Respiratory microbiome profiling for etiologic diagnosis of pneumonia in mechanically ventilated patients

Georgios D. Kitsios, Adam Fitch, Dimitris V. Manatakis, Sarah F. Rapport, Kelvin Li, Shulin Qin, Joseph Huwe, Yingze Zhang, Yohei Doi, John Evankovich, William Bain, Janet S. Lee, Barbara Methé, Panayiotis V. Benos, Alison Morris, Bryan J. McVerry

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Etiologic diagnosis of bacterial pneumonia relies on identification of causative pathogens by cultures, which require extended incubation periods and have limited sensitivity. Next-generation sequencing of microbial DNA directly from patient samples may improve diagnostic accuracy for guiding antibiotic prescriptions. In this study, we hypothesized that enhanced pathogen detection using sequencing can improve upon culture-based diagnosis and that certain sequencing profiles correlate with host response. We prospectively collected endotracheal aspirates and plasma within 72 h of intubation from patients with acute respiratory failure. We performed 16S rRNA gene sequencing to determine pathogen abundance in lung samples and measured plasma biomarkers to assess host responses to detected pathogens. Among 56 patients, 12 patients (21%) had positive respiratory cultures. Sequencing revealed lung communities with low diversity (p < 0.02) dominated by taxa (> 50% relative abundance) corresponding to clinically isolated pathogens (concordance p = 0.009). Importantly, sequencing detected dominant pathogens in 20% of the culture-negative patients exposed to broad-spectrum empiric antibiotics. Regardless of culture results, pathogen dominance correlated with increased plasma markers of host injury (receptor of advanced glycation end-products-RAGE) and inflammation (interleukin-6, tumor necrosis factor receptor 1-TNFR1) (p < 0.05), compared to subjects without dominant pathogens in their lung communities. Machine-learning algorithms identified pathogen abundance by sequencing as the most informative predictor of culture positivity. Thus, enhanced detection of pathogenic bacteria by sequencing improves etiologic diagnosis of pneumonia, correlates with host responses, and offers substantial opportunity for individualized therapeutic targeting and antimicrobial stewardship. Clinical translation will require validation with rapid whole meta-genome sequencing approaches to guide real-time antibiotic prescriptions.

Original languageEnglish
Article number1413
JournalFrontiers in Microbiology
Volume9
Issue numberJUL
DOIs
Publication statusPublished - 10-07-2018

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Microbiota
Pneumonia
Anti-Bacterial Agents
Lung
Prescriptions
Receptors, Tumor Necrosis Factor, Type I
Bacterial Pneumonia
Tumor Necrosis Factor Receptors
DNA Sequence Analysis
rRNA Genes
Intubation
Respiratory Insufficiency
Interleukin-6
Biomarkers
Genome
Inflammation
Bacteria
Wounds and Injuries

All Science Journal Classification (ASJC) codes

  • Microbiology
  • Microbiology (medical)

Cite this

Kitsios, G. D., Fitch, A., Manatakis, D. V., Rapport, S. F., Li, K., Qin, S., ... McVerry, B. J. (2018). Respiratory microbiome profiling for etiologic diagnosis of pneumonia in mechanically ventilated patients. Frontiers in Microbiology, 9(JUL), [1413]. https://doi.org/10.3389/fmicb.2018.01413
Kitsios, Georgios D. ; Fitch, Adam ; Manatakis, Dimitris V. ; Rapport, Sarah F. ; Li, Kelvin ; Qin, Shulin ; Huwe, Joseph ; Zhang, Yingze ; Doi, Yohei ; Evankovich, John ; Bain, William ; Lee, Janet S. ; Methé, Barbara ; Benos, Panayiotis V. ; Morris, Alison ; McVerry, Bryan J. / Respiratory microbiome profiling for etiologic diagnosis of pneumonia in mechanically ventilated patients. In: Frontiers in Microbiology. 2018 ; Vol. 9, No. JUL.
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Kitsios, GD, Fitch, A, Manatakis, DV, Rapport, SF, Li, K, Qin, S, Huwe, J, Zhang, Y, Doi, Y, Evankovich, J, Bain, W, Lee, JS, Methé, B, Benos, PV, Morris, A & McVerry, BJ 2018, 'Respiratory microbiome profiling for etiologic diagnosis of pneumonia in mechanically ventilated patients', Frontiers in Microbiology, vol. 9, no. JUL, 1413. https://doi.org/10.3389/fmicb.2018.01413

Respiratory microbiome profiling for etiologic diagnosis of pneumonia in mechanically ventilated patients. / Kitsios, Georgios D.; Fitch, Adam; Manatakis, Dimitris V.; Rapport, Sarah F.; Li, Kelvin; Qin, Shulin; Huwe, Joseph; Zhang, Yingze; Doi, Yohei; Evankovich, John; Bain, William; Lee, Janet S.; Methé, Barbara; Benos, Panayiotis V.; Morris, Alison; McVerry, Bryan J.

