Polyphenols are a broad class of plant secondary metabolites which carry out several biological functions for plant growth and protection and are of great interest as nutraceuticals for their antioxidant properties. However, due to their structural variability and complexity, the mass-spectrometric analysis of polyphenol content in plant matrices is still an issue. In this work, a novel approach for the identification of several classes of polyphenol derivatives based on ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry was developed. First, mass-spectrometric parameters were optimized in order to obtain a large set of diagnostic product ions for their high-confidence identification. The software Compound Discoverer 3.0 was then implemented with a comprehensive database of 45,567 polyphenol derivatives and with mass-spectrometric data for their building blocks, resulting in a specific tool for the semi-automatic identification of flavonoids, anthocyanins, ellagitannins, proanthocyanidins and phenolic acids. The method was then applied to the identification of polyphenols in industrial hemp (Cannabis sativa), a matrix whose use is recently spreading for pharmaceutical and nutraceutical purposes, resulting in the identification of 147 compounds belonging to the classes of flavonoids, proanthocyanidins and phenolic acids. The proposed method is applicable to the polyphenol profiling of any plant matrix and it is not dependent on data in the literature for their identification, allowing the discovery of compounds which have been never identified before.

A new software-assisted analytical workflow based on high-resolution mass spectrometry for the systematic study of phenolic compounds in complex matrices / Cerrato, A.; Cannazza, G.; Capriotti, A. L.; Citti, C.; La Barbera, G.; Lagana, A.; Montone, C. M.; Piovesana, S.; Cavaliere, C.. - In: TALANTA. - ISSN 0039-9140. - 209:(2020), pp. 120573-120573. [10.1016/j.talanta.2019.120573]

A new software-assisted analytical workflow based on high-resolution mass spectrometry for the systematic study of phenolic compounds in complex matrices

Cannazza G.;Citti C.;
2020

Abstract

Polyphenols are a broad class of plant secondary metabolites which carry out several biological functions for plant growth and protection and are of great interest as nutraceuticals for their antioxidant properties. However, due to their structural variability and complexity, the mass-spectrometric analysis of polyphenol content in plant matrices is still an issue. In this work, a novel approach for the identification of several classes of polyphenol derivatives based on ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry was developed. First, mass-spectrometric parameters were optimized in order to obtain a large set of diagnostic product ions for their high-confidence identification. The software Compound Discoverer 3.0 was then implemented with a comprehensive database of 45,567 polyphenol derivatives and with mass-spectrometric data for their building blocks, resulting in a specific tool for the semi-automatic identification of flavonoids, anthocyanins, ellagitannins, proanthocyanidins and phenolic acids. The method was then applied to the identification of polyphenols in industrial hemp (Cannabis sativa), a matrix whose use is recently spreading for pharmaceutical and nutraceutical purposes, resulting in the identification of 147 compounds belonging to the classes of flavonoids, proanthocyanidins and phenolic acids. The proposed method is applicable to the polyphenol profiling of any plant matrix and it is not dependent on data in the literature for their identification, allowing the discovery of compounds which have been never identified before.
2020
18-nov-2019
209
120573
120573
A new software-assisted analytical workflow based on high-resolution mass spectrometry for the systematic study of phenolic compounds in complex matrices / Cerrato, A.; Cannazza, G.; Capriotti, A. L.; Citti, C.; La Barbera, G.; Lagana, A.; Montone, C. M.; Piovesana, S.; Cavaliere, C.. - In: TALANTA. - ISSN 0039-9140. - 209:(2020), pp. 120573-120573. [10.1016/j.talanta.2019.120573]
Cerrato, A.; Cannazza, G.; Capriotti, A. L.; Citti, C.; La Barbera, G.; Lagana, A.; Montone, C. M.; Piovesana, S.; Cavaliere, C.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1190196
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