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Massively parallel pathogen identification using high‐density microarrays
Identification of microbial pathogens in clinical specimens is still performed by phenotypic methods that are often slow and cumbersome, despite the availability of more comprehensive genotyping technologies. We present an approach based on whole‐genome amplification and resequencing microarrays for...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3864434/ https://www.ncbi.nlm.nih.gov/pubmed/21261824 http://dx.doi.org/10.1111/j.1751-7915.2007.00012.x |
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author | Berthet, Nicolas Dickinson, Philip Filliol, Ingrid Reinhardt, Anita K. Batejat, Christophe Vallaeys, Tatiana Kong, Katherine A. Davies, Christopher Lee, Walter Zhang, Shenglan Turpaz, Yaron Heym, Beate Coralie, Gilberte Dacheux, Laurent Burguière, Ana Maria Bourhy, Hervé Old, Iain G. Manuguerra, Jean‐Claude Cole, Stewart T. Kennedy, Giulia C. |
author_facet | Berthet, Nicolas Dickinson, Philip Filliol, Ingrid Reinhardt, Anita K. Batejat, Christophe Vallaeys, Tatiana Kong, Katherine A. Davies, Christopher Lee, Walter Zhang, Shenglan Turpaz, Yaron Heym, Beate Coralie, Gilberte Dacheux, Laurent Burguière, Ana Maria Bourhy, Hervé Old, Iain G. Manuguerra, Jean‐Claude Cole, Stewart T. Kennedy, Giulia C. |
author_sort | Berthet, Nicolas |
collection | PubMed |
description | Identification of microbial pathogens in clinical specimens is still performed by phenotypic methods that are often slow and cumbersome, despite the availability of more comprehensive genotyping technologies. We present an approach based on whole‐genome amplification and resequencing microarrays for unbiased pathogen detection. This 10 h process identifies a broad spectrum of bacterial and viral species and predicts antibiotic resistance and pathogenicity and virulence profiles. We successfully identify a variety of bacteria and viruses, both in isolation and in complex mixtures, and the high specificity of the microarray distinguishes between different pathogens that cause diseases with overlapping symptoms. The resequencing approach also allows identification of organisms whose sequences are not tiled on the array, greatly expanding the repertoire of identifiable organisms and their variants. We identify organisms by hybridization of their DNA in as little as 1–4 h. Using this method, we identified Monkeypox virus and drug‐resistant Staphylococcus aureus in a skin lesion taken from a child suspected of an orthopoxvirus infection, despite poor transport conditions of the sample, and a vast excess of human DNA. Our results suggest this technology could be applied in a clinical setting to test for numerous pathogens in a rapid, sensitive and unbiased manner. |
format | Online Article Text |
id | pubmed-3864434 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Blackwell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-38644342014-02-12 Massively parallel pathogen identification using high‐density microarrays Berthet, Nicolas Dickinson, Philip Filliol, Ingrid Reinhardt, Anita K. Batejat, Christophe Vallaeys, Tatiana Kong, Katherine A. Davies, Christopher Lee, Walter Zhang, Shenglan Turpaz, Yaron Heym, Beate Coralie, Gilberte Dacheux, Laurent Burguière, Ana Maria Bourhy, Hervé Old, Iain G. Manuguerra, Jean‐Claude Cole, Stewart T. Kennedy, Giulia C. Microb Biotechnol Research Articles Identification of microbial pathogens in clinical specimens is still performed by phenotypic methods that are often slow and cumbersome, despite the availability of more comprehensive genotyping technologies. We present an approach based on whole‐genome amplification and resequencing microarrays for unbiased pathogen detection. This 10 h process identifies a broad spectrum of bacterial and viral species and predicts antibiotic resistance and pathogenicity and virulence profiles. We successfully identify a variety of bacteria and viruses, both in isolation and in complex mixtures, and the high specificity of the microarray distinguishes between different pathogens that cause diseases with overlapping symptoms. The resequencing approach also allows identification of organisms whose sequences are not tiled on the array, greatly expanding the repertoire of identifiable organisms and their variants. We identify organisms by hybridization of their DNA in as little as 1–4 h. Using this method, we identified Monkeypox virus and drug‐resistant Staphylococcus aureus in a skin lesion taken from a child suspected of an orthopoxvirus infection, despite poor transport conditions of the sample, and a vast excess of human DNA. Our results suggest this technology could be applied in a clinical setting to test for numerous pathogens in a rapid, sensitive and unbiased manner. Blackwell Publishing Ltd 2008-01 2007-11-22 /pmc/articles/PMC3864434/ /pubmed/21261824 http://dx.doi.org/10.1111/j.1751-7915.2007.00012.x Text en Copyright © 2007 The Authors. Journal compilation © 2007 Society for Applied Microbiology and Blackwell Publishing Ltd. |
spellingShingle | Research Articles Berthet, Nicolas Dickinson, Philip Filliol, Ingrid Reinhardt, Anita K. Batejat, Christophe Vallaeys, Tatiana Kong, Katherine A. Davies, Christopher Lee, Walter Zhang, Shenglan Turpaz, Yaron Heym, Beate Coralie, Gilberte Dacheux, Laurent Burguière, Ana Maria Bourhy, Hervé Old, Iain G. Manuguerra, Jean‐Claude Cole, Stewart T. Kennedy, Giulia C. Massively parallel pathogen identification using high‐density microarrays |
title | Massively parallel pathogen identification using high‐density microarrays |
title_full | Massively parallel pathogen identification using high‐density microarrays |
title_fullStr | Massively parallel pathogen identification using high‐density microarrays |
title_full_unstemmed | Massively parallel pathogen identification using high‐density microarrays |
title_short | Massively parallel pathogen identification using high‐density microarrays |
title_sort | massively parallel pathogen identification using high‐density microarrays |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3864434/ https://www.ncbi.nlm.nih.gov/pubmed/21261824 http://dx.doi.org/10.1111/j.1751-7915.2007.00012.x |
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