Respiratory Microbiome Profiling for Etiologic Diagnosis of Pneumonia in Mechanically Ventilated Patients
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 antibi...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-07-01
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| Series: | Frontiers in Microbiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fmicb.2018.01413/full |
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| author | Georgios D. Kitsios Georgios D. Kitsios Adam Fitch Dimitris V. Manatakis Sarah F. Rapport Kelvin Li Shulin Qin Shulin Qin Joseph Huwe Yingze Zhang Yohei Doi John Evankovich William Bain Janet S. Lee Barbara Methé Barbara Methé Panayiotis V. Benos Alison Morris Alison Morris Alison Morris Bryan J. McVerry Bryan J. McVerry |
| author_facet | Georgios D. Kitsios Georgios D. Kitsios Adam Fitch Dimitris V. Manatakis Sarah F. Rapport Kelvin Li Shulin Qin Shulin Qin Joseph Huwe Yingze Zhang Yohei Doi John Evankovich William Bain Janet S. Lee Barbara Methé Barbara Methé Panayiotis V. Benos Alison Morris Alison Morris Alison Morris Bryan J. McVerry Bryan J. McVerry |
| author_sort | Georgios D. Kitsios |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T03:26:08Z |
| format | Article |
| id | doaj.art-04023e07f1fa4e8aa4c938333cdd47bf |
| institution | Directory Open Access Journal |
| issn | 1664-302X |
| language | English |
| last_indexed | 2024-12-20T03:26:08Z |
| publishDate | 2018-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Microbiology |
| spelling | doaj.art-04023e07f1fa4e8aa4c938333cdd47bf2022-12-21T19:55:05ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2018-07-01910.3389/fmicb.2018.01413365791Respiratory Microbiome Profiling for Etiologic Diagnosis of Pneumonia in Mechanically Ventilated PatientsGeorgios D. Kitsios0Georgios D. Kitsios1Adam Fitch2Dimitris V. Manatakis3Sarah F. Rapport4Kelvin Li5Shulin Qin6Shulin Qin7Joseph Huwe8Yingze Zhang9Yohei Doi10John Evankovich11William Bain12Janet S. Lee13Barbara Methé14Barbara Methé15Panayiotis V. Benos16Alison Morris17Alison Morris18Alison Morris19Bryan J. McVerry20Bryan J. McVerry21Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesCenter for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, United StatesCenter for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, United StatesDepartment of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, United StatesDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesCenter for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, United StatesDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesCenter for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, United StatesDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesDivision of Infectious Diseases, University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesCenter for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, United StatesDepartment of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, United StatesDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesCenter for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, United StatesDepartment of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United StatesDivision of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, United StatesCenter for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, United StatesEtiologic 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.https://www.frontiersin.org/article/10.3389/fmicb.2018.01413/fullmicrobiomepneumonia16S rRNA gene sequencingrespiratory failureantibiotic stewardship |
| spellingShingle | Georgios D. Kitsios Georgios D. Kitsios Adam Fitch Dimitris V. Manatakis Sarah F. Rapport Kelvin Li Shulin Qin Shulin Qin Joseph Huwe Yingze Zhang Yohei Doi John Evankovich William Bain Janet S. Lee Barbara Methé Barbara Methé Panayiotis V. Benos Alison Morris Alison Morris Alison Morris Bryan J. McVerry Bryan J. McVerry Respiratory Microbiome Profiling for Etiologic Diagnosis of Pneumonia in Mechanically Ventilated Patients Frontiers in Microbiology microbiome pneumonia 16S rRNA gene sequencing respiratory failure antibiotic stewardship |
| title | Respiratory Microbiome Profiling for Etiologic Diagnosis of Pneumonia in Mechanically Ventilated Patients |
| title_full | Respiratory Microbiome Profiling for Etiologic Diagnosis of Pneumonia in Mechanically Ventilated Patients |
| title_fullStr | Respiratory Microbiome Profiling for Etiologic Diagnosis of Pneumonia in Mechanically Ventilated Patients |
| title_full_unstemmed | Respiratory Microbiome Profiling for Etiologic Diagnosis of Pneumonia in Mechanically Ventilated Patients |
| title_short | Respiratory Microbiome Profiling for Etiologic Diagnosis of Pneumonia in Mechanically Ventilated Patients |
| title_sort | respiratory microbiome profiling for etiologic diagnosis of pneumonia in mechanically ventilated patients |
| topic | microbiome pneumonia 16S rRNA gene sequencing respiratory failure antibiotic stewardship |
| url | https://www.frontiersin.org/article/10.3389/fmicb.2018.01413/full |
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