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Comparative metabolite profiling and fingerprinting of genus Passiflora leaves using a multiplex approach of UPLC-MS and NMR analyzed by chemometric tools

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Abstract

Passiflora incarnata as well as some other Passiflora species are reported to possess anxiolytic and sedative activity and to treat various CNS disorders. The medicinal use of only a few Passiflora species has been scientifically verified. There are over 400 species in the Passiflora genus worldwide, most of which have been little characterized in terms of phytochemical or pharmacological properties. Herein, large-scale multi-targeted metabolic profiling and fingerprinting techniques were utilized to help gain a broader insight into Passiflora species leaves’ chemical composition. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) spectra of extracted components derived from 17 Passiflora accessions and from different geographical origins were analyzed using multivariate data analyses. A total of 78 metabolites were tentatively identified, that is, 20 C-flavonoids, 8 O-flavonoids, 21 C, O-flavonoids, 2 cyanogenic glycosides, and 23 fatty acid conjugates, of which several flavonoid conjugates are for the first time to be reported in Passiflora spp. To the best of our knowledge, this study provides the most complete map for secondary metabolite distribution within that genus. Major signals in 1H-NMR and MS spectra contributing to species discrimination were assigned to those of C-flavonoids including isovitexin-2″-O-xyloside, luteolin-C-deoxyhexoside-O-hexoside, schaftoside, isovitexin, and isoorientin. P. incarnata was found most enriched in C-flavonoids, justifying its use as an official drug within that genus. Compared to NMR, LC-MS was found more effective in sample classification based on genetic and/ or geographical origin as revealed from derived multivariate data analyses. Novel insight on metabolite candidates to mediate for Passiflora CNS sedative effects is also presented.

A comparative NMR and MS spectra of extracted components derived from 17 Passiflora accessions to be analyzed using multivariate data analyses for species classification.

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Acknowledgments

This work was supported by the Alexander von Humboldt-Foundation, Germany to Dr. Mohamed Farag and Prof. Dr. Ludger Wessjohann. Dr. Mohamed Ali Farag acknowledges the funding received by Science and Technology Development fund STDF, Egypt (grant number 12594). Prof. Dr. Ludger Wessjohann and Dr. Andrea Porzel acknowledge partial support from Leibniz-Wettbewerb SAW-2015-IPB-2.

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Authors and Affiliations

  1. Pharmacognosy Department, College of Pharmacy, Cairo University, Kasr el Aini St., Cairo, P.B. 11562, Egypt

    Mohamed A. Farag, Asmaa Otify, Camilia George Michel & Aly Elsayed

  2. Department of Bioorganic Chemistry, Leibniz Institute of Plant Biochemistry, Weinberg 3, 06120, Halle (Saale), Germany

    Andrea Porzel & Ludger A. Wessjohann

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  1. Mohamed A. Farag
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  2. Asmaa Otify
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Correspondence to Mohamed A. Farag.

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Farag, M.A., Otify, A., Porzel, A. et al. Comparative metabolite profiling and fingerprinting of genus Passiflora leaves using a multiplex approach of UPLC-MS and NMR analyzed by chemometric tools. Anal Bioanal Chem 408, 3125–3143 (2016). https://doi.org/10.1007/s00216-016-9376-4

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