Bacterial communities show patterns in pulmonary exacerbation

Study results could aid in personalized treatment for CF, other diseases

Marisa Wexler, MS avatar

by Marisa Wexler, MS |

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This illustration shows different types of bacteria in a cluster.

During pulmonary exacerbation in cystic fibrosis (CF), bacterial communities in the lungs tend to change in one of two general patterns, and better understanding these patterns may help predict how patients will respond to antibiotic treatments.

That’s according to the study, “Microbial community organization designates distinct pulmonary exacerbation types and predicts treatment outcome in cystic fibrosis,” which was published in Nature Communications.

“Our study reveals a data-based, causal relationship between [pulmonary exacerbation], microbial ecology and treatment success,” Stefanie Widder, PhD, the study’s first author and a researcher at the Medical University of Vienna in Austria, said in a university press release.

The results “form an important basis for further translational research into personalized management of dysbiosis [imbalance in microbial species living in the body], both in cystic fibrosis and in other obstructive pulmonary diseases,” Widder said.

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Pulmonary exacerbation linked to bacterial infection flares

The human body is home to billions of bacteria and other single-celled organisms, collectively called the microbiome. Many of these bacteria make their home in the lungs, and normally they are important for immune responses and other processes.

Pulmonary exacerbation, referring to a sudden dip in lung function, is thought to occur in CF due to flare-ups of bacterial infections in the lungs. But how, exactly, does the lung microbiome change during an exacerbation?

To answer that question, a team of scientists from Austria and the U.S. analyzed more than 800 sputum (phlegm) samples which were collected almost daily over time from 11 adults with CF. Collectively, the samples covered 18 pulmonary exacerbations.

By analyzing the types of bacteria in each sample over time, the researchers identified two general patterns of microbiome growth that tended to accompany pulmonary exacerbations.

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Considering the microbiome’s role in lung infections

In one pattern, certain specific bacteria that are known to cause problems in CF, such as Pseudomonas aeruginosa, start to grow out of control and end up dominating the lung microbiome. The other pattern was more chaotic: Rather than a few specific species growing unchecked, there would be rapid changes in relative levels of different bacteria, particularly anaerobic bacteria (that is, bacteria that do not live or grow when oxygen is present).

Both patterns “are robust maladaptations to the disease conditions of the lung,” the researchers wrote. The results made them speculate “that [patient]-specific mucus accumulation and decreasing oxygen availability in the lung microenvironment determine CF dysbiosis states in ways.”

The findings show it’s important to consider not just specific disease-associated bacteria, but also the broader context of the lung microbiome, when trying to understand how bacterial lung infections develop in CF, the researchers said.

An important theoretical implication of the finding is that, if there are two different patterns of pulmonary exacerbation, the two patterns may respond differently to treatments. Preliminary analyses using computer modeling seemed to support this idea: The researchers found that antibiotic treatment generally had a more pronounced effect on microbiome dynamics in exacerbations that were dominated by a few disease-related bacteria, but were generally less impactful in the more chaotic exacerbations.

The team stressed that additional studies will be needed to address this question definitively, noting that their analysis was limited to data on fewer than a dozen patients. The impact of CFTR modulators on the airway microbiome is currently under study, the scientists said.

Still, they said, these data could be a crucial first step to better developing personalized treatments for lung infections in CF.