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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Antibiotic-Resistance Genes in Waste Water.
TL;DR: Some of the main methods for studying antibiotic resistance in waste waters and the latest research and main knowledge gaps on the issue are described and some future research directions are proposed.
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Metagenomic analysis reveals wastewater treatment plants as hotspots of antibiotic resistance genes and mobile genetic elements
TL;DR: The metagenomic analysis showed that the activated sludge and the digested sludge exhibited different microbial communities and changes in the types and occurrence of ARGs and MGEs, and indicated that some environmental bacteria might be potential hosts of multiple ARGs.
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Stunted microbiota and opportunistic pathogen colonization in caesarean-section birth
Yan Shao,Samuel C. Forster,Samuel C. Forster,Samuel C. Forster,Evdokia Tsaliki,Kevin Vervier,Angela Strang,Nandi Simpson,Nitin Kumar,Mark D. Stares,Alison Rodger,Peter Brocklehurst,Nigel Field,Trevor D. Lawley +13 more
TL;DR: The disrupted transmission of maternal Bacteroides strains, and high-level colonization by opportunistic pathogens associated with the hospital environment (including Enterococcus, Enterobacter and Klebsiella species), in babies delivered by caesarean section are reported.
Journal ArticleDOI
ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads
Martin Hunt,Alison E. Mather,Alison E. Mather,Leonor Sánchez-Busó,Andrew J. Page,Julian Parkhill,Jacqueline A. Keane,Simon R. Harris +7 more
TL;DR: A new tool is presented, ARIBA, that identifies AMR-associated genes and single nucleotide polymorphisms directly from short reads, and generates detailed and customizable output.
Journal ArticleDOI
DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.
Gustavo Arango-Argoty,Emily Garner,Amy Pruden,Lenwood S. Heath,Peter J. Vikesland,Liqing Zhang +5 more
TL;DR: The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice, and DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs.
References
More filters
Journal ArticleDOI
Basic Local Alignment Search Tool
TL;DR: A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score.
Journal ArticleDOI
The RAST Server: Rapid Annotations using Subsystems Technology
Ramy K. Aziz,Ramy K. Aziz,Daniela Bartels,Aaron A. Best,Matthew DeJongh,Terrence Disz,Terrence Disz,Robert Edwards,Kevin Formsma,Svetlana Gerdes,Elizabeth M. Glass,Michael Kubal,Folker Meyer,Folker Meyer,Gary J. Olsen,Gary J. Olsen,Robert Olson,Robert Olson,Andrei L. Osterman,Ross Overbeek,Leslie Klis McNeil,Daniel Paarmann,Tobias Paczian,Bruce Parrello,Gordon D. Pusch,Claudia I. Reich,Rick Stevens,Rick Stevens,Olga Vassieva,Veronika Vonstein,Andreas Wilke,Olga Zagnitko +31 more
TL;DR: A fully automated service for annotating bacterial and archaeal genomes that identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user.
Journal ArticleDOI
Identification of acquired antimicrobial resistance genes
Ea Zankari,Henrik Hasman,Salvatore Cosentino,Martin Vestergaard,Simon Rasmussen,Ole Lund,Frank Møller Aarestrup,Mette Voldby Larsen +7 more
TL;DR: A web server providing a convenient way of identifying acquired antimicrobial resistance genes in completely sequenced isolates was created, and the method was evaluated on WGS chromosomes and plasmids of 30 isolates.
Journal ArticleDOI
Improved microbial gene identification with GLIMMER
TL;DR: Significant technical improvements to GLIMMER are reported that improve its accuracy still further, and a comprehensive evaluation demonstrates that the accuracy of the system is likely to be higher than previously recognized.
Journal ArticleDOI
Antibiotic resistance is ancient
Vanessa M. D'Costa,Christine E. King,Lindsay Kalan,Mariya Morar,Wilson W L Sung,Carsten Schwarz,Duane G. Froese,Grant D. Zazula,Fabrice Calmels,Régis Debruyne,G. Brian Golding,Hendrik N. Poinar,Gerard D. Wright +12 more
TL;DR: Target metagenomic analyses of rigorously authenticated ancient DNA from 30,000-year-old Beringian permafrost sediments are reported and show conclusively that antibiotic resistance is a natural phenomenon that predates the modern selective pressure of clinical antibiotic use.