Establishes an artificial lung microbiome model for investigating bacterial interactions and therapies.
The human lung microbiome is increasingly recognized as a key player in drug metabolism, yet it remains largely understudied. To replicate this complex physiological environment in a controlled setting, we developed a simplified artificial lung microbiome model composed of four representative bacterial species: Pseudomonas koreensis , Rothia aeria , Neisseria cinerea , and Streptococcus downei . We successfully established a stable 10-day co-culture at 34°C using brain heart infusion medium, as validated by quantitative PCR, viability PCR, and conventional microbiological methodologies. Integrated bioinformatic analyses revealed a variety of potential microbe-microbe interactions, which were supported by metaproteomic analysis using mass spectrometry. Our model provides a foundation for in-depth studies, such as, for example, the effects of pulmonary drugs on the lung microbiome, and how, in turn, the microbiome may influence therapeutic outcomes. IMPORTANCE Once thought to be sterile, the lung microbiome is now understood to host a dynamic microbiome capable of influencing respiratory health and disease. Understanding interactions among the microbes within this community is essential, as these relationships may drive disease progression or foster resilience in both acute and chronic inflammatory conditions. We developed a reproducible lung microbiome model comprising Pseudomonas koreensis , Rothia aeria , Streptococcus downei , and Neisseria cinerea . Simplified models enable controlled studies to dissect specific microbial interactions, laying the foundation for insights into lung microbial ecology. In the future, more complex models will enhance our understanding of microbial roles in disease outcomes, with our platform serving as a basis for testing therapeutic strategies.
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Kulosa et al. (2026) studied this question.
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