Higher transcription levels in ascorbic acid biosynthetic and recycling genes were associated with higher ascorbic acid accumulation in blueberry

Food Chemistry 188 (2015) 399–405

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Higher transcription levels in ascorbic acid biosynthetic and recycling genes were associated with higher ascorbic acid accumulation in blueberry Fenghong Liu a,1, Lei Wang a,1, Liang Gu b, Wei Zhao c, Hongyan Su c,⇑, Xianhao Cheng c,⇑ a b c

College of Life Sciences, Ludong University, Yantai, Shandong 264025, PR China Institute of Pomology, Yantai Academy of Agricultural Sciences, Yantai, Shandong 264025, PR China College of Agriculture, Ludong University, Yantai, Shandong 264025, PR China

a r t i c l e

i n f o

Article history: Received 10 January 2015 Received in revised form 6 May 2015 Accepted 8 May 2015 Available online 8 May 2015 Keywords: Blueberry Fruit ripening Gene expression L-Ascorbic acid

a b s t r a c t In our preliminary study, the ripe fruits of two highbush blueberry (Vaccinium corymbosum L.) cultivars, cv ‘Berkeley’ and cv ‘Bluecrop’, were found to contain different levels of ascorbic acid. However, factors responsible for these differences are still unknown. In the present study, ascorbic acid content in fruits was compared with expression profiles of ascorbic acid biosynthetic and recycling genes between ‘Bluecrop’ and ‘Berkeley’ cultivars. The results indicated that the L-galactose pathway was the predominant route of ascorbic acid biosynthesis in blueberry fruits. Moreover, higher expression levels of the ascorbic acid biosynthetic genes GME, GGP, and GLDH, as well as the recycling genes MDHAR and DHAR, were associated with higher ascorbic acid content in ‘Bluecrop’ compared with ‘Berkeley’, which indicated that a higher efficiency ascorbic acid biosynthesis and regeneration was likely to be responsible for the higher ascorbic acid accumulation in ‘Bluecrop’. Ó 2015 Published by Elsevier Ltd.

1. Introduction L-Ascorbic acid (AsA), also called vitamin C, is present in various concentrations in nearly all fresh vegetables and fruits. AsA, which functions as an antioxidant and enzyme cofactor, plays a crucial role not only in the diverse biological processes of plants, but also in maintaining human health such as reducing risk of chronic diseases, promoting collagen formation and normal bone development, and assisting in cancer treatment (Olmos, Kiddle, Pellny, Kumar, & Foyer, 2006; Sarkar, Srivastava, & Dubey, 2009). Humans cannot synthesize their own AsA due to a lack of L-gulonolactone

oxidase. Thus, humans have to ingest these important vitamins regularly in their diet. AsA, along with flavonoids, polyphenolics and lipophilic antioxidants, is often used as an indicator of foodstuff nutritional value (Melino, Soole, & Ford, 2009; Naidu, 2003). Owing to its unique functions in normal plant development, as well as its benefits to human health, AsA biosynthesis and regulation in plant edible organs have received much attention in recent years. ⇑ Corresponding authors. E-mail addresses: [email protected] (H. Su), [email protected] (X. Cheng). 1 The two authors contributed equally to this work.

http://dx.doi.org/10.1016/j.foodchem.2015.05.036 0308-8146/Ó 2015 Published by Elsevier Ltd.

To date, much progress has been made toward understanding the biosynthesis of AsA in plants. As shown in Fig. 1, there are at least four AsA synthesis pathways proposed in plants to date, including L-galactose or Smirnoff-Wheeler (SW), L-glucose, D-galacturonic acid, and myo-inositol pathways (Li, Ma, Liang, Li, & Wang, 2010; Yang et al., 2011). Among them, L-galactose pathway is considered a main route of AsA biosynthesis in plants (Linster & Clarke, 2008). All of the genes encoding enzymes involved in this pathway have been characterized, including GDP-D-mannose pyrophosphorylase (GMP), GDP-D-mannose-30 ,50 -epimerase (GME), GDP-L-galactose phosphorylase (GGP), L-galactose-1-phosphate phosphatase (GPP), L-galactose

dehydrogenase (GDH) and L-galactono-1,4-lactone dehydrogenase (GLDH). The D-galacturonic acid pathway, a branch of the L-galactose pathway, which utilizes D-galacturonic acid for the synthesis of L-galactonic acid derivatives via D-galacturonate reductase (GalUR), also requires GLDH to produce AsA in the last step. However, information about how the L-galactose pathway cooperates with the three alternative pathways, in various tissues and physiological conditions, remains limited (Ishikawa, Dowdle, & Smirnoff, 2006; Li et al., 2010). When formed, AsA is not stable in vivo and can be oxidized to monodehydroascorbate (MDHA) and dehydroascorbate (DHA)

