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 (H₂O, acidified H₂O, 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.

Keywords: Beta vulgaris; Molecular networking; Pancreatic lipase; UPLC-HRMS-MS; α- amylase.