High-level aminoglycoside resistance in Acinetobacter baumannii recovered from Intensive Care Unit patients in
Supriya Upadhyay1, Annie Bakorlin Khyriem2, Prithwis Bhattacharya3
1Department of Biotechnology and Bioinformatics, North Eastern Hill University, Shillong, Meghalaya, India.
Background:
Acinetobacter baumannii has emerged as an important nosocomial pathogen, its ability to acquire resistance to carbapenems and aminoglycosides, has complicated their treatment regimen. The present study investigates the prevalence and diversity of aminoglycoside-modifying enzymes and 16S methyltransferases in A. baumannii isolates recovered from patients admitted in Intensive Care Unit (ICU) of a tertiary referral hospital in Northeastern India.
Materials And Methods:
We investigated the high-level aminoglycoside-resistance (HLAR) (gentamicin and amikacin minimum inhibitory concentration ≥ 512 μg/ml) among 164 multidrug-resistant A. baumannii obtained from ICU. Genes encoding aminoglycoside-modifying enzymes, 16S methyltransferase and coexisting beta-lactamases were amplified. Horizontal transferability, plasmid stability and elimination assays were performed. Clonality and sequence types were evaluated by repetitive extragenic palindromic-polymerase chain reaction and multilocus sequence typing (MLST) respectively.
Results:
A total of 130 (79.2%) isolates were found to exhibit HLAR, with acquired aminoglycoside-resistance genes in 109 (83.8%) isolates along with coexisting extended-spectrum beta-lactamases and metallo-beta-lactamases. Genes aph (3') I, aph (3') VIa and armA were predominant and horizontally transferable. Plasmids were eliminated with single sodium dodecyl sulphate treatment. Seventeen haplotypes were found responsible for the infection. MLST revealed circulation of ST583 and ST188 in ICU.
Conclusions:
This study reveals the presence of aminoglycoside-resistance genes in combination with blaCTXM and blaNDM, which are highly stable and not frequently reported from this geographical region. Further, the study could predict limited treatment option and need for formulating infection control strategy.
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