{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T03:03:56Z","timestamp":1790651036653,"version":"4.1.0"},"reference-count":47,"publisher":"American Society for Microbiology","issue":"2","license":[{"start":{"date-parts":[[2016,1,28]],"date-time":"2016-01-28T00:00:00Z","timestamp":1453939200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2016,2,1]],"date-time":"2016-02-01T00:00:00Z","timestamp":1454284800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.asm.org\/non-commercial-tdm-license"}],"funder":[{"DOI":"10.13039\/501100000925","name":"Department of Health | National Health and Medical Research Council","doi-asserted-by":"publisher","award":["APP1074824"],"award-info":[{"award-number":["APP1074824"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"Department of Health | National Health and Medical Research Council","doi-asserted-by":"publisher","award":["APP1008549"],"award-info":[{"award-number":["APP1008549"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"Department of Health | National Health and Medical Research Council","doi-asserted-by":"publisher","award":["APP1023526"],"award-info":[{"award-number":["APP1023526"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.asm.org"],"crossmark-restriction":true},"short-container-title":["J Clin Microbiol"],"published-print":{"date-parts":[[2016,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    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\n                    <jats:named-content content-type=\"genus-species\">Listeria monocytogenes<\/jats:named-content>\n                    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\n                    <jats:named-content content-type=\"genus-species\">L. monocytogenes<\/jats:named-content>\n                    isolates underwent WGS, and comparisons uncovered a diverse genetic population structure derived from three distinct lineages. MLST, binary typing, and serotyping results inferred\n                    <jats:italic>in silico<\/jats:italic>\n                    from the WGS data were highly concordant (&gt;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\n                    <jats:named-content content-type=\"genus-species\">L. monocytogenes<\/jats:named-content>\n                    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\n                    <jats:named-content content-type=\"genus-species\">L. monocytogenes<\/jats:named-content>\n                    surveillance and investigated for other pathogens relevant to public health.\n                  <\/jats:p>","DOI":"10.1128\/jcm.02344-15","type":"journal-article","created":{"date-parts":[[2015,11,25]],"date-time":"2015-11-25T22:23:34Z","timestamp":1448490214000},"page":"333-342","update-policy":"https:\/\/doi.org\/10.1128\/asmj-crossmark-policy-page","source":"Crossref","is-referenced-by-count":220,"title":["Prospective Whole-Genome Sequencing Enhances National Surveillance of Listeria monocytogenes"],"prefix":"10.1128","volume":"54","author":[{"given":"Jason C.","family":"Kwong","sequence":"first","affiliation":[{"name":"Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection &amp; Immunity, Melbourne, Victoria, Australia"},{"name":"Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection &amp; Immunity, Melbourne, Victoria, Australia"},{"name":"Infectious Diseases Department, Austin Health, Heidelberg, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karolina","family":"Mercoulia","sequence":"additional","affiliation":[{"name":"Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection &amp; Immunity, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takehiro","family":"Tomita","sequence":"additional","affiliation":[{"name":"Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection &amp; Immunity, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marion","family":"Easton","sequence":"additional","affiliation":[{"name":"Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection &amp; Immunity, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua Y.","family":"Li","sequence":"additional","affiliation":[{"name":"Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection &amp; Immunity, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dieter M.","family":"Bulach","sequence":"additional","affiliation":[{"name":"Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection &amp; Immunity, Melbourne, Victoria, Australia"},{"name":"Victorian Life Sciences Computation Initiative, University of Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy P.","family":"Stinear","sequence":"additional","affiliation":[{"name":"Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, University of Melbourne at the Doherty Institute for Infection &amp; 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