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Evaluating Sequence Alignment Tools for Antimicrobial Resistance Gene Detection in Assembly Graphs.

Yusreen Shah1, Somayeh Kafaie1

  • 1Department of Mathematics and Computing Science, Saint Mary's University, Halifax, NS B3H 3C3, Canada.

Microorganisms
|November 27, 2024
PubMed
Summary
This summary is machine-generated.

Bandage accurately identifies antimicrobial resistance (AMR) genes in bacterial genomes more effectively than other tools. This research aids in understanding AMR spread and developing mitigation strategies.

Keywords:
BandageGraphAlignerSPAlignerantimicrobial resistance (AMR)assembly graphssequence alignment

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Area of Science:

  • Genomics
  • Microbiology
  • Bioinformatics

Background:

  • Antimicrobial resistance (AMR) is a significant global health challenge.
  • Horizontal gene transfer (HGT) accelerates the spread of AMR genes.
  • Understanding AMR gene context is vital for controlling resistance.

Purpose of the Study:

  • To evaluate sequence alignment tools for AMR gene identification in microbial assembly graphs.
  • To compare the performance of Bandage, SPAligner, and GraphAligner.
  • To assess the efficiency and accuracy of identifying AMR genes and HGT events.

Main Methods:

  • Comparative analysis of Bandage, SPAligner, and GraphAligner.
  • Qualitative and quantitative performance evaluation.
  • Assessment of precision, computational efficiency, and accuracy using edit distance.

Main Results:

  • Bandage demonstrated superior precision and efficiency in identifying AMR gene sequences.
  • GraphAligner and SPAligner showed comparable, but lower, performance.
  • Analysis included path similarity and output accuracy metrics.

Conclusions:

  • Bandage is a highly effective tool for accurate AMR gene identification in bacterial populations.
  • This tool aids in studying AMR mechanisms and HGT events.
  • Findings support the development of strategies to mitigate AMR spread.