High Level Aminoglycoside Resistance And Distribution Of The Resistance Genes In And From Teaching Hospital In Malaysia.

High Level Aminoglycoside Resistance And Distribution Of The Resistance Genes In And From Teaching Hospital In Malaysia.

Moussa, Ayan Aden;Md Nordin, Amirah Fatihah;Hamat, Rukman Awang;Jasni, Azmiza Syawani;
Infection and drug resistance 2019 Vol. 12 pp. 3269-3274
239
moussa2019highinfection

Abstract

and are among the predominant species causing hospital-acquired infections. Currently, enterococcal infections are treated using combination therapy of an aminoglycoside with cell-wall active agents, which led to high level aminoglycoside resistance (HLAR) and vancomycin resistance (VRE) among enterococci. The aim of this study was to determine the prevalence of HLAR and the distribution of the resistance genes among clinical and isolates in Malaysia.Seventy-five enterococci isolates recovered from different clinical sources were re-identified by subculturing on selective medium, Gram staining, biochemical profiling (API 20 Strep), and 16s rRNA sequencing. Antimicrobial susceptibility testing (AST) was performed using Kirby-Bauer disc diffusion, E-test, and broth microdilution methods. PCR amplification was used to detect the presence of aminoglycoside modifying enzyme (AME) genes []. Descriptive data analysis was used to analyze the antibiotic susceptibility profiles and the distribution of HLAR genes.The majority of the isolates recovered from the clinical samples are (66.7%), with the highest recovery from the pus. The prevalence of HLGR (51%) is higher when compared to HLSR (45-49%). Analysis of the resistance genes showed that bifunctional genes and contributed to the HLAR and . The other AME genes [] were not detected in this study.This study provides the first prevalence data on HLAR and the distribution of the AME genes among and isolates from Malaysia. These highlight the need for continued antibiotic surveillance to minimize its emergence and further dissemination.

Citation

ID: 68904
Ref Key: moussa2019highinfection
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
68904
Unique Identifier:
10.2147/IDR.S219544
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet