What question did this study set out to answer?

To assess how changes in pathogen presence in the lower airway microbiome can predict ventilator-associated pneumonia (VAP) in critically ill patients.

May 20, 2026

A68-07 Dynamics of Pervasive, Potential Pathogens in the Lower Airway Microbiome Demonstrate Differential Trajectories in Ventilator-associated Pneumonia

Key Points

To assess how changes in pathogen presence in the lower airway microbiome can predict ventilator-associated pneumonia (VAP) in critically ill patients.
Collected longitudinal lower airway samples from 233 COVID-19 patients admitted to the MICU.
Performed microbiome profiling using metatranscriptome sequencing and clinical cultures.
Defined sampling phases around suspected VAP: pre, peri, and post VAP.
Identified enrichment of P. aeruginosa, Klebsiella spp., and E. coli in microbiome samples collected peri-VAP.
No change was observed in relative abundance of S. aureus between pre-VAP and post-VAP.
Positive cultures for pathogens coincided with increased relative abundance in the microbiome, showing potential for detection prior to clinical pneumonia onset.

Abstract

Abstract Rationale Non-culture-based methods aid in detection of potential pathogens and predict pneumonia diagnosis. A previous study suggested a 50% relative abundance cut-off for a pathogen to predict culture positivity. This observation was further refined by providing pathogen specific cutoffs. Neither work identified longitudinal changes preceding and following ventilator-associated pneumonia (VAP). We hypothesized that temporal changes and detection of potential pathogens in the lower airway microbiome near suspected VAP can predict the development of pneumonia and correlate with pathogens in sputum cultures for a cohort of critically ill patients sampled longitudinally. Methods We obtained longitudinal lower airway samples (bronchoalveolar lavage and tracheal aspirates) from a cohort of COVID-19 participants (n = 233) admitted to the MICU (IRB #i22-00616). Clinical cultures were collected as standard of care by the treating clinician. Microbiome profiling was performed by metatranscriptome sequencing. Relative abundance of assigned taxa was calculated and compared to the clinical culture results. We defined pre-VAP as 5 days prior to suspected VAP, peri-VAP as 5 days before and after suspected VAP, and post-VAP as 5 days after suspected VAP. We calculated significance using Mann-Whitney U test between samples taken 5 days prior to, during, and 5 days after suspected VAP. Results We collected a total of 446 lower airway samples; the most common culture result was normal flora (n = 570) and no growth (n = 105). The predominant pathogens identified in culture were Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella spp., and Escherichia coli. There was no difference in the relative abundance of S. aureus in the microbiome in the pre-VAP or post-VAP samples (Figure). P. aeruginosa, Klebsiella spp., and E. coli were enriched when the peri-VAP samples were collected within 5 days of the positive sputum culture (Figure). There was higher relative abundance of S. aureus, P. aeruginosa, Klebsiella spp., and E. coli in the microbiome for cultures positive compared to cultures negative for that specific pathogen. Conclusions Respiratory cultures often do not identify causative pathogens in pneumonia. We identified pathogen enrichment in the lower airway microbiome within 5 days of suspected VAP with positive cultures except S. aureus. As previously reported by others, we found different relative abundance cutoffs per pathogen; further analyses of the lung microbiome will help us understand why this occurs. Non-culture-based methods, such as metatranscriptomics of lower airway samples, may help improve detection of pathogens before clinically relevant pneumonia occurs. This abstract is funded by: Veterans Affairs IK2BX005309-01A2 (BGW); National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, through Grant Award Number KL2TR001446 (BGW); NYU CTSA grant (TL1 TR001447) from the National Center for Advancing Translational Sciences, National Institutes of Health (CJC); CHEST Foundation Research Grant in Chronic Obstructive Pulmonary Disease (BGW); R37 CA244775 (LNS, NCI/NIH); R33 GM147800 (LNS, NIGMS/NIH); U01 AG088351 (LNS, NIA/NIH). National Institutes of Health 5R01LM014085 (HL)

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