PLoS ONE (Jan 2024)

Whole genome sequencing and antimicrobial resistance among clinical isolates of Shigella sonnei in Addis Ababa, Ethiopia.

  • Basha Ayele,
  • Adane Mihret,
  • Zeleke Mekonnen,
  • Tesfaye Sisay Tessema,
  • Kalkidan Melaku,
  • Maeruf Fetu Nassir,
  • Abaysew Ayele,
  • Dawit Hailu Alemayehu,
  • Getenet Beyene

DOI
https://doi.org/10.1371/journal.pone.0313310
Journal volume & issue
Vol. 19, no. 11
p. e0313310

Abstract

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BackgroundShigellosis is an acute gastroenteritis infection and one of Ethiopia's most common causes of morbidity and mortality, especially in children under five. Antimicrobial resistance (AMR) has spread quickly among Shigella species due to inappropriate antibiotic use, inadequacies of diagnostic facilities, and unhygienic conditions. This study aimed to characterize Shigella sonnei (S. sonnei) using whole genome sequence (WGS) analysis in Addis Ababa, Ethiopia.MethodsThe raw reads were quality-filtered and trimmed, and a minimum length of 50bp was retained and taxonomically classified using MiniKraken version 1. The whole genome data were aligned with Antibiotic Resistance Gene (ARG) sequences of the Comprehensive Antibiotic Resistance Database (CARD) by Resistance Gene Identifier (RGI). Plasmids were analyzed using the PlasmidFinder tool version 2.1. Additionally, AMR and virulence genes were screened at the Centre for Genomic Epidemiology (CGE) web-based server.ResultsAll isolates in our investigation contained genes encoding blaEC-8 and blaZEG-1. Here, 60.7% of the isolates were phenotypically sensitive to cefoxitin among the blaEC-8 genes detected in the genotyping analysis, whereas all isolates were completely resistant to amoxicillin and erythromycin phenotypically. The study also identified genes that conferred resistance to trimethoprim (dfrA). Plasmid Col156 and Col (BS512) types were found in all isolates, while IncFII and Col (MG828) plasmids were only identified in one isolate.ConclusionThis study found that many resistant genes were present, confirming the high variety in S. sonnei strains and hence a divergence in phylogenetic relationships. Thus, combining WGS methods for AMR prediction and strain identification into active surveillance may be beneficial for monitoring the spread of AMR in S. sonnei and detecting the potential emergence of novel variations.