An Optimized SPME-GC-MS Method for Volatile Metabolite Profiling of Different Alfalfa (<i>Medicago sativa</i> L.) Tissues

Solid-phase microextraction (SPME) was coupled to gas chromatography mass spectrometry (GC-MS) and a method optimized to quantitatively and qualitatively measure a large array of volatile metabolites in alfalfa glandular trichomes isolated from stems, trichome-free stems, and leaves as part of a non...

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Autores principales:	Dong-Sik Yang, Zhentian Lei, Mohamed Bedair, Lloyd W. Sumner
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	<i>Medicago sativa</i> alfalfa SPME GC-MS volatiles Organic chemistry QD241-441
Acceso en línea:	https://doaj.org/article/502cab3bb48e4f42b7b6c388bf5ea052
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spelling	oai:doaj.org-article:502cab3bb48e4f42b7b6c388bf5ea0522021-11-11T18:28:47ZAn Optimized SPME-GC-MS Method for Volatile Metabolite Profiling of Different Alfalfa (<i>Medicago sativa</i> L.) Tissues10.3390/molecules262164731420-3049https://doaj.org/article/502cab3bb48e4f42b7b6c388bf5ea0522021-10-01T00:00:00Zhttps://www.mdpi.com/1420-3049/26/21/6473https://doaj.org/toc/1420-3049Solid-phase microextraction (SPME) was coupled to gas chromatography mass spectrometry (GC-MS) and a method optimized to quantitatively and qualitatively measure a large array of volatile metabolites in alfalfa glandular trichomes isolated from stems, trichome-free stems, and leaves as part of a non-targeted metabolomics approach. Major SPME extraction parameters optimized included SPME fiber composition, extraction temperature, and extraction time. The optimized SPME method provided the most chemically diverse coverage of alfalfa volatile and semi-volatile metabolites using a DVB/CAR/PDMS fiber, extraction temperature of 60 °C, and an extraction time of 20 min. Alfalfa SPME-GC-MS profiles were processed using automated peak deconvolution and identification (AMDIS) and quantitative data extraction software (MET-IDEA). A total of 87 trichome, 59 stem, and 99 leaf volatile metabolites were detected after background subtraction which removed contaminants present in ambient air and associated with the fibers and NaOH/EDTA buffer solution containing CaCl<sub>2</sub>. Thirty-seven volatile metabolites were detected in all samples, while 15 volatile metabolites were uniquely detected only in glandular trichomes, 9 only in stems, and 33 specifically in leaves as tissue specific volatile metabolites. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) of glandular trichomes, stems, and leaves showed that the volatile metabolic profiles obtained from the optimized SPME-GC-MS method clearly differentiated the three tissues (glandular trichomes, stems, and leaves), and the biochemical basis for this differentiation is discussed. Although optimized using plant tissues, the method can be applied to other types of samples including fruits and other foods.Dong-Sik YangZhentian LeiMohamed BedairLloyd W. SumnerMDPI AGarticle<i>Medicago sativa</i>alfalfaSPMEGC-MSvolatilesOrganic chemistryQD241-441ENMolecules, Vol 26, Iss 6473, p 6473 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	<i>Medicago sativa</i> alfalfa SPME GC-MS volatiles Organic chemistry QD241-441
spellingShingle	<i>Medicago sativa</i> alfalfa SPME GC-MS volatiles Organic chemistry QD241-441 Dong-Sik Yang Zhentian Lei Mohamed Bedair Lloyd W. Sumner An Optimized SPME-GC-MS Method for Volatile Metabolite Profiling of Different Alfalfa (<i>Medicago sativa</i> L.) Tissues
description	Solid-phase microextraction (SPME) was coupled to gas chromatography mass spectrometry (GC-MS) and a method optimized to quantitatively and qualitatively measure a large array of volatile metabolites in alfalfa glandular trichomes isolated from stems, trichome-free stems, and leaves as part of a non-targeted metabolomics approach. Major SPME extraction parameters optimized included SPME fiber composition, extraction temperature, and extraction time. The optimized SPME method provided the most chemically diverse coverage of alfalfa volatile and semi-volatile metabolites using a DVB/CAR/PDMS fiber, extraction temperature of 60 °C, and an extraction time of 20 min. Alfalfa SPME-GC-MS profiles were processed using automated peak deconvolution and identification (AMDIS) and quantitative data extraction software (MET-IDEA). A total of 87 trichome, 59 stem, and 99 leaf volatile metabolites were detected after background subtraction which removed contaminants present in ambient air and associated with the fibers and NaOH/EDTA buffer solution containing CaCl<sub>2</sub>. Thirty-seven volatile metabolites were detected in all samples, while 15 volatile metabolites were uniquely detected only in glandular trichomes, 9 only in stems, and 33 specifically in leaves as tissue specific volatile metabolites. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) of glandular trichomes, stems, and leaves showed that the volatile metabolic profiles obtained from the optimized SPME-GC-MS method clearly differentiated the three tissues (glandular trichomes, stems, and leaves), and the biochemical basis for this differentiation is discussed. Although optimized using plant tissues, the method can be applied to other types of samples including fruits and other foods.
format	article
author	Dong-Sik Yang Zhentian Lei Mohamed Bedair Lloyd W. Sumner
author_facet	Dong-Sik Yang Zhentian Lei Mohamed Bedair Lloyd W. Sumner
author_sort	Dong-Sik Yang
title	An Optimized SPME-GC-MS Method for Volatile Metabolite Profiling of Different Alfalfa (<i>Medicago sativa</i> L.) Tissues
title_short	An Optimized SPME-GC-MS Method for Volatile Metabolite Profiling of Different Alfalfa (<i>Medicago sativa</i> L.) Tissues
title_full	An Optimized SPME-GC-MS Method for Volatile Metabolite Profiling of Different Alfalfa (<i>Medicago sativa</i> L.) Tissues
title_fullStr	An Optimized SPME-GC-MS Method for Volatile Metabolite Profiling of Different Alfalfa (<i>Medicago sativa</i> L.) Tissues
title_full_unstemmed	An Optimized SPME-GC-MS Method for Volatile Metabolite Profiling of Different Alfalfa (<i>Medicago sativa</i> L.) Tissues
title_sort	optimized spme-gc-ms method for volatile metabolite profiling of different alfalfa (<i>medicago sativa</i> l.) tissues
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/502cab3bb48e4f42b7b6c388bf5ea052
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An Optimized SPME-GC-MS Method for Volatile Metabolite Profiling of Different Alfalfa (<i>Medicago sativa</i> L.) Tissues

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