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Kitsios GD, Sayed K, Fitch A, Yang H, Britton N, Shah F, Bain W, Evankovich JW, Qin S, Wang X, Li K, Patel A, Zhang Y, Radder J, Dela Cruz C, Okin DA, Huang CY, Van Tyne D, Benos PV, Methé B, Lai P, Morris A, McVerry BJ. Longitudinal multicompartment characterization of host-microbiota interactions in patients with acute respiratory failure. Nat Commun 2024; 15:4708. [PMID: 38830853 PMCID: PMC11148165 DOI: 10.1038/s41467-024-48819-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 05/13/2024] [Indexed: 06/05/2024] Open
Abstract
Critical illness can significantly alter the composition and function of the human microbiome, but few studies have examined these changes over time. Here, we conduct a comprehensive analysis of the oral, lung, and gut microbiota in 479 mechanically ventilated patients (223 females, 256 males) with acute respiratory failure. We use advanced DNA sequencing technologies, including Illumina amplicon sequencing (utilizing 16S and ITS rRNA genes for bacteria and fungi, respectively, in all sample types) and Nanopore metagenomics for lung microbiota. Our results reveal a progressive dysbiosis in all three body compartments, characterized by a reduction in microbial diversity, a decrease in beneficial anaerobes, and an increase in pathogens. We find that clinical factors, such as chronic obstructive pulmonary disease, immunosuppression, and antibiotic exposure, are associated with specific patterns of dysbiosis. Interestingly, unsupervised clustering of lung microbiota diversity and composition by 16S independently predicted survival and performed better than traditional clinical and host-response predictors. These observations are validated in two separate cohorts of COVID-19 patients, highlighting the potential of lung microbiota as valuable prognostic biomarkers in critical care. Understanding these microbiome changes during critical illness points to new opportunities for microbiota-targeted precision medicine interventions.
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Affiliation(s)
- Georgios D Kitsios
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Khaled Sayed
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
- Department of Electrical and Computer Engineering & Computer Science, University of New Haven, West Haven, CT, USA
| | - Adam Fitch
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Haopu Yang
- School of Medicine, Tsinghua University, Beijing, China
| | - Noel Britton
- Division of Pulmonary Critical Care Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MA, USA
| | - Faraaz Shah
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Veteran's Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - William Bain
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Veteran's Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - John W Evankovich
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Shulin Qin
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Xiaohong Wang
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kelvin Li
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Asha Patel
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yingze Zhang
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Josiah Radder
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Charles Dela Cruz
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daniel A Okin
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ching-Ying Huang
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Daria Van Tyne
- Division of Infectious Diseases, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Barbara Methé
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Peggy Lai
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Alison Morris
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Bryan J McVerry
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
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2
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Cho NA, Strayer K, Dobson B, McDonald B. Pathogenesis and therapeutic opportunities of gut microbiome dysbiosis in critical illness. Gut Microbes 2024; 16:2351478. [PMID: 38780485 PMCID: PMC11123462 DOI: 10.1080/19490976.2024.2351478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 04/22/2024] [Indexed: 05/25/2024] Open
Abstract
For many years, it has been hypothesized that pathological changes to the gut microbiome in critical illness is a driver of infections, organ dysfunction, and other adverse outcomes in the intensive care unit (ICU). The advent of contemporary microbiome methodologies and multi-omics tools have allowed researchers to test this hypothesis by dissecting host-microbe interactions in the gut to better define its contribution to critical illness pathogenesis. Observational studies of patients in ICUs have revealed that gut microbial communities are profoundly altered in critical illness, characterized by markedly reduced alpha diversity, loss of commensal taxa, and expansion of potential pathogens. These key features of ICU gut dysbiosis have been associated with adverse outcomes including life-threatening hospital-acquired (nosocomial) infections. Current research strives to define cellular and molecular mechanisms connecting gut dysbiosis with infections and other outcomes, and to identify opportunities for therapeutic modulation of host-microbe interactions. This review synthesizes evidence from studies of critically ill patients that have informed our understanding of intestinal dysbiosis in the ICU, mechanisms linking dysbiosis to infections and other adverse outcomes, as well as clinical trials of microbiota-modifying therapies. Additionally, we discuss novel avenues for precision microbial therapeutics to combat nosocomial infections and other life-threatening complications of critical illness.
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Affiliation(s)
- Nicole A Cho
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Kathryn Strayer
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Breenna Dobson
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Braedon McDonald
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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Musher DM. Problems with etiologic diagnosis of community-acquired pneumonia using plasma microbial cell-free DNA sequencing. ANTIMICROBIAL STEWARDSHIP & HEALTHCARE EPIDEMIOLOGY : ASHE 2023; 3:e206. [PMID: 38028926 PMCID: PMC10654952 DOI: 10.1017/ash.2023.475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 09/20/2023] [Accepted: 09/21/2023] [Indexed: 12/01/2023]
Affiliation(s)
- Daniel M. Musher
- Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, USA
- Baylor College of Medicine, Houston, TX, USA
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Poulsen SH, Søgaard KK, Fuursted K, Nielsen HL. Evaluating the diagnostic accuracy and clinical utility of 16S and 18S rRNA gene targeted next-generation sequencing based on five years of clinical experience. Infect Dis (Lond) 2023; 55:767-775. [PMID: 37535652 DOI: 10.1080/23744235.2023.2241550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 07/21/2023] [Indexed: 08/05/2023] Open
Abstract
BACKGROUND The use of 16S/18S rRNA targeted next-generation sequencing (tNGS) has improved microbial diagnostics, however, the use of tNGS in a routine clinical setting requires further elucidation. We retrospectively evaluated the diagnostic accuracy and clinical utility of 16S/18S tNGS, routinely used in the North Denmark Region between 2017 and 2021. METHODS We retrieved 544 tNGS results from 491 patients hospitalised with suspected infection (e.g. meningitis, pneumonia, intraabdominal abscess, osteomyelitis and joint infection). The tNGS assays was performed using the Illumina MiSeq desktop sequencer, and BION software for annotation. The patients' diagnosis and clinical management was evaluated by medical chart review. We calculated sensitivity and specificity, and determined the diagnostic accuracy of tNGS by defining results as true positive, true negative, false positive, and false negative. RESULTS Overall, tNGS had a sensitivity of 56% and a specificity of 97%. tNGS was more frequently true positive compared to culture (32% vs 18%), and tNGS detected a greater variety of bacteria and fungi, and was more frequently polymicrobial. However, the total diagnostic turnaround time was 16 days, and although 73% of tNGS results were true positive or true negative, only 4.4% of results led to changes in clinical management. CONCLUSIONS As a supplement to culture, tNGS improves identification of pathogenic microorganisms in a broad range of clinical specimens. However, the long turnaround time of tNGS in our setting may have contributed to a limited clinical utility. An improved turnaround time can be the key to improved clinical utility in a future setting.
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Affiliation(s)
| | - Kirstine Kobberøe Søgaard
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
- Department of Clinical Microbiology, Aalborg University Hospital, Aalborg, Denmark
| | | | - Hans Linde Nielsen
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
- Department of Clinical Microbiology, Aalborg University Hospital, Aalborg, Denmark
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Marimón JM, Sorarrain A, Ercibengoa M, Azcue N, Alonso M, Vidaur L. Lung microbiome on admission in critically ill patients with acute bacterial and viral pneumonia. Sci Rep 2023; 13:17724. [PMID: 37853062 PMCID: PMC10584954 DOI: 10.1038/s41598-023-45007-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 10/14/2023] [Indexed: 10/20/2023] Open
Abstract
Composition of pulmonary microbiome of patients with severe pneumonia is poorly known. The aim of this work was to analyse the lung microbiome of patients admitted to the intensive care unit (ICU) with severe community acquired pneumonia (CAP) between 2019 and 2021 in comparison with a control group of 6 patients undergoing digestive surgery. As a second objective, the diagnostic capabilities of metagenomics was also studied in a small group of selected patients. The lung microbiome of patients with viral (5 with Influenza A and 8 with SARS-CoV-2) pneumonia at admission showed a similar diversity as the control group (p = 0.140 and p = 0.213 respectively). Contrarily, the group of 12 patients with pneumococcal pneumonia showed a significant lower Simpson´s index (p = 0.002). In the control group (n = 6) Proteobacteria (36.6%), Firmicutes (24.2%) and Actinobacteria (23.0%) were the predominant phyla. In SARS-CoV-2 patients (n = 8), there was a predominance of Proteobacteria (mean 41.6%) (Moraxella and Pelomonas at the genus level), Actinobacteria (24.6%) (Microbacterium) and Firmicutes (22.8%) mainly Streptococcus, Staphylococcus and Veillonella. In patients with Influenza A pneumonia (n = 5) there was a predominance of Firmicutes (35.1%) mainly Streptococcus followed by Proteobacteria (29.2%) (Moraxella, Acinetobacter and Pelomonas). In the group of pneumococcal pneumonia (n = 12) two phyla predominated: Firmicutes (53.1%) (Streptococcus) and Proteobacteria (36.5%) (Haemophilus). In the 7 patients with non-pneumococcal bacterial pneumonia Haemophilus influenzae (n = 2), Legionella pneumophila (n = 2), Klebsiella pneumoniae, Streptococcus pyogenes and Leptospira were detected by metagenomics, confirming the diagnosis done using conventional microbiological techniques. The diversity of the respiratory microbiome in patients with severe viral pneumonia at ICU admission was similar to that of the control group. Contrarily, patients with pneumococcal pneumonia showed a lower grade of diversity. At initial stages of SARS-CoV-2 infection, no important alterations in the pulmonary microbiome were observed. The analysis of bacterial microbiome showed promising results as a diagnostic tool.
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Affiliation(s)
- Jose María Marimón
- Biodonostia, Infectious Diseases Area, Respiratory Infection and Antimicrobial Resistance Group, Microbiology Department, Osakidetza Basque Health Service, Donostialdea Integrated Health Organization, 20014, Donostia-San Sebastian, Spain.
- Microbiology Department, Donostia University Hospital, 20014, Donostia-San Sebastián, Spain.
| | - Ane Sorarrain
- Biodonostia, Infectious Diseases Area, Respiratory Infection and Antimicrobial Resistance Group, Microbiology Department, Osakidetza Basque Health Service, Donostialdea Integrated Health Organization, 20014, Donostia-San Sebastian, Spain
| | - Maria Ercibengoa
- Biodonostia, Infectious Diseases Area, Respiratory Infection and Antimicrobial Resistance Group, Microbiology Department, Osakidetza Basque Health Service, Donostialdea Integrated Health Organization, 20014, Donostia-San Sebastian, Spain
| | - Nekane Azcue
- Microbiology Department, Donostia University Hospital, 20014, Donostia-San Sebastián, Spain
| | - Marta Alonso
- Biodonostia, Infectious Diseases Area, Respiratory Infection and Antimicrobial Resistance Group, Microbiology Department, Osakidetza Basque Health Service, Donostialdea Integrated Health Organization, 20014, Donostia-San Sebastian, Spain
- Microbiology Department, Donostia University Hospital, 20014, Donostia-San Sebastián, Spain
| | - Loreto Vidaur
- Biodonostia, Infectious Diseases Area, Respiratory Infection and Antimicrobial Resistance Group, Microbiology Department, Osakidetza Basque Health Service, Donostialdea Integrated Health Organization, 20014, Donostia-San Sebastian, Spain
- Intensive Care Unit, Donostia University Hospital, 20014, Donostia-San Sebastián, Spain
- Centro de Investigacion Biomedica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
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Kitsios GD, Sayed K, Fitch A, Yang H, Britton N, Shah F, Bain W, Evankovich JW, Qin S, Wang X, Li K, Patel A, Zhang Y, Radder J, Dela Cruz C, Okin DA, Huang CY, van Tyne D, Benos PV, Methé B, Lai P, Morris A, McVerry BJ. Prognostic Insights from Longitudinal Multicompartment Study of Host-Microbiota Interactions in Critically Ill Patients. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.25.23296086. [PMID: 37808745 PMCID: PMC10557814 DOI: 10.1101/2023.09.25.23296086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Critical illness can disrupt the composition and function of the microbiome, yet comprehensive longitudinal studies are lacking. We conducted a longitudinal analysis of oral, lung, and gut microbiota in a large cohort of 479 mechanically ventilated patients with acute respiratory failure. Progressive dysbiosis emerged in all three body compartments, characterized by reduced alpha diversity, depletion of obligate anaerobe bacteria, and pathogen enrichment. Clinical variables, including chronic obstructive pulmonary disease, immunosuppression, and antibiotic exposure, shaped dysbiosis. Notably, of the three body compartments, unsupervised clusters of lung microbiota diversity and composition independently predicted survival, transcending clinical predictors, organ dysfunction severity, and host-response sub-phenotypes. These independent associations of lung microbiota may serve as valuable biomarkers for prognostication and treatment decisions in critically ill patients. Insights into the dynamics of the microbiome during critical illness highlight the potential for microbiota-targeted interventions in precision medicine.
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Affiliation(s)
- Georgios D. Kitsios
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Khaled Sayed
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
- Department of Electrical and Computer Engineering & Computer Science, University of New Haven, West Haven, CT, USA
| | - Adam Fitch
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Haopu Yang
- School of Medicine, Tsinghua University, Beijing, China
| | - Noel Britton
- Division of Pulmonary Critical Care Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Faraaz Shah
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Veteran’s Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - William Bain
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Veteran’s Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - John W. Evankovich
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Shulin Qin
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Xiaohong Wang
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kelvin Li
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Asha Patel
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yingze Zhang
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Josiah Radder
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Charles Dela Cruz
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daniel A Okin
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ching-Ying Huang
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Daria van Tyne
- Division of Infectious Diseases, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Barbara Methé
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Peggy Lai
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Alison Morris
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Bryan J. McVerry
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
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7
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Kitsios GD, Sayed K, Fitch A, Yang H, Britton N, Shah F, Bain W, Evankovich JW, Qin S, Wang X, Li K, Patel A, Zhang Y, Radder J, Cruz CD, Okin DA, Huang CY, van Tyne D, Benos PV, Methé B, Lai P, Morris A, McVerry BJ. Prognostic Insights from Longitudinal Multicompartment Study of Host-Microbiota Interactions in Critically Ill Patients. RESEARCH SQUARE 2023:rs.3.rs-3338762. [PMID: 37841841 PMCID: PMC10571606 DOI: 10.21203/rs.3.rs-3338762/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
Critical illness can disrupt the composition and function of the microbiome, yet comprehensive longitudinal studies are lacking. We conducted a longitudinal analysis of oral, lung, and gut microbiota in a large cohort of 479 mechanically ventilated patients with acute respiratory failure. Progressive dysbiosis emerged in all three body compartments, characterized by reduced alpha diversity, depletion of obligate anaerobe bacteria, and pathogen enrichment. Clinical variables, including chronic obstructive pulmonary disease, immunosuppression, and antibiotic exposure, shaped dysbiosis. Notably, of the three body compartments, unsupervised clusters of lung microbiota diversity and composition independently predicted survival, transcending clinical predictors, organ dysfunction severity, and host-response sub-phenotypes. These independent associations of lung microbiota may serve as valuable biomarkers for prognostication and treatment decisions in critically ill patients. Insights into the dynamics of the microbiome during critical illness highlight the potential for microbiota-targeted interventions in precision medicine.
