Flankophile: a bioinformatic pipeline for prokaryotic genomic synteny analysis

Alix Vincent Thorn, Frank M. Aarestrup, Patrick Munk*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Analysis of flanking region sequences can be useful when comparing mobile prokaryotic sequences from different bacterial isolates or metagenomes. Here, we report a new bioinformatics tool, a pipeline called Flankophile, which can analyze flanking regions and sequence variants. The main feature of Flankophile is that it visualizes flanking region synteny and sequence variants in publication-ready plots with distance trees, gene annotations, and metadata. Antimicrobial resistance is a significant threat to human health, and surveillance of the spread of antimicrobial resistance is essential. The study of acquired antimicrobial resistance genes (ARGs) is an obvious use case for Flankophile due to the typically diverse genetic context of the genes. Flanking sequences offer a stronger epidemiological signal than the gene sequence alone. To demonstrate Flankophile, we applied it to 2,057 sequenced bacterial isolates and 273 metagenomes from humans and pigs in Denmark and compared the ARGs found in each host reservoir. Gene variant results showed that just ca. 4% of all unique ARG variants found (N = 1,052) were detected in samples from both humans and pigs. Flanking region analysis of ARG variants frequently detected in this study showed multiple examples of genes where the entire 3,000-base pair flanking region was identical in samples from both hosts but also cases where no overlap was observed, and the clustering showed a complete separation of the samples from pigs and the samples from humans.
Original languageEnglish
Article numbere0241323
JournalMicrobiology Spectrum
Volume12
Issue number1
Number of pages15
ISSN2165-0497
DOIs
Publication statusPublished - 2024

Keywords

  • Bioinformatics
  • Antibiotics resistance
  • Veterinary microbiology
  • Software
  • Phylogenetic analysis
  • Epidemiology
  • Sequence analysis
  • Genomics
  • Metagenomics

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