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ARG-ANNOT, a New Bioinformatic Tool To Discover Antibiotic Resistance Genes in Bacterial Genomes

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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.

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Citations
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Computational resources in the management of antibiotic resistance: Speeding up drug discovery

TL;DR: More than 50 computational resources have been developed in past two decades for forecasting of antibiotic resistance associated mutations, genes and genomes as mentioned in this paper, with most of them based on similarity search tools such as BLAST and HMMER.
Journal ArticleDOI

Metagenomics reveals the diversity and taxonomy of antibiotic resistance genes in sufu bacterial communities

TL;DR: In this paper, genome-centered metagenomics was used to identify distribution patterns of antibiotic resistance genes (ARGs) in major bacterial species in sufu, and the number and diversity of ARGs in MAGs differed in taxonomic lineages, reflecting antibiotic resistance in different sufu bacterial species.
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Identification and Elimination of the Clinically Relevant Multi-Resistant Environmental Bacteria Ralstonia insidiosa in Primary Cell Culture.

TL;DR: A mobile cell culture contaminant with “black dot”-like microscopic appearance in newly established irreplaceable hybridoma cell lines and its identification as the ubiquitous environmental and clinically relevant Gram-negative bacterium Ralstonia insidiosa (R. insidioa), a strong biofilm producer.
References
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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

Identification of acquired antimicrobial resistance genes

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

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.
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