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Affiliation(s)
- Georgios D. Kitsios
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Khaled Sayed
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
- Department of Electrical and Computer Engineering & Computer Science, University of New Haven, West Haven, CT, USA
| | - Adam Fitch
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Haopu Yang
- School of Medicine, Tsinghua University, Beijing, China
| | - Noel Britton
- Division of Pulmonary Critical Care Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Faraaz Shah
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Veteran’s Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - William Bain
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Veteran’s Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - John W. Evankovich
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Shulin Qin
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Xiaohong Wang
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kelvin Li
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Asha Patel
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yingze Zhang
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Josiah Radder
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Charles Dela Cruz
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daniel A Okin
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ching-Ying Huang
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Daria van Tyne
- Division of Infectious Diseases, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Barbara Methé
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Peggy Lai
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Alison Morris
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Bryan J. McVerry
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
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8
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Belizário J, Garay-Malpartida M, Faintuch J. Lung microbiome and origins of the respiratory diseases. CURRENT RESEARCH IN IMMUNOLOGY 2023; 4:100065. [PMID: 37456520 PMCID: PMC10339129 DOI: 10.1016/j.crimmu.2023.100065] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 05/08/2023] [Accepted: 06/13/2023] [Indexed: 07/18/2023] Open
Abstract
The studies on the composition of the human microbiomes in healthy individuals, its variability in the course of inflammation, infection, antibiotic therapy, diets and different pathological conditions have revealed their intra and inter-kingdom relationships. The lung microbiome comprises of major species members of the phylum Bacteroidetes, Firmicutes, Actinobacteria, Fusobacteria and Proteobacteria, which are distributed in ecological niches along nasal cavity, nasopharynx, oropharynx, trachea and in the lungs. Commensal and pathogenic species are maintained in equilibrium as they have strong relationships. Bacterial overgrowth after dysbiosis and/or imbalanced of CD4+ helper T cells, CD8+ cytotoxic T cells and regulatory T cells (Treg) populations can promote lung inflammatory reactions and distress, and consequently acute and chronic respiratory diseases. This review is aimed to summarize the latest advances in resident lung microbiome and its participation in most common pulmonary infections and pneumonia, community-acquired pneumonia (CAP), ventilator-associated pneumonia (VAP), immunodeficiency associated pneumonia, SARS-CoV-2-associated pneumonia, acute respiratory distress syndrome (ARDS) and chronic obstructive pulmonary disease (COPD). We briefly describe physiological and immunological mechanisms that selectively create advantages or disadvantages for relative growth of pathogenic bacterial species in the respiratory tract. At the end, we propose some directions and analytical methods that may facilitate the identification of key genera and species of resident and transient microbes involved in the respiratory diseases' initiation and progression.
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Affiliation(s)
- José Belizário
- School of Arts, Sciences and Humanities of the University of Sao Paulo, Rua Arlindo Bettio, 1000, São Paulo, CEP 03828-000, Brazil
| | - Miguel Garay-Malpartida
- School of Arts, Sciences and Humanities of the University of Sao Paulo, Rua Arlindo Bettio, 1000, São Paulo, CEP 03828-000, Brazil
| | - Joel Faintuch
- Department of Gastroenterology of the Clinics Hospital of the University of São Paulo, Av. Dr. Enéas de Carvalho Aguiar, 255, São Paulo, CEP 05403-000, Brazil
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Thornton CS, Carmody LA, Kalikin LM, Opron K, Caverly LJ, LiPuma JJ. Airway bacterial community composition in persons with advanced cystic fibrosis lung disease. J Cyst Fibros 2023; 22:623-629. [PMID: 36628831 DOI: 10.1016/j.jcf.2023.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 12/22/2022] [Accepted: 01/04/2023] [Indexed: 01/09/2023]
Abstract
BACKGROUND The progression of lung disease in people with cystic fibrosis (pwCF) has been associated with a decrease in the diversity of airway bacterial communities. How often low diversity communities occur in advanced CF lung disease and how they may be associated with clinical outcomes is not clear, however. METHODS We sequenced a region of the bacterial 16S ribosomal RNA gene to characterize bacterial communities in sputum from 190 pwCF with advanced lung disease (FEV1≤40% predicted), with particular attention to the prevalence and relative abundance of dominant genera. We evaluated relationships between community diversity and clinical outcomes. RESULTS Although most of the 190 pwCF with advanced lung disease had airway bacterial communities characterized by low diversity with a dominant genus, a considerable minority (40%) did not. The absence of a dominant genus, presence of methicillin-susceptible Staphylococcus aureus, and greater bacterial richness positively correlated with lung function. Higher relative abundance of the dominant genus and greater antimicrobial use negatively correlated with lung function. PwCF with a low diversity community and dominant genus had reduced lung transplant-free survival compared to those without (median survival of 1.6 vs 2.9 years). CONCLUSIONS A considerable proportion of pwCF with advanced lung disease do not have airway bacterial communities characterized by low diversity and a dominant genus and these individuals had better survival. An understanding of the antecedents of low diversity airway communities- and the impact these may have on lung disease trajectory - may provide avenues for improved management strategies.
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Affiliation(s)
- Christina S Thornton
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Lisa A Carmody
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Linda M Kalikin
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Kristopher Opron
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Lindsay J Caverly
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - John J LiPuma
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
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10
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Bustos IG, Martín-Loeches I, Acosta-González A, Chotirmall SH, Dickson RP, Reyes LF. Exploring the complex relationship between the lung microbiome and ventilator-associated pneumonia. Expert Rev Respir Med 2023; 17:889-901. [PMID: 37872770 DOI: 10.1080/17476348.2023.2273424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 10/17/2023] [Indexed: 10/25/2023]
Abstract
INTRODUCTION Understanding the presence and function of a diverse lung microbiome in acute lung infections, particularly ventilator-associated pneumonia (VAP), is still limited, evidencing significant gaps in our knowledge. AREAS COVERED In this comprehensive narrative review, we aim to elucidate the contribution of the respiratory microbiome in the development of VAP by examining the current knowledge on the interactions among microorganisms. By exploring these intricate connections, we endeavor to enhance our understanding of the disease's pathophysiology and pave the way for novel ideas and interventions in studying the respiratory tract microbiome. EXPERT OPINION The conventional perception of lungs as sterile is deprecated since it is currently recognized the existence of a diverse microbial community within them. However, despite extensive research on the role of the respiratory microbiome in healthy lungs, respiratory chronic diseases and acute lung infections such as pneumonia are not fully understood. It is crucial to investigate further the relationship between the pathophysiology of VAP and the pulmonary microbiome, elucidating the mechanisms underlying the interactions between the microbiome, host immune response and mechanical ventilation for the development of VAP.
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Affiliation(s)
- Ingrid G Bustos
- Unisabana Center for Translational Science, School of Medicine, Universidad de La Sabana, Chia, Colombia
- Doctorado de Biociencias, Department of Engineering, Universidad de la Sabana, Chia, Colombia
| | - Ignacio Martín-Loeches
- Multidisciplinary Intensive Care Research Organization (MICRO), St James's Hospital, Dublin, Ireland
| | - Alejandro Acosta-González
- Unisabana Center for Translational Science, School of Medicine, Universidad de La Sabana, Chia, Colombia
- Bioprospection Research Group (GIBP), Department of Engineering, Universidad de La Sabana, Chia, Colombia
| | - Sanjay H Chotirmall
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Department of Respiratory and Critical Care Medicine, Tan Tock Seng Hospital, Singapore, Singapore
| | - Robert P Dickson
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI, USA
- Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA
- Weil Institute for Critical Care Research & Innovation, Ann Arbor, MI, USA
| | - Luis Felipe Reyes
- Unisabana Center for Translational Science, School of Medicine, Universidad de La Sabana, Chia, Colombia
- Critical Care Department, Clinica Universidad de La Sabana, Chia, Colombia
- Pandemic Sciences Institute, University of Oxford, Oxford, UK
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11
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Kitsios GD, Nguyen VD, Sayed K, Al-Yousif N, Schaefer C, Shah FA, Bain W, Yang H, Fitch A, Li K, Wang X, Qin S, Gentry H, Zhang Y, Varon J, Arciniegas Rubio A, Englert JA, Baron RM, Lee JS, Methé B, Benos PV, Morris A, McVerry BJ. The upper and lower respiratory tract microbiome in severe aspiration pneumonia. iScience 2023; 26:106832. [PMID: 37250794 PMCID: PMC10212968 DOI: 10.1016/j.isci.2023.106832] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 01/24/2023] [Accepted: 05/03/2023] [Indexed: 05/31/2023] Open
Abstract
Uncertainty persists whether anaerobic bacteria represent important pathogens in aspiration pneumonia. In a nested case-control study of mechanically ventilated patients classified as macro-aspiration pneumonia (MAsP, n = 56), non-macro-aspiration pneumonia (NonMAsP, n = 91), and uninfected controls (n = 11), we profiled upper (URT) and lower respiratory tract (LRT) microbiota with bacterial 16S rRNA gene sequencing, measured plasma host-response biomarkers, analyzed bacterial communities by diversity and oxygen requirements, and performed unsupervised clustering with Dirichlet Multinomial Models (DMM). MAsP and NonMAsP patients had indistinguishable microbiota profiles by alpha diversity and oxygen requirements with similar host-response profiles and 60-day survival. Unsupervised DMM clusters revealed distinct bacterial clusters in the URT and LRT, with low-diversity clusters enriched for facultative anaerobes and typical pathogens, associated with higher plasma levels of SPD and sCD14 and worse 60-day survival. The predictive inter-patient variability in these bacterial profiles highlights the importance of microbiome study in patient sub-phenotyping and precision medicine approaches for severe pneumonia.
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Affiliation(s)
- Georgios D. Kitsios
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA15213, USA
- University of Pittsburgh School of Medicine, Pittsburgh, PA15213, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA15213, USA
- Acute Lung Injury Center for Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, PA15213, USA
| | - Vi D. Nguyen
- University of Pittsburgh School of Medicine, Pittsburgh, PA15213, USA
- University of California Los Angeles, Department of Medicine, Internal Medicine Residency Program, Los Angeles, CA90095, USA
| | - Khaled Sayed
- University of PittsburghDepartment of Computational & Systems Biology, Pittsburgh, PA15213, USA
- Department of Epidemiology, University of Florida, Gainesville, FL32611, USA
| | - Nameer Al-Yousif
- University of Pittsburgh Medical Center Mercy, Department of Medicine, Pittsburgh, PA15219, USA
| | - Caitlin Schaefer
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA15213, USA
- Acute Lung Injury Center for Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, PA15213, USA
| | - Faraaz A. Shah
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA15213, USA
- University of Pittsburgh School of Medicine, Pittsburgh, PA15213, USA
- Acute Lung Injury Center for Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, PA15213, USA
- Veteran’s Affairs Pittsburgh Healthcare System, Pittsburgh, PA15240, USA
| | - William Bain
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA15213, USA
- University of Pittsburgh School of Medicine, Pittsburgh, PA15213, USA
- Acute Lung Injury Center for Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, PA15213, USA
- Veteran’s Affairs Pittsburgh Healthcare System, Pittsburgh, PA15240, USA
| | - Haopu Yang
- University of Pittsburgh School of Medicine, Pittsburgh, PA15213, USA
- School of Medicine, Tsinghua University, Beijing, China
| | - Adam Fitch
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA15213, USA
| | - Kelvin Li
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA15213, USA
| | - Xiaohong Wang
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA15213, USA
| | - Shulin Qin
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA15213, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA15213, USA
| | - Heather Gentry
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA15213, USA
| | - Yingze Zhang
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA15213, USA
- Acute Lung Injury Center for Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, PA15213, USA
| | - Jack Varon
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA02115, USA
| | - Antonio Arciniegas Rubio
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA02115, USA
| | - Joshua A. Englert
- Division of Pulmonary, Critical Care, and Sleep Medicine, The Ohio State University Wexner Medical Center, Columbus, OH43210, USA
| | - Rebecca M. Baron
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA02115, USA
| | - Janet S. Lee
- Division of Pulmonary and Critical Care Medicine, Washington University School of Medicine, St. Louis, MO63110, USA
| | - Barbara Methé
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA15213, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA15213, USA
| | - Panayiotis V. Benos
- Department of Epidemiology, University of Florida, Gainesville, FL32611, USA
| | - Alison Morris
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA15213, USA
- University of Pittsburgh School of Medicine, Pittsburgh, PA15213, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA15213, USA
- Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA15213, USA
| | - Bryan J. McVerry
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA15213, USA
- University of Pittsburgh School of Medicine, Pittsburgh, PA15213, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA15213, USA
- Acute Lung Injury Center for Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, PA15213, USA
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12
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Kristensen M, de Koff EM, Chu ML, Groendijk S, Tramper-Stranders GA, de Winter-de Groot KM, Janssens HM, Tiddens HA, van Westreenen M, Sanders EAM, Arets BHGM, van der Ent CK, Prevaes SMPJ, Bogaert D. 16S rRNA-Based Microbiota Profiling Assists Conventional Culture Analysis of Airway Samples from Pediatric Cystic Fibrosis Patients. Microbiol Spectr 2023; 11:e0405722. [PMID: 37199622 PMCID: PMC10269535 DOI: 10.1128/spectrum.04057-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 04/21/2023] [Indexed: 05/19/2023] Open
Abstract
16S-based sequencing provides broader information on the respiratory microbial community than conventional culturing. However, it (often) lacks species- and strain-level information. To overcome this issue, we used 16S rRNA-based sequencing results from 246 nasopharyngeal samples obtained from 20 infants with cystic fibrosis (CF) and 43 healthy infants, which were all 0 to 6 months old, and compared them to both standard (blind) diagnostic culturing and a 16S-sequencing-informed "targeted" reculturing approach. Using routine culturing, we almost uniquely detected Moraxella catarrhalis, Staphylococcus aureus, and Haemophilus influenzae (42%, 38%, and 33% of samples, respectively). Using the targeted reculturing approach, we were able to reculture 47% of the top-5 operational taxonomical units (OTUs) in the sequencing profiles. In total, we identified 60 species from 30 genera with a median of 3 species per sample (range, 1 to 8). We also identified up to 10 species per identified genus. The success of reculturing the top-5 genera present from the sequencing profile depended on the genus. In the case of Corynebacterium being in the top 5, we recultured them in 79% of samples, whereas for Staphylococcus, this value was only 25%. The success of reculturing was also correlated with the relative abundance of those genera in the corresponding sequencing profile. In conclusion, revisiting samples using 16S-based sequencing profiles to guide a targeted culturing approach led to the detection of more potential pathogens per sample than conventional culturing and may therefore be useful in the identification and, consequently, treatment of bacteria considered relevant for the deterioration or exacerbation of disease in patients like those with CF. IMPORTANCE Early and effective treatment of pulmonary infections in cystic fibrosis is vital to prevent chronic lung damage. Although microbial diagnostics and treatment decisions are still based on conventional culture methods, research is gradually focusing more on microbiome and metagenomic-based approaches. This study compared the results of both methods and proposed a way to combine the best of both worlds. Many species can relatively easily be recultured based on the 16S-based sequencing profile, and it provides more in-depth information about the microbial composition of a sample than that obtained through routine (blind) diagnostic culturing. Still, well-known pathogens can be missed by both routine diagnostic culture methods as well as by targeted reculture methods, sometimes even when they are highly abundant, which may be a consequence of either sample storage conditions or antibiotic treatment at the time of sampling.
