Characterisation of polyphenols in tunisian olive with anticancer capacity using liquid chromatography coupled to mass spectrometry

  1. Taamalli, AMANI
Dirigida por:
  1. Alberto Fernández Gutiérrez Director
  2. David Arráez Román Codirector
  3. Antonio Segura Carretero Codirector

Universidad de defensa: Universidad de Granada

Fecha de defensa: 09 de julio de 2012

Tribunal:
  1. José Luis Vílchez Quero Presidente
  2. Natalia Navas Secretario/a
  3. Edwin N. Frankel Vocal
  4. Alessandra Bendini Vocal
  5. Gabriel Beltrán Maza Vocal
Departamento:
  1. QUÍMICA ANALÍTICA

Tipo: Tesis

Resumen

The olive fruit, its oil, and the leaves of the olive tree have a rich history of nutritional, medicinal, and ceremonial uses. A large number of scientific studies have suggested that these beneficial properties are related to the high level of antioxidants, particularly phenolic compounds, in this plant species. This explains the increasing interest focused on these compounds. The present doctoral thesis deals with the analysis of phenolic compounds in the main product and by-product of Tunisian olive, namely olive oil and olive leaves. The results are presented as two main sections according to the matrix used. The SECTION I is basically dedicated to the olive oil and is divided into three chapters: The chapter 1 includes a review on the polyphenols occurring in Tunisian olive products (olive fruit and olive oil) and some by-products (olive leaves and olive-mill wastewater). The various methods used for the analysis as well as the bioactive properties of these compounds reported in recent years are described. The chapter 2 concerns the characterisation of extra-virgin olive oils from the two main Tunisian varieties and another four varieties grown in restricted geographical zones. The aim is to explore their phenolic profile and improve the potential of the secondary varieties under study. The phenolic compounds, determined using high-performance liquid chromatography coupled with electrospray time-of-flight mass spectrometry (HPLC-ESI-TOF-MS), showed significant variation among the six varieties. The parameters studied were analysed chemometrically to discriminate among the cultivars. In this sense, the principal-component analysis (PCA) showed that variables such as oleic, linoleic, quinic and vanillic acids, apigenin, luteolin, taxifolin, oleuropein aglycon, pinoresinol acetate, elenolic acid, and oxidative stability discriminate the different varieties of extra-virgin olive oil studied. The agglomerative hierarchical clustering results agreed with those found by PCA. Moreover, linear discriminant analysis (LDA) enabled the classification of the oil samples according to their geographical origin. In the chapter 3, the behaviour of the phenolic profile of extra-virgin olive oils from 13 accessions belonging to the variety ¿Chemlali¿ was studied according to the production zone. The phenolic-profile data gained using HPLC¿ESI-TOF¿MS were used for oil classification by geographical area. The production area has significantly influenced the phenolic composition of the ¿Chemlali¿ olive-oil variety, oils produced from ¿Oueslatia¿, ¿Ain Zena¿, ¿Siliana¿ and ¿Bir Ali Ben Khelifa¿, among others, being the richest in polyphenols. A discriminant analysis model gave a correct classification pathway with 100% of the correct predicted membership by selecting only 13 compounds (oleuropein aglycon, 10-hydroxy-oleuropein aglycon, hydroxy-elenolic acid, elenolic acid, ligstroside aglycon, decarboxylated oleuropein aglycon, hydroxy- decarboxylated oleuropein aglycon, decarboxylated ligstroside aglycon, ferulic acid, coumaric acid, quinic acid, and luteolin). The SECTION II is dedicated to olive leaves and is divided into three chapters: The chapter 4 describes the optimisation of a microwave-assisted extraction (MAE) method for the extraction of phenolic compounds from olive leaves and their analysis using a combination of HPLC coupled to ESI-TOF¿MS and electrospray ion trap tandem mass spectrometry (ESI-IT-MS2). The experimental variables that affect the MAE process, such as the solvent type and composition, microwave temperature, and extraction time, were optimised using a univariate method. The optimised MAE method combined with HPLC-ESI-TOF-MS and HPLC-ESI-IT-MS2 enabled the identification of a large number of phenolic compounds. Thus the proposed procedure proved useful as an alternative extraction method for characterising phenolic compounds from olive leaves, due to its efficiency, speed, and automatisation. The chapter 5 includes the comparison of advanced extraction techniques such as microwave-assisted extraction (MAE), supercritical fluid extraction (SFE) and pressurised liquid extraction (PLE), together with the traditional solid-liquid extraction to test their efficiency towards the extraction of phenolic compounds from olive leaves. Moreover, the cytotoxic capacity of different olive-leaf extracts against JIMT-1 breast-cancer-cell line was assayed. The phenolic profile analysed using a HPLC coupled to ESI-TOF-MS and ESI-IT-MS2 proved to be influenced by the olive variety and the extraction method used, mainly by the solvent employed. Among the different extraction methods, the largest number of phenolic compounds was identified by MAE. The cytotoxic capacity of the extracts, realised through the MTT assay, showed that the SFE extract derived from ¿El Hor¿ variety was the most potent. And the chapter 6 concerns the characterisation of phenolic compounds and their metabolites in the cytoplasm of JIMT-1 human breast-cancer cells treated with olive-leaf extracts. In this chapter, the metabolomic study was focused on ¿El Hor¿ olive-leaf extract obtained by SFE that showed the highest cytotoxicity for cancer cells (according to the results described in the previous chapter). The metabolites were characterised using HPLC-TOF-MS and the data obtained were analysed through a comparison of the control and treated cell cytoplasm profiles to find possible candidates. So far, three flavonoids such as luteolin, apigenin and diosmetin could have been identified.