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Dyet, K.

Publications and source records attributed to Dyet, K..

2 recordsLinked to original sources

Development and evaluation of a core genome multi-locus sequence typing scheme for the Enterobacter cloacae complex

The Enterobacter cloacae species complex (ECC) comprises a group of closely related, opportunistic Gram negative bacteria of major public health concern due to their frequent involvement in healthcare-associated infections and their capacity to acquire and disseminate multidrug resistance, including carbapenemases. Because members of this complex are often difficult to distinguish phenotypically and their taxonomic status is subject to debate, there is a need for a standardized, species-complex wide typing scheme based on whole genome sequencing (WGS) that can be applied to any species within the complex. In this study we have developed and evaluated a core genome multi-locus sequence typing (cgMLST) scheme suitable for species within the ECC. Using 3442 publicly available genomes from 27 ECC species or subspecies we developed a scheme with 1812 loci, comprising loci present in 99% of all genomes. Among the 3442 isolates in our study, 99.9% had 95% or more of the cgMLST targets, indicating that the schema is well-defined and representative for the breadth of ECC species in our study. On two independent evaluation datasets, the scheme reliably resolved epidemiologically linked isolates with 0-3 allelic differences and returned the same outbreak clusters defined previously by higher resolution core genome SNP (cgSNP) analysis. Hierarchical clustering analysis at different levels of resolution showed that the cgMLST profiles could potentially be used to differentiate between species and sub-lineages in the complex. The cgMLST schema will improve the ability of public health laboratories to perform WGS-based surveillance of ECC species.

bioinformatics↗

Resolving a neonatal intensive care unit outbreak of methicillin-resistant Staphylococcus aureus to the SNV level using Oxford Nanopore simplex reads and HERRO error correction

ObjectivesOur laboratory began prospective genomic surveillance for healthcare-associated organisms in 2022 using Oxford Nanopore Technologies (ONT) sequencing as a standalone platform. This has permitted the early detection of outbreaks but has been insufficient for single-nucleotide variant (SNV)-level analysis due to lower read accuracy than Illumina sequencing. This study aimed to determine whether Haplotype-aware ERRor cOrrection (HERRO) of ONT data could permit high-resolution comparison of outbreak isolates. MethodsWe used ONT simplex reads from isolates involved in a recent outbreak of methicillin-resistant Staphylococcus aureus (MRSA) in our neonatal unit. The raw sequence data were re-basecalled and adapter-trimmed using Dorado v0.7.0. The simplex reads then underwent HERRO correction. The resulting genome assemblies and phylogenies were compared with previous analyses (using Dorado v0.3.4, no HERRO correction and data generated by Illumina sequencing). ResultsFive of nine outbreak isolates were included in the analysis. The remaining four isolates had insufficient read lengths (N50 values <10,000 bp) and did not provide complete chromosome coverage after HERRO correction. The average chromosome sequencing depth for nanopore data was 147x (range: 44-220x) with an average read N50 of 12,215 bp (interquartile range (IQR): 11,439-12,711 bp). The median pairwise SNV distance between outbreak isolates from the original investigation was 51 SNVs (range: 40-68), which decreased to 3 SNVs (range: 1-15) with HERRO correction. Illumina sequencing generated a median SNV distance of 2 (range: 0-13). The resulting standalone ONT HERRO-corrected phylogeny was almost indistinguishable from the standalone Illumina-generated phylogeny. ConclusionsThe addition of HERRO correction meant isolates from this MRSA outbreak could be resolved to a level on par with Illumina sequencing. ONT data following HERRO correction represents a viable standalone option for high-resolution genomic analysis of hospital outbreaks, provided sufficient read lengths can be generated.

genomics↗