Literature DB >> 33076047

Profiling of the known-unknown Passiflora variant complement by liquid chromatography - Ion mobility - Mass spectrometry.

Michael McCullagh1, Jeff Goshawk2, David Eatough2, Russell J Mortishire-Smith2, Cintia Am Pereira3, Janete H Yariwake4, Johannes Pc Vissers2.   

Abstract

Liquid Chromatography - Ion Mobility - Mass Spectrometry (LC-IM-MS) was utilized for non-targeted screening analysis to understand the variance in the composition of Passiflora species. Multivariate analysis was employed to explore a chemometric processing strategy for IM based Passiflora variant differentation. This approach was applied to the comparative analyses of extracts of the medicinal plants Passiflora alata, Passiflora edulis, Passiflora incarnata and Passiflora caerulea. In total, 255 occurrences of IM-MS resolved coeluting marker isomers and isobaric species were detected, providing increased coverage and specificity of species component markers compared to conventional LC-MS. A large proportion of medical plant phytochemical analysis information often remains redundant in that it is not phenotypic specific. Here, generation of Passiflora variant 'known-unknown' libraries has been used to compare Passiflora species to investigate unique variant features. Investigations of predicted collision cross section have enabled comparison of an element of the 'known-unknown' IM isomeric complement to be performed, facilitating a reduction in the number of possible variant unique isomeric identifications. In combination with spectral interpretation, it has been possible to resassign isomeric 'known-unknowns' as 'knowns'. The strategies employed illustrates the potential to facilitate identification of medicinal plant phytochemical components.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Ion mobility mass spectrometry; LC-MS; Measured and predicted collision cross sections; Medicinal plant isomeric and isobaric flavonoids; Multivariate analysis; ‘Known-unknowns’

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Year:  2020        PMID: 33076047     DOI: 10.1016/j.talanta.2020.121311

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  3 in total

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  3 in total

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