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MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples

Metagenomic characterization of microbial communities has the potential to become a tool to identify pathogens in human samples. However, software tools able to extract strain-level typing information from metagenomic data are needed. Low-throughput molecular typing schema such as Multilocus Sequenc...

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Detalles Bibliográficos
Autores principales: Zolfo, Moreno, Tett, Adrian, Jousson, Olivier, Donati, Claudio, Segata, Nicola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5314789/
https://www.ncbi.nlm.nih.gov/pubmed/27651451
http://dx.doi.org/10.1093/nar/gkw837
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author Zolfo, Moreno
Tett, Adrian
Jousson, Olivier
Donati, Claudio
Segata, Nicola
author_facet Zolfo, Moreno
Tett, Adrian
Jousson, Olivier
Donati, Claudio
Segata, Nicola
author_sort Zolfo, Moreno
collection PubMed
description Metagenomic characterization of microbial communities has the potential to become a tool to identify pathogens in human samples. However, software tools able to extract strain-level typing information from metagenomic data are needed. Low-throughput molecular typing schema such as Multilocus Sequence Typing (MLST) are still widely used and provide a wealth of strain-level information that is currently not exploited by metagenomic methods. We introduce MetaMLST, a software tool that reconstructs the MLST loci of microorganisms present in microbial communities from metagenomic data. Tested on synthetic and spiked-in real metagenomes, the pipeline was able to reconstruct the MLST sequences with >98.5% accuracy at coverages as low as 1×. On real samples, the pipeline showed higher sensitivity than assembly-based approaches and it proved successful in identifying strains in epidemic outbreaks as well as in intestinal, skin and gastrointestinal microbiome samples.
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spelling pubmed-53147892017-02-21 MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples Zolfo, Moreno Tett, Adrian Jousson, Olivier Donati, Claudio Segata, Nicola Nucleic Acids Res Computational Biology Metagenomic characterization of microbial communities has the potential to become a tool to identify pathogens in human samples. However, software tools able to extract strain-level typing information from metagenomic data are needed. Low-throughput molecular typing schema such as Multilocus Sequence Typing (MLST) are still widely used and provide a wealth of strain-level information that is currently not exploited by metagenomic methods. We introduce MetaMLST, a software tool that reconstructs the MLST loci of microorganisms present in microbial communities from metagenomic data. Tested on synthetic and spiked-in real metagenomes, the pipeline was able to reconstruct the MLST sequences with >98.5% accuracy at coverages as low as 1×. On real samples, the pipeline showed higher sensitivity than assembly-based approaches and it proved successful in identifying strains in epidemic outbreaks as well as in intestinal, skin and gastrointestinal microbiome samples. Oxford University Press 2017-01-25 2016-09-19 /pmc/articles/PMC5314789/ /pubmed/27651451 http://dx.doi.org/10.1093/nar/gkw837 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Computational Biology
Zolfo, Moreno
Tett, Adrian
Jousson, Olivier
Donati, Claudio
Segata, Nicola
MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples
title MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples
title_full MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples
title_fullStr MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples
title_full_unstemmed MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples
title_short MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples
title_sort metamlst: multi-locus strain-level bacterial typing from metagenomic samples
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5314789/
https://www.ncbi.nlm.nih.gov/pubmed/27651451
http://dx.doi.org/10.1093/nar/gkw837
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