Title Genetic characterization of multidrug-resistant E. coli isolates from bloodstream infections in Lithuania /
Authors Kirtiklienė, Tatjana ; Mierauskaitė, Aistė ; Razmienė, Ilona ; Kuisienė, Nomeda
DOI 10.3390/microorganisms10020449
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Is Part of Microorganisms.. Basel : MDPI. 2022, vol. 10, no. 2, art. no. 449, p. [1-12].. eISSN 2076-2607
Keywords [eng] E. coli ; genotyping ; resistance genes ; virulence factors
Abstract [eng] Extraintestinal pathogenic Escherichia coli (ExPEC) isolates are a main cause of bloodstream infections. The aim of this study was to characterize 256 β-lactam–resistant, bacteremia-causing E. coli isolates collected from 12 healthcare institutions in Lithuania in 2014 and 2018. All isolates were identified as E. coli via MALDI-TOF MS and VITEK ®2. In addition, the isolates were analyzed for the presence of 29 resistance genes and 13 virulence genes, divided into phylogenetic groups (A, B1, B2, C, D, E, and F), and characterized using rep-PCR genotyping methods (BOX-PCR and (GTG)5-PCR). Analyzing the results of this study showed tetA-strB-sul2-TEM-NDM-strA-fosA-AIM-sul3-aadA-CTX-M-9 to be the most common resistance gene combination (67.2% of all isolates). Additionally, the most common virulence genes established were fimH (98.4% of all isolates), fyuA (91.8%), and traT (81.3%) and the most common gene combination was fuyA-fimH-iroN (58.6% of all isolates). Next, the isolates were separated into four phylogenetic groups: A, B1, B2, and F, where group A isolates were detected at a significantly higher frequency (79.3% of all isolates). Finally, a total of 235 genotyping profiles were established using rep-PCR methods, and all profiles were separated into fourteen genotypic clusters, with each cluster containing profiles with a variety of virulence and resistance genes not restricted to any specific cluster. The results of this study elucidate E. coli antimicrobial resistance patterns by highlighting the variability and diversity of resistance and virulence genes and providing phylogenetic classification, genetic profiling, and clustering data. These results may improve clinical control of multidrug-resistant infections in healthcare institutions and contribute to the prevention of potential outbreaks.
Published Basel : MDPI
Type Journal article
Language English
Publication date 2022
CC license CC license description