Dominance of specific lung bacteria over microbiota diversity in COVID-19 clinical trajectories

Abstract

Introduction: This study investigates the impact of lung microbiota on COVID-19 outcomes.

Methodology: Clinical data and bronchoalveolar lavage fluid (BALF) data and bronchoalveolar lavage fluid (BALF) samples were retrospectively collected from 40 COVID-19 patients for Targeted Next-generation Sequencing (TNGS). Microbial diversity was then analyzed across different clinical severity groups. Additionally, biomarkers were identified using Linear Discriminant Analysis Effect Size (LEfSe) and evaluated by Receiver Operating Characteristic (ROC) - Area Under the Curve (AUC).

Results: The patients were classified by severity as mild (n = 3), moderate (n = 13), severe (n = 16), or critical (n = 8) symptoms. The α-diversity of respiratory flora showed no significant differences between groups (p > 0.05). While β-diversity analysis revealed significant compositional distinctions (p < 0.05). Critically ill patients had higher levels of Pseudomonas aeruginosa compared to other groups, ROC-plot AUC value of 0.856. Patients were then categorized into two outcome-based groups: Non-survivors (n = 5) and Survivors (n = 35). No significant differences in α-diversity of respiratory flora were observed between the two groups (p > 0.05), while β-diversity revealed distinct compositional differences (p < 0.05). Furthermore, the ROC curve for Pseudomonas aeruginosa (AUC = 0.846) indicated its predictive value for mortality.

Conclusions: This study has elucidated the characteristics of pulmonary microbiota across different COVID-19 severities, identifying bacteria associated with severe illness, mortality, and relevant clinical markers. The lung microbiota exhibits low diversity, making the pulmonary microecology more vulnerable to disruption. Therefore, invasive species may influence clinical outcomes in affected patients.