Title |
Real-Time Whole-Genome Sequencing for Surveillance of Listeria monocytogenes, France - Volume 23, Number 9—September 2017 - Emerging Infectious Diseases journal - CDC
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Published in |
Emerging Infectious Diseases, September 2017
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DOI | 10.3201/eid2309.170336 |
Pubmed ID | |
Authors |
Alexandra Moura, Mathieu Tourdjman, Alexandre Leclercq, Estelle Hamelin, Edith Laurent, Nathalie Fredriksen, Dieter Van Cauteren, Hélène Bracq-Dieye, Pierre Thouvenot, Guillaume Vales, Nathalie Tessaud-Rita, Mylène M. Maury, Andreea Alexandru, Alexis Criscuolo, Emmanuel Quevillon, Marie-Pierre Donguy, Vincent Enouf, Henriette de Valk, Sylvain Brisse, Marc Lecuit |
Abstract |
During 2015-2016, we evaluated the performance of whole-genome sequencing (WGS) as a routine typing tool. Its added value for microbiological and epidemiologic surveillance of listeriosis was compared with that for pulsed-field gel electrophoresis (PFGE), the current standard method. A total of 2,743 Listeria monocytogenes isolates collected as part of routine surveillance were characterized in parallel by PFGE and core genome multilocus sequence typing (cgMLST) extracted from WGS. We investigated PFGE and cgMLST clusters containing human isolates. Discrimination of isolates was significantly higher by cgMLST than by PFGE (p<0.001). cgMLST discriminated unrelated isolates that shared identical PFGE profiles and phylogenetically closely related isolates with distinct PFGE profiles. This procedure also refined epidemiologic investigations to include only phylogenetically closely related isolates, improved source identification, and facilitated epidemiologic investigations, enabling identification of more outbreaks at earlier stages. WGS-based typing should replace PFGE as the primary typing method for L. monocytogenes. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 4 | 14% |
Ireland | 4 | 14% |
Australia | 2 | 7% |
United Kingdom | 2 | 7% |
Sweden | 1 | 3% |
Venezuela, Bolivarian Republic of | 1 | 3% |
Unknown | 15 | 52% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 15 | 52% |
Members of the public | 13 | 45% |
Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 127 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 26 | 20% |
Student > Ph. D. Student | 17 | 13% |
Student > Master | 17 | 13% |
Student > Bachelor | 10 | 8% |
Student > Doctoral Student | 6 | 5% |
Other | 17 | 13% |
Unknown | 34 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 28 | 22% |
Biochemistry, Genetics and Molecular Biology | 24 | 19% |
Immunology and Microbiology | 12 | 9% |
Medicine and Dentistry | 10 | 8% |
Computer Science | 3 | 2% |
Other | 8 | 6% |
Unknown | 42 | 33% |