Fruit Quality and Metabolomic Analyses of Fresh Food Accessions Provide Insights into the Key Carbohydrate Metabolism in Blueberry

Abstract

Blueberry is a nutrient-rich berry, and its taste and flavor directly determine the consumer preference. Until now, few studies have focused on the comparison of fresh food quality and the key metabolites in superior fresh-eating blueberry cultivars. Herein, fruit quality indicators of 10 highbush blueberry cultivars were evaluated using 'Bluerain' as the control. Appearance quality analysis of fruits showed that 'Brigitta' had a larger fruit size and 'Anna' was the smallest. 'Anna' fruits, followed by 'O'Neal', had the highest ratio of soluble solids to acidity because of their lowest titratable acidity content. Despite the high soluble sugar content, the antioxidants in 'Anna' fruits such as total flavonoids, anthocyanins and vitamin C were lowest among all cultivars, while 'Duke' seemed to have opposite patterns. Furthermore, a total of 553 and 557 metabolites were identified by non-targeted metabolomics liquid chromatography-tandem mass spectrometry (LC-MS/MS) in positive and negative ion mode, respectively. Particularly, the numbers of differentially accumulated metabolites (DAMs) were the most between the 'O'Neal' vs. 'Bluerain' group. The DAMs involved in the metabolic pathways, sesquiterpenoid and triterpenoid biosynthesis, monoterpenoid biosynthesis, galactose metabolism, starch and sucrose metabolism, may be mainly related to the synthesis of flavor and carbohydrate substances. Moreover, the expression patterns of genes involved in sugar metabolism were verified by quantitative real-time PCR (qRT-PCR) analysis in different cultivars. Therefore, the systematical comparison of the quality characteristics, metabolites and expression profiles of related genes in highbush blueberries with good flavor could provide some basis for further research on fresh fruit breeding of blueberries.

Keywords: LC-MS/MS; blueberry (Vaccinium corymbosum L.); flavor profile; fresh food quality; sugar metabolism.

Figure 1

Principal component analysis (PCA) score plot of 11 blueberry samples in positive (A) and negative (B) ion modes. Ann, ‘Anna’; Blu, ‘Bluerain’; Bri, ‘Brigitta’; Cam, ‘Camellia’; Dar, ‘Darrow’; Duk, ‘Duke’; Mis, ‘Misty’; ONe, ‘O’Neal’; QC, quality control; Spr, ‘Springhigh’; Sta, ‘Star’; Zho, ‘Zhongzhi 3’.

Figure 2

Pathway annotation and classification of metabolites in different databases of KEGG, HMDB and LIPID MAPS. (A) Metabolites annotated in the KEGG database in positive ion mode; (B) Metabolites in the KEGG database in negative ion mode; (C) Metabolites annotated in the HMDB database in positive ion mode; (D) Metabolites annotated in the HMDB database in negative ion mode; (E) Metabolites annotated in the LIPID MAPS database in positive ion mode; (F) Metabolites annotated in the LIPID MAPS database in positive ion mode. The bars in different color in (A,B) showed the category of metabolic pathways annotated in the KEGG database, and those in (E,F) showed the lipid category annotations in the LIPID MAPS database.

Figure 3

Classification map of metabolites of flavor substances (A) and acid substances (B).

Figure 4

Statistics of amounts of DAMs in positive (A) and negative (B) ion modes.

Figure 5

Violin plot of sugar substances dominantly accumulated in the blueberry cultivar ‘Anna’ (A), ‘O’Neal’ (B) and both cultivars (C).

Figure 6

The top 20 pathways by KEGG pathway enrichment analysis based on differentially accumulated metabolites. (A,B): Pathways in ONe vs. Blu in positive and negative mode, respectively; (C,D): Pathways in Ann vs. Blu in positive and negative mode, respectively; (E,F): Pathways in Duk vs. Blu in positive and negative mode, respectively.

Figure 7

Expression patterns of eight sugar accumulation genes in eleven blueberry cultivars. (A) VcBAM; (B) VcTMT; (C) VcSPS; (D) VcSPS1; (E) VcSS1; (F) VcINV; (G) VcNIN2; (H) VcINV9.