TY - JOUR
T1 - Whole genome sequence analysis; an improved technology that identifies underlying genotypic differences between closely related Listeria monocytogenes strains
AU - Fox, Edward
AU - Casey, Aidan
AU - Jordan, Kieran
AU - Coffey, Aidan
AU - Gahan, Cormac
AU - McAuliffe, Olivia
PY - 2017/12
Y1 - 2017/12
N2 - As the new technology of whole genome sequencing (WGS) has been shown to have greater discriminatory power in differentiating strains than the much-used pulsed-field gel electrophoresis (PFGE), there is currently a transition from using PFGE to WGS for disease outbreak investigation. Therefore, there is a need for comparison of bacterial isolates using both PFGE and WGS. In this study, two pairs of L. monocytogenes strains with geographically diverse sources of isolation but which had indistinguishable or closely related PFGE profiles, were subjected to WGS analysis. Comparative analysis of their genomes showed that one pair of strains which had closely related PFGE profiles in fact differed significantly from one another in terms of their antibiotic and heavy metal stress resistance determinants, and mobile genetic elements. Therefore, this research demonstrated the ability of WGS analysis to differentiate very closely related strains and that WGS analysis represents the most effective tool available for subtyping L. monocytogenes isolates.
AB - As the new technology of whole genome sequencing (WGS) has been shown to have greater discriminatory power in differentiating strains than the much-used pulsed-field gel electrophoresis (PFGE), there is currently a transition from using PFGE to WGS for disease outbreak investigation. Therefore, there is a need for comparison of bacterial isolates using both PFGE and WGS. In this study, two pairs of L. monocytogenes strains with geographically diverse sources of isolation but which had indistinguishable or closely related PFGE profiles, were subjected to WGS analysis. Comparative analysis of their genomes showed that one pair of strains which had closely related PFGE profiles in fact differed significantly from one another in terms of their antibiotic and heavy metal stress resistance determinants, and mobile genetic elements. Therefore, this research demonstrated the ability of WGS analysis to differentiate very closely related strains and that WGS analysis represents the most effective tool available for subtyping L. monocytogenes isolates.
KW - Whole genome sequence analysis
KW - PFGE
KW - Listeria monocytogenes
U2 - 10.1016/j.ifset.2017.07.010
DO - 10.1016/j.ifset.2017.07.010
M3 - Article
SN - 1466-8564
VL - 44
SP - 89
EP - 96
JO - Innovative Food Science and Emerging Technologies
JF - Innovative Food Science and Emerging Technologies
ER -