Poster Presentation 24th Annual Lorne Proteomics Symposium 2019

Flavonoid annotation using a product ion-dependent MSn data acquisition method on a Tribrid Orbitrap mass spectrometer (#98)

Amanda Souza 1 , Reiko Kiyonami 1 , Iwao Sakane 2 , Seema Sharma 1 , Graeme McAlister 1 , Caroline Ding 1 , Andreas Huhmer 1
  1. Thermo Fisher Scientific, San Jose, California, United States
  2. ITO EN, LTD, Tokyo, Japan


Flavonoid annotation from natural products remains challenging because of their structural diversity and lack of authentic standards. Simple MS2 based analyses are often not sufficient for complete structural annotation of flavonoids. We present a new flavonoid annotation workflow that uses comprehensive fragment ion information from HCD MS-MS and higher order FTMSn for rapid flavonoid annotation.


Flavonoid extracts from different types of natural products were analyzed using LC-MS. A Thermo Scientific™ Orbitrap ID-X™ Tribrid™ mass spectrometer was used for collecting HRAM MS and MSn data. The data were processed using Compound Discoverer™ 3.0 software. A novel structure ranking algorithm, mzLogic, was applied to the MS and MSn data for confident structure elucidation of the unknown flavonoids.



The flavonoid extracts from multiple tea and fruit/vegetable juice samples were analyzed using the developed flavonoid annotation workflow. The MSn (up to 5) scans were only triggered when one of the sugar neutral loss product ions (162.0523, 180.0628, 146.0574, 164.0685, 176.0315, and 194.0421) was detected in the MS/MS scan. The collected data were processed using Mass Frontier 8.0 and Compound Discoverer 3.0 software. A novel structure ranking algorithm included in the Compound Discoverer 3.0 software was applied to the MS-MS and MSn data for confident structure characterization of the unknown flavonoids based on ChemSpider database and custom flavonoids database. The MSn data were critical, especially for the annotation of flavonoid glycoconjugates and flavonoid isomers.



The new LC-MSn workflow allows intelligent MS/MS fragment ion dependent MSn data collection. In combination with dedicated software for data processing, the new workflow enables improved throughput, identification coverage and confidence for flavonoids annotation from natural products by using comprehensive fragment ion information from HCD MS-MS and higher order FTMSn.