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Title: Incorporating Whole-Genome Sequencing into Public Health Surveillance: Lessons from Prospective Sequencing of Salmonella Typhimurium in Australia.
Austin Authors: Ford, Laura;Carter, Glen P;Wang, Qinning;Seemann, Torsten;Sintchenko, Vitali;Glass, Kathryn;Williamson, Deborah A;Howard, Peter;Valcanis, Mary;Castillo, Cristina Fabiola Sotomayor;Sait, Michelle;Howden, Benjamin P ;Kirk, Martyn D
Affiliation: National Centre for Epidemiology and Population Health, Research School of Population Health, The Australian National University, Canberra, Australia
OzFoodNet, Health Protection Service, Population Health Protection and Prevention, ACT Health, Canberra, Australia
Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
Centre for Infectious Diseases and Microbiology Laboratory Services, Pathology West-Institute of Clinical Pathology and Medical Research, Sydney, Australia
Centre for Infectious Diseases and Microbiology-Public Health, Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney, Sydney, Australia
Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
Sydney Medical School-Westmead, The University of Sydney, Sydney, Australia
Instituto de Salud Publica, Facultad de Medicina, Universidad Austral de Chile, Valdivia, Chile
Department of Infectious Diseases, Austin Health, Heidelberg, Victoria, Australia
Issue Date: 2018 2018-01-16
Publication information: Foodborne pathogens and disease 2018; 15(3): 161-167
Abstract: In Australia, the incidence of Salmonella Typhimurium has increased dramatically over the past decade. Whole-genome sequencing (WGS) is transforming public health microbiology, but poses challenges for surveillance. To compare WGS-based approaches with conventional typing for Salmonella surveillance, we performed concurrent WGS and multilocus variable-number tandem-repeat analysis (MLVA) of Salmonella Typhimurium isolates from the Australian Capital Territory (ACT) for a period of 5 months. We exchanged data via a central shared virtual machine and performed comparative genomic analyses. Epidemiological evidence was integrated with WGS-derived data to identify related isolates and sources of infection, and we compared WGS data for surveillance with findings from MLVA typing. We found that WGS data combined with epidemiological data linked an additional 9% of isolates to at least one other isolate in the study in contrast to MLVA and epidemiological data, and 19% more isolates than epidemiological data alone. Analysis of risk factors showed that in one WGS-defined cluster, human cases had higher odds of purchasing a single egg brand. While WGS was more sensitive and specific than conventional typing methods, we identified barriers to uptake of genomic surveillance around complexity of reporting of WGS results, timeliness, acceptability, and stability. In conclusion, WGS offers higher resolution of Salmonella Typhimurium laboratory surveillance than existing methods and can provide further evidence on sources of infection in case and outbreak investigations for public health action. However, there are several challenges that need to be addressed for effective implementation of genomic surveillance in Australia.
DOI: 10.1089/fpd.2017.2352
PubMed URL: 29336594
Type: Journal Article
Subjects: MLVA
Salmonella Typhimurium
public health
whole-genome sequencing
Appears in Collections:Journal articles

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