4.7 Article

Genomic and metagenomic technologies to explore the antibiotic resistance mobilome

Journal

ANNALS OF THE NEW YORK ACADEMY OF SCIENCES
Volume 1388, Issue 1, Pages 26-41

Publisher

WILEY
DOI: 10.1111/nyas.13282

Keywords

resistome; mobilome; metagenome; antibiotic resistance; plasmid

Funding

  1. Spanish Ministry of Economy and Competitiveness [BFU2014-55534-C2-1-P, BIO2014-54507-R, JPIW2013-089-C02-01]
  2. European Seventh Framework Programme [612146/FP7-ICT-2013-10, EVOTARFP7-HEALTH-282004 (EvoTAR)]
  3. Plan Nacional de I+D+ I [ISCIIIPI12-01581, PI15-01307]
  4. Instituto de Salud Carlos III [FIS PI15-00818, CB06/02/0053]
  5. Madrid Autonomous Community [S2010/BMD2414 (PROMPT)]
  6. Instituto de Salud Carlos III (Spanish Network for Research on Infectious Diseases) [REIPI RD12/0015]
  7. European Union [HEALTH-F3-2011-282004 (EVOTAR)]
  8. European Society of Clinical Microbiology and Infectious Diseases
  9. European Development Regional Fund

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Antibiotic resistance is a relevant problem for human health that requires global approaches to establish a deep understanding of the processes of acquisition, stabilization, and spread of resistance among human bacterial pathogens. Since natural (nonclinical) ecosystems are reservoirs of resistance genes, a health-integrated study of the epidemiology of antibiotic resistance requires the exploration of such ecosystems with the aim of determining the role they may play in the selection, evolution, and spread of antibiotic resistance genes, involving the so-called resistance mobilome. High-throughput sequencing techniques allow an unprecedented opportunity to describe the genetic composition of a given microbiome without the need to subculture the organisms present inside. However, bioinformatic methods for analyzing this bulk of data, mainly with respect to binning each resistance gene with the organism hosting it, are still in their infancy. Here, we discuss how current genomic methodologies can serve to analyze the resistance mobilome and its linkage with different bacterial genomes and metagenomes. In addition, we describe the drawbacks of current methodologies for analyzing the resistance mobilome, mainly in cases of complex microbiotas, and discuss the possibility of implementing novel tools to improve our current metagenomic toolbox.

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