MicroorganismsBioinformaticsPeer-reviewed journal article
IntegronFinder 2.0: identification and analysis of integrons across Bacteria, with a focus on antibiotic resistance in Klebsiella
Bertrand NéroniD, Eloi LittneriD, Matthieu HaudiquetiD, Amandine PerriniD, Jean CuryiD, Eduardo P. C. RochaiD
Abstract
Integrons are mobile genetic elements that contain multiple cassettes encoding accessory genes whose order is shuffled by a specific integrase. Integrons within mobile genetic elements often contain multiple antibiotic resistance genes that they spread among nosocomial pathogens and contribute to the current antibiotic resistance crisis. However, most integrons are presumably sedentary and encode a much broader diversity of functions. IntegronFinder is a widely used software to identify novel integrons in bacterial genomes, but has aged and lacks some useful functionalities to handle very large datasets of draft genomes or metagenomes. Here, we present IntegronFinder version 2. We have updated the code, improved its efficiency and usability, adapted the output to incomplete genome data, and added a few novel functions. We describe these changes and illustrate the relevance of the program by analyzing the distribution of integrons across more than 20,000 fully sequenced genomes. We also take full advantage of its novel capabilities to analyze close to 4 thousand Klebsiella pneumoniae genomes for the presence of integrons and antibiotic resistance genes within them. Our data shows that K. pneumoniae has a large diversity of integrons and the largest mobile integron in our database of plasmids. The pangenome of these integrons contains a total of 165 different gene families with most of the largest families being related with resistance to numerous types of antibiotics. IntegronFinder is a free and open-source software available at https://github.com/gem-pasteur/Integron_Finder.
- organism: bacteria (other)
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: database / resource
- research focus: benchmarking
- approach: statistical model
- Citations
- 326
- FWCI
- 18.02
- Field percentile
- top 1%
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