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Multilevel genome typing: genomics-guided scalable resolution typing of microbial pathogens
- Michael Payne1 , Sandeep Kaur1 , Qinning Wang2 , Daneeta Hennessy2 , Lijuan Luo1 , Sophie Octavia1 , Mark M. Tanaka1 , Vitali Sintchenko2,3 , Ruiting Lan1
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View Affiliations Hide AffiliationsAffiliations: 1 School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia 2 Centre for Infectious Diseases and Microbiology–Public Health, Institute of Clinical Pathology and Medical Research – NSW Health Pathology, Westmead Hospital, Westmead, Australia 3 Marie Bashir Institute for Infectious Diseases and Biosecurity, Sydney Medical School, University of Sydney, Westmead, AustraliaRuiting Lanr.lan unsw.edu.au
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Citation style for this article: Payne Michael, Kaur Sandeep, Wang Qinning, Hennessy Daneeta, Luo Lijuan, Octavia Sophie, Tanaka Mark M., Sintchenko Vitali, Lan Ruiting. Multilevel genome typing: genomics-guided scalable resolution typing of microbial pathogens. Euro Surveill. 2020;25(20):pii=1900519. https://doi.org/10.2807/1560-7917.ES.2020.25.20.1900519 Received: 13 Aug 2019; Accepted: 12 Nov 2019
Abstract
Both long- and short-term epidemiology are fundamental to disease control and require accurate bacterial typing. Genomic data resulting from implementation of whole genome sequencing in many public health laboratories can potentially provide highly sensitive and accurate descriptions of strain relatedness. Previous typing efforts using these data have mainly focussed on outbreak detection.
We aimed to develop multilevel genome typing (MGT), using consecutive multilocus sequence typing (MLST) schemes of increasing sizes, stepping up from seven-gene MLST to core genome MLST, to allow examination of genetic relatedness at multiple resolution levels.
The system was applied to Salmonellaenterica serovar Typhimurium. The MLST scheme used at each step (MGT level), defined a given MGT-level specific sequence type (ST). The list of STs generated from all of these increasing MGT levels, was named a genome type (GT). Using MGT, we typed 9,096 previously characterised isolates with publicly available data.
Our approach could identify previously described S. Typhimurium populations, such as the DT104 multidrug resistance lineage (GT 19-2-11) and two invasive lineages of African isolates (GT 313-2-3 and 313-2-752). Further, we showed that MGT-derived clusters can accurately distinguish five outbreaks from each other and five background isolates.
MGT provides a universal and stable nomenclature at multiple resolutions for S. Typhimurium strains and could be implemented as an internationally standardised strain identification system. While established so far only for S. Typhimurium, the results here suggest that MGT could form the basis for typing systems in other similar microorganisms.
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