In-depth resistome analysis by targeted metagenomics
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 a...
| Autores: | , , , , , , , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Universidad de Cantabria (UC) |
| Repositorio: | UCrea Repositorio Abierto de la Universidad de Cantabria |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unican.es:10902/15932 |
| Acceso en línea: | http://hdl.handle.net/10902/15932 |
| Access Level: | acceso abierto |
| Palabra clave: | Antimicrobial Resistance Resistome Metagenomics Differential Abundance Analysis Targeted Metagenomics |
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España |
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| dc.title.none.fl_str_mv |
In-depth resistome analysis by targeted metagenomics |
| title |
In-depth resistome analysis by targeted metagenomics |
| spellingShingle |
In-depth resistome analysis by targeted metagenomics Lanza, Val F. Antimicrobial Resistance Resistome Metagenomics Differential Abundance Analysis 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 |
| dc.creator.none.fl_str_mv |
Lanza, Val F. Baquero, Fernando Martínez, José Luís Ramos-Ruíz, Ricardo González-Zorn, Bruno Andremont, Antoine Sánchez-Valenzuela, Antonio Ehrlich, Stanislav Dusko Kennedy, Sean Ruppé, Etienne Schaik, Willem van Willems, Rob J. Cruz, Fernando de la|||0000-0003-4758-6857 Coque, Teresa M. |
| author |
Lanza, Val F. |
| author_facet |
Lanza, Val F. Baquero, Fernando Martínez, José Luís Ramos-Ruíz, Ricardo González-Zorn, Bruno Andremont, Antoine Sánchez-Valenzuela, Antonio Ehrlich, Stanislav Dusko Kennedy, Sean Ruppé, Etienne Schaik, Willem van Willems, Rob J. Cruz, Fernando de la|||0000-0003-4758-6857 Coque, Teresa M. |
| author_role |
author |
| author2 |
Baquero, Fernando Martínez, José Luís Ramos-Ruíz, Ricardo González-Zorn, Bruno Andremont, Antoine Sánchez-Valenzuela, Antonio Ehrlich, Stanislav Dusko Kennedy, Sean Ruppé, Etienne Schaik, Willem van Willems, Rob J. Cruz, Fernando de la|||0000-0003-4758-6857 Coque, Teresa M. |
| author2_role |
author author author author author author author author author author author author author |
| dc.contributor.none.fl_str_mv |
Universidad de Cantabria |
| dc.subject.none.fl_str_mv |
Antimicrobial Resistance Resistome Metagenomics Differential Abundance Analysis Targeted Metagenomics |
| topic |
Antimicrobial Resistance Resistome Metagenomics Differential Abundance Analysis Targeted Metagenomics |
| description |
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. |
| publishDate |
2018 |
| dc.date.none.fl_str_mv |
2018 2018-01-01 |
| dc.type.none.fl_str_mv |
journal article http://purl.org/coar/resource_type/c_6501 NA http://purl.org/coar/version/c_be7fb7dd8ff6fe43 |
| dc.type.openaire.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.none.fl_str_mv |
http://hdl.handle.net/10902/15932 |
| url |
http://hdl.handle.net/10902/15932 |
| dc.language.none.fl_str_mv |
Inglés eng |
| language_invalid_str_mv |
Inglés |
| language |
eng |
| dc.relation.none.fl_str_mv |
European Commission http://dx.doi.org/10.13039/501100000780 Framework Programme Seven 612146 |
| dc.rights.none.fl_str_mv |
open access http://purl.org/coar/access_right/c_abf2 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.openaire.fl_str_mv |
info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
open access http://purl.org/coar/access_right/c_abf2 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
| eu_rights_str_mv |
openAccess |
| dc.publisher.none.fl_str_mv |
BMC |
| publisher.none.fl_str_mv |
BMC |
| dc.source.none.fl_str_mv |
Microbiome. 2018 Jan 15;6(1):11 reponame:UCrea Repositorio Abierto de la Universidad de Cantabria instname:Universidad de Cantabria (UC) |
| instname_str |
Universidad de Cantabria (UC) |
| reponame_str |
UCrea Repositorio Abierto de la Universidad de Cantabria |
| collection |
UCrea Repositorio Abierto de la Universidad de Cantabria |
| repository.name.fl_str_mv |
|
| repository.mail.fl_str_mv |
|
| _version_ |
1869408576948142080 |
| spelling |
In-depth resistome analysis by targeted metagenomicsLanza, Val F.Baquero, FernandoMartínez, José LuísRamos-Ruíz, RicardoGonzález-Zorn, BrunoAndremont, AntoineSánchez-Valenzuela, AntonioEhrlich, Stanislav DuskoKennedy, SeanRuppé, EtienneSchaik, Willem vanWillems, Rob J.Cruz, Fernando de la|||0000-0003-4758-6857Coque, Teresa M.Antimicrobial ResistanceResistomeMetagenomicsDifferential Abundance AnalysisTargeted MetagenomicsBACKGROUND: 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.This study was supported by the European Commission, Seven Framework Program (EVOTARFP7-HEALTH-282004 for VFL, FB, JLM, AA, DE, ER, RJLW, WvS, FdlC, and TMC), the Joint Programming Initiative in Antimicrobial Resistance (JPIAMR Third call, STARCS, JPIAMR2016-AC16/00039 to TMC, RJLW, WvS), the Joint Programming Initiative in Water (JPI Water StARE JPIW2013-089-C02-01 to JLM) and the Ministry of Economy and Competitiveness of Spain (BIO2014-54507-R to JLM, and PLASWIRES-612146/FP7-ICT-2013-10 and BFU2014-55534-C2-1-P for FdlC). The authors also acknowledge the European Development Regional Fund “A way to achieve Europe” (ERDF) for co-founding the Spanish R&D National Plan 2012-2019 (BIO2014-54507-R to JLM, PI15-0512 to TMC, PI15-00818 to FB, and BFU2014-55534-C2-1-P to FdlC), CIBER (CIBER in Epidemiology and Public Health, CIBERESP; CB06/02/0053 to FB), the Spanish Network for Research on Infectious Diseases (REIPI RD12/0015 to JLM) and the Regional Government of Madrid (InGeMICSB2017/BMD-3691). Val F. Lanza was further funded by a Research Award Grant 2016 of the European Society for Clinical Microbiology and Infectious Diseases (ESCMID). Additional funding was from the Metagenopolis grant ANR-11-DPBS-0001 to DE.BMCUniversidad de Cantabria20182018-01-01journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articlehttp://hdl.handle.net/10902/15932Microbiome. 2018 Jan 15;6(1):11reponame:UCrea Repositorio Abierto de la Universidad de Cantabriainstname:Universidad de Cantabria (UC)InglésengEuropean Commission http://dx.doi.org/10.13039/501100000780 Framework Programme Seven 612146open accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositorio.unican.es:10902/159322026-06-02T12:39:31Z |
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15,300719 |