ARS | Publication request: An integrated high resolution mass spectrometric and informatics approach for the rapid identification of phenolics in plant extract

Submitted to: Journal of Chromatography A
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: February 23, 2011
Publication Date: May 20, 2011
Citation: Aldini, G., Regazzoni, L., Pedretti, A., Carini, M., Cho, S., Park, K., Yeum, K. 2011. An integrated high resolution mass spectrometric and informatics approach for the rapid identification of phenolics in plant extract. Journal of Chromatography A. DOI: 10.1016/j.chroma.2011.02.065.

Interpretive Summary: A combined approach with a highly sensitive analytical method (mass spectrometry) and data base searching for rapid identification of bioactive plant components is reported. The approach was firstly validated by using a mixture of bioactive plant component standards. The rapid and highly sensitive analytical method consists of the following steps 1) identification of molecular mass of each bioactive plant component using highly sensitive mass spectrometry, 2) searching the experimental molecular mass in a commercially available plant components data base, and 3) fragment the interested molecule using mass spectrometry/mass spectrometry and compare the experimental data with the data base. Using the newly developed method, various bioactive plant components in Angelica keiskei, a green leafy vegetable, were successfully identified.

Technical Abstract: An integrated approach based on high resolution MS analysis (orbitrap), database (db) searching and MS/MS fragmentation prediction for the rapid identification of plant phenols is reported. The approach was firstly validated by using a mixture of phenolic standards (phenolic acids, flavones, flavonols, flavanones, flavanols, isoflavones). In particular, the integrated approach consists of the following steps: (1) LC-ESI-MS/MS analysis in data dependent scan mode using an orbitrap mass analyzer (resolution 60,000; positive ion-mode, ESI source); (2) searching the experimental monoisotopic masses (tolerance 1 ppm) in plant phenols databases; (3) filtering the entries on the basis of the phenol class to which the unknown belongs, as determined on the basis of the UV spectrum. Final identification is achieved by matching the isotopic pattern and by MS/MS fragmentation studies. In particular, experimental MS/MS fragments are matched with those predicted by a commercially available software. The method was then successfully applied for the rapid identification of phenolics contained in an EtOH extract of Angelica keiskei.