Journal of personalized medicine · 2022
Metagenomic Analysis of Plasma Microbial Extracellular Vesicles in Patients Receiving Mechanical Ventilation: A Pilot Study.
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Park Jinkyeong, Lee Jae Jun, Hong Yoonki, Seo Hochan, Shin Tae-Seop, Hong Ji Young
Аннотация
BACKGROUND: Previous studies reported a significant association between pneumonia outcome and the respiratory microbiome. There is increasing interest in the roles of bacterial extracellular vesicles (EVs) in various diseases. We studied the composition and function of microbiota-derived EVs in the plasma of patients receiving mechanical ventilation to evaluate whether they can be used as a diagnostic marker and to predict clinical outcomes.
METHODS: Plasma samples (n = 111) from 59 mechanically ventilated patients (41 in the pneumonia group; 24 in the nursing home and hospital-associated infection [NHAI] group) were prospectively collected on days one and seven. After isolating the bacterial EVs from plasma samples, nucleic acid was extracted for 16S rRNA gene pyrosequencing. The samples were evaluated to determine the α and β diversity, bacterial composition, and predicted functions.
RESULTS: Principal coordinates analysis revealed significantly different clustering of microbial EVs between the pneumonia and non-pneumonia groups. The proportions of Lactobacillus, Cutibacterium, and Sphingomonas were significantly different between the pneumonia and non-pneumonia groups. In addition, the abundances of Lactobacillus and Bifidobacterium were significantly higher in the non-NHAI than the NHAI group. In the analysis of β diversity, the structure of microbial EVs differed significantly different between 28-day survivors and non-survivors (Bray-Curtis distance, p = 0.014). Functional profiling revealed significant differences between the pneumonia and non-pneumonia groups. The longitudinal change in predicted functions of microbial EV genes showed a significant difference between 28-day survivors and non-survivors.
CONCLUSIONS: Bacterial microbiota-derived EVs in the plasma have potential as diagnostic and prognostic markers for patients receiving mechanical ventilation. Further large prospective studies are needed to determine the clinical utility of plasma microbiota-EVs in intubated patients.
METHODS: Plasma samples (n = 111) from 59 mechanically ventilated patients (41 in the pneumonia group; 24 in the nursing home and hospital-associated infection [NHAI] group) were prospectively collected on days one and seven. After isolating the bacterial EVs from plasma samples, nucleic acid was extracted for 16S rRNA gene pyrosequencing. The samples were evaluated to determine the α and β diversity, bacterial composition, and predicted functions.
RESULTS: Principal coordinates analysis revealed significantly different clustering of microbial EVs between the pneumonia and non-pneumonia groups. The proportions of Lactobacillus, Cutibacterium, and Sphingomonas were significantly different between the pneumonia and non-pneumonia groups. In addition, the abundances of Lactobacillus and Bifidobacterium were significantly higher in the non-NHAI than the NHAI group. In the analysis of β diversity, the structure of microbial EVs differed significantly different between 28-day survivors and non-survivors (Bray-Curtis distance, p = 0.014). Functional profiling revealed significant differences between the pneumonia and non-pneumonia groups. The longitudinal change in predicted functions of microbial EV genes showed a significant difference between 28-day survivors and non-survivors.
CONCLUSIONS: Bacterial microbiota-derived EVs in the plasma have potential as diagnostic and prognostic markers for patients receiving mechanical ventilation. Further large prospective studies are needed to determine the clinical utility of plasma microbiota-EVs in intubated patients.