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Affiliation(s)
- Maartje Kristensen
- Department of Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Emma M. de Koff
- Department of Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- Spaarne Gasthuis Academy, Spaarne Gasthuis, Hoofddorp, The Netherlands
| | - Mei Ling Chu
- Department of Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Simone Groendijk
- Department of Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Karin M. de Winter-de Groot
- Department of Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hettie M. Janssens
- Department of Pediatric Pulmonology and Allergology, Sophia Children’s Hospital, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Harm A. Tiddens
- Department of Pediatric Pulmonology and Allergology, Sophia Children’s Hospital, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Mireille van Westreenen
- Department of Medical Microbiology and Infectious Diseases, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Elisabeth A. M. Sanders
- Department of Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, The Netherlands
| | - Bert H. G. M. Arets
- Department of Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cornelis K. van der Ent
- Department of Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Sabine M. P. J. Prevaes
- Department of Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Debby Bogaert
- Department of Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
- The Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
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13
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Chen T, Zhang L, Huang W, Zong H, Li Q, Zheng Y, Lv Q, Kong D, Ren Y, Jiang Y, Li Y, Liu P. Detection of Pathogens and Antimicrobial Resistance Genes in Ventilator-Associated Pneumonia by Metagenomic Next-Generation Sequencing Approach. Infect Drug Resist 2023; 16:923-936. [PMID: 36814827 PMCID: PMC9939671 DOI: 10.2147/idr.s397755] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/26/2023] [Indexed: 02/16/2023] Open
Abstract
Background The early identification of pathogens and their antibiotic resistance are essential for the management and treatment of patients affected by ventilator-associated pneumonia (VAP). However, microbiological culture may be time-consuming and has a limited culturability of many potential pathogens. In this study, we developed a rapid nanopore-based metagenomic next-generation sequencing (mNGS) diagnostic assay for detection of VAP pathogens and antimicrobial resistance genes (ARGs). Patients and Methods Endotracheal aspirate (ETA) samples from 63 patients with suspected VAP were collected between November 2021 and July 2022. Receiver operating characteristic (ROC) curves were established to compare the pathogen identification performance of the target pathogen reads, reads percent of microbes (RPM) and relative abundance (RA). The evaluation of the accuracy of mNGS was performed comparing with the gold standard and the composite standard, respectively. Then, the ARGs were analyzed by mNGS. Results ROC curves showed that RA has the highest diagnostic value and the corresponding threshold was 9.93%. The sensitivity and specificity of mNGS test were 91.3% and 78.3%, respectively, based on the gold standard, while the sensitivity and specificity of mNGS test were 97.4% and 100%, respectively, based on the composite standard. A total of 13 patients were virus-positive based on mNGS results, while the coinfection rate increased from 27% to 46% compared to the rate obtained based on clinical findings. The mNGS test also performed well at predicting antimicrobial resistance phenotypes. Patients with a late-onset VAP had a significantly greater proportion of ARGs in their respiratory microbiome compared to those with early-onset VAP (P = 0.041). Moreover, the median turnaround time of mNGS was 4.43 h, while routine culture was 72.00 h. Conclusion In this study, we developed a workflow that can accurately detect VAP pathogens and enable prediction of antimicrobial resistance phenotypes within 5 h of sample receipt by mNGS.
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Affiliation(s)
- Ting Chen
- The PLA 307 Clinical College of Anhui Medical University, The Fifth Clinical Medical College of Anhui Medical University, Hefei, People’s Republic of China,Department of Critical Care Medicine, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, 100071, People’s Republic of China
| | - Lei Zhang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, People’s Republic of China
| | - Wenhua Huang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, People’s Republic of China
| | - Huijun Zong
- The PLA 307 Clinical College of Anhui Medical University, The Fifth Clinical Medical College of Anhui Medical University, Hefei, People’s Republic of China,Department of Critical Care Medicine, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, 100071, People’s Republic of China
| | - Qian Li
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, People’s Republic of China
| | - Yuling Zheng
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, People’s Republic of China
| | - Qingyu Lv
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, People’s Republic of China
| | - Decong Kong
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, People’s Republic of China
| | - Yuhao Ren
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, People’s Republic of China
| | - Yongqiang Jiang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, People’s Republic of China
| | - Yan Li
- The PLA 307 Clinical College of Anhui Medical University, The Fifth Clinical Medical College of Anhui Medical University, Hefei, People’s Republic of China,Department of Critical Care Medicine, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, 100071, People’s Republic of China,Correspondence: Yan Li, The PLA 307 Clinical College of Anhui Medical University, The Fifth Clinical Medical College of Anhui Medical University, Hefei, 230032, People’s Republic of China, Email
| | - Peng Liu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, People’s Republic of China,Peng Liu, Beijing Institute of Microbiology and Epidemiology, Dongdajie Road 20, Beijing, 100071, People’s Republic of China, Tel +86-010-66948487, Email
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14
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Vallianou NG, Skourtis A, Kounatidis D, Margellou E, Panagopoulos F, Geladari E, Evangelopoulos A, Jahaj E. The Role of the Respiratory Microbiome in the Pathogenesis of Aspiration Pneumonia: Implications for Diagnosis and Potential Therapeutic Choices. Antibiotics (Basel) 2023; 12:antibiotics12010140. [PMID: 36671341 PMCID: PMC9855160 DOI: 10.3390/antibiotics12010140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 01/07/2023] [Accepted: 01/10/2023] [Indexed: 01/12/2023] Open
Abstract
Although the lungs were considered to be sterile until recently, the advent of molecular biology techniques, such as polymerase chain reaction, 16 S rRNA sequencing and metagenomics has led to our expanding knowledge of the lung microbiome. These methods may be particularly useful for the identification of the causative agent(s) in cases of aspiration pneumonia, in which there is usually prior administration of antibiotics. The most common empirical treatment of aspiration pneumonia is the administration of broad-spectrum antibiotics; however, this may result in negative cultures from specimens taken from the respiratory tract. Therefore, in such cases, polymerase chain reaction or metagenomic next-generation sequencing may be life-saving. Moreover, these modern molecular methods may assist with antimicrobial stewardship. Based upon factors such as age, altered mental consciousness and recent hospitalization, there is a shift towards the predominance of aerobes, especially Gram-negative bacteria, over anaerobes in aspiration pneumonia. Thus, the therapeutic choices should be expanded to cover multi-drug resistant Gram-negative bacteria in selected cases of aspiration pneumonia.
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15
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Li L, Ma J, Li M, Cheng P, Li M, Yu Z, Zhang W, Yu Z, Sun H. Species-level respiratory microbiome profiling for etiologic diagnosis of children pneumonia using full length 16S rRNA gene sequencing. Indian J Med Microbiol 2022; 43:11-17. [PMID: 36241528 DOI: 10.1016/j.ijmmb.2022.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/20/2022] [Accepted: 09/25/2022] [Indexed: 11/05/2022]
Abstract
PURPOSE The study was conducted to analyze the role of respiratory microbiome composition in children pneumonia etiology diagnosis. METHODS The bronchoalveolar lavage fluid bacterial community between the Mycoplasma pneumoniae pneumonia (MP group, n = 13) and the pathogen negative pneumonia (N group, n = 20) children were compared using the full-length 16S rRNA gene sequencing. RESULTS Distinct bacterial communities were identified in two groups and lower α-diversity was revealed in the MP patients indicating the lower abundance microbiota composition. Dominant bacteria were Mycoplasma and Mycoplasma pneumoniae for MP patients at genus and species levels. Possible pathogens were characterized in 17 out of 20 patients in the N group by detection of higher abundance using the 16S rRNA gene sequencing. CONCLUSIONS The high taxonomic resolution of full-length 16S rRNA gene sequencing assists in improving characterization of potential pathogens, and more studies are necessary to further evaluate the prognostic roles of specific bacteria in the pathogenicity of pneumonia.
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Affiliation(s)
- Lifeng Li
- Henan International Joint Laboratory of Children's Infectious Diseases, Department of Neonatology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Jiayue Ma
- Henan International Joint Laboratory of Children's Infectious Diseases, Department of Neonatology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Min Li
- Department of Respiratory, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Ping Cheng
- Henan International Joint Laboratory of Children's Infectious Diseases, Department of Neonatology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Mingchao Li
- Henan International Joint Laboratory of Children's Infectious Diseases, Department of Neonatology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Zengyuan Yu
- Henan International Joint Laboratory of Children's Infectious Diseases, Department of Neonatology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Wancun Zhang
- Henan International Joint Laboratory of Children's Infectious Diseases, Department of Neonatology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Zhidan Yu
- Henan International Joint Laboratory of Children's Infectious Diseases, Department of Neonatology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China
| | - Huiqing Sun
- Henan International Joint Laboratory of Children's Infectious Diseases, Department of Neonatology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, 450018, China.
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16
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Ni Q, Dong S, Xing B, Zeng B, Kong F, Xu H, Yao Y, Li D, Zhang M, Fan X, Yang D, Yang M, Xie M. Oral and fecal microbiome of confiscated Bengal slow lorises in response to confinement duration. Front Microbiol 2022; 13:941261. [PMID: 36238588 PMCID: PMC9553000 DOI: 10.3389/fmicb.2022.941261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 08/22/2022] [Indexed: 11/13/2022] Open
Abstract
Slow lorises are small arboreal and nocturnal primates. Due to the illegal trade, a large number of slow lorises were confiscated into wildlife sanctuaries or rescue centers. The re-release has been considered a preferable approach for alleviating the captive pressure, but inappropriate and long-term confinement make it difficult to achieve this goal. In this study, we investigated and compared the fecal and oral microbiome of Bengal slow lorises (Nycticebus bengalensis) under long-term captivity (LC) and short-term captivity (SC) groups based on 16s rRNA high-throughput gene sequencing. The oral microbiome displayed higher Chao1 richness but lower Shannon and Simpson indices than the fecal microbiome. The Bengal slow lorises under long-term captivity had abundant pathogenic genera in both gut and oral microbiomes, such as Desulfovibrio, Actinomyces, Capnocytophaga, Neisseria, and Fusobacterium, while some specific bacterial taxa associated with intestinal balance were more enriched in the SC group. Due to the plant gum scarcity in the diet, both groups had a low abundance of Bifidobacterium. Function profile prediction indicated that the LC group was enriched with genetic information processing and metabolism pathways due to the stable food intake. The increased membrane transport and xenobiotic metabolism and degradation functions in the SC group could be explained by the function of the host microbiome in facilitating adaptation to changing environments and diets. The results demonstrated that the oral microbiome had the potential to be used as a regular surveillance tool. Also, current captive management should be improved to ensure reintroduction success.
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Affiliation(s)
- Qingyong Ni
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
- *Correspondence: Qingyong Ni,
| | - Shasha Dong
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Bolin Xing
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Bo Zeng
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Fanli Kong
- College of Life Science, Sichuan Agricultural University, Yaan, China
| | - Huailiang Xu
- College of Life Science, Sichuan Agricultural University, Yaan, China
| | - Yongfang Yao
- College of Life Science, Sichuan Agricultural University, Yaan, China
| | - Diyan Li
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Mingwang Zhang
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Xiaolan Fan
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Deying Yang
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Mingyao Yang
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, China
| | - Meng Xie
- College of Life Science, Sichuan Agricultural University, Yaan, China
- Meng Xie,
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17
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Cifuentes EA, Sierra MA, Yepes AF, Baldión AM, Rojas JA, Álvarez-Moreno CA, Anzola JM, Zambrano MM, Huertas MG. Endotracheal tube microbiome in hospitalized patients defined largely by hospital environment. Respir Res 2022; 23:168. [PMID: 35751068 PMCID: PMC9233342 DOI: 10.1186/s12931-022-02086-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 06/13/2022] [Indexed: 11/16/2022] Open
Abstract
Background Studies of the respiratory tract microbiome primarily focus on airway and lung microbial diversity, but it is still unclear how these microbial communities may be affected by intubation and long periods in intensive care units (ICU), an aspect that today could aid in the understanding of COVID19 progression and disease severity. This study aimed to explore and characterize the endotracheal tube (ETT) microbiome by analyzing ETT-associated microbial communities. Methods This descriptive study was carried out on adult patients subjected to invasive mechanical ventilation from 2 to 21 days. ETT samples were obtained from 115 patients from ICU units in two hospitals. Bacteria isolated from endotracheal tubes belonging to the ESKAPE group were analyzed for biofilm formation using crystal violet quantification. Microbial profiles were obtained using Illumina sequencing of 16S rRNA gene. Results The ETT microbiome was mainly composed by the phyla Proteobacteria, Firmicutes and Bacteroidetes. Microbiome composition correlated with the ICU in which patients were hospitalized, while intubation time and diagnosis of ventilator-associated pneumonia (VAP) did not show any significant association. Conclusion These results suggest that the ICU environment, or medical practices, could be a key to microbial colonization and have a direct influence on the ETT microbiomes of patients that require mechanical ventilation. Supplementary Information The online version contains supplementary material available at 10.1186/s12931-022-02086-7.
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Affiliation(s)
| | - Maria A Sierra
- Corporación CorpoGen Research Center, Bogotá, Colombia.,Tri-Institutional Computational Biology & Medicine Program, Weill Cornell Medicine, New York, NY, USA
| | | | | | | | | | - Juan Manuel Anzola
- Corporación CorpoGen Research Center, Bogotá, Colombia.,Universidad Central, Bogotá, Colombia
| | - María Mercedes Zambrano
- Corporación CorpoGen Research Center, Bogotá, Colombia.,Universidad Central, Bogotá, Colombia
| | - Monica G Huertas
- Corporación CorpoGen Research Center, Bogotá, Colombia. .,Universidad Pedagógica y Tecnológica de Colombia, Tunja, Boyacá, Colombia.
