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Early identification of a ward-based outbreak of Clostridioides difficile using prospective multilocus sequence
Max Bloomfield1,2, Samantha Hutton1, Megan Burton1
1Awanui Labs Wellington, Department of Microbiology and Molecular Pathology, Wellington, New Zealand.
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.
Insights
Genomic surveillance using Oxford Nanopore Technologies identified a Clostridioides difficile (CDI) outbreak. This system detected sequence type 2 CDI cases on a hemato-oncology ward, enabling targeted interventions.
Area of Science:
- Infectious disease epidemiology
- Genomic surveillance
- Microbial genomics
Background:
- Clostridioides difficile infection (CDI) poses a significant healthcare challenge.
- Traditional surveillance methods may not detect localized outbreaks effectively.
- Emerging genomic technologies offer new possibilities for real-time pathogen tracking.
Purpose of the Study:
- To describe a Clostridioides difficile infection (CDI) outbreak.
- To evaluate a prospective genomic surveillance system using Oxford Nanopore Technologies (ONT) and multilocus sequence typing (MLST).
- To identify the specific sequence type (ST) involved in the outbreak.
Main Methods:
- Prospective sequencing of all C. difficile isolates from inpatients using ONT MinION.
- Real-time generation of MLST profiles.
- Construction of ST-specific incidence charts using bed-movement data.
- Retrospective phylogenetic analysis of outbreak-associated cases.
Main Results:
- Between February and October 2022, 76 of 118 (64.4%) CDI cases were sequenced.
- A predominance of ST2 CDI cases was identified among patients with hemato-oncology ward exposure.
- Ten ST2 CDI cases were linked to the hemato-oncology ward.
- No overall increase in CDI incidence was detected hospital-wide.
- Phylogenetic analysis confirmed clustering of outbreak cases, excluding two.
- Interventions, including a change in cleaning product, led to the cessation of new ST2 cases.
Conclusions:
- Prospective genomic surveillance with ONT sequencing successfully identified an otherwise undetected ST2 CDI outbreak.
- The MLST-based system enabled rapid detection and characterization of the outbreak.
- Genomic surveillance is a valuable tool for controlling healthcare-associated infections.
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