Sequencing

11th Annual Sequencing, Finishing, and Analysis in the Future Meeting
EXAMINATION OF WHOLE GENOME MULTI-
LOCUS SEQUENCE TYPING (WGMLST) FOR
CAMPYLOBACTER SURVEILLANCE
Wednesday, 1st June 20:00 La Fonda NM Room (1st floor) Poster (PS‐1b.13)
Lavin Joseph, Heather Carleton, Darlene Wagner, Michael Judd, Eija Trees, Vikrant Dutta, Janet
Pruckler, Grant Williams, Kelley Hise, Collette Fitzgerald
Centers for Disease Control and Prevention
Background: Campylobacter species are a leading cause of bacterial foodborne illness in the United States. Pulsedfield
gel electrophoresis (PFGE) is the current method used within PulseNet USA for surveillance and outbreak
investigations. However, PulseNet USA is implementing whole genome sequencing (WGS) for surveillance of all the
pathogens it tracks including Campylobacter. In this study, we examined the utility of whole genome multi‐locus
sequence typing (wgMLST) to cluster or differentiate outbreak‐associated and sporadic Campylobacter isolates.
Methods: A BioNumerics 7.5 wgMLST database was developed in collaboration with domestic and international
partners for Campylobacter surveillance. Fourteen public health laboratories (PHL) performed real‐time WGS on
262 Campylobacter isolates (219 C. jejuni, 35 C. coli, 6 C. lari, 1 C. upsaliensis, and 1 C. fetus) isolates. In addition, 14
C. jejuni isolates from two temporarily associated outbreaks linked to a family reunion (two isolates) and church
fundraiser (12 isolates) originating in the same state were sequenced by the local PHL. Sequencing was performed
on the Illumina MiSeq using Nextera XT DNA libraries and 2x150 bp or 2x250 bp sequencing chemistry. Sequences
with >20X coverage and average quality scores for R1 and R2 >30 were assembled using SPAdes and analyzed
using wgMLST (2531 loci). For comparison, the C. jejuni sequences associated with the two outbreaks were also
characterized with high quality single nucleotide polymorphism (hqSNP) analysis using the LYVE‐SET pipeline
(github.com/lskatz/lyve‐SET) as well as K‐mer analysis using the NCBI Pathogen Detection Pipeline
(http://www.ncbi.nlm.nih.gov/pathogens/). PFGE patterns for all isolates were generated using the PulseNet
Campylobacter protocol, analyzed in BioNumerics 6.6.10, and named in accordance with PulseNet naming
guidelines.
Results: On average, 1547 (915‐1752), 573 (250‐737), 344 (305‐473), 371, and 453 wgMLST loci were identified
within C. jejuni, C. coli, C. lari, C. upsaliensis, and C. fetus sequences, respectively. C. jejuni and C. coli isolates
presumed to be epidemiologically unrelated (n=20) formed 12 clusters containing indistinguishable SmaI/KpnI
patterns; nine of these clusters contained isolates that were also indistinguishable or highly similar by wgMLST (0‐
5 allele differences). The isolates in the remaining clusters were further differentiated by wgMLST (21‐98 allele
differences). C. jejuni isolates from the two outbreaks clustered together by wgMLST (0‐3 allele differences), hqSNP
(0‐3 SNP differences), and K‐mer analysis even though these outbreaks clustered separately by PFGE.
Conclusion: The majority (82%) of the sporadic Campylobacter isolates indistinguishable by PFGE were not
separated by wgMLST. The isolates within each cluster were from the same state and may be from patients exposed
to a common source, whereas isolates differentiated by wgMLST could be epidemiologically unrelated.
Interestingly, C. jejuni isolates from the two Campylobacter outbreaks clustered together by wgMLST, hqSNP, and
K‐mer analysis, indicating that they may have origi‐ nated from the same source that was not discovered during the
epidemiological investigations. It is also possible the sequence type associated with these isolates is relatively
common. Our study shows that wgMLST appears to be a promising and user‐friendly high resolution tool for
Campylobacter surveillance that can be implemented in local PHLs.
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