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Real-time analysis of nanopore-based metagenomic sequencing from infected orthopaedic devices
BACKGROUND: Prosthetic joint infections are clinically difficult to diagnose and treat. Previously, we demonstrated metagenomic sequencing on an Illumina MiSeq replicates the findings of current gold standard microbiological diagnostic techniques. Nanopore sequencing offers advantages in speed of de...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6161345/ https://www.ncbi.nlm.nih.gov/pubmed/30261842 http://dx.doi.org/10.1186/s12864-018-5094-y |
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author | Sanderson, Nicholas D Street, Teresa L Foster, Dona Swann, Jeremy Atkins, Bridget L Brent, Andrew J McNally, Martin A Oakley, Sarah Taylor, Adrian Peto, Tim E A Crook, Derrick W Eyre, David W |
author_facet | Sanderson, Nicholas D Street, Teresa L Foster, Dona Swann, Jeremy Atkins, Bridget L Brent, Andrew J McNally, Martin A Oakley, Sarah Taylor, Adrian Peto, Tim E A Crook, Derrick W Eyre, David W |
author_sort | Sanderson, Nicholas D |
collection | PubMed |
description | BACKGROUND: Prosthetic joint infections are clinically difficult to diagnose and treat. Previously, we demonstrated metagenomic sequencing on an Illumina MiSeq replicates the findings of current gold standard microbiological diagnostic techniques. Nanopore sequencing offers advantages in speed of detection over MiSeq. Here, we report a real-time analytical pathway for Nanopore sequence data, designed for detecting bacterial composition of prosthetic joint infections but potentially useful for any microbial sequencing, and compare detection by direct-from-clinical-sample metagenomic nanopore sequencing with Illumina sequencing and standard microbiological diagnostic techniques. RESULTS: DNA was extracted from the sonication fluids of seven explanted orthopaedic devices, and additionally from two culture negative controls, and was sequenced on the Oxford Nanopore Technologies MinION platform. A specific analysis pipeline was assembled to overcome the challenges of identifying the true infecting pathogen, given high levels of host contamination and unavoidable background lab and kit contamination. The majority of DNA classified (> 90%) was host contamination and discarded. Using negative control filtering thresholds, the species identified corresponded with both routine microbiological diagnosis and MiSeq results. By analysing sequences in real time, causes of infection were robustly detected within minutes from initiation of sequencing. CONCLUSIONS: We demonstrate a novel, scalable pipeline for real-time analysis of MinION sequence data and use of this pipeline to show initial proof of concept that metagenomic MinION sequencing can provide rapid, accurate diagnosis for prosthetic joint infections. The high proportion of human DNA in prosthetic joint infection extracts prevents full genome analysis from complete coverage, and methods to reduce this could increase genome depth and allow antimicrobial resistance profiling. The nine samples sequenced in this pilot study have shown a proof of concept for sequencing and analysis that will enable us to investigate further sequencing to improve specificity and sensitivity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-5094-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6161345 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61613452018-10-01 Real-time analysis of nanopore-based metagenomic sequencing from infected orthopaedic devices Sanderson, Nicholas D Street, Teresa L Foster, Dona Swann, Jeremy Atkins, Bridget L Brent, Andrew J McNally, Martin A Oakley, Sarah Taylor, Adrian Peto, Tim E A Crook, Derrick W Eyre, David W BMC Genomics Methodology Article BACKGROUND: Prosthetic joint infections are clinically difficult to diagnose and treat. Previously, we demonstrated metagenomic sequencing on an Illumina MiSeq replicates the findings of current gold standard microbiological diagnostic techniques. Nanopore sequencing offers advantages in speed of detection over MiSeq. Here, we report a real-time analytical pathway for Nanopore sequence data, designed for detecting bacterial composition of prosthetic joint infections but potentially useful for any microbial sequencing, and compare detection by direct-from-clinical-sample metagenomic nanopore sequencing with Illumina sequencing and standard microbiological diagnostic techniques. RESULTS: DNA was extracted from the sonication fluids of seven explanted orthopaedic devices, and additionally from two culture negative controls, and was sequenced on the Oxford Nanopore Technologies MinION platform. A specific analysis pipeline was assembled to overcome the challenges of identifying the true infecting pathogen, given high levels of host contamination and unavoidable background lab and kit contamination. The majority of DNA classified (> 90%) was host contamination and discarded. Using negative control filtering thresholds, the species identified corresponded with both routine microbiological diagnosis and MiSeq results. By analysing sequences in real time, causes of infection were robustly detected within minutes from initiation of sequencing. CONCLUSIONS: We demonstrate a novel, scalable pipeline for real-time analysis of MinION sequence data and use of this pipeline to show initial proof of concept that metagenomic MinION sequencing can provide rapid, accurate diagnosis for prosthetic joint infections. The high proportion of human DNA in prosthetic joint infection extracts prevents full genome analysis from complete coverage, and methods to reduce this could increase genome depth and allow antimicrobial resistance profiling. The nine samples sequenced in this pilot study have shown a proof of concept for sequencing and analysis that will enable us to investigate further sequencing to improve specificity and sensitivity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-5094-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-27 /pmc/articles/PMC6161345/ /pubmed/30261842 http://dx.doi.org/10.1186/s12864-018-5094-y Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article Sanderson, Nicholas D Street, Teresa L Foster, Dona Swann, Jeremy Atkins, Bridget L Brent, Andrew J McNally, Martin A Oakley, Sarah Taylor, Adrian Peto, Tim E A Crook, Derrick W Eyre, David W Real-time analysis of nanopore-based metagenomic sequencing from infected orthopaedic devices |
title | Real-time analysis of nanopore-based metagenomic sequencing from infected orthopaedic devices |
title_full | Real-time analysis of nanopore-based metagenomic sequencing from infected orthopaedic devices |
title_fullStr | Real-time analysis of nanopore-based metagenomic sequencing from infected orthopaedic devices |
title_full_unstemmed | Real-time analysis of nanopore-based metagenomic sequencing from infected orthopaedic devices |
title_short | Real-time analysis of nanopore-based metagenomic sequencing from infected orthopaedic devices |
title_sort | real-time analysis of nanopore-based metagenomic sequencing from infected orthopaedic devices |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6161345/ https://www.ncbi.nlm.nih.gov/pubmed/30261842 http://dx.doi.org/10.1186/s12864-018-5094-y |
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