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L-galactose pathway

1 GDP-D-mannose

Galacturonic acid pathway

2

myo-inositol pathway myo-inositol

L-glucose GDP-L-galactose pathway

Cell wall polymers

3

Biosynthesis pathway

D-mannose-1-P

L-galactose-1-P GDP-L-gulose

4

L-galactonic acid

L-galactose 5 L-gulono-1, 4-lactone

L-galactono-1, 4-lactone 6

7, 8 10

2,3-diketogulonic acid

9

Monodehydroascorbate

Dehydroascorbate

Recycling system

L-ascorbic acid

Fig. 1. Possible schemes for AsA accumulation in plants (Li et al., 2010; Yang et al., 2011). Enzymes catalyzing the numbered reactions are: (1) GDP-D-mannose pyrophosphorylase (GMP); (2) GDP-D-mannose-30 ,50 -epimerase (GME); (3) GDP-L-galactose phosphorylase (GGP); (4) L-galactose-1-phosphate phosphatase (GPP); (5) L-galactose dehydrogenase (GDH); (6) L-galactono-1,4-lactone dehydrogenase (GLDH); (7) ascorbate oxidase (AO); (8) ascorbate peroxidase (APX); (9) monodehydroascorbate (MDHA); (10) dehydroascorbate (DHA).

through ascorbate oxidase (AO) and ascorbate peroxidase (APX). These oxidized forms can then be reduced to AsA by the monodehydroascorbate reductase (MDHAR) and dehydroascorbate reductase (DHAR), respectively. If DHA cannot be reduced back to AsA in time, it will easily undergo irreversible hydrolysis to 2,3-diketogulonic acid. Accumulation of AsA in plant tissues is controlled by an efficient balance between biosynthesis and recycling (Ishikawa et al., 2006; Yang et al., 2011). Fruit is an important source of AsA for humans. Data from AsA metabolism studies in some fruit species, such as kiwifruit, apple, peach, tomato, peach, and citrus, imply that AsA content in fruit can be modulated during development (Alhagdow et al., 2007; Badejo, Fujikawa, & Esaka, 2009; Bulley et al., 2009; Do Nascimento, Higuchi, Gomez, Oshiro, & Lajolo, 2005; Eltelib, Badejo, Fujikawa, & Esaka, 2011; Imai, Ban, Terakami, Yamamoto, & Moriguchi, 2009; Ioannidi et al., 2009; Li et al., 2010; Yang et al., 2011). However, the regulation mechanisms of AsA accumulation in fruits are far from elucidated. Characterization of synthesis pathways, along with the expression profiling of AsA biosynthesis and recycling related genes, could bring new insights into regulation mechanisms. Highbush blueberry (Vaccinium corymbosum L.) is one of the most economically important fruit crops in the world, especially in North American (Zifkin et al., 2012). In recent years, the planting area of highbush blueberry has increased in North China annually. Blueberry fruits have been the focus of much recent attention due to numerous reports of their positive effects on human health. These benefits are generally attributed to high levels of flavonoids, AsA, and mineral composition (Prior, Lazarus, Cao, Muccitelli, & Hammerstone, 2001; Rasmussen, Frederiksen, Struntze Krogholm, & Poulsen, 2005; Tan et al., 2014; Taverniti et al., 2014). However, compared with the considerable research focused on the flavonoid metabolism of blueberries, little information is

