Title |
Implementation of Nationwide Real-time Whole-genome Sequencing to Enhance Listeriosis Outbreak Detection and Investigation
|
---|---|
Published in |
Clinical Infectious Diseases, April 2016
|
DOI | 10.1093/cid/ciw242 |
Pubmed ID | |
Authors |
Brendan R Jackson, Cheryl Tarr, Errol Strain, Kelly A Jackson, Amanda Conrad, Heather Carleton, Lee S Katz, Steven Stroika, L Hannah Gould, Rajal K Mody, Benjamin J Silk, Jennifer Beal, Yi Chen, Ruth Timme, Matthew Doyle, Angela Fields, Matthew Wise, Glenn Tillman, Stephanie Defibaugh-Chavez, Zuzana Kucerova, Ashley Sabol, Katie Roache, Eija Trees, Mustafa Simmons, Jamie Wasilenko, Kristy Kubota, Hannes Pouseele, William Klimke, John Besser, Eric Brown, Marc Allard, Peter Gerner-Smidt |
Abstract |
Listeria monocytogenes(Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all U.S.Lmisolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Whole-genome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 40% |
Sweden | 1 | 10% |
Unknown | 5 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 6 | 60% |
Members of the public | 3 | 30% |
Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | <1% |
Canada | 1 | <1% |
Unknown | 244 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 39 | 16% |
Researcher | 35 | 14% |
Student > Master | 33 | 13% |
Student > Bachelor | 18 | 7% |
Other | 14 | 6% |
Other | 38 | 15% |
Unknown | 69 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 58 | 24% |
Biochemistry, Genetics and Molecular Biology | 31 | 13% |
Immunology and Microbiology | 31 | 13% |
Medicine and Dentistry | 18 | 7% |
Veterinary Science and Veterinary Medicine | 8 | 3% |
Other | 23 | 9% |
Unknown | 77 | 31% |