Quantitation of ethanol in UTI assay for volatile organic compound detection by electronic nose using the validated headspace GC-MS method

Disease detection through gas analysis has long been the topic of many studies because of its potential as a rapid diagnostic technique. In particular, the pathogens that cause urinary tract infection (UTI) have been shown to generate different profiles of volatile organic compounds, thus enabling t...

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Main Authors: Than, Nam, Chik, Zamri, Bowers, Amy, Bozano, Luisa, Adebiyi, Aminat
Format: Article
Published: Public Library of Science 2022
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Online Access:http://eprints.um.edu.my/46244/
https://doi.org/10.1371/journal.pone.0275517
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spelling my.um.eprints.462442024-07-25T00:56:39Z http://eprints.um.edu.my/46244/ Quantitation of ethanol in UTI assay for volatile organic compound detection by electronic nose using the validated headspace GC-MS method Than, Nam Chik, Zamri Bowers, Amy Bozano, Luisa Adebiyi, Aminat RB Pathology S Agriculture (General) Disease detection through gas analysis has long been the topic of many studies because of its potential as a rapid diagnostic technique. In particular, the pathogens that cause urinary tract infection (UTI) have been shown to generate different profiles of volatile organic compounds, thus enabling the discrimination of causative agents using an electronic nose. While past studies have performed data collection on either agar culture or jellified urine culture, this study measures the headspace volume of liquid urine culture samples. Evaporation of the liquid and the presence of background compounds during electronic nose (e-nose) device operation could introduce variability to the collected data. Therefore, a headspace gas chromatography-mass spectrometry method was developed and validated for quantitating ethanol in the headspace of the urine samples. By leveraging the new method to characterize the sample stability during e-nose measurement, it was revealed that ethanol concentration dropped more than 15% after only three measurement cycles, which equal 30 minutes for this study. It was further shown that by using only data within the first three cycles, better accuracies for between-day classification were achieved, which was 73.7% and 97.0%, compared to using data from within the first nine cycles, which resulted in 65.0% and 81.1% accuracies. Therefore, the newly developed method provides better quality control for data collection, paving ways for the future establishment of a training data library for UTI. Public Library of Science 2022-10 Article PeerReviewed Than, Nam and Chik, Zamri and Bowers, Amy and Bozano, Luisa and Adebiyi, Aminat (2022) Quantitation of ethanol in UTI assay for volatile organic compound detection by electronic nose using the validated headspace GC-MS method. PLoS ONE, 17 (10). ISSN 1932-6203, DOI https://doi.org/10.1371/journal.pone.0275517 <https://doi.org/10.1371/journal.pone.0275517>. https://doi.org/10.1371/journal.pone.0275517 10.1371/journal.pone.0275517
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic RB Pathology
S Agriculture (General)
spellingShingle RB Pathology
S Agriculture (General)
Than, Nam
Chik, Zamri
Bowers, Amy
Bozano, Luisa
Adebiyi, Aminat
Quantitation of ethanol in UTI assay for volatile organic compound detection by electronic nose using the validated headspace GC-MS method
description Disease detection through gas analysis has long been the topic of many studies because of its potential as a rapid diagnostic technique. In particular, the pathogens that cause urinary tract infection (UTI) have been shown to generate different profiles of volatile organic compounds, thus enabling the discrimination of causative agents using an electronic nose. While past studies have performed data collection on either agar culture or jellified urine culture, this study measures the headspace volume of liquid urine culture samples. Evaporation of the liquid and the presence of background compounds during electronic nose (e-nose) device operation could introduce variability to the collected data. Therefore, a headspace gas chromatography-mass spectrometry method was developed and validated for quantitating ethanol in the headspace of the urine samples. By leveraging the new method to characterize the sample stability during e-nose measurement, it was revealed that ethanol concentration dropped more than 15% after only three measurement cycles, which equal 30 minutes for this study. It was further shown that by using only data within the first three cycles, better accuracies for between-day classification were achieved, which was 73.7% and 97.0%, compared to using data from within the first nine cycles, which resulted in 65.0% and 81.1% accuracies. Therefore, the newly developed method provides better quality control for data collection, paving ways for the future establishment of a training data library for UTI.
format Article
author Than, Nam
Chik, Zamri
Bowers, Amy
Bozano, Luisa
Adebiyi, Aminat
author_facet Than, Nam
Chik, Zamri
Bowers, Amy
Bozano, Luisa
Adebiyi, Aminat
author_sort Than, Nam
title Quantitation of ethanol in UTI assay for volatile organic compound detection by electronic nose using the validated headspace GC-MS method
title_short Quantitation of ethanol in UTI assay for volatile organic compound detection by electronic nose using the validated headspace GC-MS method
title_full Quantitation of ethanol in UTI assay for volatile organic compound detection by electronic nose using the validated headspace GC-MS method
title_fullStr Quantitation of ethanol in UTI assay for volatile organic compound detection by electronic nose using the validated headspace GC-MS method
title_full_unstemmed Quantitation of ethanol in UTI assay for volatile organic compound detection by electronic nose using the validated headspace GC-MS method
title_sort quantitation of ethanol in uti assay for volatile organic compound detection by electronic nose using the validated headspace gc-ms method
publisher Public Library of Science
publishDate 2022
url http://eprints.um.edu.my/46244/
https://doi.org/10.1371/journal.pone.0275517
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score 13.18916