Comparative analysis of core genome MLST and SNP typing within a European Salmonella serovar Enteritidis outbreak.
Comparative analysis of core genome MLST and SNP typing within a European Salmonella serovar Enteritidis outbreak.
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DOI:
10.1016/j.ijfoodmicro.2018.02.023
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发表时间:
2018-06-02
影响因子:
5.4
通讯作者:
Maiden MCJ
中科院分区:
文献类型:
--
作者:
Pearce ME;Alikhan NF;Dallman TJ;Zhou Z;Grant K;Maiden MCJ
Multi-country outbreaks of foodborne bacterial disease present challenges in their detection, tracking, and notification. As food is increasingly distributed across borders, such outbreaks are becoming more common. This increases the need for high-resolution, accessible, and replicable isolate typing schemes. Here we evaluate a core genome multilocus typing (cgMLST) scheme for the high-resolution reproducible typing of Salmonella enterica (S. enterica) isolates, by its application to a large European outbreak of S. enterica serovar Enteritidis. This outbreak had been extensively characterised using single nucleotide polymorphism (SNP)-based approaches. The cgMLST analysis was congruent with the original SNP-based analysis, the epidemiological data, and whole genome MLST (wgMLST) analysis. Combination of the cgMLST and epidemiological data confirmed that the genetic diversity among the isolates predated the outbreak, and was likely present at the infection source. There was consequently no link between country of isolation and genetic diversity, but the cgMLST clusters were congruent with date of isolation. Furthermore, comparison with publicly available Enteritidis isolate data demonstrated that the cgMLST scheme presented is highly scalable, enabling outbreaks to be contextualised within the Salmonella genus. The cgMLST scheme is therefore shown to be a standardised and scalable typing method, which allows Salmonella outbreaks to be analysed and compared across laboratories and jurisdictions. cgMLST is proposed as a universal typing scheme for Salmonella. cgMLST is congruent with SNP analyses and easier to implement across laboratories. Genomic data are consistent with the epidemiology of the outbreak.
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影响因子:
3.3
作者:
Hoffmann M;Zhao S;Pettengill J;Luo Y;Monday SR;Abbott J;Ayers SL;Cinar HN;Muruvanda T;Li C;Allard MW;Whichard J;Meng J;Brown EW;McDermott PF
通讯作者:
McDermott PF
影响因子:
2.8
作者:
Hendriksen, Rene S.;Vieira, Antonio R.;Aarestrup, Frank M.
通讯作者:
Aarestrup, Frank M.
影响因子:
1.7
作者:
Bankevich, Anton;Nurk, Sergey;Pevzner, Pavel A.
通讯作者:
Pevzner, Pavel A.
影响因子:
11.8
作者:
Galanis, E;Wong, DMALF;WHO Global Salm Surv
通讯作者:
WHO Global Salm Surv
DOI:
10.2307/2412448
发表时间:
1970-01-01
期刊:
SYSTEMATIC ZOOLOGY
影响因子:
--
作者:
FITCH, WM
通讯作者:
FITCH, WM