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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

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Authors

Keith Hewett

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



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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http://creativecommons.org/licenses/by/4.0/

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http://creativecommons.org/licenses/by/4.0/

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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