Background and objective Ventilator-associated pneumonia (VAP) is a leading cause of morbidity and mortality in critically ill patients receiving mechanical ventilation for over 48 hours. This study aims to explore the spatiotemporal dynamics of respiratory microbiota in the upper (URT) and lower respiratory tracts (LRT) across three phases, including intubated controls, a newly defined VAP pre-occurrence phase, and confirmed VAP to identify early diagnostic biomarkers and enhance understanding of VAP pathophysiology. Methods We analyzed 16S rRNA gene sequencing data from 123 samples retrieved from public database. Raw data were processed using the DADA2 pipeline for quality control and denoising. Taxonomy was assigned using the Silva 138 rRNA database. Alpha and beta diversity metrics were calculated, and LEfSe analysis was employed to identify differentially abundant taxa. The diagnostic potential of key bacterial genera was evaluated using ROC curve analysis, with precision, sensitivity, and specificity values reported. Results URT alpha diversity increased significantly in VAP groups compared to controls and pre-VAP phase groups, with no significant changes in LRT alpha diversity. Beta diversity analysis revealed distinct microbial community structures across all three disease stages in both URT and LRT. Key genera, including Prevotella, Leptotrichia, and Peptostreptococcus, were identified as potential early diagnostic biomarkers, with high precision, sensitivity, and specificity. Microbial translocation from the URT to the LRT became increasingly synchronized by day 7 post-intubation, suggesting a critical window for intervention. Conclusions This study highlights the dynamic changes in respiratory microbiota during VAP progression and identifies potential microbial biomarkers for early detection. These findings pave the way for microbiota-based diagnostic strategies and targeted interventions. Future research should validate these biomarkers in independent cohorts and explore their functional roles in VAP pathogenesis. Monitoring URT-LRT microbial interactions could enable proactive management of this devastating infection.
Yang et al. (Fri,) studied this question.