title: Prospective Whole-Genome Sequencing Enhances National Surveillance of Listeria monocytogenes.
abstract: Whole-genome sequencing (WGS) has emerged as a powerful tool for comparing bacterial isolates in outbreak detection and investigation. Here we demonstrate that WGS performed prospectively for national epidemiologic surveillance of Listeria monocytogenes has the capacity to be superior to our current approaches using pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), multilocus variable-number tandem-repeat analysis (MLVA), binary typing, and serotyping. Initially 423 L. monocytogenes isolates underwent WGS, and comparisons uncovered a diverse genetic population structure derived from three distinct lineages. MLST, binary typing, and serotyping results inferred in silico from the WGS data were highly concordant (>99%) with laboratory typing performed in parallel. However, WGS was able to identify distinct nested clusters within groups of isolates that were otherwise indistinguishable using our current typing methods. Routine WGS was then used for prospective epidemiologic surveillance on a further 97 L. monocytogenes isolates over a 12-month period, which provided a greater level of discrimination than that of conventional typing for inferring linkage to point source outbreaks. A risk-based alert system based on WGS similarity was used to inform epidemiologists required to act on the data. Our experience shows that WGS can be adopted for prospective L. monocytogenes surveillance and investigated for other pathogens relevant to public health.
authors.affiliation: Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia Infectious Diseases Department, Austin Health, Heidelberg, Victoria, Australia.
authors.forename: Jason C
authors.initials: JC
authors.lastname: Kwong
authors.affiliation: Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.
authors.forename: Karolina
authors.initials: K
authors.lastname: Mercoulia
authors.affiliation: Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.
authors.forename: Takehiro
authors.initials: T
authors.lastname: Tomita
authors.affiliation: Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.
authors.forename: Marion
authors.initials: M
authors.lastname: Easton
authors.affiliation: Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.
authors.forename: Hua Y
authors.initials: HY
authors.lastname: Li
authors.affiliation: Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia Victorian Life Sciences Computation Initiative, University of Melbourne, Victoria, Australia.
authors.forename: Dieter M
authors.initials: DM
authors.lastname: Bulach
authors.affiliation: Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.
authors.forename: Timothy P
authors.initials: TP
authors.lastname: Stinear
authors.affiliation: Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia Victorian Life Sciences Computation Initiative, University of Melbourne, Victoria, Australia.
authors.forename: Torsten
authors.initials: T
authors.lastname: Seemann
authors.affiliation: Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia Infectious Diseases Department, Austin Health, Heidelberg, Victoria, Australia bhowden@unimelb.edu.au.
authors.forename: Benjamin P
authors.initials: BP
authors.lastname: Howden
mesh_terms: D019295:Computational Biology / Q000379:methods; D016680:Genome, Bacterial; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008089:Listeria monocytogenes / Q000235:genetics*; D008088:Listeriosis / Q000453:epidemiology* / Q000382:microbiology*; D018598:Minisatellite Repeats; D058885:Multilocus Sequence Typing; D010802:Phylogeny; D020641:Polymorphism, Single Nucleotide; D011159:Population Surveillance; D015203:Reproducibility of Results; D012703:Serotyping