In: Frontiers in Microbiology, Vol. 9, No. JUL, 1413, 10.07.2018.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Respiratory microbiome profiling for etiologic diagnosis of pneumonia in mechanically ventilated patients

AU - Kitsios, Georgios D.

AU - Fitch, Adam

AU - Manatakis, Dimitris V.

AU - Rapport, Sarah F.

AU - Li, Kelvin

AU - Qin, Shulin

AU - Huwe, Joseph

AU - Zhang, Yingze

AU - Doi, Yohei

AU - Evankovich, John

AU - Bain, William

AU - Lee, Janet S.

AU - Methé, Barbara

AU - Benos, Panayiotis V.

AU - Morris, Alison

AU - McVerry, Bryan J.

PY - 2018/7/10

Y1 - 2018/7/10

N2 - Etiologic diagnosis of bacterial pneumonia relies on identification of causative pathogens by cultures, which require extended incubation periods and have limited sensitivity. Next-generation sequencing of microbial DNA directly from patient samples may improve diagnostic accuracy for guiding antibiotic prescriptions. In this study, we hypothesized that enhanced pathogen detection using sequencing can improve upon culture-based diagnosis and that certain sequencing profiles correlate with host response. We prospectively collected endotracheal aspirates and plasma within 72 h of intubation from patients with acute respiratory failure. We performed 16S rRNA gene sequencing to determine pathogen abundance in lung samples and measured plasma biomarkers to assess host responses to detected pathogens. Among 56 patients, 12 patients (21%) had positive respiratory cultures. Sequencing revealed lung communities with low diversity (p < 0.02) dominated by taxa (> 50% relative abundance) corresponding to clinically isolated pathogens (concordance p = 0.009). Importantly, sequencing detected dominant pathogens in 20% of the culture-negative patients exposed to broad-spectrum empiric antibiotics. Regardless of culture results, pathogen dominance correlated with increased plasma markers of host injury (receptor of advanced glycation end-products-RAGE) and inflammation (interleukin-6, tumor necrosis factor receptor 1-TNFR1) (p < 0.05), compared to subjects without dominant pathogens in their lung communities. Machine-learning algorithms identified pathogen abundance by sequencing as the most informative predictor of culture positivity. Thus, enhanced detection of pathogenic bacteria by sequencing improves etiologic diagnosis of pneumonia, correlates with host responses, and offers substantial opportunity for individualized therapeutic targeting and antimicrobial stewardship. Clinical translation will require validation with rapid whole meta-genome sequencing approaches to guide real-time antibiotic prescriptions.

AB - Etiologic diagnosis of bacterial pneumonia relies on identification of causative pathogens by cultures, which require extended incubation periods and have limited sensitivity. Next-generation sequencing of microbial DNA directly from patient samples may improve diagnostic accuracy for guiding antibiotic prescriptions. In this study, we hypothesized that enhanced pathogen detection using sequencing can improve upon culture-based diagnosis and that certain sequencing profiles correlate with host response. We prospectively collected endotracheal aspirates and plasma within 72 h of intubation from patients with acute respiratory failure. We performed 16S rRNA gene sequencing to determine pathogen abundance in lung samples and measured plasma biomarkers to assess host responses to detected pathogens. Among 56 patients, 12 patients (21%) had positive respiratory cultures. Sequencing revealed lung communities with low diversity (p < 0.02) dominated by taxa (> 50% relative abundance) corresponding to clinically isolated pathogens (concordance p = 0.009). Importantly, sequencing detected dominant pathogens in 20% of the culture-negative patients exposed to broad-spectrum empiric antibiotics. Regardless of culture results, pathogen dominance correlated with increased plasma markers of host injury (receptor of advanced glycation end-products-RAGE) and inflammation (interleukin-6, tumor necrosis factor receptor 1-TNFR1) (p < 0.05), compared to subjects without dominant pathogens in their lung communities. Machine-learning algorithms identified pathogen abundance by sequencing as the most informative predictor of culture positivity. Thus, enhanced detection of pathogenic bacteria by sequencing improves etiologic diagnosis of pneumonia, correlates with host responses, and offers substantial opportunity for individualized therapeutic targeting and antimicrobial stewardship. Clinical translation will require validation with rapid whole meta-genome sequencing approaches to guide real-time antibiotic prescriptions.

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