COMPARISON OF WHOLE GENOME SEQUENCE-BASED METHODS AND PCR RIBOTYPING FOR SUBTYPING OF Clostridioides difficile

Author:

Baktash A1,Corver J1,Harmanus C12,Smits W. K.1,Fawley W3,Wilcox M. H.4,Kumar N5,Eyre D. W.6,Indra A7,Mellmann A8,Kuijper E. J.12

Affiliation:

1. Department of Medical Microbiology, Section Experimental Bacteriology, Leiden University Medical Center, Leiden, the Netherlands

2. National Reference Laboratory Clostridium difficile, National Institute of Public Health and the Environment, Leiden University Medical Center, Leiden, the Netherlands

3. National Infection Service, Public Health England, and University of Leeds, Leeds, United Kingdom

4. Department of Microbiology, Leeds Teaching Hospitals & University of Leeds, Leeds, United Kingdom

5. Microbiota Interactions Laboratory, Wellcome Sanger Institute, Hinxton, UK

6. Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom

7. Paracelsus Medical University of Salzburg, Salzburg, Austria

8. Institute of Hygiene, University Hospital Münster, and National Reference Center for C. difficile, Münster Branch, Münster, Germany

Abstract

Clostridioides difficile is the most common cause of antibiotic-associated gastrointestinal infections. Capillary-electrophoresis (CE)-PCR ribotyping is currently the gold standard for C. difficile typing but lacks discriminatory power to study transmission and outbreaks in detail. New molecular methods have the capacity to differentiate better and provide standardized and interlaboratory exchangeable data. Using a well-characterized collection of diverse strains (N=630; 100 unique ribotypes (RTs)), we compared the discriminatory power of core genome multilocus sequence typing (cgMLST) (SeqSphere & EnteroBase), whole genome MLST (wgMLST) (EnteroBase) and single nucleotide polymorphism (SNP) analysis. A unique cgMLST profile (>6 allele differences) was observed in 82/100 RTs, indicating that cgMLST could distinguish most, but not all, RTs. Application of cgMLST in two outbreak settings with RT078 and RT181 (known with a low intra-RT allele difference) showed no distinction between outbreak- and non-outbreak strains, in contrast to wgMLST and SNP analysis. We conclude that cgMLST has the potential to be an alternative to CE-PCR ribotyping. The method is reproducible, easy to standardize and offers higher discrimination. However, adjusted cut-off thresholds and epidemiological data are necessary to recognize outbreaks of some specific RTs. We propose to use an allelic threshold 3 alleles to identify outbreaks.

Publisher

American Society for Microbiology

Subject

Microbiology (medical)

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