In-depth resistome analysis by targeted metagenomics

Abstract Background Antimicrobial resistance is a major global health challenge. Metagenomics allows analyzing the presence and dynamics of “resistomes” (the ensemble of genes encoding antimicrobial resistance in a given microbiome) in disparate microbial ecosystems. However, the low sensitivity and...

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Main Authors: Val F. Lanza, Fernando Baquero, José Luís Martínez, Ricardo Ramos-Ruíz, Bruno González-Zorn, Antoine Andremont, Antonio Sánchez-Valenzuela, Stanislav Dusko Ehrlich, Sean Kennedy, Etienne Ruppé, Willem van Schaik, Rob J. Willems, Fernando de la Cruz, Teresa M. Coque
Format: Article
Language:English
Published: BMC 2018-01-01
Series:Microbiome
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40168-017-0387-y
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spelling doaj-e564182b43804a24a7e1823cba0fd5852020-11-24T22:05:35ZengBMCMicrobiome2049-26182018-01-016111410.1186/s40168-017-0387-yIn-depth resistome analysis by targeted metagenomicsVal F. Lanza0Fernando Baquero1José Luís Martínez2Ricardo Ramos-Ruíz3Bruno González-Zorn4Antoine Andremont5Antonio Sánchez-Valenzuela6Stanislav Dusko Ehrlich7Sean Kennedy8Etienne Ruppé9Willem van Schaik10Rob J. Willems11Fernando de la Cruz12Teresa M. Coque13Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Health Research Institute (IRYCIS)Department of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Health Research Institute (IRYCIS)Joint Unit of Antibiotic Resistance and Bacterial Virulence associated with the Spanish National Research Council (CSIC)Genomics UnitFaculty of Veterinary Medicine, Complutense University of MadridIAME, UMR 1137, INSERM, Paris Diderot University, Sorbonne Paris Cité, Bacteriology Laboratory, Hospital Bichat, AP-HPDepartment of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Health Research Institute (IRYCIS)MGP MetaGénoPolis, INRA, University of Paris-SaclayMGP MetaGénoPolis, INRA, University of Paris-SaclayIAME, UMR 1137, INSERM, Paris Diderot University, Sorbonne Paris Cité, Bacteriology Laboratory, Hospital Bichat, AP-HPDepartment of Medical Microbiology, University Medical CenterDepartment of Medical Microbiology, University Medical CenterDepartment of Molecular Biology, University of CantabriaDepartment of Microbiology, Ramón y Cajal University Hospital, Ramón y Cajal Health Research Institute (IRYCIS)Abstract Background Antimicrobial resistance is a major global health challenge. Metagenomics allows analyzing the presence and dynamics of “resistomes” (the ensemble of genes encoding antimicrobial resistance in a given microbiome) in disparate microbial ecosystems. However, the low sensitivity and specificity of available metagenomic methods preclude the detection of minority populations (often present below their detection threshold) and/or the identification of allelic variants that differ in the resulting phenotype. Here, we describe a novel strategy that combines targeted metagenomics using last generation in-solution capture platforms, with novel bioinformatics tools to establish a standardized framework that allows both quantitative and qualitative analyses of resistomes. Methods We developed ResCap, a targeted sequence capture platform based on SeqCapEZ (NimbleGene) technology, which includes probes for 8667 canonical resistance genes (7963 antibiotic resistance genes and 704 genes conferring resistance to metals or biocides), and 2517 relaxase genes (plasmid markers) and 78,600 genes homologous to the previous identified targets (47,806 for antibiotics and 30,794 for biocides or metals). Its performance was compared with metagenomic shotgun sequencing (MSS) for 17 fecal samples (9 humans, 8 swine). ResCap significantly improves MSS to detect “gene abundance” (from 2.0 to 83.2%) and “gene diversity” (26 versus 14.9 genes unequivocally detected per sample per million of reads; the number of reads unequivocally mapped increasing up to 300-fold by using ResCap), which were calculated using novel bioinformatic tools. ResCap also facilitated the analysis of novel genes potentially involved in the resistance to antibiotics, metals, biocides, or any combination thereof. Conclusions ResCap, the first targeted sequence capture, specifically developed to analyze resistomes, greatly enhances the sensitivity and specificity of available metagenomic methods and offers the possibility to analyze genes related to the selection and transfer of antimicrobial resistance (biocides, heavy metals, plasmids). The model opens the possibility to study other complex microbial systems in which minority populations play a relevant role.http://link.springer.com/article/10.1186/s40168-017-0387-yAntimicrobial resistanceResistomeMetagenomicsDifferential abundance analysisTargeted metagenomics