currently available on the mechanism controlling AsA levels in blueberries to date. In the present study, the AsA content, along with expression of genes that encode enzymes involved in AsA biosynthetic and recycling routes, were systematically compared between two cultivars, cv ‘Berkeley’ and cv ‘Bluecrop’, during fruit development. The ripe fruits of the two cultivars were found to contain different levels of AsA in our preliminary study. However, factors responsible for this difference are still unknown. To the best of our knowledge, this is the first report about the AsA metabolism of blueberry fruit. The results of the present study will provide new information toward understanding the mechanisms that regulates AsA accumulation in fruits, but also inform breeding programs focused on improving AsA content in fruits. 2. Materials and methods 2.1. Plant materials Two highbush blueberry cultivars, cv ‘Berkeley’ and cv ‘Bluecrop’, planted in an organic blueberry farm in Yantai, Shandong Province, China (37°310 N, 121°210 E) were used in this study. Six 6-year-old trees of each cultivar were selected and randomly divided into three groups, with two trees in each group. Since fruit set and ripening initiation of blueberry is asynchronous, the fruits were randomly harvested in batches during the harvest season in 2013 and 2014 and sorted into six stages by size and fruit color, according to the validated methods for blueberry fruit (Zifkin et al., 2012). The fruits at the same stage were mixed together as a sample, which were collected from the two trees belonging to the same group. The number of fruits from each tree was equal. Thus, each cultivar had three berry pools at each stage. Each sample was collected into a centrifugal tube and immediately frozen in liquid nitrogen and stored at 80 °C until use.

F. Liu et al. / Food Chemistry 188 (2015) 399–405

2.2. AsA content analysis Determination of AsA content was performed using high-performance liquid chromatography (HPLC) according to Sinelli, Spinardi, Di Egidio, Mignani, and Casiraghi (2008). Five grams of berries were homogenized in cold 6% (w/v) metaphosphoric acid and centrifuged at 4 °C. The supernatants were collected, and the pellet was washed with 6% cold metaphosphoric acid and centrifuged again. The supernatants were combined and 6% metaphosphoric acid was added to a final volume of 16 mL. After filtration through a 0.45 lm filter, the 10 lL sample was injected onto 4.6 mm  250 mm Inertsil ODS-3 column (GL Sciences, Tokyo, Japan) with 5 lm particle size. The column was run with 0.02 M orthophosphoric acid at a flow rate of 0.7 mL/min, and the AsA amount was calculated from absorbance at 245 nm. Data were acquired and processed using Hewlett Packard ChemStation software (Agilent Technologies). 2.3. RNA extraction and cDNA synthesis Five fruits from each berry pool were ground in liquid nitrogen and the modified CTAB method was used to extract RNA. Two micrograms of the total RNA were used to synthesize the first-strand cDNA using the PrimeScript First Strand cDNA Synthesis Kit (Takara, China). 2.4. Semi-quantitative RT-PCR and qRT-PCR analysis Except for MDHAR (GenBank ABY49995), the other nine objective genes of blueberry, including GMP, GME, GGP, GPP, GDH, GLDH, APX, AO, and DHAR are not available. Full or partial gene sequences from other plants, such as kiwifruit, acerola, citrus, and Arabidopsis, were downloaded from the National Center for Biotechnology Information (NCBI). Based on these sequences, degenerate primers were designed (Supplementary Table S1) and the nine objective genes were cloned from both cv ‘Berkeley’ and cv ‘Bluecrop’. Gene-specific primers were designed from these sequences of blueberry genes using the Primer 5 software (Supplementary Table S2). Primer specificity was confirmed by corresponding melting curves with a single sharp peak (Bio-Rad iCycler) or a single amplified fragment with the correct predicted length. To further verify the PCR results, the PCR fragments were inserted into the pGEM-T vector and sequenced. Semi-quantitative RT-PCR and real-time RT-PCR (qRT-PCR) was simultaneously performed to detect expression profiles of the above mentioned 10 genes. The blueberry GAPDH, as well as SAND, was selected as the reference genes according to Zifkin et al. (2012). For semi-quantitative RT-PCR, the reactions were performed under the condition, which consisted of a pre-denaturation at 94 °C for 3 min, 25–28 cycles of 94 °C for 30 s, 56 °C for 30 s and 72 °C for 15 s, and a final extension step at 72 °C for 10 min. The PCR products were separated in 1.3% agarose gel, stained with ethidium bromide and photographed using GelDoc XR System (Bio-Rad, USA). The relative amount of transcripts was counted using Quantity One 1-D analysis software (Bio-Rad, USA). For qRT-PCR, the reaction was performed in 25-lL volumes containing 10 lM of each primer (Supplementary Table S2), 50 ng of cDNA, and 12.5 lL of SYBR Premix Ex Taq II. The PCR amplification conditions included an initial heat-denaturing step at 95 °C for 3 min and then 40 cycles of 95 °C for 20 s, 56 °C for 20 s, and 72 °C for 20 s. Fluorescence was measured at the end of each cycle. A melting-curve analysis was performed by heating the PCR product from 55 to 95 °C. The expression data for these genes were presented as relative units after normalization to the reference genes, used as the internal control, using the 2DDCT method (Matamoros et al., 2006; Su et al., 2013). As we described above, each cultivar

