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title: 'LisSero: In silico serotyping of Listeria monocytogenes' tags:

  • Python
  • bioinformatics
  • public health microbiology
  • microbial genomics
  • Listeria authors:
  • name: Jason Kwong^[Corresponding author] orcid: XXX affiliation: "1, 2"
  • name: Josh Zhang affiliation: 2
  • name: Kristy A. Horan affiliation: 2
  • name: William R. Pitchers affiliation: 2
  • name: Karolina Mercoulia affiliation: 2
  • name: Susan Ballard affiliation: 2
  • name: Anders Gonçalves da Silva affiliation: 2
  • name: Timothy P. Stinear affiliation: 3
  • name: Benjamin P. Howden affiliation: "2, 3"
  • name: Torsten Seemann^[Corresponding author] affiliation: "2, 3" affiliations:
  • name: Austin Health index: 1
  • name: Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The Doherty Institute for Infection and Immunity, The University of Melbourne index: 2
  • name: Department of Microbiology and Immunology, The Doherty Institute for Infection and Immunity, The University of Melbourne index: 3 date: 13 July 2020 bibliography: paper.bib

Summary

One of the corner stones of transition to genomics in public health are Bioinformatic tools to assist in replicating wet lab processes using whole-genome sequence data. A number of tools have been written to carry out various bacterial sub-typing techniques, such as multi-locus sequence typing, and various types of phenotypic serotype inferences (e.g., Salmonella serotyping, and Neisseria gonorrhoeae multi-antigen sequence typing). Here we present LisSero, a tool for performing Listeria monocytogenes in silico serotype inferences based on draft assemblies obtained from whole-genome sequence data. LisSero will add a valuable tool to the growing number of Bioinformatics tools designed to provide backwards compatibility with data generated prior to the dissemination of whole-genome sequencing technology.

Statement of need

LisSero is a Python package that automates the process of BLASTing a set of contigs from a draft assembly of a Listeria monocytogenes genome against a curated database of five genes. The serotype is assigned in accordance with the combination of identified genes [@doumithDifferentiationMajorListeria2004]. The five genes (NAME GENES) have been described as the minimum necessary to classify L. monocytogenes isolates into distinct serotypes of public health importance [@doumithDifferentiationMajorListeria2004].

LisSero was designed to provide an in silico replacement for the muliplex PCR based L monocytogenes serotyping. We provide validation data, and demonstrate the capability of the tool to recover the expected serotype from draft assemblies of L. monocytogenes. The tool is important in providing backwards compatibility, allowing researchers and public health labs wishing to move to WGS the ability to compare their strains with previously available data. The tool is already use in routinely in our lab, and it has already been used in a number of publications [@kwongProspectiveWholeGenomeSequencing2016, @toledoGenomicDiversityListeria2018, @bainesCompleteMicrobialGenomes2019a, @knijnAdvancedResearchInfrastructure2020].

Acknowledgements

We would like to acknowledge all the public health laboratories that provided validation data. We would like to acknowledge funding from the Victorian Department of Health and Human Services for funding towards our Transition to Genomics.

References