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In-depth resistome analysis by targeted metagenomics

Microbiome publish this investigation article

January 15th, 2018

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




Lanza VF., Baquero F., Martinez JL., Ramos-Ruiz R., Gonzalez-Zorn B., Andremont A., Sanchez-Valenzuela A., Ehrlich SD., Kennedy S., Ruppe E., van Schaik W., Willems RJ., de la Cruz F. and Coque TM.




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In-depth resistome analysis by targeted metagenomics

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In-depth resistome analysis by targeted metagenomics



Participants:

Comunidad de MadridServicio de Microbiología. Hospital Universitario Ramón y Cajal. Salud Madrid. Comunidad de Madrid.

Comunidad de MadridInstituto Ramón y Cajal de Investigación Sanitaria (IRYCIS). Universidad Complutense (UCM). Universidad Autónoma de Madrid (UAM). Universidad de Alcalá (UAH). Salud Madrid. Comunidad de Madrid.

Consejo Superior de Investigaciones CientíficasUnidad asociada de Resistencia a Antibióticos y Virulencia Bacteriana. Consejo Superior de Investigaciones Científicas (CSIC).

Instituto de Salud Carlos IIICentro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP). Instituto de Salud Carlos III (ISCIII).

Consejo Superior de Investigaciones CientíficasCentro Nacional de Biotecnología (CNB). Consejo Superior de Investigaciones Científicas (CSIC).

Fundación Parque Científico de MadridUnidad de Genómica. Fundación Parque Científico de Madrid (FPCM).

Universidad ComplutenseServicio de Zoonosis de Transmisión Alimentaria y Resistencia a Antimicrobianos (ZTA). Centro de Vigilancia Sanitaria Veterinaria (VISAVET). Universidad Complutense (UCM).

Universidad ComplutenseDepartamento de Sanidad Animal. Facultad de Veterinaria. Universidad Complutense (UCM).

Université Paris DiderotHôpital Bichat-Claude Bernard. Université Paris Diderot.

MetaGénoPolis (MGP).

Université Paris-Saclay.

Center of Host Microbiome Interactions (CHMI). King´s College London (KCL).

Institut PasteurBioinformatics and Biostatistics HUB. Institut Pasteur.

Institut PasteurC3BI and Biomics Pole. Institut Pasteur.

Institut PasteurCentr d´innovation et reserche technologique (CITECH). Institut Pasteur.

Universitair Medisch Centrum UtrechtMedical Microbiology. Universitair Medisch Centrum Utrecht (UMC Utrecht).

Institute of Microbiology and Infection. University of Birmingham.

Universidad de CantabriaBiología Molecular. Instituto de Biomedicina y Biotecnología de Cantabria. Universidad de Cantabria (UC).

Comunidad de MadridHospital Universitario Ramón y Cajal. Salud Madrid. Comunidad de Madrid.

Comunidad de MadridInstituto Ramón y Cajal de Investigación Sanitaria (IRYCIS). Universidad Complutense (UCM). Universidad Autónoma de Madrid (UAM). Universidad de Alcalá (UAH). Salud Madrid. Comunidad de Madrid.







FACTOR YEAR Q
10.465 2018

NLMID: 101615147

PMID: 29335005

ISSN: 2049-2618



TITLE: In-depth resistome analysis by targeted metagenomics


JOURNAL: Microbiome


NUMERACIÓN: 6(1):11


AÑO: 2018


PUBLISHER: London: BioMed Central, 2013


AUTHORS: Lanza VF., Baquero F., Martinez JL., Ramos-Ruiz R., Gonzalez-Zorn B., Andremont A., Sanchez-Valenzuela A., Ehrlich SD., Kennedy S., Ruppe E., van Schaik W., Willems RJ., de la Cruz F. and Coque TM.


Bruno González Zorn

DOI: https://doi.org/10.1186/s40168-017-0387-y


CITE THIS PUBLICATION:

Lanza VF., Baquero F., Martinez JL., Ramos-Ruiz R., Gonzalez-Zorn B., Andremont A., Sanchez-Valenzuela A., Ehrlich SD., Kennedy S., Ruppe E., van Schaik W., Willems RJ., de la Cruz F. and Coque TM. In-depth resistome analysis by targeted metagenomics. Microbiome. 6(1):11. 2018. (A). ISSN: 2049-2618. DOI: 10.1186/s40168-017-0387-y


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