Literature DB >> 28673041

Using metagenomics to investigate human and environmental resistomes.

Johan Bengtsson-Palme1,2, D G Joakim Larsson1,2, Erik Kristiansson2,3.   

Abstract

Antibiotic resistance is a global health concern declared by the WHO as one of the largest threats to modern healthcare. In recent years, metagenomic DNA sequencing has started to be applied as a tool to study antibiotic resistance in different environments, including the human microbiota. However, a multitude of methods exist for metagenomic data analysis, and not all methods are suitable for the investigation of resistance genes, particularly if the desired outcome is an assessment of risks to human health. In this review, we outline the current state of methods for sequence handling, mapping to databases of resistance genes, statistical analysis and metagenomic assembly. In addition, we provide an overview of important considerations related to the analysis of resistance genes, and recommend some of the currently used tools and methods that are best equipped to inform research and clinical practice related to antibiotic resistance.
© The Author 2017. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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Year:  2017        PMID： 28673041     DOI： 10.1093/jac/dkx199

Source DB:  PubMed          Journal:  J Antimicrob Chemother        ISSN： 0305-7453            Impact factor:   5.790


  21 in total

1.  Viruses as key reservoirs of antibiotic resistance genes in the environment.

Authors:  Didier Debroas; Cléa Siguret
Journal:  ISME J       Date:  2019-07-29       Impact factor: 10.302

2.  Identification of a Novel Plasmid-Borne Gentamicin Resistance Gene in Nontyphoidal Salmonella Isolated from Retail Turkey.

Authors:  Happy-Sarah L Kim; Ricardo D Rodriguez; Sydney K Morris; Shaohua Zhao; Justin J Donato
Journal:  Antimicrob Agents Chemother       Date:  2020-10-20       Impact factor: 5.191

3.  Evaluation of Metagenomic-Enabled Antibiotic Resistance Surveillance at a Conventional Wastewater Treatment Plant.

Authors:  Haniyyah J Majeed; Maria V Riquelme; Benjamin C Davis; Suraj Gupta; Luisa Angeles; Diana S Aga; Emily Garner; Amy Pruden; Peter J Vikesland
Journal:  Front Microbiol       Date:  2021-05-13       Impact factor: 5.640

4.  The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples.

Authors:  H Soon Gweon; Liam P Shaw; Jeremy Swann; Nicola De Maio; Manal AbuOun; Rene Niehus; Alasdair T M Hubbard; Mike J Bowes; Mark J Bailey; Tim E A Peto; Sarah J Hoosdally; A Sarah Walker; Robert P Sebra; Derrick W Crook; Muna F Anjum; Daniel S Read; Nicole Stoesser
Journal:  Environ Microbiome       Date:  2019-10-24

5.  Characterization of Metagenomes in Urban Aquatic Compartments Reveals High Prevalence of Clinically Relevant Antibiotic Resistance Genes in Wastewaters.

Authors:  Charmaine Ng; Martin Tay; Boonfei Tan; Thai-Hoang Le; Laurence Haller; Hongjie Chen; Tse H Koh; Timothy M S Barkham; Karina Y-H Gin
Journal:  Front Microbiol       Date:  2017-11-16       Impact factor: 5.640

Review 6.  Environmental factors influencing the development and spread of antibiotic resistance.

Authors:  Johan Bengtsson-Palme; Erik Kristiansson; D G Joakim Larsson
Journal:  FEMS Microbiol Rev       Date:  2018-01-01       Impact factor: 16.408

Review 7.  The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies.

Authors:  Alexandre Angers-Loustau; Mauro Petrillo; Johan Bengtsson-Palme; Thomas Berendonk; Burton Blais; Kok-Gan Chan; Teresa M Coque; Paul Hammer; Stefanie Heß; Dafni M Kagkli; Carsten Krumbiegel; Val F Lanza; Jean-Yves Madec; Thierry Naas; Justin O'Grady; Valentina Paracchini; John W A Rossen; Etienne Ruppé; Jessica Vamathevan; Vittorio Venturi; Guy Van den Eede
Journal:  F1000Res       Date:  2018-04-13

8.  DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

Authors:  Gustavo Arango-Argoty; Emily Garner; Amy Pruden; Lenwood S Heath; Peter Vikesland; Liqing Zhang
Journal:  Microbiome       Date:  2018-02-01       Impact factor: 14.650

9.  Maternal gut and breast milk microbiota affect infant gut antibiotic resistome and mobile genetic elements.

Authors:  Katariina Pärnänen; Antti Karkman; Jenni Hultman; Christina Lyra; Johan Bengtsson-Palme; D G Joakim Larsson; Samuli Rautava; Erika Isolauri; Seppo Salminen; Himanshu Kumar; Reetta Satokari; Marko Virta
Journal:  Nat Commun       Date:  2018-09-24       Impact factor: 14.919

10.  The Association between Insertion Sequences and Antibiotic Resistance Genes.

Authors:  Mohammad Razavi; Erik Kristiansson; Carl-Fredrik Flach; D G Joakim Larsson
Journal:  mSphere       Date:  2020-09-02       Impact factor: 4.389
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