Chronic lung diseases can be worsened by polymicrobial infections, and a study led by MedUni Vienna has found two types of these dysbioses in cystic fibrosis. These dysbioses have different characteristics and may require different treatments. The study was published in a journal.Nature Communications published a report on chronic lung diseases like COPD, asthma, and cystic fibrosis, which affect a large number of people globally. In 2019, there were 454.6 million recorded cases worldwide. These diseases result in a gradual decline in lung function and are linked to a high mortality rate. Respiratory tract infections caused by multiple bacteria that persist in the lungs for extended periods pose a significant risk and are challenging to treat. These infections are often connected to recurrent acute exacerbations of symptoms, which have a detrimental effect on the progression of the disease.A recent study conducted by Stefanie Widder from MedUni Vienna and John J. LiPuma from the University of Michigan Medical School Ann Arbor has examined the bacterial communities associated with cystic fibrosis and studied their ecological networks. The goal was to create hypotheses that could lead to more effective treatment strategies for individuals with chronic lung diseases.
The study identified two different types of dysbiosis, or microbial imbalances, in sputum samples collected from individuals with cystic fibrosis. This research aimed to improve the understanding of disease-associated bacterial communities and their impact on lung health.Cystic fibrosis has been studied over a long period of time and was recently sequenced and analyzed using computational models by Stefanie Widder from the Department of Medicine I, Division of Infection Biology at MedUni Vienna. From this analysis, two opposite types of dysbiosis were identified, which are fundamentally different in their organization: they either form hierarchical or stochastic networks. The structural differences of the microbiota have significant implications. The sequencing data revealed that important pathogens such as Pseudomonas aeruginosa or Staphylococcus aureus only caused infection if they were at the top of the microbial hierarchy. This has important implications for treatment and understanding the disease.Microbiota that are hierarchically organized tend to have more stable dynamics, while those with altered microbiota show more random dynamics, indicating they may have less impact on the infection’s progression. Additionally, a computer model suggests that different dysbiosis types may have varied responses to treatments. The model indicates that antimicrobial drugs may be more effective with hierarchically organized microbiota. This information is important for patients and their medical teams, as it reveals a data-based, causal link between PEx, microbial ecology, and treatment outcomes.According to the study’s lead researcher, Stefanie Widder, the results are a crucial starting point for additional research on personalized treatment for dysbiosis in cystic fibrosis and other obstructive pulmonary diseases.
