Characterization of the Proteome of Theobroma cacao Beans by Nano‐UHPLC‐ESI MS/MS. Issue 3 (2nd February 2018)

• Record Type: Journal Article
• Authors: Scollo, Emanuele; Neville, David; Oruna‐Concha, M. Jose; Trotin, Martine; Cramer, Rainer
• Is Part Of: Proteomics. Volume 18:Issue 3/4(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-02-02
• Subjects: cocoa beans -- cocoa bean proteome -- plant proteomics -- storage proteins -- Theobroma cacao; Proteins -- Separation -- Periodicals; Bioinformatics -- Periodicals; Proteomics -- Periodicals; Genomes -- Periodicals; Molecular genetics -- Periodicals; 572.605
• DOI: 10.1002/pmic.201700339
• Languages: English
• ISSNs: 1615-9853

Abstract

Abstract: Cocoa seed storage proteins play an important role in flavour development as aroma precursors are formed from their degradation during fermentation. Major proteins in the beans of Theobroma cacao are the storage proteins belonging to the vicilin and albumin classes. Although both these classes of proteins have been extensively characterized, there is still limited information on the expression and abundance of other proteins present in cocoa beans. This work is the first attempt to characterize the whole cocoa bean proteome by nano‐UHPLC‐ESI MS/MS analysis using tryptic digests of cocoa bean protein extracts. The results of this analysis show that >1000 proteins could be identified using a species‐specific Theobroma cacao database. The majority of the identified proteins were involved with metabolism and energy. Additionally, a significant number of the identified proteins were linked to protein synthesis and processing. Several proteins were also involved with plant response to stress conditions and defence. Albumin and vicilin storage proteins showed the highest intensity values among all detected proteins, although only seven entries were identified as storage proteins. A comparison of MS/MS data searches carried out against larger non‐specific databases confirmed that using a species‐specific database can increase the number of identified proteins, and at the same time reduce the number of false positives. The results of this work will be useful in developing tools that can allow the comparison of the proteomic profile of cocoa beans from different genotypes and geographic origins. Data are available via ProteomeXchange with identifier PXD005586.