A comprehensive comparison of four methods for extracting lipids from Arabidopsis tissues.

Arabidopsis HPLC LC–MS Lipid extraction methods Lipids Mass spectrometry QTOF Untargeted lipid analysis

Journal

Plant methods
ISSN: 1746-4811
Titre abrégé: Plant Methods
Pays: England
ID NLM: 101245798

Informations de publication

Date de publication:
03 Dec 2020
Historique:
received: 10 07 2020
accepted: 24 11 2020
entrez: 9 12 2020
pubmed: 10 12 2020
medline: 10 12 2020
Statut: epublish

Résumé

The plant lipidome is highly complex, and the composition of lipids in different tissues as well as their specific functions in plant development, growth and stress responses have yet to be fully elucidated. To do this, efficient lipid extraction protocols which deliver target compounds in solution at concentrations adequate for subsequent detection, quantitation and analysis through spectroscopic methods are required. To date, numerous methods are used to extract lipids from plant tissues. However, a comprehensive analysis of the efficiency and reproducibility of these methods to extract multiple lipid classes from diverse tissues of a plant has not been undertaken. In this study, we report the comparison of four different lipid extraction procedures in order to determine the most effective lipid extraction protocol to extract lipids from different tissues of the model plant Arabidopsis thaliana. While particular methods were best suited to extract different lipid classes from diverse Arabidopsis tissues, overall a single-step extraction method with a 24 h extraction period, which uses a mixture of chloroform, isopropanol, methanol and water, was the most efficient, reproducible and the least labor-intensive to extract a broad range of lipids for untargeted lipidomic analysis of Arabidopsis tissues. This method extracted a broad range of lipids from leaves, stems, siliques, roots, seeds, seedlings and flowers of Arabidopsis. In addition, appropriate methods for targeted lipid analysis of specific lipids from particular Arabidopsis tissues were also identified.

Sections du résumé

BACKGROUND BACKGROUND
The plant lipidome is highly complex, and the composition of lipids in different tissues as well as their specific functions in plant development, growth and stress responses have yet to be fully elucidated. To do this, efficient lipid extraction protocols which deliver target compounds in solution at concentrations adequate for subsequent detection, quantitation and analysis through spectroscopic methods are required. To date, numerous methods are used to extract lipids from plant tissues. However, a comprehensive analysis of the efficiency and reproducibility of these methods to extract multiple lipid classes from diverse tissues of a plant has not been undertaken.
RESULTS RESULTS
In this study, we report the comparison of four different lipid extraction procedures in order to determine the most effective lipid extraction protocol to extract lipids from different tissues of the model plant Arabidopsis thaliana.
CONCLUSION CONCLUSIONS
While particular methods were best suited to extract different lipid classes from diverse Arabidopsis tissues, overall a single-step extraction method with a 24 h extraction period, which uses a mixture of chloroform, isopropanol, methanol and water, was the most efficient, reproducible and the least labor-intensive to extract a broad range of lipids for untargeted lipidomic analysis of Arabidopsis tissues. This method extracted a broad range of lipids from leaves, stems, siliques, roots, seeds, seedlings and flowers of Arabidopsis. In addition, appropriate methods for targeted lipid analysis of specific lipids from particular Arabidopsis tissues were also identified.

Identifiants

pubmed: 33292337
doi: 10.1186/s13007-020-00697-z
pii: 10.1186/s13007-020-00697-z
pmc: PMC7713330
doi:

Types de publication

Journal Article

Langues

eng

Pagination

155

Subventions

Organisme : Australian Research Council Future Fellowship
ID : FT160100276
Organisme : Mizutani Foundation for Glycoscience
ID : 18-0237

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Auteurs

Cheka Kehelpannala (C)

School of BioSciences, The University of Melbourne, Melbourne, VIC, 3010, Australia. ckehelpannal@student.unimelb.edu.au.

Thusitha W T Rupasinghe (TWT)

School of BioSciences, The University of Melbourne, Melbourne, VIC, 3010, Australia.
Sciex, 2 Gilda Ct, Mulgrave, VIC, 3170, Australia.

Thomas Hennessy (T)

Agilent Technologies Australia Pty Ltd, 679 Springvale Road, Mulgrave, VIC, 3170, Australia.

David Bradley (D)

Agilent Technologies Australia Pty Ltd, 679 Springvale Road, Mulgrave, VIC, 3170, Australia.

Berit Ebert (B)

School of BioSciences, The University of Melbourne, Melbourne, VIC, 3010, Australia.

Ute Roessner (U)

School of BioSciences, The University of Melbourne, Melbourne, VIC, 3010, Australia.

Classifications MeSH