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Catwalk: identifying closely related sequences in large microbial sequence databases.

Denis Volk1, Fan Yang-Turner1,2, Xavier Didelot3,4

  • 1Nuffield Department of Medicine, University of Oxford, Oxford, UK.

Microbial Genomics
|June 30, 2022
PubMed
Summary
This summary is machine-generated.

Catwalk is a new, fast software tool designed to rapidly identify highly similar microbial genomes, such as SARS-CoV-2, within massive datasets. This enables efficient tracking of transmission chains and importations for public health surveillance.

Keywords:
bacterial genomicsmicrobial relatednessoutbreak detection

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Accurate identification of microbial transmission chains and importations is crucial for public health, especially with large-scale sequencing of pathogens like SARS-CoV-2.
  • Existing reference-based compression tools struggle with the immense volume of genomic data generated by modern sequencing programs.
  • Efficiently comparing millions of microbial genomes is a significant computational challenge.

Purpose of the Study:

  • To develop a high-performance software tool, Catwalk, for rapid detection of highly similar microbial sequences within large genomic collections.
  • To address the performance and memory limitations of current sequence analysis methods for outbreak detection.
  • To facilitate the identification of transmission chains and imported cases of infectious diseases.

Main Methods:

  • Developed Catwalk, a compiled software solution using the Nim programming language for enhanced performance.
  • Implemented a novel approach to bypass bottlenecks in reference mapping, genome comparison, and in-memory storage.
  • Provided command-line, REST API, and web server interfaces for accessibility.
  • Tested Catwalk with SARS-CoV-2 and Mycobacterium tuberculosis genomes from public health sequencing programs.

Main Results:

  • Catwalk achieves exceptionally fast pairwise sequence comparisons (0.39–0.66 μs) with clinically relevant similarity cut-offs.
  • The tool can process 1 to 2 million sequences per second.
  • Catwalk is approximately 1700 times faster and uses only 8% of the RAM compared to a current Python-based reference tool.
  • Demonstrated rapid identification of close relatives within millions of SARS-CoV-2 and M. tuberculosis genomes.

Conclusions:

  • Catwalk significantly enhances the speed and efficiency of microbial genome comparison for large-scale public health surveillance.
  • The tool overcomes limitations of existing methods, enabling faster detection of disease transmission and importations.
  • Catwalk is a valuable asset for genomic epidemiology, particularly for rapidly evolving pathogens like SARS-CoV-2 and persistent threats like M. tuberculosis.