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18
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Qian M, Zhu B, Zhan Y, Wang L, Shen Q, Zhang M, Yue L, Wu D, Chen H, Wang X, Cheng Y. Analysis of Negative Results of Metagenomics Next-Generation Sequencing in Clinical Practice. Front Cell Infect Microbiol 2022; 12:892076. [PMID: 35651750 PMCID: PMC9149223 DOI: 10.3389/fcimb.2022.892076] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 04/19/2022] [Indexed: 12/16/2022] Open
Abstract
BackgroundMetagenomics next-generation sequencing (mNGS) has been increasingly used in the clinic, which provides a powerful tool for the etiological diagnosis of infectious diseases. Precise treatment can be carried out according to the positive mNGS results. However, the role of negative results of mNGS remains poorly defined in clinical practice.MethodsThe results of 1,021 samples from patients who received the mNGS test at Zhongshan Hospital, Fudan University, between January 2019 and December 2019 were analyzed.ResultsThere were 308 samples (30.17%) of negative results included in the current study. The top 2 types of negative samples were blood (130/308) and tissue (63/308), which also accounted for the highest negative proportion in diseases. Sputum and bronchoalveolar lavage fluid (BALF) were more likely to have positive results. In false-negative results (defined as negative in mNGS test but reported positive in other sample types or assays), 118 samples were found when compared to regular microbiological assays. The negative predictive value (NPV) of mNGS was 95.79% [95%CI, 93.8%–97.8%] as compared to culture and smear. Mycobacterium, Aspergillus, and Mycoplasma ranked as the top 3 microorganisms on the undetected pathogen list.ConclusionsThe present data indicate that when the mNGS test is negative, the negative prediction accuracy rate of the original specimen is significant. However, other laboratory assays results and clinical presentations should always be carefully considered prior to drawing a diagnosis.
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Affiliation(s)
- Mengjia Qian
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Bijun Zhu
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yanxia Zhan
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Lingyan Wang
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Qi Shen
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Miaomiao Zhang
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Lei Yue
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Duojiao Wu
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, China
| | - Hao Chen
- Department of Thoracic Surgery, Zhongshan Hospital Xuhui Branch, Fudan University, Shanghai, China
| | - Xiangdong Wang
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, China
- *Correspondence: Yunfeng Cheng, ; Xiangdong Wang,
| | - Yunfeng Cheng
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, China
- Department of Hematology, Zhongshan Hospital Qingpu Branch, Fudan University, Shanghai, China
- *Correspondence: Yunfeng Cheng, ; Xiangdong Wang,
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19
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Bing X, Lovelace T, Bunea F, Wegkamp M, Kasturi SP, Singh H, Benos PV, Das J. Essential Regression: A generalizable framework for inferring causal latent factors from multi-omic datasets. PATTERNS (NEW YORK, N.Y.) 2022; 3:100473. [PMID: 35607614 PMCID: PMC9122954 DOI: 10.1016/j.patter.2022.100473] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 09/17/2021] [Accepted: 03/01/2022] [Indexed: 01/19/2023]
Abstract
High-dimensional cellular and molecular profiling of biological samples highlights the need for analytical approaches that can integrate multi-omic datasets to generate prioritized causal inferences. Current methods are limited by high dimensionality of the combined datasets, the differences in their data distributions, and their integration to infer causal relationships. Here, we present Essential Regression (ER), a novel latent-factor-regression-based interpretable machine-learning approach that addresses these problems by identifying latent factors and their likely cause-effect relationships with system-wide outcomes/properties of interest. ER can integrate many multi-omic datasets without structural or distributional assumptions regarding the data. It outperforms a range of state-of-the-art methods in terms of prediction. ER can be coupled with probabilistic graphical modeling, thereby strengthening the causal inferences. The utility of ER is demonstrated using multi-omic system immunology datasets to generate and validate novel cellular and molecular inferences in a wide range of contexts including immunosenescence and immune dysregulation.
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Affiliation(s)
- Xin Bing
- Department of Statistics and Data Science, Cornell University, Ithaca, NY, USA
| | - Tyler Lovelace
- Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
- Joint CMU-Pitt PhD Program in Computational Biology, Carnegie Mellon – University of Pittsburgh, Pittsburgh, PA, USA
| | - Florentina Bunea
- Department of Statistics and Data Science, Cornell University, Ithaca, NY, USA
| | - Marten Wegkamp
- Department of Statistics and Data Science, Cornell University, Ithaca, NY, USA
- Department of Mathematics, Cornell University, Ithaca, NY, USA
| | - Sudhir Pai Kasturi
- Division of Microbiology and Immunology, Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Harinder Singh
- Center for Systems Immunology, Departments of Immunology and Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Panayiotis V. Benos
- Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jishnu Das
- Center for Systems Immunology, Departments of Immunology and Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
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20
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Assefa M. Multi-drug resistant gram-negative bacterial pneumonia: etiology, risk factors, and drug resistance patterns. Pneumonia (Nathan) 2022; 14:4. [PMID: 35509063 PMCID: PMC9069761 DOI: 10.1186/s41479-022-00096-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 04/11/2022] [Indexed: 12/27/2022] Open
Abstract
Bacterial pneumonia is one of the most serious public health issues owing to its medical and economic costs, which result in increased morbidity and mortality in people of all ages around the world. Furthermore, antimicrobial resistance has risen over time, and the advent of multi-drug resistance in GNB complicates therapy and has a detrimental impact on patient outcomes. The current review aimed to summarize bacterial pneumonia with an emphasis on gram-negative etiology, pathogenesis, risk factors, resistance mechanisms, treatment updates, and vaccine concerns to tackle the problem before it causes a serious consequence. In conclusion, the global prevalence of GNB in CAP was reported 49.7% to 83.1%, whereas in VAP patients ranged between 76.13% to 95.3%. The most commonly reported MDR-GNB causes of pneumonia were A. baumannii, K. pneumoniae, and P. aeruginosa, with A. baumannii isolated particularly in VAP patients and the elderly. In most studies, ampicillin, tetracyclines, amoxicillin-clavulanic acid, cephalosporins, and carbapenems were shown to be highly resistant. Prior MDR-GNB infection, older age, previous use of broad-spectrum antibiotics, high frequency of local antibiotic resistance, prolonged hospital stays, ICU admission, mechanical ventilation, and immunosuppression are associated with the MDR-GNB colonization. S. maltophilia was reported as a severe cause of HAP/VAP in patients with mechanically ventilated and having hematologic malignancy due to its ability of biofilm formation, site adhesion in respiratory devices, and its intrinsic and acquired drug resistance mechanisms. Effective combination therapies targeting PDR strains and drug-resistant genes, antibiofilm agents, gene-based vaccinations, and pathogen-specific lymphocytes should be developed in the future.
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Affiliation(s)
- Muluneh Assefa
- Department of Medical Microbiology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, P.O. Box 196, Gondar, Ethiopia.
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21
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Artificial Intelligence in Clinical Immunology. Artif Intell Med 2022. [DOI: 10.1007/978-3-030-64573-1_83] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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22
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Cho SY, Choi JH, Lee SH, Choi YS, Hwang SW, Kim YJ. Metataxonomic investigation of the microbial community in the trachea and oropharynx of healthy controls and diabetic patients using endotracheal tubes. PLoS One 2021; 16:e0259596. [PMID: 34739518 PMCID: PMC8570478 DOI: 10.1371/journal.pone.0259596] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 10/21/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Although the study of respiratory microbiota has been an active field of research, obtaining the appropriate respiratory samples for healthy controls remains to be a challenge. As such, this study aims to evaluate the use of endotracheal tube washing as a viable control for sputum samples. METHODS A total of 14 subjects, including 8 healthy respiratory controls and 6 diabetic patients without any respiratory disease, were enrolled in this study, during which the endotracheal tubes used in their scheduled routine surgery were collected. Pre-operative oral gargles were also collected from non-diabetic subjects. RESULTS 16S amplicon sequencing revealed similar taxa composition in endotracheal tube washings and oral gargles in the healthy control subjects, although the relative abundance of 11 genus level operational taxonomic units was significantly different between the two sample sources. The diabetic subjects showed relatively lower diversity than those of non-diabetic subjects. The proportion range of the most abundant taxa detected in each endotracheal tube washings were 10.1-33.2%. CONCLUSION Endotracheal tube washing fluid may provide healthy control samples for upper respiratory investigations without incurring any additional risk to the subject.
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Affiliation(s)
- Sun Young Cho
- Department of Laboratory Medicine, Kyung Hee University Hospital, Kyung Hee University School of Medicine, Seoul, Republic of Korea
| | - Jeong-Hyun Choi
- Department of Anesthesiology, Kyung Hee University Hospital, Kyung Hee University School of Medicine, Seoul, Republic of Korea
| | - Seung Hyeun Lee
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kyung Hee University Hospital, Kyung Hee University School of Medicine, Seoul, Republic of Korea
| | - Yong-Sung Choi
- Department of Pediatrics, Kyung Hee University Hospital, Kyung Hee University School of Medicine, Seoul, Republic of Korea
| | - Sung Wook Hwang
- Department of Anesthesiology and Pain Medicine, Kyung Hee University Hospital, Seoul, Republic of Korea
| | - Young Jin Kim
- Department of Laboratory Medicine, Kyung Hee University Hospital, Kyung Hee University School of Medicine, Seoul, Republic of Korea
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23
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Exploring the nasopharyngeal microbiota composition in infants with whooping cough: A test-negative case-control study. PLoS One 2021; 16:e0259318. [PMID: 34714887 PMCID: PMC8555781 DOI: 10.1371/journal.pone.0259318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 10/16/2021] [Indexed: 01/04/2023] Open
Abstract
Purpose The purpose of this study was to characterize the nasopharyngeal microbiota of infants with possible and confirmed pertussis compared to healthy controls. Methods This prospective study included all infants <1 year with microbiologically confirmed diagnosis of pertussis attended at a University Hospital over a 12-month period. For each confirmed case, up to 2 consecutive patients within the same age range and meeting the clinical case definition of pertussis but testing PCR-negative were included as possible cases. A third group of asymptomatic infants (healthy controls) were also included. Nasopharyngeal microbiota was characterized by sequencing the V3-V4 region of the 16S rRNA gene. Common respiratory DNA/RNA viral co-infection was tested by multiplex PCR. Results Twelve confirmed cases, 21 possible cases and 9 healthy controls were included. Confirmed whooping cough was primarily driven by detection of Bordetella with no other major changes on nasopharyngeal microbiota. Possible cases had limited abundance or absence of Bordetella and a distinctive microbiota with lower bacterial richness and diversity and higher rates of viral co-infection than both confirmed cases and healthy controls. Bordetella reads determined by 16S rRNA gene sequencing were found in all 12 confirmed cases (100%), 3 out of the 21 possible cases (14.3%) but in any healthy control. Conclusion This study supports the usefulness of 16S rRNA gene sequencing for improved sensitivity on pertussis diagnosis compared to real-time PCR and to understand other microbial changes occurring in the nasopharynx in children <1 year old with suspected whooping cough compared to healthy controls.
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24
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Tourelle KM, Boutin S, Weigand MA, Schmitt FCF. Sepsis and the Human Microbiome. Just Another Kind of Organ Failure? A Review. J Clin Med 2021; 10:jcm10214831. [PMID: 34768350 PMCID: PMC8585089 DOI: 10.3390/jcm10214831] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/17/2021] [Accepted: 10/18/2021] [Indexed: 01/05/2023] Open
Abstract
Next-generation sequencing (NGS) has been further optimised during the last years and has given us new insights into the human microbiome. The 16S rDNA sequencing, especially, is a cheap, fast, and reliable method that can reveal significantly more microorganisms compared to culture-based diagnostics. It might be a useful method for patients suffering from severe sepsis and at risk of organ failure because early detection and differentiation between healthy and harmful microorganisms are essential for effective therapy. In particular, the gut and lung microbiome in critically ill patients have been probed by NGS. For this review, an iterative approach was used. Current data suggest that an altered microbiome with a decreased alpha-diversity compared to healthy individuals could negatively influence the individual patient’s outcome. In the future, NGS may not only contribute to the diagnosis of complications. Patients at risk could also be identified before surgery or even during their stay in an intensive care unit. Unfortunately, there is still a lack of knowledge to make precise statements about what constitutes a healthy microbiome, which patients exactly have an increased perioperative risk, and what could be a possible therapy to strengthen the microbiome. This work is an iterative review that presents the current state of knowledge in this field.
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Affiliation(s)
- Kevin M. Tourelle
- Department of Anesthesiology, Heidelberg University Hospital, 420, Im Neuenheimer Feld, 69120 Heidelberg, Germany; (K.M.T.); (M.A.W.)
| | - Sebastien Boutin
- Department of Infectious Disease, Medical Microbiology and Hygiene, University Hospital, 324, Im Neuenheimer Feld, 69120 Heidelberg, Germany;
| | - Markus A. Weigand
- Department of Anesthesiology, Heidelberg University Hospital, 420, Im Neuenheimer Feld, 69120 Heidelberg, Germany; (K.M.T.); (M.A.W.)
| | - Felix C. F. Schmitt
- Department of Anesthesiology, Heidelberg University Hospital, 420, Im Neuenheimer Feld, 69120 Heidelberg, Germany; (K.M.T.); (M.A.W.)
- Correspondence:
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25
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Khan AA, Singh H, Bilal M, Ashraf MT. Microbiota, probiotics and respiratory infections: the three musketeers can tip off potential management of COVID-19. Am J Transl Res 2021; 13:10977-10993. [PMID: 34786037 PMCID: PMC8581851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 08/15/2021] [Indexed: 06/13/2023]
Abstract
Rapid infectivity of SARS-CoV2 with recent viral variants is posing a challenge in the development of robust therapeutic strategies. On the other hand, microbiota is debated for its involvement in SARS-CoV2 infection with varied opinions. Although ample data about the role of microbiota and probiotics in respiratory viral infections are available, their role in COVID-19 is limited albeit emerging rapidly. The utilization of probiotics for the management of COVID-19 is still under investigation in many clinical trials. Existing information coupled with recent COVID-19 related studies can suggest various ways to use microbiota modulation and probiotics for managing this pandemic. Present article indicates the role of microbiota modulation and probiotics in respiratory infections. In addition, scattered evidence was gathered to understand the potential of microbiota and probiotics in the management of SARS-CoV2. Gut-airway microbiota connection is already apparent in respiratory tract viral infections, including SARS-CoV2. Though few clinical trials are evaluating microbiota and probiotics for COVID-19 management, the safety evaluation must be given more serious consideration because of the possibility of opportunistic infections among COVID-19 patients. Nevertheless, the information about microbiota modulation using probiotics and prebiotics can be helpful to manage this outbreak and this review presents different aspects of this idea.
