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Identification and reconstruction of novel antibiotic resistance genes from metagenomes

BACKGROUND: Environmental and commensal bacteria maintain a diverse and largely unknown collection of antibiotic resistance genes (ARGs) that, over time, may be mobilized and transferred to pathogens. Metagenomics enables cultivation-independent characterization of bacterial communities but the resu...

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Autores principales: Berglund, Fanny, Österlund, Tobias, Boulund, Fredrik, Marathe, Nachiket P., Larsson, D. G. Joakim, Kristiansson, Erik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444489/
https://www.ncbi.nlm.nih.gov/pubmed/30935407
http://dx.doi.org/10.1186/s40168-019-0670-1
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author Berglund, Fanny
Österlund, Tobias
Boulund, Fredrik
Marathe, Nachiket P.
Larsson, D. G. Joakim
Kristiansson, Erik
author_facet Berglund, Fanny
Österlund, Tobias
Boulund, Fredrik
Marathe, Nachiket P.
Larsson, D. G. Joakim
Kristiansson, Erik
author_sort Berglund, Fanny
collection PubMed
description BACKGROUND: Environmental and commensal bacteria maintain a diverse and largely unknown collection of antibiotic resistance genes (ARGs) that, over time, may be mobilized and transferred to pathogens. Metagenomics enables cultivation-independent characterization of bacterial communities but the resulting data is noisy and highly fragmented, severely hampering the identification of previously undescribed ARGs. We have therefore developed fARGene, a method for identification and reconstruction of ARGs directly from shotgun metagenomic data. RESULTS: fARGene uses optimized gene models and can therefore with high accuracy identify previously uncharacterized resistance genes, even if their sequence similarity to known ARGs is low. By performing the analysis directly on the metagenomic fragments, fARGene also circumvents the need for a high-quality assembly. To demonstrate the applicability of fARGene, we reconstructed β-lactamases from five billion metagenomic reads, resulting in 221 ARGs, of which 58 were previously not reported. Based on 38 ARGs reconstructed by fARGene, experimental verification showed that 81% provided a resistance phenotype in Escherichia coli. Compared to other methods for detecting ARGs in metagenomic data, fARGene has superior sensitivity and the ability to reconstruct previously unknown genes directly from the sequence reads. CONCLUSIONS: We conclude that fARGene provides an efficient and reliable way to explore the unknown resistome in bacterial communities. The method is applicable to any type of ARGs and is freely available via GitHub under the MIT license. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40168-019-0670-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-64444892019-04-11 Identification and reconstruction of novel antibiotic resistance genes from metagenomes Berglund, Fanny Österlund, Tobias Boulund, Fredrik Marathe, Nachiket P. Larsson, D. G. Joakim Kristiansson, Erik Microbiome Software BACKGROUND: Environmental and commensal bacteria maintain a diverse and largely unknown collection of antibiotic resistance genes (ARGs) that, over time, may be mobilized and transferred to pathogens. Metagenomics enables cultivation-independent characterization of bacterial communities but the resulting data is noisy and highly fragmented, severely hampering the identification of previously undescribed ARGs. We have therefore developed fARGene, a method for identification and reconstruction of ARGs directly from shotgun metagenomic data. RESULTS: fARGene uses optimized gene models and can therefore with high accuracy identify previously uncharacterized resistance genes, even if their sequence similarity to known ARGs is low. By performing the analysis directly on the metagenomic fragments, fARGene also circumvents the need for a high-quality assembly. To demonstrate the applicability of fARGene, we reconstructed β-lactamases from five billion metagenomic reads, resulting in 221 ARGs, of which 58 were previously not reported. Based on 38 ARGs reconstructed by fARGene, experimental verification showed that 81% provided a resistance phenotype in Escherichia coli. Compared to other methods for detecting ARGs in metagenomic data, fARGene has superior sensitivity and the ability to reconstruct previously unknown genes directly from the sequence reads. CONCLUSIONS: We conclude that fARGene provides an efficient and reliable way to explore the unknown resistome in bacterial communities. The method is applicable to any type of ARGs and is freely available via GitHub under the MIT license. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40168-019-0670-1) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-01 /pmc/articles/PMC6444489/ /pubmed/30935407 http://dx.doi.org/10.1186/s40168-019-0670-1 Text en © The Author(s). 2019 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 Software
Berglund, Fanny
Österlund, Tobias
Boulund, Fredrik
Marathe, Nachiket P.
Larsson, D. G. Joakim
Kristiansson, Erik
Identification and reconstruction of novel antibiotic resistance genes from metagenomes
title Identification and reconstruction of novel antibiotic resistance genes from metagenomes
title_full Identification and reconstruction of novel antibiotic resistance genes from metagenomes
title_fullStr Identification and reconstruction of novel antibiotic resistance genes from metagenomes
title_full_unstemmed Identification and reconstruction of novel antibiotic resistance genes from metagenomes
title_short Identification and reconstruction of novel antibiotic resistance genes from metagenomes
title_sort identification and reconstruction of novel antibiotic resistance genes from metagenomes
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444489/
https://www.ncbi.nlm.nih.gov/pubmed/30935407
http://dx.doi.org/10.1186/s40168-019-0670-1
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