Deciphering the role of insertion sequences in the evolution of bacterial epidemic pathogens with panISa software.

Next-generation sequencing (NGS) is now extensively utilized in microbiology to discover genome evolution and the construction of pathogen outbreaks. Bioinformatics pipelines readily detect single-nucleotide polymorphisms or quick indels. However, bacterial genomes additionally evolve by the motion of small transposable components referred to as insertion sequences (ISs), that are troublesome to detect attributable to their quick size and a number of repetitions all through the genome. We designed panISa software program for the ab initio detection of IS insertions within the genomes of prokaryotes. 

PanISa has been launched as open supply software program (GPL3) obtainable from In this examine, we assessed the utility of this software program for evolutionary research, by reanalysing 5 revealed datasets for outbreaks of human main pathogens during which ISs had not been particularly investigated.

We reanalysed the uncooked information from every examine, by aligning the reads towards reference genomes and working panISa on the alignments. Each hit was routinely curated and IS-related occasions had been validated on the idea of nucleotide sequence similarity, by comparability with the ISFinder database.

In Acinetobacter baumannii, the panISa pipeline recognized ISAba1 or ISAba125 upstream from the ampC gene, which encodes a cephalosporinase in all third-generation cephalosporin-resistant isolates. In the genomes of Vibrio cholerae isolates, we discovered that early Haitian isolates had the identical ISs as Nepalese isolates, confirming the inferred historical past of the contamination of this island. In Enterococcus faecalispanISa recognized areas of excessive plasticity, together with a pathogenicity island enriched in IS-related occasions.

The total distribution of ISs deduced with panISa was in line with SNP-based phylogenic timber, for all species thought of. The position of ISs in pathogen evolution has most likely been underestimated attributable to difficulties detecting these transposable components. We present right here that panISa is a helpful addition to the bioinformatics toolbox for analyses of the evolution of bacterial genomes. PanISa will facilitate explorations of the useful influence of ISs and enhance our understanding of prokaryote evolution.

Scroll to Top