how to improve antibiotic efficacy.

“CF is a genetic disease that leads to the build-up of mucus in the lungs and is very difficult to clear. In turn, any bacteria that colonize the airways are also difficult to clear, so this leaves any patient with CF prone to long-term chronic bacterial infections, a leading cause of patient mortality,” Dr. Hunter said. “As a result, one of the main treatments is aggressive antibiotic therapy. Current approaches have been somewhat effective, but there’s room for improvement.”

To make informed decisions about which type of antibiotic to use clinically, patient mucus samples are sent to a clinical lab where bacteria, likePseudomonas aeruginosa (a common CF pathogen), are isolated and tested against a panel of different antibiotics. Predictions can then be made about their effectiveness when administered to a patient. However, for chronic bacterial infections like those in the CF lung, recent data show that antibiotic susceptibility testing data poorly correlate with clinical efficacy or patient outcomes. The reason, which Dr. Hunter and colleagues speculated, is that culturing bacteria in a lab isn’t the same as growing them in the patient’s body.

“By culturing bacteria in a lab, you are taking it out of the environment it is used to growing in. It in no way reflects what is actually happening in the body,” Dr. Hunter explained. “You are also taking it away from other bacteria it grows with. We know that pathogens, like Pseudomonas, live in a very complex bacterial community, and just by targeting a single pathogen, you ignore the rest of the bacteria that it lives with in the lungs.”

This led to Dr. Hunter and his colleagues, Jeffrey Flynn and William Harcombe, to research the question, “If we can better mimic the lung environment on the lab bench, will we be able to make better predictions as to how effective specific antibiotics may be for a patient with CF?”

They started by taking the patient’s mucus samples and, instead of culturing just one type of bacteria, they cultured multiple, recreating a “community of bacteria” similar to what exists in the patient’s lungs. Under these conditions, bacteria, like Pseudomonas, rely on others for nutrients while they consume oxygen and allow less oxygen-tolerant bacteria to grow. Their findings were recently published in the journal, “mSphere.” 

“In this paper, we showed that if we cultured all of the bacteria together under conditions in which they rely on one another and grow as a community, Pseudomonas aeruginosa, even if antibiotic-resistant, can be inhibited simply by reducing the growth of other bacteria that are present there,” Dr. Hunter explained. “We showed that by using these antibiotics to target more of a community-type bacterial growth, you can really improve the efficacy of antibiotics when you don’t just consider the single pathogen on it’s own under artificial conditions.”

A logical next step of their research is to guide patient therapy using this approach. Dr. Hunter will compare his laboratory approach with the current approaches to test the antibiotic efficacy between patients with CF.

“What’s exciting is that our approach is broadly applicable. We use CF as our model system, but when it comes to the treatment of other chronic bacterial infections, such as sinus and gastrointestinal infections, this is applicable,” Dr. Hunter said. “I think the real impact of this is that it won’t just be applied to one disease but to many.”