OBJECTIVES: We utilized whole-genome mapping (WGM) and WGS to characterize 12 clinical carbapenem-resistant Klebsiella pneumoniae strains (TGH1-TGH12). METHODS: All strains were screened for carbapenemase genes by PCR, and typed by MLST, PFGE (XbaI) and WGM (AflII) (OpGen, USA). WGS (Illumina) was performed on TGH8 and TGH10. Reads were de novo assembled and annotated [SPAdes, Rapid Annotation Subsystem Technology (RAST)]. Contigs were aligned directly, and after in silico AflII restriction, with corresponding WGMs (MapSolver, OpGen; BioNumerics, Applied Maths). RESULTS: All 12 strains were ST383. Of the 12 strains, 11 were carbapenem resistant, 7 harboured blaKPC-2 and 11 harboured blaVIM-19. Varying the parameters for assigning WGM clusters showed that these were comparable to STs and to the eight PFGE types or subtypes (difference of three or more bands). A 95% similarity coefficient assigned all 12 WGMs to a single cluster, whereas a 99% similarity coefficient (or ≥10 unmatched-fragment difference) assigned the 12 WGMs to eight (sub)clusters. Based on a difference of three or more bands between PFGE profiles, the Simpson's diversity indices (SDIs) of WGM (0.94, Jackknife pseudo-values CI: 0.883-0.996) and PFGE (0.93, Jackknife pseudo-values CI: 0.828-1.000) were similar (P = 0.649). However, the discriminatory power of WGM was significantly higher (SDI: 0.94, Jackknife pseudo-values CI: 0.883-0.996) than that of PFGE profiles typed on a difference of seven or more bands (SDI: 0.53, Jackknife pseudo-values CI: 0.212-0.849) (P = 0.007). CONCLUSIONS: This study demonstrates the application of WGM to understanding the epidemiology of hospital-associated K. pneumoniae. Utilizing a combination of WGM and WGS, we also present here the first longitudinal genomic characterization of the highly dynamic carbapenem-resistant ST383 K. pneumoniae clone that is rapidly gaining importance in Europe.
OBJECTIVES: We utilized whole-genome mapping (WGM) and WGS to characterize 12 clinical carbapenem-resistant Klebsiella pneumoniae strains (TGH1-TGH12). METHODS: All strains were screened for carbapenemase genes by PCR, and typed by MLST, PFGE (XbaI) and WGM (AflII) (OpGen, USA). WGS (Illumina) was performed on TGH8 and TGH10. Reads were de novo assembled and annotated [SPAdes, Rapid Annotation Subsystem Technology (RAST)]. Contigs were aligned directly, and after in silico AflII restriction, with corresponding WGMs (MapSolver, OpGen; BioNumerics, Applied Maths). RESULTS: All 12 strains were ST383. Of the 12 strains, 11 were carbapenem resistant, 7 harboured blaKPC-2 and 11 harboured blaVIM-19. Varying the parameters for assigning WGM clusters showed that these were comparable to STs and to the eight PFGE types or subtypes (difference of three or more bands). A 95% similarity coefficient assigned all 12 WGMs to a single cluster, whereas a 99% similarity coefficient (or ≥10 unmatched-fragment difference) assigned the 12 WGMs to eight (sub)clusters. Based on a difference of three or more bands between PFGE profiles, the Simpson's diversity indices (SDIs) of WGM (0.94, Jackknife pseudo-values CI: 0.883-0.996) and PFGE (0.93, Jackknife pseudo-values CI: 0.828-1.000) were similar (P = 0.649). However, the discriminatory power of WGM was significantly higher (SDI: 0.94, Jackknife pseudo-values CI: 0.883-0.996) than that of PFGE profiles typed on a difference of seven or more bands (SDI: 0.53, Jackknife pseudo-values CI: 0.212-0.849) (P = 0.007). CONCLUSIONS: This study demonstrates the application of WGM to understanding the epidemiology of hospital-associated K. pneumoniae. Utilizing a combination of WGM and WGS, we also present here the first longitudinal genomic characterization of the highly dynamic carbapenem-resistant ST383 K. pneumoniae clone that is rapidly gaining importance in Europe.
Authors: María Soledad Ramirez; Gang Xie; German M Traglia; Shannon L Johnson; Karen W Davenport; David van Duin; Azam Ramazani; Federico Perez; Michael R Jacobs; David J Sherratt; Robert A Bonomo; Patrick S G Chain; Marcelo E Tolmasky Journal: Genome Biol Evol Date: 2016-07-03 Impact factor: 3.416