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@article{1405561,
author = {Brhelová, Eva and Antonova, Mariya and Pardy, Filip and Kocmanová, Iva and Mayer, Jiří and Ráčil, Zdeněk and Lengerová, Martina},
article_location = {Reading},
article_number = {11},
doi = {http://dx.doi.org/10.1099/jmm.0.000624},
keywords = {next generation sequencing; Klebsiella pneumoniae; MLST; ResFinder; PlasmidFinder; BIGSdb-Kp},
language = {eng},
issn = {0022-2615},
journal = {Journal of Medical Microbiology},
title = {Investigation of next-generation sequencing data of Klebsiella pneumoniae using web-based tools},
volume = {66},
year = {2017}
}
TY - JOUR
ID - 1405561
AU - Brhelová, Eva - Antonova, Mariya - Pardy, Filip - Kocmanová, Iva - Mayer, Jiří - Ráčil, Zdeněk - Lengerová, Martina
PY - 2017
TI - Investigation of next-generation sequencing data of Klebsiella pneumoniae using web-based tools
JF - Journal of Medical Microbiology
VL - 66
IS - 11
SP - 1673-1683
EP - 1673-1683
PB - Society for General Microbiology
SN - 00222615
KW - next generation sequencing
KW - Klebsiella pneumoniae
KW - MLST
KW - ResFinder
KW - PlasmidFinder
KW - BIGSdb-Kp
N2 - Purpose. Rapid identification and characterization of multidrug-resistant Klebsiella pneumoniae strains is necessary due to the increasing frequency of severe infections in patients. The decreasing cost of next-generation sequencing enables us to obtain a comprehensive overview of genetic information in one step. The aim of this study is to demonstrate and evaluate the utility and scope of the application of web-based databases to next-generation sequenced (NGS) data. Methodology. The whole genomes of 11 clinical Klebsiella pneumoniae isolates were sequenced using Illumina MiSeq. Selected web-based tools were used to identify a variety of genetic characteristics, such as acquired antimicrobial resistance genes, multilocus sequence types, plasmid replicons, and identify virulence factors, such as virulence genes, cps clusters, urease-nickel clusters and efflux systems. Results. Using web-based tools hosted by the Center for Genomic Epidemiology, we detected resistance to 8 main antimicrobial groups with at least 11 acquired resistance genes. The isolates were divided into eight sequence types (ST11, 23, 37, 323, 433, 495 and 562, and a new one, ST1646). All of the isolates carried replicons of large plasmids. Capsular types, virulence factors and genes coding AcrAB and OqxAB efflux pumps were detected using BIGSdb-Kp, whereas the selected virulence genes, identified in almost all of the isolates, were detected using CLC Genomic Workbench software. Conclusion. Applying appropriate web-based online tools to NGS data enables the rapid extraction of comprehensive information that can be used for more efficient diagnosis and treatment of patients, while data processing is free of charge, easy and time-efficient.
ER -
BRHELOVÁ, Eva, Mariya ANTONOVA, Filip PARDY, Iva KOCMANOVÁ, Jiří MAYER, Zdeněk RÁČIL and Martina LENGEROVÁ. Investigation of next-generation sequencing data of Klebsiella pneumoniae using web-based tools. \textit{Journal of Medical Microbiology}. Reading: Society for General Microbiology, 2017, vol.~66, No~11, p.~1673-1683. ISSN~0022-2615. Available from: https://dx.doi.org/10.1099/jmm.0.000624.
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