Metabolomics analysis of oil palm (Elaeis guineensis) leaf: evaluation of sample preparation steps using UHPLC–MS/MS
Introduction Metabolomics analysis of oil palm leaves is a promising strategy to prospect new added-value compounds of this underutilized oil industry by-product. Although previous studies had reported some metabolites identified in this matrix, they had been focused on few compounds using conventio...
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creator | Vargas, Luiz Henrique Galli Neto, Jorge Candido Rodrigues de Aquino Ribeiro, José Antônio Ricci-Silva, Maria Esther Souza, Manoel Teixeira Rodrigues, Clenilson Martins de Oliveira, Anselmo Elcana Abdelnur, Patrícia Verardi |
description | Introduction
Metabolomics analysis of oil palm leaves is a promising strategy to prospect new added-value compounds of this underutilized oil industry by-product. Although previous studies had reported some metabolites identified in this matrix, they had been focused on few compounds using conventional analytical techniques.
Objectives
This study aimed to develop a new high throughput method based on metabolomics able to detect a wide range of metabolites classes in
Elaeis guineensis
leaves. Furthermore, we investigate the effects caused by harvesting/sample preparation steps for the metabolites identification.
Method
Metabolites analyses were performed by ultra-high liquid chromatography—mass spectrometry (UHPLC–MS) using both ionization modes, ESI(+)–MS and ESI(−)–MS. ANOVA simultaneous component analysis (ASCA) of the resulting complex multivariate dataset was applied to evaluate metabolic alterations. Identification of major metabolites was performed by high resolution mass spectrometry and MS/MS experiments.
Result
A high throughput method based on UHPLC–MS was successfully developed to
E. guineensis
leaves, detecting from polar to non-polar acid and basic metabolites. According to ASCA, oil palm leaves metabolic fingerprintings have shown influence of transportation/storage and extraction solvent used chosen. In fact, the most significant effect is due to the solvent composition. A total of thirteen metabolites were assigned based on HRMS and MS/MS experiments. However, only seven metabolites identified were previously reported, which represents a potential field to discover new metabolites.
Conclusion
Sample preparation steps should be carefully performed in metabolomics studies, because metabolites will be extracted and identified based on transport and solvent of extraction conditions. In this study, we established a reliable analytical protocol, from sample preparation to data analyses, to prospect new metabolites in oil palm leaves. This protocol could be further applied to similar oil-bearing crops. |
doi_str_mv | 10.1007/s11306-016-1100-z |
format | Article |
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Metabolomics analysis of oil palm leaves is a promising strategy to prospect new added-value compounds of this underutilized oil industry by-product. Although previous studies had reported some metabolites identified in this matrix, they had been focused on few compounds using conventional analytical techniques.
Objectives
This study aimed to develop a new high throughput method based on metabolomics able to detect a wide range of metabolites classes in
Elaeis guineensis
leaves. Furthermore, we investigate the effects caused by harvesting/sample preparation steps for the metabolites identification.
Method
Metabolites analyses were performed by ultra-high liquid chromatography—mass spectrometry (UHPLC–MS) using both ionization modes, ESI(+)–MS and ESI(−)–MS. ANOVA simultaneous component analysis (ASCA) of the resulting complex multivariate dataset was applied to evaluate metabolic alterations. Identification of major metabolites was performed by high resolution mass spectrometry and MS/MS experiments.
Result
A high throughput method based on UHPLC–MS was successfully developed to
E. guineensis
leaves, detecting from polar to non-polar acid and basic metabolites. According to ASCA, oil palm leaves metabolic fingerprintings have shown influence of transportation/storage and extraction solvent used chosen. In fact, the most significant effect is due to the solvent composition. A total of thirteen metabolites were assigned based on HRMS and MS/MS experiments. However, only seven metabolites identified were previously reported, which represents a potential field to discover new metabolites.