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Affiliation(s)
- Abdul Arif Khan
- Division of Microbiology, Indian Council of Medical Research-National AIDS Research InstitutePune, Maharashtra 411026, India
| | - HariOm Singh
- Division of Molecular Biology, Indian Council of Medical Research-National AIDS Research InstitutePune, Maharashtra 411026, India
| | - Muhammad Bilal
- School of Life Science and Food Engineering, Huaiyin Institute of TechnologyHuaian 223003, China
| | - Mohd Tashfeen Ashraf
- School of Biotechnology, Gautam Buddha UniversityGautam Budh Nagar, Greater Noida (UP), India
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Raghu VK, Horvat CM, Kochanek PM, Fink EL, Clark RSB, Benos PV, Au AK. Neurological Complications Acquired During Pediatric Critical Illness: Exploratory "Mixed Graphical Modeling" Analysis Using Serum Biomarker Levels. Pediatr Crit Care Med 2021; 22:906-914. [PMID: 34054117 PMCID: PMC8490289 DOI: 10.1097/pcc.0000000000002776] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Neurologic complications, consisting of the acute development of a neurologic disorder, that is, not present at admission but develops during the course of illness, can be difficult to detect in the PICU due to sedation, neuromuscular blockade, and young age. We evaluated the direct relationships of serum biomarkers and clinical variables to the development of neurologic complications. Analysis was performed using mixed graphical models, a machine learning approach that allows inference of cause-effect associations from continuous and discrete data. DESIGN Secondary analysis of a previous prospective observational study. SETTING PICU, single quaternary-care center. PATIENTS Individuals admitted to the PICU, younger than18 years old, with intravascular access via an indwelling catheter. INTERVENTIONS None. MEASUREMENTS About 101 patients were included in this analysis. Serum (days 1-7) was analyzed for glial fibrillary acidic protein, ubiquitin C-terminal hydrolase-L1, and alpha-II spectrin breakdown product 150 utilizing enzyme-linked immunosorbent assays. Serum levels of neuron-specific enolase, myelin basic protein, and S100 calcium binding protein B used in these models were reported previously. Demographic data, use of selected clinical therapies, lengths of stay, and ancillary neurologic testing (head CT, brain MRI, and electroencephalogram) results were recorded. The Mixed Graphical Model-Fast-Causal Inference-Maximum algorithm was applied to the dataset. MAIN RESULTS About 13 of 101 patients developed a neurologic complication during their critical illness. The mixed graphical model identified peak levels of the neuronal biomarker neuron-specific enolase and ubiquitin C-terminal hydrolase-L1, and the astrocyte biomarker glial fibrillary acidic protein to be the direct causal determinants for the development of a neurologic complication; in contrast, clinical variables including age, sex, length of stay, and primary neurologic diagnosis were not direct causal determinants. CONCLUSIONS Graphical models that include biomarkers in addition to clinical data are promising methods to evaluate direct relationships in the development of neurologic complications in critically ill children. Future work is required to validate and refine these models further, to determine if they can be used to predict which patients are at risk for/or with early neurologic complications.
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Affiliation(s)
- Vineet K. Raghu
- Department of Computer Science, University of Pittsburgh,
Pittsburgh, PA
| | - Christopher M. Horvat
- Department of Critical Care Medicine, University of
Pittsburgh School of Medicine, Pittsburgh, PA; Department of Pediatrics, University
of Pittsburgh School of Medicine, Pittsburgh, PA
- Safar Center for Resuscitation Research, University of
Pittsburgh School of Medicine, Pittsburgh, PA; Brain Care Institute, UPMC
Children’s Hospital of Pittsburgh, PA
| | - Patrick M. Kochanek
- Department of Critical Care Medicine, University of
Pittsburgh School of Medicine, Pittsburgh, PA; Department of Pediatrics, University
of Pittsburgh School of Medicine, Pittsburgh, PA
- Safar Center for Resuscitation Research, University of
Pittsburgh School of Medicine, Pittsburgh, PA; Brain Care Institute, UPMC
Children’s Hospital of Pittsburgh, PA
| | - Ericka L. Fink
- Department of Critical Care Medicine, University of
Pittsburgh School of Medicine, Pittsburgh, PA; Department of Pediatrics, University
of Pittsburgh School of Medicine, Pittsburgh, PA
- Safar Center for Resuscitation Research, University of
Pittsburgh School of Medicine, Pittsburgh, PA; Brain Care Institute, UPMC
Children’s Hospital of Pittsburgh, PA
| | - Robert S. B. Clark
- Department of Critical Care Medicine, University of
Pittsburgh School of Medicine, Pittsburgh, PA; Department of Pediatrics, University
of Pittsburgh School of Medicine, Pittsburgh, PA
- Safar Center for Resuscitation Research, University of
Pittsburgh School of Medicine, Pittsburgh, PA; Brain Care Institute, UPMC
Children’s Hospital of Pittsburgh, PA
| | - Panayiotis V. Benos
- Department of Computer Science, University of Pittsburgh,
Pittsburgh, PA
- Department of Computational and Systems Biology, University
of Pittsburgh, Pittsburgh PA
| | - Alicia K. Au
- Department of Critical Care Medicine, University of
Pittsburgh School of Medicine, Pittsburgh, PA; Department of Pediatrics, University
of Pittsburgh School of Medicine, Pittsburgh, PA
- Safar Center for Resuscitation Research, University of
Pittsburgh School of Medicine, Pittsburgh, PA; Brain Care Institute, UPMC
Children’s Hospital of Pittsburgh, PA
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27
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Harrigan JJ, Abdallah H, Clarke EL, Oganisian A, Roy JA, Lautenbach E, Reesey E, Wernovsky M, Tolomeo P, Morawski Z, Jacob J, Grippi MA, Kelly BJ. Respiratory microbiome disruption and risk for ventilator-associated lower respiratory tract infection. Clin Infect Dis 2021; 74:1564-1571. [PMID: 34363467 DOI: 10.1093/cid/ciab678] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Ventilator-associated lower respiratory tract infection (VA-LRTI) is a common among critically ill patients and has been associated with increased morbidity and mortality. In acute critical illness, respiratory microbiome disruption indices (MDIs) have been shown to predict risk for VA-LRTI, but their utility beyond the first days of critical illness is unknown. We sought to characterize how MDIs previously shown to predict VA-LRTI at initiation of mechanical ventilation change with prolonged mechanical ventilation, and if they remain associated with VA-LRTI risk. METHODS We developed a cohort of 83 subjects admitted to a long-term acute care hospital due to their prolonged dependence on mechanical ventilation; performed dense, longitudinal sampling of the lower respiratory tract, collecting 1066 specimens; and characterized the lower respiratory microbiome by 16S rRNA sequencing as well as total bacterial abundance by 16S rRNA qPCR. RESULTS Cross-sectional MDIs, including low Shannon diversity and high total bacterial abundance, were associated with risk for VA-LRTI, but the associations had wide posterior credible intervals. Persistent lower respiratory microbiome disruption showed a more robust association with VA-LRTI risk, with each day of (base e) Shannon diversity < 2.0 associated with a VA-LRTI odds ratio of 1.36 (95% credible interval 1.10 to 1.72). The observed association was consistent across multiple clinical definitions of VA-LRTI. CONCLUSIONS Cross-sectional MDIs have limited ability to discriminate VA-LRTI risk during prolonged mechanical ventilation, but persistent lower respiratory tract microbiome disruption, best characterized by consecutive days with low Shannon diversity, may identify a population at high risk for infection and may help target infection prevention interventions.
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Affiliation(s)
- James J Harrigan
- Division of Infectious Diseases, Department of Medicine; , Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Hatem Abdallah
- Division of Infectious Diseases, Department of Medicine; , Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Erik L Clarke
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arman Oganisian
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jason A Roy
- Department of Biostatistics and Epidemiology, Rutgers School of Public Health, Ruthers University, Piscataway, NJ, USA
| | - Ebbing Lautenbach
- Division of Infectious Diseases, Department of Medicine; , Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Emily Reesey
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Magda Wernovsky
- Division of Infectious Diseases, Department of Medicine; , Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pam Tolomeo
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Zygmunt Morawski
- Good Shepherd Penn-Partners Specialty Hospital, Philadelphia, PA, USA
| | - Jerry Jacob
- Division of Infectious Diseases, Department of Medicine; , Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Good Shepherd Penn-Partners Specialty Hospital, Philadelphia, PA, USA
| | - Michael A Grippi
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Good Shepherd Penn-Partners Specialty Hospital, Philadelphia, PA, USA
| | - Brendan J Kelly
- Division of Infectious Diseases, Department of Medicine; , Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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McGinniss JE, Whiteside SA, Simon-Soro A, Diamond JM, Christie JD, Bushman FD, Collman RG. The lung microbiome in lung transplantation. J Heart Lung Transplant 2021; 40:733-744. [PMID: 34120840 PMCID: PMC8335643 DOI: 10.1016/j.healun.2021.04.014] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 04/13/2021] [Accepted: 04/19/2021] [Indexed: 12/21/2022] Open
Abstract
Culture-independent study of the lower respiratory tract after lung transplantation has enabled an understanding of the microbiome - that is, the collection of bacteria, fungi, and viruses, and their respective gene complement - in this niche. The lung has unique features as a microbial environment, with balanced entry from the upper respiratory tract, clearance, and local replication. There are many pressures impacting the microbiome after transplantation, including donor allograft factors, recipient host factors such as underlying disease and ongoing exposure to the microbe-rich upper respiratory tract, and transplantation-related immunosuppression, antimicrobials, and postsurgical changes. To date, we understand that the lung microbiome after transplant is dysbiotic; that is, it has higher biomass and altered composition compared to a healthy lung. Emerging data suggest that specific microbiome features may be linked to host responses, both immune and non-immune, and clinical outcomes such as chronic lung allograft dysfunction (CLAD), but many questions remain. The goal of this review is to put into context our burgeoning understanding of the lung microbiome in the postlung transplant patient, the interactions between microbiome and host, the role the microbiome may play in post-transplant complications, and critical outstanding research questions.
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Affiliation(s)
- John E McGinniss
- Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Samantha A Whiteside
- Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Aurea Simon-Soro
- Department of Orthodontics and Divisions of Community Oral Health and Pediatric Dentistry, School of Dental Medicine at the University of Pennsylvania
| | - Joshua M Diamond
- Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jason D Christie
- Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Fredrick D Bushman
- Department of Microbiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Ronald G Collman
- Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; Department of Microbiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
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29
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Kitsios GD, Kotok D, Yang H, Finkelman MA, Zhang Y, Britton N, Li X, Levochkina MS, Wagner AK, Schaefer C, Villandre JJ, Guo R, Evankovich JW, Bain W, Shah F, Zhang Y, Methé BA, Benos PV, McVerry BJ, Morris A. Plasma 1,3-β-d-glucan levels predict adverse clinical outcomes in critical illness. JCI Insight 2021; 6:e141277. [PMID: 34128840 PMCID: PMC8410081 DOI: 10.1172/jci.insight.141277] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 06/09/2021] [Indexed: 01/19/2023] Open
Abstract
BACKGROUNDThe fungal cell wall constituent 1,3-β-d-glucan (BDG) is a pathogen-associated molecular pattern that can stimulate innate immunity. We hypothesized that BDG from colonizing fungi in critically ill patients may translocate into the systemic circulation and be associated with host inflammation and outcomes.METHODSWe enrolled 453 mechanically ventilated patients with acute respiratory failure (ARF) without invasive fungal infection and measured BDG, innate immunity, and epithelial permeability biomarkers in serially collected plasma samples.RESULTSCompared with healthy controls, patients with ARF had significantly higher BDG levels (median [IQR], 26 pg/mL [15-49 pg/mL], P < 0.001), whereas patients with ARF with high BDG levels (≥40 pg/mL, 31%) had higher odds for assignment to the prognostically adverse hyperinflammatory subphenotype (OR [CI], 2.88 [1.83-4.54], P < 0.001). Baseline BDG levels were predictive of fewer ventilator-free days and worse 30-day survival (adjusted P < 0.05). Integrative analyses of fungal colonization and epithelial barrier disruption suggested that BDG may translocate from either the lung or gut compartment. We validated the associations between plasma BDG and host inflammatory responses in 97 hospitalized patients with COVID-19.CONCLUSIONBDG measurements offered prognostic information in critically ill patients without fungal infections. Further research in the mechanisms of translocation and innate immunity recognition and stimulation may offer new therapeutic opportunities in critical illness.FUNDINGUniversity of Pittsburgh Clinical and Translational Science Institute, COVID-19 Pilot Award and NIH grants (K23 HL139987, U01 HL098962, P01 HL114453, R01 HL097376, K24 HL123342, U01 HL137159, R01 LM012087, K08HK144820, F32 HL142172, K23 GM122069).
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Affiliation(s)
- Georgios D Kitsios
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Center for Medicine and the Microbiome and.,Acute Lung Injury Center of Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Daniel Kotok
- Department of Pulmonary and Critical Care Medicine, Cleveland Clinic Florida, Weston Hospital, Weston, Florida, USA
| | - Haopu Yang
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,School of Medicine, Tsinghua University, Beijing, China.,Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | | | - Yonglong Zhang
- Associates of Cape Cod Inc., East Falmouth, Massachusetts, USA
| | - Noel Britton
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Center for Medicine and the Microbiome and
| | - Xiaoyun Li
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Marina S Levochkina
- Department of Infectious Diseases and Microbiology and.,Departments of Physical Medicine and Rehabilitation, Neuroscience, and Clinical and Translational Science, Center for Neuroscience, Safar Center for Resuscitation Research, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Amy K Wagner
- Departments of Physical Medicine and Rehabilitation, Neuroscience, and Clinical and Translational Science, Center for Neuroscience, Safar Center for Resuscitation Research, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Caitlin Schaefer
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - John J Villandre
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Rui Guo
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Department of Emergency and Critical Care Medicine, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - John W Evankovich
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Acute Lung Injury Center of Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - William Bain
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Acute Lung Injury Center of Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, USA
| | - Faraaz Shah
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Acute Lung Injury Center of Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, USA
| | - Yingze Zhang
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Acute Lung Injury Center of Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Barbara A Methé
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Center for Medicine and the Microbiome and
| | - Panayiotis V Benos
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Bryan J McVerry
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Center for Medicine and the Microbiome and.,Acute Lung Injury Center of Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Alison Morris
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.,Center for Medicine and the Microbiome and.,Acute Lung Injury Center of Excellence, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
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30
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An inter-laboratory study to investigate the impact of the bioinformatics component on microbiome analysis using mock communities. Sci Rep 2021; 11:10590. [PMID: 34012005 PMCID: PMC8134577 DOI: 10.1038/s41598-021-89881-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 04/23/2021] [Indexed: 11/08/2022] Open
Abstract
Despite the advent of whole genome metagenomics, targeted approaches (such as 16S rRNA gene amplicon sequencing) continue to be valuable for determining the microbial composition of samples. Amplicon microbiome sequencing can be performed on clinical samples from a normally sterile site to determine the aetiology of an infection (usually single pathogen identification) or samples from more complex niches such as human mucosa or environmental samples where multiple microorganisms need to be identified. The methodologies are frequently applied to determine both presence of micro-organisms and their quantity or relative abundance. There are a number of technical steps required to perform microbial community profiling, many of which may have appreciable precision and bias that impacts final results. In order for these methods to be applied with the greatest accuracy, comparative studies across different laboratories are warranted. In this study we explored the impact of the bioinformatic approaches taken in different laboratories on microbiome assessment using 16S rRNA gene amplicon sequencing results. Data were generated from two mock microbial community samples which were amplified using primer sets spanning five different variable regions of 16S rRNA genes. The PCR-sequencing analysis included three technical repeats of the process to determine the repeatability of their methods. Thirteen laboratories participated in the study, and each analysed the same FASTQ files using their choice of pipeline. This study captured the methods used and the resulting sequence annotation and relative abundance output from bioinformatic analyses. Results were compared to digital PCR assessment of the absolute abundance of each target representing each organism in the mock microbial community samples and also to analyses of shotgun metagenome sequence data. This ring trial demonstrates that the choice of bioinformatic analysis pipeline alone can result in different estimations of the composition of the microbiome when using 16S rRNA gene amplicon sequencing data. The study observed differences in terms of both presence and abundance of organisms and provides a resource for ensuring reproducible pipeline development and application. The observed differences were especially prevalent when using custom databases and applying high stringency operational taxonomic unit (OTU) cut-off limits. In order to apply sequencing approaches with greater accuracy, the impact of different analytical steps needs to be clearly delineated and solutions devised to harmonise microbiome analysis results.
