MDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

As antibiotics resistance on superbugs has risen, more and more studies have focused on developing rapid antibiotics susceptibility tests (AST). Meanwhile, identification of multiple antibiotics resistance on Staphylococcus aureus provides instant information which can assist clinicians in administr...

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Autores principales:	Chia-Ru Chung, Zhuo Wang, Jing-Mei Weng, Hsin-Yao Wang, Li-Ching Wu, Yi-Ju Tseng, Chun-Hsien Chen, Jang-Jih Lu, Jorng-Tzong Horng, Tzong-Yi Lee
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	antibiotics susceptibility test multidrug resistance MALDI-TOF MS machine learning AST (antibiotic susceptibility testing) Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/bb59b0c9de934a2fb1004d2e40e78c05
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spelling	oai:doaj.org-article:bb59b0c9de934a2fb1004d2e40e78c052021-12-03T07:14:41ZMDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry1664-302X10.3389/fmicb.2021.766206https://doaj.org/article/bb59b0c9de934a2fb1004d2e40e78c052021-12-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fmicb.2021.766206/fullhttps://doaj.org/toc/1664-302XAs antibiotics resistance on superbugs has risen, more and more studies have focused on developing rapid antibiotics susceptibility tests (AST). Meanwhile, identification of multiple antibiotics resistance on Staphylococcus aureus provides instant information which can assist clinicians in administrating the appropriate prescriptions. In recent years, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has emerged as a powerful tool in clinical microbiology laboratories for the rapid identification of bacterial species. Yet, lack of study devoted on providing efficient methods to deal with the MS shifting problem, not to mention to providing tools incorporating the MALDI-TOF MS for the clinical use which deliver the instant administration of antibiotics to the clinicians. In this study, we developed a web tool, MDRSA, for the rapid identification of oxacillin-, clindamycin-, and erythromycin-resistant Staphylococcus aureus. Specifically, the kernel density estimation (KDE) was adopted to deal with the peak shifting problem, which is critical to analyze mass spectra data, and machine learning methods, including decision trees, random forests, and support vector machines, which were used to construct the classifiers to identify the antibiotic resistance. The areas under the receiver operating the characteristic curve attained 0.8 on the internal (10-fold cross validation) and external (independent testing) validation. The promising results can provide more confidence to apply these prediction models in the real world. Briefly, this study provides a web-based tool to provide rapid predictions for the resistance of antibiotics on Staphylococcus aureus based on the MALDI-TOF MS data. The web tool is available at: http://fdblab.csie.ncu.edu.tw/mdrsa/.Chia-Ru ChungZhuo WangJing-Mei WengHsin-Yao WangHsin-Yao WangLi-Ching WuYi-Ju TsengYi-Ju TsengChun-Hsien ChenChun-Hsien ChenJang-Jih LuJang-Jih LuJang-Jih LuJorng-Tzong HorngJorng-Tzong HorngTzong-Yi LeeFrontiers Media S.A.articleantibiotics susceptibility testmultidrug resistanceMALDI-TOF MSmachine learningAST (antibiotic susceptibility testing)MicrobiologyQR1-502ENFrontiers in Microbiology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	antibiotics susceptibility test multidrug resistance MALDI-TOF MS machine learning AST (antibiotic susceptibility testing) Microbiology QR1-502
spellingShingle	antibiotics susceptibility test multidrug resistance MALDI-TOF MS machine learning AST (antibiotic susceptibility testing) Microbiology QR1-502 Chia-Ru Chung Zhuo Wang Jing-Mei Weng Hsin-Yao Wang Hsin-Yao Wang Li-Ching Wu Yi-Ju Tseng Yi-Ju Tseng Chun-Hsien Chen Chun-Hsien Chen Jang-Jih Lu Jang-Jih Lu Jang-Jih Lu Jorng-Tzong Horng Jorng-Tzong Horng Tzong-Yi Lee MDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry
description	As antibiotics resistance on superbugs has risen, more and more studies have focused on developing rapid antibiotics susceptibility tests (AST). Meanwhile, identification of multiple antibiotics resistance on Staphylococcus aureus provides instant information which can assist clinicians in administrating the appropriate prescriptions. In recent years, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has emerged as a powerful tool in clinical microbiology laboratories for the rapid identification of bacterial species. Yet, lack of study devoted on providing efficient methods to deal with the MS shifting problem, not to mention to providing tools incorporating the MALDI-TOF MS for the clinical use which deliver the instant administration of antibiotics to the clinicians. In this study, we developed a web tool, MDRSA, for the rapid identification of oxacillin-, clindamycin-, and erythromycin-resistant Staphylococcus aureus. Specifically, the kernel density estimation (KDE) was adopted to deal with the peak shifting problem, which is critical to analyze mass spectra data, and machine learning methods, including decision trees, random forests, and support vector machines, which were used to construct the classifiers to identify the antibiotic resistance. The areas under the receiver operating the characteristic curve attained 0.8 on the internal (10-fold cross validation) and external (independent testing) validation. The promising results can provide more confidence to apply these prediction models in the real world. Briefly, this study provides a web-based tool to provide rapid predictions for the resistance of antibiotics on Staphylococcus aureus based on the MALDI-TOF MS data. The web tool is available at: http://fdblab.csie.ncu.edu.tw/mdrsa/.
format	article
author	Chia-Ru Chung Zhuo Wang Jing-Mei Weng Hsin-Yao Wang Hsin-Yao Wang Li-Ching Wu Yi-Ju Tseng Yi-Ju Tseng Chun-Hsien Chen Chun-Hsien Chen Jang-Jih Lu Jang-Jih Lu Jang-Jih Lu Jorng-Tzong Horng Jorng-Tzong Horng Tzong-Yi Lee
author_facet	Chia-Ru Chung Zhuo Wang Jing-Mei Weng Hsin-Yao Wang Hsin-Yao Wang Li-Ching Wu Yi-Ju Tseng Yi-Ju Tseng Chun-Hsien Chen Chun-Hsien Chen Jang-Jih Lu Jang-Jih Lu Jang-Jih Lu Jorng-Tzong Horng Jorng-Tzong Horng Tzong-Yi Lee
author_sort	Chia-Ru Chung
title	MDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry
title_short	MDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry
title_full	MDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry
title_fullStr	MDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry
title_full_unstemmed	MDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry
title_sort	mdrsa: a web based-tool for rapid identification of multidrug resistant staphylococcus aureus based on matrix-assisted laser desorption ionization-time of flight mass spectrometry
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/bb59b0c9de934a2fb1004d2e40e78c05
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MDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

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