Open Access
Journal of Advanced Research, volume 24, pages 545-555
Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects
1
Phytochemistry and Plant Systematics Department, Division of Pharmaceutical Industries, National Research Centre, PO Box 12622, Cairo, Egypt.
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2
Biochemistry Department, Faculty of Pharmacy, Sinai University-Kantara Branch, El Ismailia, 41611, Egypt.
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Publication type: Journal Article
Publication date: 2020-07-01
Journal:
Journal of Advanced Research
Quartile SCImago
Q1
Quartile WOS
Q1
Impact factor: 10.7
ISSN: 20901232
PubMed ID:
32637174
Multidisciplinary
Abstract
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.
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- We do not take into account publications that without a DOI.
- Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
- Statistics recalculated weekly.
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Hegazi N. M. et al. Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects // Journal of Advanced Research. 2020. Vol. 24. pp. 545-555.
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Hegazi N. M., Radwan R. A., Bakry S. M., Saad H. H. Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects // Journal of Advanced Research. 2020. Vol. 24. pp. 545-555.
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TY - JOUR
DO - 10.1016/j.jare.2020.06.001
UR - https://doi.org/10.1016%2Fj.jare.2020.06.001
TI - Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects
T2 - Journal of Advanced Research
AU - Hegazi, Nesrine M
AU - Radwan, Rasha A
AU - Bakry, Sherein M
AU - Saad, Hamada H
PY - 2020
DA - 2020/07/01 00:00:00
PB - Cairo University
SP - 545-555
VL - 24
PMID - 32637174
SN - 2090-1232
ER -
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@article{2020_Hegazi
author = {Nesrine M Hegazi and Rasha A Radwan and Sherein M Bakry and Hamada H Saad},
title = {Molecular networking aided metabolomic profiling of beet leaves using three extraction solvents and in relation to its anti-obesity effects},
journal = {Journal of Advanced Research},
year = {2020},
volume = {24},
publisher = {Cairo University},
month = {jul},
url = {https://doi.org/10.1016%2Fj.jare.2020.06.001},
pages = {545--555},
doi = {10.1016/j.jare.2020.06.001}
}