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Volume 7, Issue 6

Enhancing genomics-based outbreak detection of endemic serovar Typhimurium using dynamic thresholds Open Access

Abstract

serovar Typhimurium is the leading cause of salmonellosis in Australia, and the ability to identify outbreaks and their sources is vital to public health. Here, we examined the utility of whole-genome sequencing (WGS), including complete genome sequencing with Oxford Nanopore technologies, in examining 105 isolates from an endemic multi-locus variable number tandem repeat analysis (MLVA) type over 5 years. The MLVA type was very homogeneous, with 90 % of the isolates falling into groups with a five SNP cut-off. We developed a new two-step approach for outbreak detection using WGS. The first clustering at a zero single nucleotide polymorphism (SNP) cut-off was used to detect outbreak clusters that each occurred within a 4 week window and then a second clustering with dynamically increased SNP cut-offs were used to generate outbreak investigation clusters capable of identifying all outbreak cases. This approach offered optimal specificity and sensitivity for outbreak detection and investigation, in particular of those caused by endemic MLVA types or clones with low genetic diversity. We further showed that inclusion of complete genome sequences detected no additional mutational events for genomic outbreak surveillance. Phylogenetic analysis found that the MLVA type was likely to have been derived recently from a single source that persisted over 5 years, and seeded numerous sporadic infections and outbreaks. Our findings suggest that SNP cut-offs for outbreak cluster detection and public-health surveillance should be based on the local diversity of the relevant strains over time. These findings have general applicability to outbreak detection of bacterial pathogens.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): bacterial population genomics , genetic clustering , genomic epidemiology , outbreak detection and Salmonella Typhimurium
Funding
This study was supported by the:
  • National Health and Medical Research Council (Award 1129713)
    • Principle Award Recipient: Ruiting Lan
© 2019 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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2019-11-04
2024-04-19
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Enhancing genomics-based outbreak detection of endemic Salmonella enterica serovar Typhimurium using dynamic thresholds
M Gen 7, 000310 (2021); https://doi.org/10.1099/mgen.0.000310
/content/journal/mgen/10.1099/mgen.0.000310
/content/journal/mgen/10.1099/mgen.0.000310
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