ARG-ANNOT, a New Bioinformatic Tool To Discover Antibiotic Resistance Genes in Bacterial Genomes
Sushim K. Gupta,Babu Roshan Padmanabhan,Seydina M. Diene,Rafael López-Rojas,Marie Kempf,Luce Landraud,Jean-Marc Rolain +6 more
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TLDR
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 geneticeterminants is created.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.read more
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Journal ArticleDOI
Natural Horizontal Gene Transfer of Antimicrobial Resistance Genes in Campylobacter spp. From Turkeys and Swine.
Vanina Guernier-Cambert,Vanina Guernier-Cambert,Julian Trachsel,Joel J. Maki,Joel J. Maki,Joel J. Maki,Jing Qi,Matthew J. Sylte,Zahra Hanafy,Sophia Kathariou,Torey Looft +10 more
TL;DR: In this article, the authors used experimental designs closer to real-world conditions to evaluate the possible transfer of antimicrobial resistance genes between Campylobacter strains of the same or different species and originating from different animal hosts (swine or turkeys).
Journal ArticleDOI
Overview of bioinformatic methods for analysis of antibiotic resistome from genome and metagenome data
TL;DR: In this paper, a review of computational workflows used in the research field of antibiotic resistome based on genome or metagenome sequencing is presented, which can be used to list the known antibiotic resistance genes from genomes and metagenomes, quantitatively profile them, and investigate the epidemiological and evolutionary contexts behind their emergence and transmission.
Journal ArticleDOI
Antibiotic resistance genes are differentially mobilized according to resistance mechanism
TL;DR: The ARG-MOB scale is proposed in this paper , which indicates how mobilized detected ARGs are in bacterial genomes, and the results have consequences for the design and interpretation of studies screening for resistance determinants, as mobilized ARGs pose a more concrete risk to human health.
Journal ArticleDOI
Whole-Genome Sequencing of a Colistin-Resistant Acinetobacter baumannii Strain Isolated at a Tertiary Health Facility in Pretoria, South Africa
TL;DR: The mosaic of the virulence factors coupled with the resistance-associated genes and the phenotypic resistance profile highlights the risk that this strain is at this South African tertiary health facility.
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ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data
TL;DR: This work introduces ResistoXplorer, a user-friendly tool that integrates recent advancements in statistics and visualization, coupled with extensive functional annotations and phenotype collection, to enable high-throughput analysis of common outputs generated from metagenomic resistome studies.
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