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31
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Raghu VK, Ge X, Balajiee A, Shirer DJ, Das I, Benos PV, Chrysanthis PK. A Pipeline for Integrated Theory and Data-Driven Modeling of Biomedical Data. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2021; 18:811-822. [PMID: 32841121 PMCID: PMC8237279 DOI: 10.1109/tcbb.2020.3019237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Genome sequencing technologies have the potential to transform clinical decision making and biomedical research by enabling high-throughput measurements of the genome at a granular level. However, to truly understand mechanisms of disease and predict the effects of medical interventions, high-throughput data must be integrated with demographic, phenotypic, environmental, and behavioral data from individuals. Further, effective knowledge discovery methods must infer relationships between these data types. We recently proposed a pipeline (CausalMGM) to achieve this. CausalMGM uses probabilistic graphical models to infer the relationships between variables in the data; however, CausalMGM's graphical structure learning algorithm can only handle small datasets efficiently. We propose a new methodology (piPref-Div) that selects the most informative variables for CausalMGM, enabling it to scale. We validate the efficacy of piPref-Div against other feature selection methods and demonstrate how the use of the full pipeline improves breast cancer outcome prediction and provides biologically interpretable views of gene expression data.
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32
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Mourani PM, Sontag MK, Williamson KM, Harris JK, Reeder R, Locandro C, Carpenter TC, Maddux AB, Ziegler K, Simões EAF, Osborne CM, Ambroggio L, Leroue MK, Robertson CE, Langelier C, DeRisi JL, Kamm J, Hall MW, Zuppa AF, Carcillo J, Meert K, Sapru A, Pollack MM, McQuillen P, Notterman DA, Dean JM, Wagner BD. Temporal airway microbiome changes related to ventilator-associated pneumonia in children. Eur Respir J 2021; 57:13993003.01829-2020. [PMID: 33008935 DOI: 10.1183/13993003.01829-2020] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 09/02/2020] [Indexed: 12/27/2022]
Abstract
We sought to determine whether temporal changes in the lower airway microbiome are associated with ventilator-associated pneumonia (VAP) in children.Using a multicentre prospective study of children aged 31 days to 18 years requiring mechanical ventilation support for >72 h, daily tracheal aspirates were collected and analysed by sequencing of the 16S rRNA gene. VAP was assessed using 2008 Centers for Disease Control and Prevention paediatric criteria. The association between microbial factors and VAP was evaluated using joint longitudinal time-to-event modelling, matched case-control comparisons and unsupervised clustering.Out of 366 eligible subjects, 66 (15%) developed VAP at a median of 5 (interquartile range 3-5) days post intubation. At intubation, there was no difference in total bacterial load (TBL), but Shannon diversity and the relative abundance of Streptococcus, Lactobacillales and Prevotella were lower for VAP subjects versus non-VAP subjects. However, higher TBL on each sequential day was associated with a lower hazard (hazard ratio 0.39, 95% CI 0.23-0.64) for developing VAP, but sequential values of diversity were not associated with VAP. Similar findings were observed from the matched analysis and unsupervised clustering. The most common dominant VAP pathogens included Prevotella species (19%), Pseudomonas aeruginosa (14%) and Streptococcus mitis/pneumoniae (10%). Mycoplasma and Ureaplasma were also identified as dominant organisms in several subjects.In mechanically ventilated children, changes over time in microbial factors were marginally associated with VAP risk, although these changes were not suitable for predicting VAP in individual patients. These findings suggest that focusing exclusively on pathogen burden may not adequately inform VAP diagnosis.
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Affiliation(s)
- Peter M Mourani
- Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO, USA
| | - Marci K Sontag
- Epidemiology, University of Colorado, Colorado School of Public Health, Aurora, CO, USA
| | - Kayla M Williamson
- Biostatistics and Informatics, University of Colorado, Colorado School of Public Health, Aurora, CO, USA
| | - J Kirk Harris
- Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO, USA
| | - Ron Reeder
- Pediatrics, University of Utah, Salt Lake City, UT, USA
| | | | - Todd C Carpenter
- Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO, USA
| | - Aline B Maddux
- Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO, USA
| | - Katherine Ziegler
- Epidemiology, University of Colorado, Colorado School of Public Health, Aurora, CO, USA
| | - Eric A F Simões
- Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO, USA.,Epidemiology, University of Colorado, Colorado School of Public Health, Aurora, CO, USA
| | - Christina M Osborne
- Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO, USA
| | - Lilliam Ambroggio
- Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO, USA.,Epidemiology, University of Colorado, Colorado School of Public Health, Aurora, CO, USA
| | - Matthew K Leroue
- Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO, USA
| | - Charles E Robertson
- Medicine, Division of Infectious Diseases, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO, USA
| | - Charles Langelier
- Medicine, Division of Infectious Diseases, University of California San Francisco, San Francisco, CA, USA.,Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Joseph L DeRisi
- Chan Zuckerberg Biohub, San Francisco, CA, USA.,Dept of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Jack Kamm
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Mark W Hall
- Dept of Pediatrics, Nationwide Children's Hospital, Columbus, OH, USA
| | - Athena F Zuppa
- Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Kathleen Meert
- Pediatrics, Children's Hospital of Michigan, Detroit, MI, USA
| | - Anil Sapru
- Pediatrics, University of California Los Angeles, Los Angeles, CA, USA
| | - Murray M Pollack
- Pediatrics, Children's National Medical Center and George Washington School of Medicine and Health Sciences, Washington, DC, USA
| | - Patrick McQuillen
- Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | | | | | - Brandie D Wagner
- Biostatistics and Informatics, University of Colorado, Colorado School of Public Health, Aurora, CO, USA
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Sazal M, Stebliankin V, Mathee K, Yoo C, Narasimhan G. Causal effects in microbiomes using interventional calculus. Sci Rep 2021; 11:5724. [PMID: 33707536 PMCID: PMC7970971 DOI: 10.1038/s41598-021-84905-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 02/23/2021] [Indexed: 01/31/2023] Open
Abstract
Causal inference in biomedical research allows us to shift the paradigm from investigating associational relationships to causal ones. Inferring causal relationships can help in understanding the inner workings of biological processes. Association patterns can be coincidental and may lead to wrong conclusions about causality in complex systems. Microbiomes are highly complex, diverse, and dynamic environments. Microbes are key players in human health and disease. Hence knowledge of critical causal relationships among the entities in a microbiome, and the impact of internal and external factors on microbial abundance and their interactions are essential for understanding disease mechanisms and making appropriate treatment recommendations. In this paper, we employ causal inference techniques to understand causal relationships between various entities in a microbiome, and to use the resulting causal network to make useful computations. We introduce a novel pipeline for microbiome analysis, which includes adding an outcome or "disease" variable, and then computing the causal network, referred to as a "disease network", with the goal of identifying disease-relevant causal factors from the microbiome. Internventional techniques are then applied to the resulting network, allowing us to compute a measure called the causal effect of one or more microbial taxa on the outcome variable or the condition of interest. Finally, we propose a measure called causal influence that quantifies the total influence exerted by a microbial taxon on the rest of the microiome. Our pipeline is robust, sensitive, different from traditional approaches, and able to predict interventional effects without any controlled experiments. The pipeline can be used to identify potential eubiotic and dysbiotic microbial taxa in a microbiome. We validate our results using synthetic data sets and using results on real data sets that were previously published.
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Affiliation(s)
- Musfiqur Sazal
- grid.65456.340000 0001 2110 1845Bioinformatics Research Group (BioRG), Florida International University, Miami, 33199 USA
| | - Vitalii Stebliankin
- grid.65456.340000 0001 2110 1845Bioinformatics Research Group (BioRG), Florida International University, Miami, 33199 USA
| | - Kalai Mathee
- grid.65456.340000 0001 2110 1845Herbert Wertheim College of Medicine, Florida International University, Miami, 33199 USA ,grid.65456.340000 0001 2110 1845Biomolecular Sciences Institute, Florida International University, Miami, 33199 USA
| | - Changwon Yoo
- grid.65456.340000 0001 2110 1845Department of Biostatistics, Florida International University, Miami, 33199 USA
| | - Giri Narasimhan
- grid.65456.340000 0001 2110 1845Bioinformatics Research Group (BioRG), Florida International University, Miami, 33199 USA ,grid.65456.340000 0001 2110 1845Biomolecular Sciences Institute, Florida International University, Miami, 33199 USA
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34
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Shiraishi Y, Kryukov K, Tomomatsu K, Sakamaki F, Inoue S, Nakagawa S, Imanishi T, Asano K. Diagnosis of pleural empyema/parapneumonic effusion by next-generation sequencing. Infect Dis (Lond) 2021; 53:450-459. [PMID: 33689538 DOI: 10.1080/23744235.2021.1892178] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
BACKGROUND Although a microbiological diagnosis of pleural infection is clinically important, it is often complicated by prior antibiotic treatment and/or difficulties with culturing some bacterial species. Therefore, we aimed to identify probable causative bacteria in pleural empyema/parapneumonic effusions by combining 16S ribosomal RNA (rRNA) gene amplification and next-generation sequencing (NGS). METHODS Pleural fluids were collected from 19 patients with infectious effusions and nine patients with non-infectious malignant effusions. We analysed DNA extracted from the pleural fluid supernatant by NGS using the Genome Search Toolkit and GenomeSync database, either directly or after PCR amplification of the 16S rRNA gene. Infectious and non-infectious effusions were distinguished by semi-quantitative PCR of the 16S rRNA gene. RESULTS Only 8 (42%) effusions were culture-positive, however, NGS of the 16S rRNA gene amplicon identified 14 anaerobes and 7 aerobes/facultative anaerobes in all patients, including Streptococcus sp. (n = 6), Fusobacterium sp. (n = 5), Porphyromonas sp. (n = 5), and Prevotella sp. (n = 4), accounting for >10% of the total genomes. The culture and NGS results were discordant for 3 out of 8 patients, all of whom had previously been treated with antibiotics. Total (2ΔCT value in semi-quantitative PCR of the 16S rRNA gene) and specific (total bacterial load multiplied by the proportion of primary bacteria in NGS) bacterial loads could efficiently distinguish empyema/parapneumonic effusion from non-infectious effusion. CONCLUSION Combining NGS with semi-quantitative PCR can facilitate the diagnosis of pleural empyema/parapneumonic effusion and its causal bacteria.
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Affiliation(s)
- Yoshiki Shiraishi
- Division of Pulmonary Medicine, Department of Medicine, Tokai University School of Medicine, Isehara, Japan
| | - Kirill Kryukov
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Japan.,Department of Genomics and Evolutionary Biology, National Institute of Genetics, Mishima, Japan
| | - Katsuyoshi Tomomatsu
- Division of Pulmonary Medicine, Department of Medicine, Tokai University School of Medicine, Isehara, Japan
| | - Fumio Sakamaki
- Division of Respiratory Disease, Department of Medicine, Tokai University Hachioji Hospital, Tokyo, Japan
| | - Shigeaki Inoue
- Department of Emergency and Critical Care Medicine, Tokai University School of Medicine, Isehara, Japan
| | - So Nakagawa
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Japan
| | - Tadashi Imanishi
- Department of Molecular Life Science, Tokai University School of Medicine, Isehara, Japan
| | - Koichiro Asano
- Division of Pulmonary Medicine, Department of Medicine, Tokai University School of Medicine, Isehara, Japan
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35
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Detection of associated bacteria in aspiration pneumonia and lung abscesses using partial 16S rRNA gene amplicon sequencing. Anaerobe 2021; 69:102325. [PMID: 33540111 DOI: 10.1016/j.anaerobe.2021.102325] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 01/02/2021] [Accepted: 01/19/2021] [Indexed: 11/24/2022]
Abstract
OBJECTIVES Lower respiratory tract infections (LRTIs) are often caused by the patient's own oral commensal bacteria. Causative bacteria must be identified to select the appropriate antimicrobial agents; however, the pathogens are identified via routine culture methods in only approximately half of LRTI cases. METHODS To investigate LRTI-associated bacteria, we conducted culture testing under aerobic and anaerobic conditions using culture-independent partial 16S rRNA gene amplicon sequencing analysis using a high-throughput sequencer in cases of aspiration pneumonia and lung abscesses. RESULTS Culture testing of 17 aspiration pneumonia cases revealed Streptococcus spp. (n = 13), Prevotella spp. (n = 9), and Veillonella spp. (n = 8); 16S rRNA analysis of these cases yielded Streptococcus spp. (n = 16), Veillonella spp. (n = 12), Haemophilus spp. (n = 12), Prevotella spp. (n = 11), and Rothia spp. (n = 11). Culture testing of 8 lung abscess cases revealed Streptococcus spp. (n = 7) and Fusobacterium spp. (n = 4); 16S rRNA analysis of these cases yielded Fusobacterium spp. (n = 8), Prevotella spp. (n = 7), Streptococcus spp. (n = 6), and Porphyromonas spp. (n = 5). All taxa with abundance ratios of ≥50% on the 16S rRNA analysis were also detected in the cultures. However, several taxa were either undetected in the cultures despite relatively high abundance ratios on the 16S rRNA analysis or negative on the 16S rRNA analysis and isolated only by culturing. CONCLUSION Our data provide a comprehensive list of bacterial taxa that may be associated with aspiration pneumonia and lung abscesses. In empirically treating LRTIs, this information will help determine the best treatment against the targeted anaerobes.
