Journal
MICROBIAL GENOMICS
Volume 7, Issue 7, Pages -Publisher
MICROBIOLOGY SOC
DOI: 10.1099/mgen.0.000605
Keywords
genomic epidemiology; global database; MGT; population structure; Salmonella entericaserovar Enteritidis; virulence
Categories
Funding
- National Health and Medical Research Council of Australia [1129713]
- UNSW scholarship (University International Postgraduate Award)
- National Health and Medical Research Council of Australia [1129713] Funding Source: NHMRC
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Salmonella enterica serovar Enteritidis is a major cause of foodborne infections and outbreaks, and multilevel genome typing has been developed as a promising tool for surveillance and outbreak detection. The study identified globally prevalent and regionally restricted sequence types, as well as multidrug resistance associated sequence types at various levels. The majority of global S. Enteritidis population falls within two predominant lineages with significantly different propensity of causing large scale outbreaks, highlighting the importance of MGT for surveillance and outbreak detection.
Salmonella enterica serovar Enteritidis is a major cause of foodborne Salmonella infections and outbreaks in humans. Effective surveillance and timely outbreak detection are essential for public health control. Multilevel genome typing (MGT) with multiple levels of resolution has been previously demonstrated as a promising tool for this purpose. In this study, we developed MGT with nine levels for S. Enteritidis and characterised the genomic epidemiology of S. Enteritidis in detail. We examined 26 670 publicly available S. Enteritidis genome sequences from isolates spanning 101 years from 86 countries to reveal their spatial and temporal distributions. Using the lower resolution MGT levels, globally prevalent and regionally restricted sequence types (STs) were identified; avian associated MGT4- STs were found that were common in human cases in the USA; temporal trends were observed in the UK with MGT5- STs from 2014 to 2018 revealing both long lived endemic STs and the rapid expansion of new STs. Using MGT3 to MGT6, we identified multidrug resistance (MDR) associated STs at various MGT levels, which improves precision of detection and global tracking of MDR clones. We also found that the majority of the global S. Enteritidis population fell within two predominant lineages, which had significantly different propensity of causing large scale outbreaks. An online open MGT database has been established for unified international surveillance of S. Enteritidis. We demonstrated that MGT provides a flexible and high- resolution genome typing tool for S. Enteritidis surveillance and outbreak detection.
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