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Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects
In the present study, the efficiency of three different solvents (H(2)O, acidified H(2)O, and 70% Methanol) for metabolites extraction from the leaves of sugar beet (Beta vulgaris subsp. vulgaris var. rubra) was investigated along with their inhibitory activity on pancreatic α-amylase and lipase for...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327829/ https://www.ncbi.nlm.nih.gov/pubmed/32637174 http://dx.doi.org/10.1016/j.jare.2020.06.001 |
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author | Hegazi, Nesrine M. Radwan, Rasha A. Bakry, Sherein M. Saad, Hamada H. |
author_facet | Hegazi, Nesrine M. Radwan, Rasha A. Bakry, Sherein M. Saad, Hamada H. |
author_sort | Hegazi, Nesrine M. |
collection | PubMed |
description | In the present study, the efficiency of three different solvents (H(2)O, acidified H(2)O, and 70% Methanol) for metabolites extraction from the leaves of sugar beet (Beta vulgaris subsp. vulgaris var. rubra) was investigated along with their inhibitory activity on pancreatic α-amylase and lipase for obesity management. The metabolic profile of the three extracts was analyzed by ultra-performance liquid chromatography (UPLC) coupled with electrospray ionization high-resolution mass spectrometric (ESI-HRMS-MS). Mass spectrometry-based molecular networking was employed to aid in metabolites annotation and for the visual investigation of the known metabolites and their analogues. The study led to the tentative identification of 45 metabolites including amino acids, purine derivatives, phenolic acids, flavonoids, fatty acids, and an alkaloid, articulating 24 compounds as a first time report from beet leaves along with 2 new putatively identified compounds: a flavone feruloyl conjugate (39) and a malonylated acacetin diglycoside (40). The three extracting systems exhibited comparable efficiency for pulling out the secondary metabolites from the beet leaves. The in vitro study supported this finding and demonstrated that the three extracts inhibited the activity of both pancreatic α-amylase and lipase enzymes with no significant difference observed regarding the percentage of the inhibition of the enzymes. Conclusively, the extraction protocol has a minimal effect on the anti-obesity properties of beet leaves. |
format | Online Article Text |
id | pubmed-7327829 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-73278292020-07-06 Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects Hegazi, Nesrine M. Radwan, Rasha A. Bakry, Sherein M. Saad, Hamada H. J Adv Res Article In the present study, the efficiency of three different solvents (H(2)O, acidified H(2)O, and 70% Methanol) for metabolites extraction from the leaves of sugar beet (Beta vulgaris subsp. vulgaris var. rubra) was investigated along with their inhibitory activity on pancreatic α-amylase and lipase for obesity management. The metabolic profile of the three extracts was analyzed by ultra-performance liquid chromatography (UPLC) coupled with electrospray ionization high-resolution mass spectrometric (ESI-HRMS-MS). Mass spectrometry-based molecular networking was employed to aid in metabolites annotation and for the visual investigation of the known metabolites and their analogues. The study led to the tentative identification of 45 metabolites including amino acids, purine derivatives, phenolic acids, flavonoids, fatty acids, and an alkaloid, articulating 24 compounds as a first time report from beet leaves along with 2 new putatively identified compounds: a flavone feruloyl conjugate (39) and a malonylated acacetin diglycoside (40). The three extracting systems exhibited comparable efficiency for pulling out the secondary metabolites from the beet leaves. The in vitro study supported this finding and demonstrated that the three extracts inhibited the activity of both pancreatic α-amylase and lipase enzymes with no significant difference observed regarding the percentage of the inhibition of the enzymes. Conclusively, the extraction protocol has a minimal effect on the anti-obesity properties of beet leaves. Elsevier 2020-06-03 /pmc/articles/PMC7327829/ /pubmed/32637174 http://dx.doi.org/10.1016/j.jare.2020.06.001 Text en © 2020 THE AUTHORS. Published by Elsevier BV on behalf of Cairo University. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Hegazi, Nesrine M. Radwan, Rasha A. Bakry, Sherein M. Saad, Hamada H. Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects |
title | Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects |
title_full | Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects |
title_fullStr | Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects |
title_full_unstemmed | Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects |
title_short | Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects |
title_sort | molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327829/ https://www.ncbi.nlm.nih.gov/pubmed/32637174 http://dx.doi.org/10.1016/j.jare.2020.06.001 |
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