Since the COVID-19 pandemic, there has been a notable resurgence of Mycoplasma pneumoniae pneumonia (MPP) in children, with a concerning rise in the severity of cases. Although changes in post-pandemic respiratory infection patterns have been documented, the reasons behind the increased severity of MPP, especially concerning shifts in the respiratory microbiota, are not well understood. This study aims to explore how pandemic-associated disruptions in respiratory microbiota contribute to MPP severity. Through analysis of multiple independent cohorts, we found that the depletion of protective respiratory microbiota exacerbates MPP severity by reducing colonization resistance against M. pneumoniae. We identified two antagonistic microbiota modules with distinct metabolic features and community structures that regulate pathogen colonization and disease severity. Using a Susceptible-Infected-Recovered (SIR) model, we simulated M. pneumoniae infection dynamics across different microbiota states. Additionally, a machine-learning model based on eight key microbes effectively distinguished between cases and controls and predicted infection severity, offering insights into post-pandemic respiratory infections. This study underscores the essential role of the respiratory microbiota in influencing the severity of M. pneumoniae infections. Our findings offer a framework for managing respiratory infections in the post-pandemic era, highlighting the significance of understanding microbial community dynamics in determining disease outcomes. These insights could guide the development of therapeutic strategies focused on restoring or enhancing the protective microbiota, which may offer an effective strategy for the management of MPP and other respiratory infections.
Huang et al. (2025) studied this question.