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Molecules 2016-Jan

Insight of Saffron Proteome by Gel-Electrophoresis.

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Врската е зачувана во таблата со исечоци
Gianluca Paredi
Samanta Raboni
Francesco Marchesani
Stella A Ordoudi
Maria Z Tsimidou
Andrea Mozzarelli

Клучни зборови

Апстракт

Saffron is a spice comprised of the dried stigmas and styles of Crocus sativus L. flowers and, since it is very expensive, it is frequently adulterated. So far, proteomic tools have never been applied to characterize the proteome of saffron or identify possible cases of fraud. In this study, 1D-Gel Electrophoresis was carried out to characterize the protein profile of (i) fresh stigmas and styles of the plant; (ii) dried stigmas and styles from different geographical origins (Spanish, Italian, Greek and Iranian) that had been stored for various periods of time after their processing; and (iii) two common plant adulterants, dried petals of Carthamus tinctorius L. and dried fruits of Gardenia jasminoides Ellis. A selective protein extraction protocol was applied to avoid interference from colored saffron metabolites, such as crocins, during electrophoretic analyses of saffron. We succeeded in separating and assigning the molecular weights to more than 20 proteins. In spite of the unavailability of the genome of saffron, we were able to identify five proteins by Peptide Mass Fingerprinting: phosphoenolpyruvate carboxylase 3, heat shock cognate 70 KDa protein, crocetin glucosyltransferase 2, α-1,4-glucan-protein synthase and glyceraldehydes-3-phosphate dehydrogenase-2. Our findings indicate that (i) few bands are present in all saffron samples independently of origin and storage time, with amounts that significantly vary among samples and (ii) aging during saffron storage is associated with a reduction in the number of detectable bands, suggesting that proteases are still active. The protein pattern of saffron was quite distinct from those of two common adulterants, such as the dried petals of Carthamus tinctorius and the dried fruits of Gardenia jasminoides indicating that proteomic analyses could be exploited for detecting possible frauds.

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