UPLC-UV-MS(E) analysis for quantification and identification of major carotenoid and chlorophyll species in algae.

TitleUPLC-UV-MS(E) analysis for quantification and identification of major carotenoid and chlorophyll species in algae.
Publication TypeJournal Article
Year of Publication2012
AuthorsFu W, Magnúsdóttir M, Brynjólfson S, Palsson BO, Paglia G
JournalAnal Bioanal Chem
Volume404
Issue10
Pagination3145-54
PubMed Date2012-10-12
ISSN1618-2650
Abstract

A fast method for quantification and identification of carotenoid and chlorophyll species utilizing liquid chromatography coupled with UV detection and mass spectrometry has been demonstrated and validated for the analysis of algae samples. This method allows quantification of targeted pigments and identification of unexpected compounds, providing isomers separation, UV detection, accurate mass measurements, and study of fragment ions for structural elucidation in a single run. This is possible using parallel alternating low- and high-energy collision spectral acquisition modes, which provide accurate mass full scan chromatograms and accurate mass high-energy chromatograms. Here, it is shown how this approach can be used to confirm carotenoid and chlorophyll species by identification of key diagnostic fragmentations during high-energy mode. The developed method was successfully applied for the analysis of Dunaliella salina samples during defined red LED lighting growth conditions, identifying 37 pigments including 19 carotenoid species and 18 chlorophyll species, and providing quantification of 7 targeted compounds. Limit of detections for targeted pigments ranged from 0.01 ng/mL for lutein to 0.24 ng/mL for chlorophyll a. Inter-run precision ranged for of 3 to 24 (RSD%) while inter-run inaccuracy ranged from -17 to 11.

Alternate JournalAnal Bioanal Chem
PubMed ID23052878

Location

Location

417 Powell-Focht Bioengineering Hall

9500 Gilman Drive La Jolla, CA 92093-0412

Contact Us

Contact Us

In Silico Lab:  858-822-1144

Wet Lab:  858-246-1625

FAX:   858-822-3120

Website Concerns: sbrgit@ucsd.edu

User Login