Discriminatory power of three typing techniques in determining relatedness of nosocomial

Autor: Swathi, Purighalla, Sarita, Esakimuthu, Mallika, Reddy, George K, Varghese, Vijay S, Richard, Vasan K, Sambandamurthy
Rok vydání: 2017
Předmět:
Zdroj: Indian journal of medical microbiology. 35(3)
ISSN: 1998-3646
Popis: The purpose of this study was to evaluate the discriminatory power of two DNA-based technique and a protein-based technique for the typing of nosocomial isolates of Klebsiella pneumoniae. A second objective was to determine the antimicrobial susceptibility pattern and characterise the presence of genes encoding extended-spectrum beta-lactamases (ESBLs) and carbapenemases.Forty-six K. pneumoniae isolates from patients with bloodstream infections at a tertiary care hospital in India between December 2014 and December 2015 were studied. All isolates were typed using enterobacterial repetitive intergenic consensus sequence-polymerase chain reaction (ERIC-PCR), randomly amplified polymorphic DNA (RAPD) analysis and matrix-assisted laser desorption ionisation time-of-flight (MALDI-TOF) mass spectrometry. Antimicrobial susceptibility profiles and ESBLs were detected using the BD Phoenix system. The types of ESBL and carbapenemase genes present were detected using PCR.Isolates were subtyped into 31, 30 and 33 distinct genotypes by ERIC-PCR, RAPD and MALDI-TOF, respectively. Several isolates displaying identical DNA fingerprints were binned into different branches based on their proteomic fingerprint. Antimicrobial susceptibility tests revealed that 33/46 strains were multidrug resistant (MDR); a majority of the strains (83%) were sensitive to colistin. PCR-based analysis demonstrated 19 strains to harbour two or more ESBL and carbapenemase genes.ERIC-PCR was the most reproducible method for typing K. pneumoniae isolates and could not be substituted by MALDI-TOF for clonality analysis. A high degree of genetic diversity and the presence of MDR genes highlight the challenges in treating K. pneumoniae-associated infections.
Databáze: OpenAIRE