Keith Hewett
Towards the identification of antibiotic-resistant bacteria causing urinary tract infections using volatile organic compounds analysis—a pilot study
Hewett, Keith; Drabinska, Natalia; White, Paul; Avison, Matthew; Persad, Raj; Ratcliffe, Norman; de Lacy Costello, Ben
Authors
Natalia Drabinska
Paul White Paul.White@uwe.ac.uk
Professor in Applied Statistics
Matthew Avison
Raj Persad
Norman Ratcliffe Norman.Ratcliffe@uwe.ac.uk
Professor in Materials & Sensors Science
Benjamin De Lacy Costello Ben.DeLacyCostello@uwe.ac.uk
Associate Professor in Diagnostics and Bio-Sensing Technology
Abstract
Antibiotic resistance is an unprecedented threat to modern medicine. The analysis of volatile organic compounds (VOCs) from bacteria potentially offers a rapid way to determine antibiotic susceptibility in bacteria. This study aimed to find the optimal conditions to obtain the maximum number of VOCs detected which next allowed the assessment of differences in VOC profiles between susceptible and resistant isolates of Escherichia coli causing urinary tract infections. The analysis of VOCs in the headspace above the bacterial cultures allowed the distinguishing of resistant and susceptible bacteria based on the abundance of six VOCs with 85.7% overall accuracy. The results of this preliminary study are promising, and with development could lead to a practical, faster diagnostic method for use in routine microbiology.
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 10, 2020 |
Online Publication Date | Nov 11, 2020 |
Publication Date | Nov 11, 2020 |
Deposit Date | Jul 15, 2022 |
Publicly Available Date | Jul 15, 2022 |
Journal | Antibiotics |
Electronic ISSN | 2079-6382 |
Publisher | MDPI |
Peer Reviewed | Peer Reviewed |
Volume | 9 |
Issue | 11 |
Pages | 797 |
DOI | https://doi.org/10.3390/antibiotics9110797 |
Keywords | volatile; metabolite; profiles; gas chromatography-mass spectrometry; antibiotic resistance; bacteria; urinary tract infection; susceptibility; E. coli |
Public URL | https://uwe-repository.worktribe.com/output/9700697 |
Publisher URL | https://www.mdpi.com/2079-6382/9/11/797 |
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Copyright Statement
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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