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Kitsios GD, Yang H, Yang L, Qin S, Fitch A, Wang XH, Fair K, Evankovich J, Bain W, Shah F, Li K, Methé B, Benos PV, Morris A, McVerry BJ. Respiratory Tract Dysbiosis Is Associated with Worse Outcomes in Mechanically Ventilated Patients. Am J Respir Crit Care Med 2021; 202:1666-1677. [PMID: 32717152 DOI: 10.1164/rccm.201912-2441oc] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Rationale: Host inflammatory responses have been strongly associated with adverse outcomes in critically ill patients, but the biologic underpinnings of such heterogeneous responses have not been defined.Objectives: We examined whether respiratory tract microbiome profiles are associated with host inflammation and clinical outcomes of acute respiratory failure.Methods: We collected oral swabs, endotracheal aspirates (ETAs), and plasma samples from mechanically ventilated patients. We performed 16S ribosomal RNA gene sequencing to characterize upper and lower respiratory tract microbiota and classified patients into host-response subphenotypes on the basis of clinical variables and plasma biomarkers of innate immunity and inflammation. We derived diversity metrics and composition clusters with Dirichlet multinomial models and examined our data for associations with subphenotypes and clinical outcomes.Measurements and Main Results: Oral and ETA microbial communities from 301 mechanically ventilated subjects had substantial heterogeneity in α and β diversity. Dirichlet multinomial models revealed a cluster with low α diversity and enrichment for pathogens (e.g., high Staphylococcus or Pseudomonadaceae relative abundance) in 35% of ETA samples, associated with a hyperinflammatory subphenotype, worse 30-day survival, and longer time to liberation from mechanical ventilation (adjusted P < 0.05), compared with patients with higher α diversity and relative abundance of typical oral microbiota. Patients with evidence of dysbiosis (low α diversity and low relative abundance of "protective" oral-origin commensal bacteria) in both oral and ETA samples (17%, combined dysbiosis) had significantly worse 30-day survival and longer time to liberation from mechanical ventilation than patients without dysbiosis (55%; adjusted P < 0.05).Conclusions: Respiratory tract dysbiosis may represent an important, modifiable contributor to patient-level heterogeneity in systemic inflammatory responses and clinical outcomes.
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Affiliation(s)
- Georgios D Kitsios
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center.,Center for Medicine and the Microbiome
| | - Haopu Yang
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center.,Department of Computational and Systems Biology, and.,Department of Immunology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Libing Yang
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center.,Center for Medicine and the Microbiome.,Department of Immunology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Shulin Qin
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center.,Center for Medicine and the Microbiome
| | | | - Xiao-Hong Wang
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center
| | - Katherine Fair
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center
| | - John Evankovich
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center
| | - William Bain
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center
| | - Faraaz Shah
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center.,School of Medicine, Tsinghua University, Beijing, China; and
| | - Kelvin Li
- Center for Medicine and the Microbiome
| | - Barbara Methé
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center.,Center for Medicine and the Microbiome
| | | | - Alison Morris
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center.,Center for Medicine and the Microbiome.,Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania
| | - Bryan J McVerry
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine and University of Pittsburgh Medical Center.,Center for Medicine and the Microbiome
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37
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Kitsios GD, Terasawa T. Reply to the author. Clin Infect Dis 2021; 73:e1768-e1769. [PMID: 33388747 DOI: 10.1093/cid/ciaa1914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Georgios D Kitsios
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Teruhiko Terasawa
- Department of Emergency and General Internal Medicine, Fujita Health University, Toyoake, Aichi, Japan
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Artificial Intelligence in Clinical Immunology. Artif Intell Med 2021. [DOI: 10.1007/978-3-030-58080-3_83-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Wang Q, Feng J, Zhang J, Shi L, Jin Z, Liu D, Wu B, Chen J. Diagnosis of complication in lung transplantation by TBLB + ROSE + mNGS. Open Med (Wars) 2020; 15:968-980. [PMID: 33313416 PMCID: PMC7706120 DOI: 10.1515/med-2020-0232] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Revised: 07/26/2020] [Accepted: 09/02/2020] [Indexed: 11/18/2022] Open
Abstract
Lung transplantation is a potentially life-saving therapy for patients with terminal respiratory illnesses. Long-term survival is limited by the development of a variety of opportunistic infections and rejection. Optimal means of differential diagnosis of infection and rejection have not been established. With these challenges in mind, we tried to use transbronchial lung biopsy (TBLB) rapid on-site cytological evaluation (ROSE), metagenomic next-generation sequencing (mNGS), and routine histologic examination to timely distinguish infection and rejection, and accurately detect etiologic pathogens. We reviewed the medical records of all patients diagnosed with infection or rejection by these means from December 2017 to September 2018 in our center. We identified seven recipients whose clinical course was complicated by infection or rejection. Three patients were diagnosed with acute rejection, organizing pneumonia, and acute fibrinoid organizing pneumonia, respectively. Four of the seven patients were diagnosed with infections, including Pneumocystis carinii pneumonia, cytomegalovirus, Aspergillus, and bacterial pneumonia. These patients recovered after proper treatment. TBLB + ROSE + mNGS might be a good method to accurately detect etiologic pathogens, which may help us to facilitate the use of targeted and precision medicine therapy in postoperative complications and avoid unnecessary potential adverse effects of drugs.
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Affiliation(s)
- Qing Wang
- Respiratory Department of Kunming Municipal First People’s Hospital, Kunming 650000, China
- Graduate School, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jing Feng
- Respiratory Department of Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Ji Zhang
- Respiratory Department of Lung Transplant Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi 214023, China
| | - Lingzhi Shi
- Respiratory Department of Lung Transplant Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi 214023, China
| | - Zhixian Jin
- Respiratory Department of Kunming Municipal First People’s Hospital, Kunming 650000, China
| | - Dong Liu
- Respiratory Department of Lung Transplant Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi 214023, China
| | - Bo Wu
- Respiratory Department of Lung Transplant Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi 214023, China
| | - Jingyu Chen
- Respiratory Department of Lung Transplant Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi 214023, China
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Baek MG, Woo SJ, Kim NE, Baek C, Won S, Kim Y, Lee JJ, Yi H, Hong JY. Respiratory microbiome profiles differ by recent hospitalization and nursing home residence in patients on mechanical ventilation. J Transl Med 2020; 18:464. [PMID: 33287847 PMCID: PMC7720271 DOI: 10.1186/s12967-020-02642-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 11/27/2020] [Indexed: 02/08/2023] Open
Abstract
Background Healthcare-associated pneumonia (HCAP) is a heterogeneous disease. We redefined nursing-home- and hospital-associated infections (NHAI) group by revising existing HCAP risk factors. The NHAI group comprised nursing home residents with a poor functional status, or recent (past 90 days) hospitalization or recent (past 180 days) antibiotic therapy. Our aim was to determine whether respiratory microbiota profiles are related to newly defined NHAI group in critically ill patients on mechanical ventilation. Methods The 180 endotracheal aspirates (ETAs) from 60 mechanically ventilated ICU patients (NHAI group, n = 24; non-NHAI group, n = 36) were prospectively collected on days 1, 3 and 7 in a university hospital. The bacterial community profiles of the ETAs were explored by 16S rRNA gene sequencing. A phylogenetic-tree-based microbiome association test (TMAT), generalized linear mixed models (GLMMs), the Wilcoxon test and the reference frame method were used to analyze the association between microbiome abundance and disease phenotype. Results The relative abundance of the genus Corynebacterium was significantly higher in the pneumonia than in the non-pneumonia group. The microbiome analysis revealed significantly lower α-diversity in the NHAI group than in the non-NHAI group. In the analysis of β-diversity, the structure of the microbiome also differed significantly between the two groups (weighted UniFrac distance, Adonis, p < 0.001). The abundance of Corynebacterium was significantly higher, and the relative abundances of Granulicatella, Staphylococcus, Streptococcus and Veillonella were significantly lower, in the NHAI group than in the non-NHAI group. Conclusions The microbiota signature of the ETAs distinguished between patients with and without risk factors for NHAI. The lung microbiome may serve as a therapeutic target for NHAI group.
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Affiliation(s)
- Min-Gyung Baek
- Department of Public Health, Korea University, Seoul, Republic of Korea
| | - Seong Ji Woo
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon, Republic of Korea
| | - Nam Eun Kim
- Department of Public Health Science, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea
| | - Chaeyun Baek
- Department of Public Health, Korea University, Seoul, Republic of Korea
| | - Sungho Won
- Institute of Health and Environment, Seoul National University, Seoul, Republic of Korea.,Interdisciplinary Program of Bioinformatics, Seoul National University, Seoul, Republic of Korea
| | - Youngmi Kim
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon, Republic of Korea
| | - Jae Jun Lee
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon, Republic of Korea
| | - Hana Yi
- School of Biosystems and Biomedical Sciences, College of Health Science, Korea University, Seoul, Republic of Korea.
| | - Ji Young Hong
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon, Republic of Korea. .,Division of Pulmonary and Critical Care Medicine, Department of Medicine, Chuncheon Sacred Heart Hospital, Hallym University Medical Center, 77, Sakju-ro, Chuncheon-si, Gangwon-do, 200-704, Republic of Korea.
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Wang Q, Wu B, Yang D, Yang C, Jin Z, Cao J, Feng J. Optimal specimen type for accurate diagnosis of infectious peripheral pulmonary lesions by mNGS. BMC Pulm Med 2020; 20:268. [PMID: 33059646 PMCID: PMC7566056 DOI: 10.1186/s12890-020-01298-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 09/21/2020] [Indexed: 12/30/2022] Open
Abstract
Background Reports on the application of metagenomic next-generation sequencing (mNGS) to the diagnosis of peripheral pulmonary lesions (PPLs) are scarce. There have been no studies investigating the optimal specimen type for mNGS. Methods We used mNGS to detect pathogens in matched transbronchial lung biopsy (TBLB), bronchoalveolar lavage fluid (BALF), and bronchial needle brushing (BB) specimens from 39 patients suspected of having infectious PPLs. We explored differences in microbial composition and diagnostic accuracy of mNGS for the 3 specimen types. Results mNGS was more sensitive than conventional culture for detection of bacteria and fungi in TBLB, BALF, and BB specimens, with no difference in the sensitivity of mNGS across the different specimen types. mNGS showed higher sensitivity for fungi or uncategorized pulmonary pathogens in TBLB+BALF+BB compared to TBLB but not BALF or BB specimens. There were no significant differences between the 3 specimen types in the relative abundance of pathogens, or between TBLB and BB specimens in the relative abundance of 6 common lower respiratory tract commensals. Conclusions mNGS has a higher sensitivity than the conventional culture method for detecting pathogens in TBLB, BALF, or BB specimens. mNGS of BB samples is a less invasive alternative to TBLB for the diagnosis of infectious PPLs.
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Affiliation(s)
- Qing Wang
- Department of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China.,Respiratory Department of Kunming Municipal First People's Hospital, Kunming, 650000, China
| | - Bo Wu
- Transplantation Center, Nanjing Medical University, Affiliated Wuxi People's Hospital, Wuxi, 214023, China
| | - Donglin Yang
- Hematopoietic Stem Cell Transplantation Center, Institute of Hematology and Blood Disease Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, 300052, China
| | - Chao Yang
- Respiratory Department of Kunming Municipal First People's Hospital, Kunming, 650000, China
| | - Zhixian Jin
- Respiratory Department of Kunming Municipal First People's Hospital, Kunming, 650000, China.
| | - Jie Cao
- Department of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jing Feng
- Department of Respiratory and Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China.
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Fernández-Barat L, López-Aladid R, Torres A. Reconsidering ventilator-associated pneumonia from a new dimension of the lung microbiome. EBioMedicine 2020; 60:102995. [PMID: 32950001 PMCID: PMC7492164 DOI: 10.1016/j.ebiom.2020.102995] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 08/25/2020] [Accepted: 08/25/2020] [Indexed: 12/12/2022] Open
Abstract
Complex microbial communities that reside in the lungs, skin and gut are now appreciated for their role in maintaining organ, tissue and immune homoeostasis. As lungs are currently seen as an ecosystem, the shift in paradigm calls for the consideration of new algorithms related to lung ecology in pulmonology. Evidence of lung microbiota does not solely challenge the traditional physiopathology of ventilator-associated pneumonia (VAP); indeed, it also reinforces the need to include molecular techniques in VAP diagnosis and accelerate the use of immunomodulatory drugs, including corticosteroids, and other supplements such as probiotics for VAP prevention and/or treatment. With that stated, both microbiome and virome, including phageome, can lead to new opportunities in further understanding the relationship between health and dysbiosis in VAP. Previous knowledge may be, however, reconsidered at a microbiome scale.
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Affiliation(s)
- Laia Fernández-Barat
- Cellex Laboratory, CibeRes (Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, 06/06/0028), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Spain; School of Medicine, University of Barcelona, Barcelona, Spain.
| | - Ruben López-Aladid
- Cellex Laboratory, CibeRes (Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, 06/06/0028), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Spain
| | - Antoni Torres
- Cellex Laboratory, CibeRes (Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, 06/06/0028), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Spain; School of Medicine, University of Barcelona, Barcelona, Spain; Department of Pneumology, Thorax Institute, Hospital Clinic of Barcelona, Spain.
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43
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Yang H, Benos PV, Kitsios GD. Protecting the lungs but hurting the kidneys: causal inference study for the risk of ventilation-induced kidney injury in ARDS. ANNALS OF TRANSLATIONAL MEDICINE 2020; 8:985. [PMID: 32953785 PMCID: PMC7475484 DOI: 10.21037/atm-20-2050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 04/28/2020] [Indexed: 12/16/2022]
Affiliation(s)
- Haopu Yang
- School of Medicine, Tsinghua University, Beijing, China
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
| | - Panayiotis V Benos
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Georgios D Kitsios
- Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA, USA
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Ge X, Raghu VK, Chrysanthis PK, Benos P. CausalMGM: an interactive web-based causal discovery tool. Nucleic Acids Res 2020; 48:W597-W602. [PMID: 32392295 PMCID: PMC7319538 DOI: 10.1093/nar/gkaa350] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 04/21/2020] [Accepted: 04/25/2020] [Indexed: 12/03/2022] Open
Abstract
High-throughput sequencing and the availability of large online data repositories (e.g. The Cancer Genome Atlas and Trans-Omics for Precision Medicine) have the potential to revolutionize systems biology by enabling researchers to study interactions between data from different modalities (i.e. genetic, genomic, clinical, behavioral, etc.). Currently, data mining and statistical approaches are confined to identifying correlates in these datasets, but researchers are often interested in identifying cause-and-effect relationships. Causal discovery methods were developed to infer such cause-and-effect relationships from observational data. Though these algorithms have had demonstrated successes in several biomedical applications, they are difficult to use for non-experts. So, there is a need for web-based tools to make causal discovery methods accessible. Here, we present CausalMGM (http://causalmgm.org/), the first web-based causal discovery tool that enables researchers to find cause-and-effect relationships from observational data. Web-based CausalMGM consists of three data analysis tools: (i) feature selection and clustering; (ii) automated identification of cause-and-effect relationships via a graphical model; and (iii) interactive visualization of the learned causal (directed) graph. We demonstrate how CausalMGM enables an end-to-end exploratory analysis of biomedical datasets, giving researchers a clearer picture of its capabilities.
