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Identification of pleural infection microbiological patterns by applying next generation sequencing and bioinformatics analysis

Nikolaos I. Kanellakis, Eihab O. Bedawi, John M. Wrightson, John P. Corcoran, Robert Hallifax, Rachel M. Mercer, Vineeth George, Radhika Banka, Maisha Jabeen, Rachelle Asciak, Robert F. Miller, Nick A. Maskell, Ioannis Psallidas, Timothy Hinks, Derrick Crook, Najib M. Rahman
European Respiratory Journal 2020 56: 4673; DOI: 10.1183/13993003.congress-2020.4673
Nikolaos I. Kanellakis
1Laboratory of Lung Cancer and Pleural Translational Research, Nuffield Department of Medicine, University of Oxford, OX3 7FZ, Oxford, United Kingdom
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  • For correspondence: nikolaos.kanellakis@ndm.ox.ac.uk
Eihab O. Bedawi
2Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, OX3 7LE, Oxford, United Kingdom
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John M. Wrightson
2Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, OX3 7LE, Oxford, United Kingdom
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John P. Corcoran
2Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, OX3 7LE, Oxford, United Kingdom
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Robert Hallifax
2Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, OX3 7LE, Oxford, United Kingdom
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Rachel M. Mercer
2Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, OX3 7LE, Oxford, United Kingdom
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Vineeth George
2Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, OX3 7LE, Oxford, United Kingdom
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Radhika Banka
2Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, OX3 7LE, Oxford, United Kingdom
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Maisha Jabeen
3Respiratory Medicine Unit, Nuffield Department of Medicine, University of Oxford, OX3 9DU, Oxford, United Kingdom
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Rachelle Asciak
2Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, OX3 7LE, Oxford, United Kingdom
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Robert F. Miller
4Infection and Population Health, Institute for Global Health, University College London, WC1E 6BT, London, United Kingdom
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Nick A. Maskell
5Academic Respiratory Unit, University of Bristol, BS10 5NB, Bristol, United Kingdom
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Ioannis Psallidas
1Laboratory of Lung Cancer and Pleural Translational Research, Nuffield Department of Medicine, University of Oxford, OX3 7FZ, Oxford, United Kingdom
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Timothy Hinks
3Respiratory Medicine Unit, Nuffield Department of Medicine, University of Oxford, OX3 9DU, Oxford, United Kingdom
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Derrick Crook
6Modernising Clinical Microbiology, Nuffield Department of Medicine, John Raddcliffe Hospital, University of Oxford, OX3 9DU, Oxford, United Kingdom
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Najib M. Rahman
2Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, OX3 7LE, Oxford, United Kingdom
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Abstract

Background: Pleural infection (PI) is a common and complex disease which can be life threatening for immunocompromised and elderly populations. Prior antibiotic use and special bacterial nutritional requirements hamper the accuracy of bacterial identification using current clinical culture-based techniques. Consequently, PI microbiology remains unclear. Next generation sequencing (NGS) has the potential to improve identification of the total bacterial population of a complex sample.

Aim: To discover and characterise the microbial patterns of PI using NGS and bioinformatics techniques.

Methods: Pleural fluid samples from the “Pleural Infection Longitudinal Outcome Study” (PILOT, ISRCTN50236700, n=243) underwent bacterial DNA extraction followed by 16S rRNA NGS using Illumina MiSeq. Data were analysed with DADA2 and Phyloseq R packages.

Results: Analysis showed diverse microbiological patterns for PI as 391 different pathogens were identified up to the genus level. 131 (54%) samples had one pathogen with relative abundance over 50% and 89 (36%) samples had at least three pathogens with relative abundance over 10%, suggesting a polymicrobial infection. Streptococcus pneumoniae was detected in 40 (16%) and Staphylococcus aureus in 20 (8%) samples.

Discussion: We established a methodology to extract bacterial DNA from patients with PI and used it as a template to apply NGS. 16S rRNA gene NGS provides a robust method to investigate the bacteriological patterns in pleural fluid of patients with PI.

Funding: National Institute for Health Research, Oxford Biomedical Research Centre

  • Pleura
  • Bacteria
  • Mirobiome/Microbiota

Footnotes

Cite this article as: European Respiratory Journal 2020; 56: Suppl. 64, 4673.

This abstract was presented at the 2020 ERS International Congress, in session “Respiratory viruses in the "pre COVID-19" era”.

This is an ERS International Congress abstract. No full-text version is available. Further material to accompany this abstract may be available at www.ers-education.org (ERS member access only).

  • Copyright ©the authors 2020
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Identification of pleural infection microbiological patterns by applying next generation sequencing and bioinformatics analysis
Nikolaos I. Kanellakis, Eihab O. Bedawi, John M. Wrightson, John P. Corcoran, Robert Hallifax, Rachel M. Mercer, Vineeth George, Radhika Banka, Maisha Jabeen, Rachelle Asciak, Robert F. Miller, Nick A. Maskell, Ioannis Psallidas, Timothy Hinks, Derrick Crook, Najib M. Rahman
European Respiratory Journal Sep 2020, 56 (suppl 64) 4673; DOI: 10.1183/13993003.congress-2020.4673

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Identification of pleural infection microbiological patterns by applying next generation sequencing and bioinformatics analysis
Nikolaos I. Kanellakis, Eihab O. Bedawi, John M. Wrightson, John P. Corcoran, Robert Hallifax, Rachel M. Mercer, Vineeth George, Radhika Banka, Maisha Jabeen, Rachelle Asciak, Robert F. Miller, Nick A. Maskell, Ioannis Psallidas, Timothy Hinks, Derrick Crook, Najib M. Rahman
European Respiratory Journal Sep 2020, 56 (suppl 64) 4673; DOI: 10.1183/13993003.congress-2020.4673
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