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Next-generation sequencing diagnostics of bacteremia in septic patients
BACKGROUND: Bloodstream infections remain one of the major challenges in intensive care units, leading to sepsis or even septic shock in many cases. Due to the lack of timely diagnostic approaches with sufficient sensitivity, mortality rates of sepsis are still unacceptably high. However a prompt di...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4930583/ https://www.ncbi.nlm.nih.gov/pubmed/27368373 http://dx.doi.org/10.1186/s13073-016-0326-8 |
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author | Grumaz, Silke Stevens, Philip Grumaz, Christian Decker, Sebastian O. Weigand, Markus A. Hofer, Stefan Brenner, Thorsten von Haeseler, Arndt Sohn, Kai |
author_facet | Grumaz, Silke Stevens, Philip Grumaz, Christian Decker, Sebastian O. Weigand, Markus A. Hofer, Stefan Brenner, Thorsten von Haeseler, Arndt Sohn, Kai |
author_sort | Grumaz, Silke |
collection | PubMed |
description | BACKGROUND: Bloodstream infections remain one of the major challenges in intensive care units, leading to sepsis or even septic shock in many cases. Due to the lack of timely diagnostic approaches with sufficient sensitivity, mortality rates of sepsis are still unacceptably high. However a prompt diagnosis of the causative microorganism is critical to significantly improve outcome of bloodstream infections. Although various targeted molecular tests for blood samples are available, time-consuming blood culture-based approaches still represent the standard of care for the identification of bacteria. METHODS: Here we describe the establishment of a complete diagnostic workflow for the identification of infectious microorganisms from seven septic patients based on unbiased sequence analyses of free circulating DNA from plasma by next-generation sequencing. RESULTS: We found significant levels of DNA fragments derived from pathogenic bacteria in samples from septic patients. Quantitative evaluation of normalized read counts and introduction of a sepsis indicating quantifier (SIQ) score allowed for an unambiguous identification of Gram-positive as well as Gram-negative bacteria that exactly matched with blood cultures from corresponding patient samples. In addition, we also identified species from samples where blood cultures were negative. Reads of non-human origin also comprised fragments derived from antimicrobial resistance genes, showing that, in principle, prediction of specific types of resistance might be possible. CONCLUSIONS: The complete workflow from sample preparation to species identification report could be accomplished in roughly 30 h, thus making this approach a promising diagnostic platform for critically ill patients suffering from bloodstream infections. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-016-0326-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4930583 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49305832016-07-03 Next-generation sequencing diagnostics of bacteremia in septic patients Grumaz, Silke Stevens, Philip Grumaz, Christian Decker, Sebastian O. Weigand, Markus A. Hofer, Stefan Brenner, Thorsten von Haeseler, Arndt Sohn, Kai Genome Med Research BACKGROUND: Bloodstream infections remain one of the major challenges in intensive care units, leading to sepsis or even septic shock in many cases. Due to the lack of timely diagnostic approaches with sufficient sensitivity, mortality rates of sepsis are still unacceptably high. However a prompt diagnosis of the causative microorganism is critical to significantly improve outcome of bloodstream infections. Although various targeted molecular tests for blood samples are available, time-consuming blood culture-based approaches still represent the standard of care for the identification of bacteria. METHODS: Here we describe the establishment of a complete diagnostic workflow for the identification of infectious microorganisms from seven septic patients based on unbiased sequence analyses of free circulating DNA from plasma by next-generation sequencing. RESULTS: We found significant levels of DNA fragments derived from pathogenic bacteria in samples from septic patients. Quantitative evaluation of normalized read counts and introduction of a sepsis indicating quantifier (SIQ) score allowed for an unambiguous identification of Gram-positive as well as Gram-negative bacteria that exactly matched with blood cultures from corresponding patient samples. In addition, we also identified species from samples where blood cultures were negative. Reads of non-human origin also comprised fragments derived from antimicrobial resistance genes, showing that, in principle, prediction of specific types of resistance might be possible. CONCLUSIONS: The complete workflow from sample preparation to species identification report could be accomplished in roughly 30 h, thus making this approach a promising diagnostic platform for critically ill patients suffering from bloodstream infections. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-016-0326-8) contains supplementary material, which is available to authorized users. BioMed Central 2016-07-01 /pmc/articles/PMC4930583/ /pubmed/27368373 http://dx.doi.org/10.1186/s13073-016-0326-8 Text en © The Author(s). 2016 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 | Research Grumaz, Silke Stevens, Philip Grumaz, Christian Decker, Sebastian O. Weigand, Markus A. Hofer, Stefan Brenner, Thorsten von Haeseler, Arndt Sohn, Kai Next-generation sequencing diagnostics of bacteremia in septic patients |
title | Next-generation sequencing diagnostics of bacteremia in septic patients |
title_full | Next-generation sequencing diagnostics of bacteremia in septic patients |
title_fullStr | Next-generation sequencing diagnostics of bacteremia in septic patients |
title_full_unstemmed | Next-generation sequencing diagnostics of bacteremia in septic patients |
title_short | Next-generation sequencing diagnostics of bacteremia in septic patients |
title_sort | next-generation sequencing diagnostics of bacteremia in septic patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4930583/ https://www.ncbi.nlm.nih.gov/pubmed/27368373 http://dx.doi.org/10.1186/s13073-016-0326-8 |
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