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. 2014 Feb 7;13(2):555-69.
doi: 10.1021/pr400731p. Epub 2013 Dec 6.

iTRAQ-based quantitative proteomics of developing and ripening muscadine grape berry

Affiliations

iTRAQ-based quantitative proteomics of developing and ripening muscadine grape berry

Devaiah Kambiranda et al. J Proteome Res. .

Abstract

Grapes are among the widely cultivated fruit crops in the world. Grape berries like other nonclimacteric fruits undergo a complex set of dynamic, physical, physiological, and biochemical changes during ripening. Muscadine grapes are widely cultivated in the southern United States for fresh fruit and wine. To date, changes in the metabolites composition of muscadine grapes have been well documented; however, the molecular changes during berry development and ripening are not fully known. The aim of this study was to investigate changes in the berry proteome during ripening in muscadine grape cv. Noble. Isobaric tags for relative and absolute quantification (iTRAQ) MS/MS was used to detect statistically significant changes in the berry proteome. A total of 674 proteins were detected, and 76 were differentially expressed across four time points in muscadine berry. Proteins obtained were further analyzed to provide information about its potential functions during ripening. Several proteins involved in abiotic and biotic stimuli and sucrose and hexose metabolism were upregulated during berry ripening. Quantitative real-time PCR analysis validated the protein expression results for nine proteins. Identification of vicilin-like antimicrobial peptides indicates additional disease tolerance proteins are present in muscadines for berry protection during ripening. The results provide new information for characterization and understanding muscadine berry proteome and grape ripening.

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Figures

Figure 1
Figure 1
Sampling dates were based the Brix content, size, fresh weight, anthocyanin content, and titratable acidity of the berry. Clusters were tagged from four different vines. Individual berries representing each stage from same vine served as one biological replicate.
Figure 2
Figure 2
Changes in fresh weight (blue diamonds), concentration of soluble solids (green triangles), anthocyanin content (red squares), and texture measurement (blue X’s) of Noble berries sampled at different developmental stages. GH-green hard; GS-green soft; PS-pink soft; and ripe.
Figure 3
Figure 3
iTRAQ 8-plex workflow labeling of different stages of muscadine berry with iTRAQ 8-plex isobaric tags.
Figure 4
Figure 4
Venn diagram showing proteins identified with two peptide match among both the data sets and common proteins among both iTRAQ data sets.
Figure 5
Figure 5
Cluster analyses of proteins significantly up- and downregulated among four replications. Four clusters were generated to classify proteins during four time points: GH (green hard), GS (green soft), PS (pink soft), and ripe.
Figure 6
Figure 6
GO term enriched broader functional classification of the 76 differentially expressed proteins during development and ripening of muscadine berry.
Figure 7
Figure 7
Cluster profiles of protein functional clusters during muscadine grape berry ripening. A heat map of the log 2 relative abundance of proteins throughout ripening in relation to the green hard stage was created using Genesis v1.7 with the iTRAQ-derived quantitative data. For each protein, an abbreviation, the Uniprot accession number, and the sequence description assigned with Blast2GO are provided. Proteins were grouped according to their known or putative role in metabolic pathways or cellular process.
Figure 8
Figure 8
Relative expression levels of transcripts. Data were normalized against expression of the housekeeping gene ubiquitin. To determine relative fold differences for each gene in each experiment, the Ct value of the genes was normalized to the Ct value for ubiquitin (control gene), and relative expression was calculated relative to a calibrator using the formula 2−ΔΔCt. All the values shown are mean ± SE.
Figure 8
Figure 8
Relative expression levels of transcripts. Data were normalized against expression of the housekeeping gene ubiquitin. To determine relative fold differences for each gene in each experiment, the Ct value of the genes was normalized to the Ct value for ubiquitin (control gene), and relative expression was calculated relative to a calibrator using the formula 2−ΔΔCt. All the values shown are mean ± SE.

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