sonneityping

sonneityping provides a standardized genotyping framework for analysis of Shigella sonnei whole-genome sequencing (WGS) data to assign genotypes and detect antimicrobial resistance determinants.


Key Features:

  • Genomic Framework: Implements a robust, S. sonnei-specific genomic framework to assign genotypes and identify resistance determinants from WGS data.
  • Integration with Mykrobe Software: Integrated into the Mykrobe software package and rigorously tested on thousands of genomes for genomic analysis.
  • Resistance Determinant Identification: Detects antimicrobial resistance determinants including those associated with ciprofloxacin and azithromycin.
  • Outbreak Investigation and Surveillance: Applied to over 4,000 S. sonnei isolates from public health laboratories in three countries to identify common genotypes linked with elevated resistance rates.
  • Monitoring Resistant Clones: Enables monitoring of resistant clones and their intercontinental spread.

Scientific Applications:

  • Epidemiological Studies: Enables tracking of spread and evolution of S. sonnei clones through detailed genotyping.
  • Public Health Surveillance: Supports monitoring of antimicrobial resistance trends in S. sonnei to inform public health strategies.
  • Outbreak Response: Supports rapid identification of resistant strains during outbreaks to inform interventions.

Methodology:

Application of a standardized genotyping scheme to WGS data; identification of resistance determinants (including ciprofloxacin and azithromycin) from genomic data; implementation within the Mykrobe software; testing on thousands of genomes and application to over 4,000 S. sonnei isolates from public health laboratories in three countries.

Topics

Details

License:
MIT
Maturity:
Mature
Cost:
Free of charge
Tool Type:
command-line tool
Programming Languages:
Python
Added:
3/12/2024
Last Updated:
11/6/2024

Operations

Data Inputs & Outputs

Antimicrobial resistance prediction

Outputs

    Publications

    Hawkey J, Paranagama K, Baker KS, Bengtsson RJ, Weill F, Thomson NR, Baker S, Cerdeira L, Iqbal Z, Hunt M, Ingle DJ, Dallman TJ, Jenkins C, Williamson DA, Holt KE. Global population structure and genotyping framework for genomic surveillance of the major dysentery pathogen, Shigella sonnei. Nature Communications. 2021;12(1). doi:10.1038/s41467-021-22700-4. PMID:33976138. PMCID:PMC8113504.

    Funding: - Bill and Melinda Gates Foundation: OPP1175797 - Department of Health | National Health and Medical Research Council: APP1174555