Conclusion
Sample preparation steps should be carefully performed in metabolomics studies, because metabolites will be extracted and identified based on transport and solvent of extraction conditions. In this study, we established a reliable analytical protocol, from sample preparation to data analyses, to prospect new metabolites in oil palm leaves. This protocol could be further applied to similar oil-bearing crops.</description><identifier>ISSN: 1573-3882</identifier><identifier>EISSN: 1573-3890</identifier><identifier>DOI: 10.1007/s11306-016-1100-z</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Biochemistry ; Biomedical and Life Sciences ; Biomedicine ; Cell Biology ; Developmental Biology ; Life Sciences ; Molecular Medicine ; Original Article</subject><ispartof>Metabolomics, 2016-10, Vol.12 (10), p.1, Article 153</ispartof><rights>Springer Science+Business Media New York 2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-db59ec298d05b65f165008ff128de2275f036260b68c4aebeb90935d8039b1323</citedby><cites>FETCH-LOGICAL-c316t-db59ec298d05b65f165008ff128de2275f036260b68c4aebeb90935d8039b1323</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11306-016-1100-z$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11306-016-1100-z$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Vargas, Luiz Henrique Galli</creatorcontrib><creatorcontrib>Neto, Jorge Candido Rodrigues</creatorcontrib><creatorcontrib>de Aquino Ribeiro, José Antônio</creatorcontrib><creatorcontrib>Ricci-Silva, Maria Esther</creatorcontrib><creatorcontrib>Souza, Manoel Teixeira</creatorcontrib><creatorcontrib>Rodrigues, Clenilson Martins</creatorcontrib><creatorcontrib>de Oliveira, Anselmo Elcana</creatorcontrib><creatorcontrib>Abdelnur, Patrícia Verardi</creatorcontrib><title>Metabolomics analysis of oil palm (Elaeis guineensis) leaf: evaluation of sample preparation steps using UHPLC–MS/MS</title><title>Metabolomics</title><addtitle>Metabolomics</addtitle><description>Introduction
Metabolomics analysis of oil palm leaves is a promising strategy to prospect new added-value compounds of this underutilized oil industry by-product. Although previous studies had reported some metabolites identified in this matrix, they had been focused on few compounds using conventional analytical techniques.
Objectives
This study aimed to develop a new high throughput method based on metabolomics able to detect a wide range of metabolites classes in
Elaeis guineensis
leaves. Furthermore, we investigate the effects caused by harvesting/sample preparation steps for the metabolites identification.
Method
Metabolites analyses were performed by ultra-high liquid chromatography—mass spectrometry (UHPLC–MS) using both ionization modes, ESI(+)–MS and ESI(−)–MS. ANOVA simultaneous component analysis (ASCA) of the resulting complex multivariate dataset was applied to evaluate metabolic alterations. Identification of major metabolites was performed by high resolution mass spectrometry and MS/MS experiments.
Result
A high throughput method based on UHPLC–MS was successfully developed to
E. guineensis
leaves, detecting from polar to non-polar acid and basic metabolites. According to ASCA, oil palm leaves metabolic fingerprintings have shown influence of transportation/storage and extraction solvent used chosen. In fact, the most significant effect is due to the solvent composition. A total of thirteen metabolites were assigned based on HRMS and MS/MS experiments. However, only seven metabolites identified were previously reported, which represents a potential field to discover new metabolites.
Conclusion
Sample preparation steps should be carefully performed in metabolomics studies, because metabolites will be extracted and identified based on transport and solvent of extraction conditions. In this study, we established a reliable analytical protocol, from sample preparation to data analyses, to prospect new metabolites in oil palm leaves. This protocol could be further applied to similar oil-bearing crops.</description><subject>Biochemistry</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Cell Biology</subject><subject>Developmental Biology</subject><subject>Life Sciences</subject><subject>Molecular Medicine</subject><subject>Original Article</subject><issn>1573-3882</issn><issn>1573-3890</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kM1Kw0AUhYMoWKsP4G7AjS6id2aSScadlGqFFoXa9TBJbkrK5MeZpNCufAff0CcxJSJuXN3LueccuJ_nXVK4pQDRnaOUg_CBCp_2gr8_8kY0jLjPYwnHv3vMTr0z5zYAQSAjGHnbBbY6qU1dFqkjutJm5wpH6pzUhSGNNiW5nhqNvbbuigqx6s83xKDO7wlutel0W9TVIeB02RgkjcVG20F1LTaOdK6o1mQ1e51Pvj4-F8u7xfLcO8m1cXjxM8fe6nH6Npn585en58nD3E85Fa2fJaHElMk4gzARYU5FCBDnOWVxhoxFYQ5cMAGJiNNAY4KJBMnDLAYuE8oZH3tXQ29j6_cOXas2dWf7L52iMZVChFEgexcdXKmtnbOYq8YWpbY7RUEd8KoBr-rxqgNete8zbMi43lut0f5p_jf0Ddcxfn8</recordid><startdate>20161001</startdate><enddate>20161001</enddate><creator>Vargas, Luiz Henrique Galli</creator><creator>Neto, Jorge Candido Rodrigues</creator><creator>de Aquino