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GIPSy: Genomic island prediction software.

Siomar C Soares1, Hakan Geyik2, Rommel T J Ramos3

  • 1Department of Immunology, Microbiology and Parasitology, Federal University of Triângulo Mineiro, Uberaba, Minas Gerais, Brazil; Department of General Biology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.

Journal of Biotechnology
|September 17, 2015
PubMed
Summary

GIPSy is a new, user-friendly software that predicts genomic islands (GEIs) in bacteria, including pathogenicity islands (PAIs), metabolic islands (MIs), resistance islands (RIs), and symbiotic islands (SIs). This tool aids in understanding bacterial genome plasticity and adaptation.

Keywords:
Genome plasticityGenomic islandsHorizontal gene transferMetabolic islandsPathogenicity islandsResistance islandsSymbiotic islands

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Area of Science:

  • Microbiology
  • Genomics
  • Bioinformatics

Background:

  • Bacteria exhibit significant genomic plasticity, enabling adaptation to diverse environments and hosts.
  • Horizontal gene transfer facilitates this plasticity through the integration of genomic islands (GEIs).
  • GEIs encompass various functional types, including pathogenicity islands (PAIs), metabolic islands (MIs), resistance islands (RIs), and symbiotic islands (SIs).

Purpose of the Study:

  • To introduce GIPSy, a standalone and user-friendly software for predicting diverse genomic islands (GEIs).
  • To address limitations of existing tools that primarily focus on PAI prediction and often have complex interfaces.
  • To provide a comprehensive tool for analyzing bacterial genome plasticity across different lifestyles.

Main Methods:

  • GIPSy was developed as a standalone, user-friendly software based on prior PIPS software for pathogenicity island prediction.
  • The software was validated through four application cases, crosslinking literature data with predicted GEIs.
  • Specific GEIs were analyzed in bacterial species including Escherichia coli, Burkholderia pseudomallei, Acinetobacter baumannii, and Mesorhizobium loti.

Main Results:

  • GIPSy successfully predicted previously described GEIs across different bacterial species.
  • The software identified 13 PAIs (>30kb) in Escherichia coli CFT073.
  • It also predicted 1 MI in Burkholderia pseudomallei K96243, 1 RI (AbaR1) in Acinetobacter baumannii AYE, and 1 mosaic SI in Mesorhizobium loti MAFF303099.

Conclusions:

  • GIPSy is the first software capable of predicting multiple lifestyle-specific genomic islands (PAIs, MIs, RIs, SIs).
  • This tool enhances the understanding of bacterial genome plasticity and the acquisition of new traits.
  • GIPSy offers a user-friendly platform for comprehensive GEI analysis in bacterial genomics.