Exploratory optimisation of a LC-HRMS based analytical method for untargeted metabolomic screening of Cannabis Sativa L. through Data Mining.
Cannabis sativa L.
Data mining
Experimental factors
LC-HRMS
Metabolomic coverage
Plant metabolomics
Journal
Analytica chimica acta
ISSN: 1873-4324
Titre abrégé: Anal Chim Acta
Pays: Netherlands
ID NLM: 0370534
Informations de publication
Date de publication:
23 Oct 2023
23 Oct 2023
Historique:
received:
27
06
2023
revised:
22
09
2023
accepted:
23
09
2023
medline:
1
11
2023
pubmed:
13
10
2023
entrez:
12
10
2023
Statut:
ppublish
Résumé
Recent increase in public acceptance of cannabis as a natural medical alternative for certain neurological pathologies has led to its approval in different regions of the world. However, due to its previous illegal background, little research has been conducted around its biochemical insights. Therefore, in the current framework, metabolomics may be a suitable approach for deepening the knowledge around this plant species. Nevertheless, experimental methods in metabolomics must be carefully handled, as slight modifications can lead to metabolomic coverage loss. Hence, the main objective of this work was to optimise an analytical method for appropriate untargeted metabolomic screening of cannabis. We present an empirically optimised experimental procedure through which the broadest metabolomic coverage was obtained, in which extraction solvents for metabolite isolation, chromatographic columns for LC-qOrbitrap analysis and plant-representative biological tissues were compared. By exploratory means, it was determined that the solvent combination composed of CHCl It was concluded that the optimised experimental procedure could significantly ease the path for future research works related to cannabis metabolomics by LC-HRMS means, as the work was based on previous plant metabolomics literature. Furthermore, it is crucial to highlight that an optimal analytical method can vary depending on the main objective of the research, as changes in the experimental factors can lead to different outcomes, regardless of whether the results are better or worse.
Sections du résumé
BACKGROUND
BACKGROUND
Recent increase in public acceptance of cannabis as a natural medical alternative for certain neurological pathologies has led to its approval in different regions of the world. However, due to its previous illegal background, little research has been conducted around its biochemical insights. Therefore, in the current framework, metabolomics may be a suitable approach for deepening the knowledge around this plant species. Nevertheless, experimental methods in metabolomics must be carefully handled, as slight modifications can lead to metabolomic coverage loss. Hence, the main objective of this work was to optimise an analytical method for appropriate untargeted metabolomic screening of cannabis.
RESULTS
RESULTS
We present an empirically optimised experimental procedure through which the broadest metabolomic coverage was obtained, in which extraction solvents for metabolite isolation, chromatographic columns for LC-qOrbitrap analysis and plant-representative biological tissues were compared. By exploratory means, it was determined that the solvent combination composed of CHCl
SIGNIFICANCE
CONCLUSIONS
It was concluded that the optimised experimental procedure could significantly ease the path for future research works related to cannabis metabolomics by LC-HRMS means, as the work was based on previous plant metabolomics literature. Furthermore, it is crucial to highlight that an optimal analytical method can vary depending on the main objective of the research, as changes in the experimental factors can lead to different outcomes, regardless of whether the results are better or worse.
Identifiants
pubmed: 37827627
pii: S0003-2670(23)01069-3
doi: 10.1016/j.aca.2023.341848
pii:
doi:
Substances chimiques
Solvents
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
341848Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare no conflicts of interest.