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Genomic analysis of Clostridioides difficile in two regions reveals a diversity of strains and limited transmission

Published online by Cambridge University Press:  02 November 2020

Nicole Pecora
Affiliation:
University of Rochester Medical Center
Stacy Holzbauer
Affiliation:
Minnesota Department of Health
Xiong Wang
Affiliation:
Public Health Laboratory, Minnesota Dept. of Health, Saint Paul, MN
Yu Gu
Affiliation:
Dept. of Biostatistics and Computational Biology, University of Rochester, Rochester, NY
Trupti Hatwar
Affiliation:
New York Emerging Infections Program and University of Rochester Medical Center
Michelle Dziejman
Affiliation:
Dept. of Microbiology and Immunology, University of Rochester, Rochester, NY
Jason Myers
Affiliation:
Genomics Research Center, University of Rochester, Rochester, NY
Paige D’Heilly
Affiliation:
Minnesota EIP, Minnesota Department of Health, St Paul , MN
Alice Guh
Affiliation:
CDC
Xing Qiu
Affiliation:
Dept. of Biostatistics and Computational Biology, University of Rochester, Rochester, NY
Steven Gill
Affiliation:
Dept. of Microbiology and Immunology, University of Rochester, Rochester, NY
Ghinwa Dumyati
Affiliation:
University of Rochester
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Abstract

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Background: The epidemic NAP1/027 Clostridioides difficile strain (MLST1, ST1) that emerged in the mid-2000 is on the decline. The current distribution of C. difficile strain types and their transmission dynamics are poorly defined. We performed whole-genome sequencing (WGS) of C. difficile isolates in 2 regions to identify the predominant multilocus sequence types (MLSTs) in community- and healthcare-associated cases and potential transmission between cases using whole-genome single-nucleotide polymorphism (SNP) analysis. Methods: Isolates were collected through the CDC Emerging Infections Program population-based surveillance for C. difficile infections (CDI) for 3 months between 2016 and 2017 in 5 Minnesota counties and 1 New York county. Isolates were limited to incident cases (CDI in a county resident with no positive C. difficile test in the preceding 8 weeks). Cases were classified as healthcare associated (HA-CDI) or community associated (CA-CDI) based on healthcare exposures as previously described. WGS was performed on an Illumina Miseq. The CFSAN (FDA) pipeline was used to compute whole-genome SNPs, SPAdes was used for assembly, and MLST was assigned according to www.pubmlst.org. Results: Of 431 isolates, 269 originated from New York and 162 from Minnesota; 203 cases were classified as CA-CDI and 221 as HA-CDI. The proportion of CA-CDI cases was higher in Minnesota than in New York: 62% vs 38%. The predominant MLSTs across both sites were ST42 (9%), ST8 (8%), and ST2 (8%). MLSTs more frequently encountered in HA-CDI than CA-CDI included ST1 (note that this ST includes PCR Ribotype 027; 76% HA-CDI), ST53 (84% HA-CDI), and ST43 (80% HA-CDI). In contrast, ST110 (63% CA-CDI) and ST3 (67% CA-CDI) were more commonly isolated from CA-CDI cases. ST1 accounted for 7.6% of circulating strains and was more common in New York than Minnesota (10% vs 3%) and was concentrated among New York HA-CDI cases. Also, 412 isolates (1 per patient) were included in the final whole-genome SNP analysis. Of these, only 12 pairs were separated by 0–3 SNPs, indicating potential transmission, and most involved HA-CDI cases. ST1, ST17, and ST46 accounted for 8 of 12 pairs, with ST17 and ST46 potentially forming small clusters. Conclusions: This analysis provides a snapshot of the current genomic epidemiology of C. difficile across 2 geographically and epidemiologically distinct regions of the United States and supports other studies suggesting that the role of direct transmission in the spread of CDI may be limited.

Funding: None

Disclosures: None

Type
Poster Presentations
Copyright
© 2020 by The Society for Healthcare Epidemiology of America. All rights reserved.