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Affiliation(s)
- Xiaoyu Ge
- Department of Computer Science, University of Pittsburgh, 4200 Fifth Avenue, Pittsburgh, PA 15260, USA
| | - Vineet K Raghu
- Department of Computer Science, University of Pittsburgh, 4200 Fifth Avenue, Pittsburgh, PA 15260, USA
- Department of Computational and Systems Biology, University of Pittsburgh, 3420 Forbes Ave, Pittsburgh, PA 15213, USA
| | - Panos K Chrysanthis
- Department of Computer Science, University of Pittsburgh, 4200 Fifth Avenue, Pittsburgh, PA 15260, USA
| | - Panayiotis V Benos
- Department of Computer Science, University of Pittsburgh, 4200 Fifth Avenue, Pittsburgh, PA 15260, USA
- Department of Computational and Systems Biology, University of Pittsburgh, 3420 Forbes Ave, Pittsburgh, PA 15213, USA
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45
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Choi CW, Yang BR, Suh DI, Kim MS, Ohn J, Hong JS, Lee J, Kim KH. Infection, antibiotic exposure and development of atopic dermatitis: A nationwide case-control study. J Dermatol 2020; 47:707-713. [PMID: 32441365 DOI: 10.1111/1346-8138.15387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Accepted: 04/14/2020] [Indexed: 11/28/2022]
Abstract
Previous studies suggest an association between atopic dermatitis (AD) and exposure to microorganisms and antibiotics. However, these studies have limitations, and the sole influence on the development of AD was elusive. We performed a nationwide population-based case-control study in a Korean population to investigate the association between AD and early-life infection or antibiotic exposure. A total of 244 805 children with AD from the 2 283 601 children born between January 2010 and December 2014 and an equal number of sex- and age-matched healthy children were enrolled. A conditional logistic regression analysis showed that the episode of infection and antibiotic exposure were associated with an increased risk of AD (odds ratio [OR], 1.60; 95% confidence interval [CI], 1.58-1.63 for infection; and OR, 1.11; 95% CI, 1.09-1.13 for antibiotic exposure). A dose-dependent relationship was observed between risk for AD, the number of infection episodes and antibiotic cycles and the duration of antibiotic exposure. On further analysis using a conditional logistic model, the risk of AD was less when the antibiotics were used during the infection episode than that without the use of antibiotics, especially if the duration of the infection was short. Although our study could not consider the effect of cause or severity of infection, class of antibiotics and genetic or environmental factors of enrolled subjects, our results suggested that infection and antibiotic exposure were associated with an increased risk of AD. In addition, the results also implied that the use of antibiotics during an infection episode can decrease the risk of AD induced by the infection and that appropriate management of infections can minimize the risk of AD induced by infection or antibiotics.
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Affiliation(s)
- Chong Won Choi
- Laboratory of Cutaneous Aging and Hair Research, Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea.,Institute of Human-Environment Interface Biology, Seoul National University College of Medicine, Seoul, Korea.,Department of Dermatology, Seoul National University College of Medicine, Seoul, Korea
| | - Bo Ram Yang
- Division of Clinical Epidemiology, Medical Research Collaborating Center, Biomedical Research Institution, Seoul National University Hospital, Seoul, Korea
| | - Dong In Suh
- Department of Pediatrics, Seoul National University Children's Hospital, Seoul, Korea
| | - Mi-Sook Kim
- Division of Clinical Epidemiology, Medical Research Collaborating Center, Biomedical Research Institution, Seoul National University Hospital, Seoul, Korea
| | - Jungyoon Ohn
- Laboratory of Cutaneous Aging and Hair Research, Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea.,Institute of Human-Environment Interface Biology, Seoul National University College of Medicine, Seoul, Korea.,Department of Dermatology, Seoul National University College of Medicine, Seoul, Korea
| | - Jong Soo Hong
- Laboratory of Cutaneous Aging and Hair Research, Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea.,Institute of Human-Environment Interface Biology, Seoul National University College of Medicine, Seoul, Korea.,Department of Dermatology, Seoul National University College of Medicine, Seoul, Korea.,Department of dermatology, Dongguk university Ilsan Hospital, Goyang, Korea
| | - Joongyub Lee
- Division of Clinical Epidemiology, Medical Research Collaborating Center, Biomedical Research Institution, Seoul National University Hospital, Seoul, Korea
| | - Kyu Han Kim
- Laboratory of Cutaneous Aging and Hair Research, Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea.,Institute of Human-Environment Interface Biology, Seoul National University College of Medicine, Seoul, Korea.,Department of Dermatology, Seoul National University College of Medicine, Seoul, Korea
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Kotok D, Yang L, Evankovich JW, Bain W, Dunlap DG, Shah F, Zhang Y, Manatakis DV, Benos PV, Barbash IJ, Rapport SF, Lee JS, Morris A, McVerry BJ, Kitsios GD. The evolution of radiographic edema in ARDS and its association with clinical outcomes: A prospective cohort study in adult patients. J Crit Care 2020; 56:222-228. [PMID: 32028223 PMCID: PMC7136845 DOI: 10.1016/j.jcrc.2020.01.012] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2019] [Revised: 12/13/2019] [Accepted: 01/12/2020] [Indexed: 12/21/2022]
Abstract
PURPOSE To assess the longitudinal evolution of radiographic edema using chest X-rays (CXR) in patients with Acute Respiratory Distress Syndrome (ARDS) and to examine its association with prognostic biomarkers, ARDS subphenotypes and outcomes. MATERIALS AND METHODS We quantified radiographic edema on CXRs from patients with ARDS or cardiogenic pulmonary edema (controls) using the Radiographic Assessment of Lung Edema (RALE) score on day of intubation and up to 10 days after. We measured baseline plasma biomarkers and recorded clinical variables. RESULTS The RALE score had good inter-rater agreement (r = 0.83, p < 0.0001) applied on 488 CXRs from 129 patients, with higher RALE scores in patients with ARDS (n = 108) compared to controls (n = 21, p = 0.01). Baseline RALE scores were positively correlated with levels of the receptor for end-glycation end products (RAGE) in ARDS patients (p < 0.05). Baseline RALE scores were not predictive of 30- or 90-day survival. Persistently elevated RALE scores were associated with prolonged need for mechanical ventilation (p = 0.002). CONCLUSIONS The RALE score is easily implementable with high inter-rater reliability. Longitudinal RALE scoring appears to be a reproducible approach to track the evolution of radiographic edema in patients with ARDS and can potentially predict prolonged need for mechanical ventilation.
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Affiliation(s)
- Daniel Kotok
- Internal Medicine Residency Program, University of Pittsburgh Medical Center McKeesport, USA
| | - Libing Yang
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - John W Evankovich
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - William Bain
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Daniel G Dunlap
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Faraaz Shah
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Yingze Zhang
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Dimitris V Manatakis
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Panayiotis V Benos
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ian J Barbash
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Sarah F Rapport
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Janet S Lee
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Alison Morris
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA; Center for Medicine and the Microbiome, University of Pittsburgh, USA; Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Bryan J McVerry
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA; Center for Medicine and the Microbiome, University of Pittsburgh, USA
| | - Georgios D Kitsios
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA; Center for Medicine and the Microbiome, University of Pittsburgh, USA.
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47
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Zhang H, Zhan D, Chen D, Huang W, Yu M, Li Q, Marcos PJ, Tattevin P, Wu D, Wang L. Next-generation sequencing diagnosis of severe pneumonia from fulminant psittacosis with multiple organ failure: a case report and literature review. ANNALS OF TRANSLATIONAL MEDICINE 2020; 8:401. [PMID: 32355845 PMCID: PMC7186658 DOI: 10.21037/atm.2020.03.17] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
This study includes a retrospective analysis of the diagnosis and treatment of a case of severe pneumonia from fulminant psittacosis with multiple organ failure. Next-generation sequencing (NGS) of the pathogen was conducted. The purpose of this study was to summarize the clinical, laboratory, and imaging characteristics of the case and to improve understanding of the value of NGS in the diagnosis of severe community-acquired pneumonia (CAP). Fulminant psittacosis can be manifested as severe pneumonia with rapid progression, acute respiratory distress syndrome, sepsis, and multiple organ failure. Imaging shows unilateral lung consolidation, which is difficult to differentiate from CAP caused by common pathogens. The NGS technology can early detect rare pathogens, thus reducing unnecessary use of antibiotics and shortening the course of the disease.
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Affiliation(s)
- Heng Zhang
- Department of Respiratory and Critical Care Medicine, Shenzhen People's Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medical College of Jinan University, Shenzhen Institute of Respiratory Diseases, Shenzhen Key Laboratory of Respiratory Diseases, Shenzhen 518020, China
| | - Danting Zhan
- Department of Respiratory and Critical Care Medicine, Shenzhen People's Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medical College of Jinan University, Shenzhen Institute of Respiratory Diseases, Shenzhen Key Laboratory of Respiratory Diseases, Shenzhen 518020, China
| | - Dandan Chen
- Department of Respiratory and Critical Care Medicine, Shenzhen People's Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medical College of Jinan University, Shenzhen Institute of Respiratory Diseases, Shenzhen Key Laboratory of Respiratory Diseases, Shenzhen 518020, China
| | - Weibin Huang
- Department of Respiratory and Critical Care Medicine, Shenzhen People's Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medical College of Jinan University, Shenzhen Institute of Respiratory Diseases, Shenzhen Key Laboratory of Respiratory Diseases, Shenzhen 518020, China
| | - Min Yu
- Department of Respiratory and Critical Care Medicine, Shenzhen People's Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medical College of Jinan University, Shenzhen Institute of Respiratory Diseases, Shenzhen Key Laboratory of Respiratory Diseases, Shenzhen 518020, China
| | - Qiuwen Li
- Department of Respiratory and Critical Care Medicine, Shenzhen People's Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medical College of Jinan University, Shenzhen Institute of Respiratory Diseases, Shenzhen Key Laboratory of Respiratory Diseases, Shenzhen 518020, China
| | - Pedro J Marcos
- Pneumology Service, Institute of Biomedical Research of A Coruña (INIBIC), University Hospital Complex of A Coruña (CHUAC), Universidade da Coruna (UDC), A Coruña, Spain
| | - Pierre Tattevin
- Infectious Diseases and Intensive Care Unit, Pontchaillou University Hospital, Rennes, France
| | - Di Wu
- Department of Respiratory and Critical Care Medicine, Shenzhen People's Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medical College of Jinan University, Shenzhen Institute of Respiratory Diseases, Shenzhen Key Laboratory of Respiratory Diseases, Shenzhen 518020, China
| | - Lingwei Wang
- Department of Respiratory and Critical Care Medicine, Shenzhen People's Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medical College of Jinan University, Shenzhen Institute of Respiratory Diseases, Shenzhen Key Laboratory of Respiratory Diseases, Shenzhen 518020, China
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48
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Carney SM, Clemente JC, Cox MJ, Dickson RP, Huang YJ, Kitsios GD, Kloepfer KM, Leung JM, LeVan TD, Molyneaux PL, Moore BB, O'Dwyer DN, Segal LN, Garantziotis S. Methods in Lung Microbiome Research. Am J Respir Cell Mol Biol 2020; 62:283-299. [PMID: 31661299 PMCID: PMC7055701 DOI: 10.1165/rcmb.2019-0273tr] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 10/29/2019] [Indexed: 12/13/2022] Open
Abstract
The lung microbiome is associated with host immune response and health outcomes in experimental models and patient cohorts. Lung microbiome research is increasing in volume and scope; however, there are no established guidelines for study design, conduct, and reporting of lung microbiome studies. Standardized approaches to yield reliable and reproducible data that can be synthesized across studies will ultimately improve the scientific rigor and impact of published work and greatly benefit microbiome research. In this review, we identify and address several key elements of microbiome research: conceptual modeling and hypothesis framing; study design; experimental methodology and pitfalls; data analysis; and reporting considerations. Finally, we explore possible future directions and research opportunities. Our goal is to aid investigators who are interested in this burgeoning research area and hopefully provide the foundation for formulating consensus approaches in lung microbiome research.
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Affiliation(s)
| | | | | | | | - Yvonne J Huang
- University of Michigan Medical School, Ann Arbor, Michigan
| | - Georgios D Kitsios
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Kirsten M Kloepfer
- Division of Pulmonary, Allergy and Sleep Medicine, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Janice M Leung
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Philip L Molyneaux
- Fibrosis Research Group, National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Royal Brompton and Harefield Foundation National Health Service Trust, London, United Kingdom
| | | | | | - Leopoldo N Segal
- Division of Pulmonary, Critical Care and Sleep Medicine, New York University School of Medicine, New York, New York; and
| | - Stavros Garantziotis
- National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina
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49
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The Dynamics of Respiratory Microbiota during Mechanical Ventilation in Patients with Pneumonia. J Clin Med 2020; 9:jcm9030638. [PMID: 32120914 PMCID: PMC7141134 DOI: 10.3390/jcm9030638] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 02/21/2020] [Accepted: 02/21/2020] [Indexed: 11/17/2022] Open
Abstract
Bacterial pneumonia is a major cause of mechanical ventilation in intensive care units. We hypothesized that the presence of particular microbiota in endotracheal tube aspirates during the course of intubation was associated with clinical outcomes such as extubation failure or 28-day mortality. Sixty mechanically ventilated ICU (intensive care unit) patients (41 patients with pneumonia and 19 patients without pneumonia) were included, and tracheal aspirates were obtained on days 1, 3, and 7. Gene sequencing of 16S rRNA was used to measure the composition of the respiratory microbiome. A total of 216 endotracheal aspirates were obtained from 60 patients. A total of 22 patients were successfully extubatedwithin3 weeks, and 12 patients died within 28days. Microbiota profiles differed significantly between the pneumonia group and the non-pneumonia group (Adonis, p < 0.01). While α diversity (Shannon index) significantly decreased between day 1 and day 7 in the successful extubation group, it did not decrease in the failed extubation group among intubated patients with pneumonia. There was a significant difference in the change of βdiversity between the successful extubation group and the failed extubation group for Bray-Curtis distances (p < 0.001). At the genus level, Rothia, Streptococcus, and Prevotella correlated with the change of β diversity. A low relative abundance of Streptococci at the time of intubation was strongly associated with 28-day mortality. The dynamics of respiratory microbiome were associated with clinical outcomes such as extubation failure and mortality. Further large prospective studies are needed to test the predictive value of endotracheal aspirates in intubated patients.
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50
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Bakare OO, Fadaka AO, Klein A, Keyster M, Pretorius A. Diagnostic approaches of pneumonia for commercial-scale biomedical applications: an overview. ALL LIFE 2020. [DOI: 10.1080/26895293.2020.1826363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
Affiliation(s)
- Olalekan Olanrewaju Bakare
- Bioinformatics Research Group, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
- Environmental Biotechnology Laboratory, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - Adewale Oluwaseun Fadaka
- Bioinformatics Research Group, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
- Department of Science and Technology/Mintek Nanotechnology Innovation Centre, Bio-labels Node, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - Ashwil Klein
- Environmental Biotechnology Laboratory, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - Marshall Keyster
- Environmental Biotechnology Laboratory, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - Ashley Pretorius
- Bioinformatics Research Group, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
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