Ribeiro, José Antônio</creator><creator>Ricci-Silva, Maria Esther</creator><creator>Souza, Manoel Teixeira</creator><creator>Rodrigues, Clenilson Martins</creator><creator>de Oliveira, Anselmo Elcana</creator><creator>Abdelnur, Patrícia Verardi</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20161001</creationdate><title>Metabolomics analysis of oil palm (Elaeis guineensis) leaf: evaluation of sample preparation steps using UHPLC–MS/MS</title><author>Vargas, Luiz Henrique Galli ; Neto, Jorge Candido Rodrigues ; de Aquino Ribeiro, José Antônio ; Ricci-Silva, Maria Esther ; Souza, Manoel Teixeira ; Rodrigues, Clenilson Martins ; de Oliveira, Anselmo Elcana ; Abdelnur, Patrícia Verardi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-db59ec298d05b65f165008ff128de2275f036260b68c4aebeb90935d8039b1323</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Biochemistry</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Cell Biology</topic><topic>Developmental Biology</topic><topic>Life Sciences</topic><topic>Molecular Medicine</topic><topic>Original Article</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vargas, Luiz Henrique Galli</creatorcontrib><creatorcontrib>Neto, Jorge Candido Rodrigues</creatorcontrib><creatorcontrib>de Aquino Ribeiro, José Antônio</creatorcontrib><creatorcontrib>Ricci-Silva, Maria Esther</creatorcontrib><creatorcontrib>Souza, Manoel Teixeira</creatorcontrib><creatorcontrib>Rodrigues, Clenilson Martins</creatorcontrib><creatorcontrib>de Oliveira, Anselmo Elcana</creatorcontrib><creatorcontrib>Abdelnur, Patrícia Verardi</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Biological Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Metabolomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vargas, Luiz Henrique Galli</au><au>Neto, Jorge Candido Rodrigues</au><au>de Aquino Ribeiro, José Antônio</au><au>Ricci-Silva, Maria Esther</au><au>Souza, Manoel Teixeira</au><au>Rodrigues, Clenilson Martins</au><au>de Oliveira, Anselmo Elcana</au><au>Abdelnur, Patrícia Verardi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Metabolomics analysis of oil palm (Elaeis guineensis) leaf: evaluation of sample preparation steps using UHPLC–MS/MS</atitle><jtitle>Metabolomics</jtitle><stitle>Metabolomics</stitle><date>2016-10-01</date><risdate>2016</risdate><volume>12</volume><issue>10</issue><spage>1</spage><pages>1-</pages><artnum>153</artnum><issn>1573-3882</issn><eissn>1573-3890</eissn><abstract>Introduction
Metabolomics analysis of oil palm leaves is a promising strategy to prospect new added-value compounds of this underutilized oil industry by-product. Although previous studies had reported some metabolites identified in this matrix, they had been focused on few compounds using conventional analytical techniques.
Objectives
This study aimed to develop a new high throughput method based on metabolomics able to detect a wide range of metabolites classes in
Elaeis guineensis
leaves. Furthermore, we investigate the effects caused by harvesting/sample preparation steps for the metabolites identification.
Method
Metabolites analyses were performed by ultra-high liquid chromatography—mass spectrometry (UHPLC–MS) using both ionization modes, ESI(+)–MS and ESI(−)–MS. ANOVA simultaneous component analysis (ASCA) of the resulting complex multivariate dataset was applied to evaluate metabolic alterations. Identification of major metabolites was performed by high resolution mass spectrometry and MS/MS experiments.
Result
A high throughput method based on UHPLC–MS was successfully developed to
E. guineensis
leaves, detecting from polar to non-polar acid and basic metabolites. According to ASCA, oil palm leaves metabolic fingerprintings have shown influence of transportation/storage and extraction solvent used chosen. In fact, the most significant effect is due to the solvent composition. A total of thirteen metabolites were assigned based on HRMS and MS/MS experiments. However, only seven metabolites identified were previously reported, which represents a potential field to discover new metabolites.
Conclusion
Sample preparation steps should be carefully performed in metabolomics studies, because metabolites will be extracted and identified based on transport and solvent of extraction conditions. In this study, we established a reliable analytical protocol, from sample preparation to data analyses, to prospect new metabolites in oil palm leaves. This protocol could be further applied to similar oil-bearing crops.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11306-016-1100-z</doi></addata></record> |
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subjects | Biochemistry Biomedical and Life Sciences Biomedicine Cell Biology Developmental Biology Life Sciences Molecular Medicine Original Article |
title | Metabolomics analysis of oil palm (Elaeis guineensis) leaf: evaluation of sample preparation steps using UHPLC–MS/MS |
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