Objectives: To utilize long-read nanopore sequencing (R10.4.1 flowcells) for WGS of a cluster of MDR Shigella sonnei, specifically characterizing genetic predictors of antimicrobial resistance (AMR).
Methods: WGS was performed on S. sonnei isolates identified from stool and blood between September 2021 and October 2022. Bacterial DNA from clinical isolates was extracted on the MagNA Pure 24 and sequenced on the GridION utilizing R10.4.1 flowcells. Phenotypic antimicrobial susceptibility testing was interpreted based on CLSI breakpoints. Sequencing data were processed with BugSeq, and AMR was assessed with BugSplit and ResFinder.
Results: Fifty-six isolates were sequenced, including 53 related to the cluster of cases. All cluster isolates were identified as S. sonnei by sequencing, with global genotype 3.6.1.1.2 (CipR.MSM5), MLST 152 and PopPUNK cluster 3. Core genome MLST (cgMLST, examining 2513 loci) and reference-based MLST (refMLST, examining 4091 loci) both confirmed the clonality of the isolates. Cluster isolates were resistant to ampicillin (blaTEM-1), trimethoprim/sulfamethoxazole (dfA1, dfrA17; sul1, sul2), azithromycin (ermB, mphA) and ciprofloxacin (gyrA S83L, gyrA D87G, parC S80I). No genomic predictors of resistance to carbapenems were identified.
Conclusions: WGS with R10.4.1 enabled rapid sequencing and identification of an MDR S. sonnei community cluster. Genetic predictors of AMR were concordant with phenotypic antimicrobial susceptibility testing.
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