Accession Number : ADA625182


Title :   Comparative Analysis of Subtyping Methods against a Whole- Genome-Sequencing Standard for Salmonella enterica Serotype Enteritidis


Descriptive Note : Journal article


Corporate Author : PENNSYLVANIA STATE UNIV STATE COLLEGE


Personal Author(s) : Deng, Xiangyu ; Shariat, Nikki ; Driebe, Elizabeth M ; Roe, Chandler C ; Tolar, Beth ; Trees, Eija ; Keim, Paul ; Zhang, Wei ; Dudley, Edward G ; Fields, Patricia I


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a625182.pdf


Report Date : Jan 2015


Pagination or Media Count : 10


Abstract : A retrospective investigation was performed to evaluate whole-genome sequencing as a benchmark for comparing molecular subtyping methods for Salmonella enterica serotype Enteritidis and survey the population structure of commonly encountered S. enterica serotype Enteritidis outbreak isolates in the United States. A total of 52 S. enterica serotype Enteritidis isolates representing 16 major outbreaks and three sporadic cases collected between 2001 and 2012 were sequenced and subjected to subtyping by four different methods: (i) whole-genome single-nucleotidepolymorphism typing (WGST), (ii) multiple-locus variable-number tandem-repeat (VNTR) analysis (MLVA), (iii) clustered regularly interspaced short palindromic repeats combined with multi-virulence-locus sequence typing (CRISPR-MVLST), and (iv) pulsed-field gel electrophoresis (PFGE). WGST resolved all outbreak clusters and provided useful robust phylogenetic inference results with high epidemiological correlation. While both MLVA and CRISPR-MVLST yielded higher discriminatory power than PFGE, MLVA outperformed the other methods in delineating outbreak clusters whereas CRISPR-MVLST showed the potential to trace major lineages and ecological origins of S. enterica serotype Enteritidis. Our results suggested that whole-genome sequencing makes a viable platform for the evaluation and benchmarking of molecular subtyping methods.


Descriptors :   *EPIDEMIOLOGY , *MICROBIOLOGY , *SALMONELLA , BACTERIAL DISEASES , CLASSIFICATION , CLUSTERING , CORRELATION , DEMOGRAPHY , DISEASE VECTORS , ELECTROPHORESIS , FOOD , GELS , GENOME , MOLECULAR DYNAMICS , MORTALITY RATE , NUCLEOTIDES , POLYMORPHISM , STRAINS(BIOLOGY) , VIABILITY


Subject Categories : Medicine and Medical Research
      Microbiology


Distribution Statement : APPROVED FOR PUBLIC RELEASE