collection DOAJ
language English
format Article
sources DOAJ
author Val F. Lanza
Fernando Baquero
José Luís Martínez
Ricardo Ramos-Ruíz
Bruno González-Zorn
Antoine Andremont
Antonio Sánchez-Valenzuela
Stanislav Dusko Ehrlich
Sean Kennedy
Etienne Ruppé
Willem van Schaik
Rob J. Willems
Fernando de la Cruz
Teresa M. Coque
spellingShingle Val F. Lanza
Fernando Baquero
José Luís Martínez
Ricardo Ramos-Ruíz
Bruno González-Zorn
Antoine Andremont
Antonio Sánchez-Valenzuela
Stanislav Dusko Ehrlich
Sean Kennedy
Etienne Ruppé
Willem van Schaik
Rob J. Willems
Fernando de la Cruz
Teresa M. Coque
In-depth resistome analysis by targeted metagenomics
Microbiome
Antimicrobial resistance
Resistome
Metagenomics
Differential abundance analysis
Targeted metagenomics
author_facet Val F. Lanza
Fernando Baquero
José Luís Martínez
Ricardo Ramos-Ruíz
Bruno González-Zorn
Antoine Andremont
Antonio Sánchez-Valenzuela
Stanislav Dusko Ehrlich
Sean Kennedy
Etienne Ruppé
Willem van Schaik
Rob J. Willems
Fernando de la Cruz
Teresa M. Coque
author_sort Val F. Lanza
title In-depth resistome analysis by targeted metagenomics
title_short In-depth resistome analysis by targeted metagenomics
title_full In-depth resistome analysis by targeted metagenomics
title_fullStr In-depth resistome analysis by targeted metagenomics
title_full_unstemmed In-depth resistome analysis by targeted metagenomics
title_sort in-depth resistome analysis by targeted metagenomics
publisher BMC
series Microbiome
issn 2049-2618
publishDate 2018-01-01
description Abstract Background Antimicrobial resistance is a major global health challenge. Metagenomics allows analyzing the presence and dynamics of “resistomes” (the ensemble of genes encoding antimicrobial resistance in a given microbiome) in disparate microbial ecosystems. However, the low sensitivity and specificity of available metagenomic methods preclude the detection of minority populations (often present below their detection threshold) and/or the identification of allelic variants that differ in the resulting phenotype. Here, we describe a novel strategy that combines targeted metagenomics using last generation in-solution capture platforms, with novel bioinformatics tools to establish a standardized framework that allows both quantitative and qualitative analyses of resistomes. Methods We developed ResCap, a targeted sequence capture platform based on SeqCapEZ (NimbleGene) technology, which includes probes for 8667 canonical resistance genes (7963 antibiotic resistance genes and 704 genes conferring resistance to metals or biocides), and 2517 relaxase genes (plasmid markers) and 78,600 genes homologous to the previous identified targets (47,806 for antibiotics and 30,794 for biocides or metals). Its performance was compared with metagenomic shotgun sequencing (MSS) for 17 fecal samples (9 humans, 8 swine). ResCap significantly improves MSS to detect “gene abundance” (from 2.0 to 83.2%) and “gene diversity” (26 versus 14.9 genes unequivocally detected per sample per million of reads; the number of reads unequivocally mapped increasing up to 300-fold by using ResCap), which were calculated using novel bioinformatic tools. ResCap also facilitated the analysis of novel genes potentially involved in the resistance to antibiotics, metals, biocides, or any combination thereof. Conclusions ResCap, the first targeted sequence capture, specifically developed to analyze resistomes, greatly enhances the sensitivity and specificity of available metagenomic methods and offers the possibility to analyze genes related to the selection and transfer of antimicrobial resistance (biocides, heavy metals, plasmids). The model opens the possibility to study other complex microbial systems in which minority populations play a relevant role.
topic Antimicrobial resistance
Resistome
Metagenomics
Differential abundance analysis
Targeted metagenomics
url http://link.springer.com/article/10.1186/s40168-017-0387-y
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