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Molecular epidemiology of an extended multiple-species OXA-48 CPE outbreak in a hospital ward in Ireland, 2018–2019

Published online by Cambridge University Press:  08 December 2021

Carina Brehony*
Affiliation:
European Public Health Microbiology Training (EUPHEM), European Centre for Disease Prevention and Control, (ECDC), Stockholm, SwedenPublic Health Laboratory, Cherry Orchard, Health Service Executive, Dublin, Ireland
Lisa Domegan
Affiliation:
European Programme for Intervention Epidemiology Training (EPIET), European Centre for Disease Prevention and Control, (ECDC), Stockholm, SwedenHealth Service Executive, Health Protection Surveillance Centre, Dublin, Ireland
Margaret Foley
Affiliation:
Department of Clinical Microbiology, Infection Prevention & Control, Beaumont Hospital, Dublin, Ireland
Margaret Fitzpatrick
Affiliation:
Department of Clinical Microbiology, Infection Prevention & Control, Beaumont Hospital, Dublin, Ireland
Jacqueline P. Cafferkey
Affiliation:
Department of Clinical Microbiology, Infection Prevention & Control, Beaumont Hospital, Dublin, Ireland
Karina O’Connell
Affiliation:
Department of Clinical Microbiology, Infection Prevention & Control, Beaumont Hospital, Dublin, IrelandDepartment of Clinical Microbiology, Royal College of Surgeons in Ireland, Dublin, Ireland
Binu Dinesh
Affiliation:
Department of Clinical Microbiology, Infection Prevention & Control, Beaumont Hospital, Dublin, IrelandDepartment of Clinical Microbiology, Royal College of Surgeons in Ireland, Dublin, Ireland
Eleanor McNamara
Affiliation:
Public Health Laboratory, Cherry Orchard, Health Service Executive, Dublin, Ireland
Fionnuala Duffy
Affiliation:
Department of Clinical Microbiology, Infection Prevention & Control, Beaumont Hospital, Dublin, Ireland
Fidelma Fitzpatrick
Affiliation:
Department of Clinical Microbiology, Infection Prevention & Control, Beaumont Hospital, Dublin, IrelandDepartment of Clinical Microbiology, Royal College of Surgeons in Ireland, Dublin, Ireland
Karen Burns
Affiliation:
Department of Clinical Microbiology, Infection Prevention & Control, Beaumont Hospital, Dublin, IrelandDepartment of Clinical Microbiology, Royal College of Surgeons in Ireland, Dublin, Ireland
*
Author for correspondence: Carina Brehony, Health Service Executive, Health Protection Surveillance Centre, 25-27 Middle Gardiner Street, Dublin, Ireland. E-mail: carina.brehony@hpsc.ie

Abstract

Objectives:

Molecular epidemiological description of an OXA-48 CPE outbreak affecting a tertiary-care hospital ward in Ireland over an extended period (2018–2019).

Methods:

Microbiological testing and whole-genome sequencing (WGS) were performed on all 56 positive OXA-48 outbreak case isolates.

Results:

In total, 7 different species were identified: Enterobacter hormaechei (n = 35, 62.5%), Escherichia coli (n = 12, 21.4%), Klebsiella pneumoniae (n = 5, 8.9%), Klebsiella oxytoca (n = 1, 1.8%), Klebsiella michiganensis (n = 1, 1.8%), Citrobacter freundii (n = 1, 1.8%), and Serratia marcesens (n = 1, 1.8%). E. hormaechei ST78 was the most common genotype (n = 14, 25%). Two major pOXA-48 plasmid types were identified throughout the outbreak, ‘types’ 1 and 2, and 5 major E. hormaechei clonal groupings were identified: ST78, ST108, ST1126, ST135, and ST66. Within each of the ST108, ST1126, ST135 and ST66 groups, the pOXA-48 harbored within each isolate were the same. Within ST78, 9 isolates contained the pOXA48 ‘type 2’ plasmid and 5 contained the ‘type 1’ plasmid. Environmental specimens were taken from different outbreak ward locations: handwash basins, sink and shower drains, and taps. Of 394 environmental specimens, OXA-48 CPE was isolated from 26 (6.6%).

Conclusions:

This prolonged outbreak of OXA-48 CPE was confined to one ward, but it exemplifies the complexity and difficulty in the control of these organisms. With multiple species and genotypes involved, they may be better described as ‘plasmid outbreaks.’ WGS provided insights into this diversity and potential transmission among cases, though its usefulness would be enhanced by analysis as close as possible to real time so that interventions can be implemented as soon as data are available.

Information

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction in any medium, provided the original article is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America
Figure 0

Fig. 1.Minimum-spanning tree of ribosomal MLST locus (n = 53) allele differences among 56 outbreak cases and 3 environmental isolates. Each circle (node) contains isolates that are indistinguishable at all loci. Nodes are colored by species, as determined by WGS. Numbers on lines (edges) connecting nodes indicate the number of allele differences between connected nodes. Nodes are divided in pie-chart form for individual isolates.

Figure 1

Fig. 2.Minimum-spanning tree of pOXA-48 plasmid MLST locus (n = 71) allele differences among 56 outbreak cases and 3 environmental isolates. Each circle (node) contains isolates that are indistinguishable at all loci. Nodes are colored by species, as determined by WGS. Numbers on lines (edges) connecting nodes indicate the number of allele differences between connected nodes. Nodes are divided in pie-chart form for individual isolates.

Figure 2

Fig. 3.Species by week of outbreak that clinical specimen was taken (the week beginning July 29, 2018, to the week beginning August 11, 2019). Plasmid type 1 is indicated by checkered bars. All others plasmid are type 2.

Figure 3

Fig. 4.Minimum-spanning tree of Enterobacter cloacae complex wgMLST locus (n = 15,605) allele differences among 35 outbreak isolates. Each circle (node) contains isolates that are indistinguishable at all loci. Nodes are colored by 7 locus multilocus sequence types. Numbers on lines (edges) connecting nodes indicate the number of allele differences between connected nodes. Nodes are divided in pie-chart form for individual isolates.

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