Early identification of a ward-based outbreak of Clostridioides difficile using prospective multilocus sequence type-based Oxford Nanopore genomic surveillance.

OBJECTIVE: To describe an outbreak of sequence type (ST)2 Clostridioides difficile infection (CDI) detected by a recently implemented multilocus sequence type (MLST)-based prospective genomic surveillance system using Oxford Nanopore Technologies (ONT) sequencing. SETTING: Hemato-oncology ward of a public tertiary referral centre. METHODS: From February 2022, we began prospectively sequencing all C. difficile isolated from inpatients at our institution on the ONT MinION device, with the output being an MLST. Bed-movement data are used to construct real-time ST-specific incidence charts based on ward exposures over the preceding three months. RESULTS: Between February and October 2022, 76 of 118 (64.4%) CDI cases were successfully sequenced. There was wide ST variation across cases and the hospital, with only four different STs being seen in >4 patients. A clear predominance of ST2 CDI cases emerged among patients with exposure to our hemato-oncology ward between May and October 2022, which totalled ten patients. There was no detectable rise in overall CDI incidence for the ward or hospital due to the outbreak. Following a change in cleaning product to an accelerated hydrogen peroxide wipe and several other interventions, no further outbreak-associated ST2 cases were detected. A retrospective phylogenetic analysis using original sequence data showed clustering of the suspected outbreak cases, with the exception of two cases that were retrospectively excluded from the outbreak. CONCLUSIONS: Prospective genomic surveillance of C. difficile using ONT sequencing permitted the identification of an outbreak of ST2 CDI that would have otherwise gone undetected.

Rapid identification and subsequent contextualization of an outbreak of methicillin-resistant Staphylococcus aureus in a neonatal intensive care unit using nanopore sequencing.

Outbreaks of methicillin-resistant Staphylococcus aureus (MRSA) are well described in the neonatal intensive care unit (NICU) setting. Genomics has revolutionized the investigation of such outbreaks; however, to date, this has largely been completed retrospectively and has typically relied on short-read platforms. In 2022, our laboratory established a prospective genomic surveillance system using Oxford Nanopore Technologies sequencing for rapid outbreak detection. Herein, using this system, we describe the detection and control of an outbreak of sequence-type (ST)97 MRSA in our NICU. The outbreak was identified 13 days after the first MRSA-positive culture and at a point where there were only two known cases. Ward screening rapidly defined the extent of the outbreak, with six other infants found to be colonized. There was minimal transmission once the outbreak had been detected and appropriate infection control measures had been instituted; only two further ST97 cases were detected, along with three unrelated non-ST97 MRSA cases. To contextualize the outbreak, core-genome single-nucleotide variants were identified for phylogenetic analysis after de novo assembly of nanopore data. Comparisons with global (n=45) and national surveillance (n=35) ST97 genomes revealed the stepwise evolution of methicillin resistance within this ST97 subset. A distinct cluster comprising nine of the ten ST97-IVa genomes from the NICU was identified, with strains from 2020 to 2022 national surveillance serving as outgroups to this cluster. One ST97-IVa genome presumed to be part of the outbreak formed an outgroup and was retrospectively excluded. A second phylogeny was created using Illumina sequencing, which considerably reduced the branch lengths of the NICU isolates on the phylogenetic tree. However, the overall tree topology and conclusions were unchanged, with the exception of the NICU outbreak cluster, where differences in branch lengths were observed. This analysis demonstrated the ability of a nanopore-only prospective genomic surveillance system to rapidly identify and contextualize an outbreak of MRSA in a NICU.

The design, validation and clinical verification of an in-house qualitative PCR to detect Yersinia enterocolitica and Yersinia pseudotuberculosis in faeces.

Yersiniosis is a zoonotic foodborne infection of public health significance. The aim of this study was to design and validate a simple, accurate and cost-effective polymerase chain reaction (PCR) to detect pathogenic Yersinia spp. in faecal samples. An intercalating dye (EvaGreen)-based real-time multiplex PCR assay was designed to detect yadA, ystB and inv by melt curve analysis, allowing undifferentiated detection of all Yersinia enterocolitica biotypes, including biotype 1A, and Yersinia pseudotuberculosis. The assay was validated using cultured bacteria and clinical samples. A total of 107 positive and 51 negative samples were tested. The sensitivity and specificity was 98% and 100%. The limit of detection was 104-105 CFU/g faeces. A total of 605 samples (9 positive) were tested in the clinical verification with an accuracy and negative predictive value of 99% [95% confidence interval (CI) 97.9-99.6%] and 99.8% (95% CI 97.9-99.6%), respectively. This is an accurate, simple and cost-effective assay for the detection of pathogenic Yersinia spp.