Literature DB >> 24145532

ARG-ANNOT, a new bioinformatic tool to discover antibiotic resistance genes in bacterial genomes.

Sushim Kumar Gupta1, Babu Roshan Padmanabhan, Seydina M Diene, Rafael Lopez-Rojas, Marie Kempf, Luce Landraud, Jean-Marc Rolain.   

Abstract

ARG-ANNOT (Antibiotic Resistance Gene-ANNOTation) is a new bioinformatic tool that was created to detect existing and putative new antibiotic resistance (AR) genes in bacterial genomes. ARG-ANNOT uses a local BLAST program in Bio-Edit software that allows the user to analyze sequences without a Web interface. All AR genetic determinants were collected from published works and online resources; nucleotide and protein sequences were retrieved from the NCBI GenBank database. After building a database that includes 1,689 antibiotic resistance genes, the software was tested in a blind manner using 100 random sequences selected from the database to verify that the sensitivity and specificity were at 100% even when partial sequences were queried. Notably, BLAST analysis results obtained using the rmtF gene sequence (a new aminoglycoside-modifying enzyme gene sequence that is not included in the database) as a query revealed that the tool was able to link this sequence to short sequences (17 to 40 bp) found in other genes of the rmt family with significant E values. Finally, the analysis of 178 Acinetobacter baumannii and 20 Staphylococcus aureus genomes allowed the detection of a significantly higher number of AR genes than the Resfinder gene analyzer and 11 point mutations in target genes known to be associated with AR. The average time for the analysis of a genome was 3.35 ± 0.13 min. We have created a concise database for BLAST using a Bio-Edit interface that can detect AR genetic determinants in bacterial genomes and can rapidly and easily discover putative new AR genetic determinants.

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Year:  2013        PMID: 24145532      PMCID: PMC3910750          DOI: 10.1128/AAC.01310-13

Source DB:  PubMed          Journal:  Antimicrob Agents Chemother        ISSN: 0066-4804            Impact factor:   5.191


  29 in total

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5.  Identification of acquired antimicrobial resistance genes.

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7.  Acquired antibiotic resistance genes: an overview.

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Journal:  Front Microbiol       Date:  2011-09-28       Impact factor: 5.640

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Journal:  BMC Genomics       Date:  2008-02-08       Impact factor: 3.969

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  458 in total

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Journal:  J Clin Microbiol       Date:  2016-01-27       Impact factor: 5.948

2.  Antimicrobial resistance dashboard application for mapping environmental occurrence and resistant pathogens.

Authors:  Robert D Stedtfeld; Maggie R Williams; Umama Fakher; Timothy A Johnson; Tiffany M Stedtfeld; Fang Wang; Walid T Khalife; Mary Hughes; Brett E Etchebarne; James M Tiedje; Syed A Hashsham
Journal:  FEMS Microbiol Ecol       Date:  2016-02-04       Impact factor: 4.194

3.  Whole-Genome Sequence of a blaOXA-48-Harboring Raoultella ornithinolytica Clinical Isolate from Lebanon.

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Journal:  Antimicrob Agents Chemother       Date:  2016-03-25       Impact factor: 5.191

4.  Occurrence of Clinically Important Lineages, Including the Sequence Type 131 C1-M27 Subclone, among Extended-Spectrum-β-Lactamase-Producing Escherichia coli in Wastewater.

Authors:  Ryota Gomi; Tomonari Matsuda; Yasufumi Matsumura; Masaki Yamamoto; Michio Tanaka; Satoshi Ichiyama; Minoru Yoneda
Journal:  Antimicrob Agents Chemother       Date:  2017-08-24       Impact factor: 5.191

5.  Characterization of Carbapenemase-Producing Klebsiella oxytoca in Spain, 2016-2017.

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Journal:  Antimicrob Agents Chemother       Date:  2019-05-24       Impact factor: 5.191

6.  Antimicrobial resistance and molecular epidemiology using whole-genome sequencing of Neisseria gonorrhoeae in Ireland, 2014-2016: focus on extended-spectrum cephalosporins and azithromycin.

Authors:  L Ryan; D Golparian; N Fennelly; L Rose; P Walsh; B Lawlor; M Mac Aogáin; M Unemo; B Crowley
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2018-06-07       Impact factor: 3.267

7.  Validating the AMRFinder Tool and Resistance Gene Database by Using Antimicrobial Resistance Genotype-Phenotype Correlations in a Collection of Isolates.

Authors:  Michael Feldgarden; Vyacheslav Brover; Daniel H Haft; Arjun B Prasad; Douglas J Slotta; Igor Tolstoy; Gregory H Tyson; Shaohua Zhao; Chih-Hao Hsu; Patrick F McDermott; Daniel A Tadesse; Cesar Morales; Mustafa Simmons; Glenn Tillman; Jamie Wasilenko; Jason P Folster; William Klimke
Journal:  Antimicrob Agents Chemother       Date:  2019-10-22       Impact factor: 5.191

8.  An Integrative Database of β-Lactamase Enzymes: Sequences, Structures, Functions, and Phylogenetic Trees.

Authors:  Vivek Keshri; Seydina M Diene; Adrien Estienne; Justine Dardaillon; Olivier Chabrol; Laurent Tichit; Jean-Marc Rolain; Didier Raoult; Pierre Pontarotti
Journal:  Antimicrob Agents Chemother       Date:  2019-04-25       Impact factor: 5.191

Review 9.  Overview of bioinformatic methods for analysis of antibiotic resistome from genome and metagenome data.

Authors:  Kihyun Lee; Dae-Wi Kim; Chang-Jun Cha
Journal:  J Microbiol       Date:  2021-02-23       Impact factor: 3.422

10.  Intraspecies Transfer of the Chromosomal Acinetobacter baumannii blaNDM-1 Carbapenemase Gene.

Authors:  Thomas Krahn; Daniel Wibberg; Irena Maus; Anika Winkler; Séverine Bontron; Alexander Sczyrba; Patrice Nordmann; Alfred Pühler; Laurent Poirel; Andreas Schlüter
Journal:  Antimicrob Agents Chemother       Date:  2016-04-22       Impact factor: 5.191

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