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had three berry pools at each stage, and RNA were isolated from each pool and further used to synthesize cDNA, respectively. Thus, we performed the PCR triplicates represent three berry pools. The values for the mean expression and standard deviation (SD) were calculated from the results of three independent replicates. 2.5. Statistical analysis Statistical analyses were performed using SigmaPlot 11.0 and SPSS 13.0 software. Mean values ± SD of three replicates were reported, and significant differences were defined as P < 0.05 in Duncan’s analysis. 3. Results and discussion 3.1. Growth analysis of blueberry fruits Fruits from two commercial cultivars, cv ‘Berkeley’ and cv ‘Bluecrop’, were chosen for the present study. In local region, ‘Berkeley’ and ‘Bluecrop’ have similar harvest seasons, which start in the late April and continue until the middle July. Since fruit setting and ripening initiation are not synchronous in blueberries, fruits were harvested in batches during the harvest season and sorted into six developmental stages by fruit size and color (Fig. 2). From stage 1 to stage 3, the young fruits were hard and dark green, and differed primarily in size. While from stage 4 to stage 6, the enlarged light green fruits began to soften, and accumulate red then blue pigments. 3.2. Changes in AsA levels during blueberry fruit development AsA levels were measured by HPLC in fruit samples at the above six stages collected from ‘Berkeley’ and ‘Bluecrop’, respectively. The results indicated that AsA accumulation in ‘Bluecrop’ during fruit development was similar to that of ‘Berkeley’ (Fig. 3). The AsA contents of both cultivars peaked at stage 3, and then declined along with fruit ripening. In stage 3, 25–50% fruit skin has turned red, and the fruit weight and diameter have increased significantly. It was notable that the AsA content of ‘Bluecrop’ was just slightly higher than that of ‘Berkeley’ in stage 3. However, due to an obvious drop in ‘Berkeley’ fruit and a gradual decrease in ‘Bluecrop’ fruit in stage 4, ‘Bluecrop’ had a larger AsA content from stage 4 until fruit ripening. Since the samples of two cultivars were collected from the same local blueberry plantations, and their harvest time were basically consistent, it was speculated that the differences in the AsA profile between the two cultivars was primarily due to the variety. It has been clear that AsA accumulation might vary between species and even between genotypes for one given species. For instance, AsA content is reported to remain constant throughout the fruit ripening process in melon, bilberry and tomato varieties (cv. West Virginia 106) (Alhagdow et al., 2007; Cocetta et al., 2012). Another pattern, in which AsA concentration increases with fruit ripening and reaches a maximum level at the fully ripe stage, is observed in grape and tomato varieties (cv. Ailsa Craig) (Cruz-Rus, Amaya, Sanchez-Sevilla, Botella, & Valpuesta, 2011; Cruz-Rus, Botella, Valpuesta, & Gomez-Jimenez, 2010; Ioannidi et al., 2009). The opposite pattern is observed in apples, peaches, and kiwifruits, with AsA content decreasing during fruit development (Badejo et al., 2009; Eltelib et al., 2011; Imai et al., 2009; Li et al., 2009). In the present study, AsA accumulation patterns in the two blueberry cultivars, ‘Bluecrop’ and ‘Berkeley’, were consistent with the decreasing pattern. Abundant AsA in young fruit might be related to rapid cell growth and expansion (Eltelib et al., 2011).

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S1

S2

S3

S4

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A Berkeley

Bluecrop Fruit weight

1800

Fruit diameter

c

1600

Mean fruit fw (mg)

a

20

a

18

b b

16

d

1400

b

c

1200 1000

b

14 12

e

800

10

600 400 200

d

8

f

6

0

4 S1

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C 900 800

14 a

Fruit weight Fruit diameter

a a

700

b b

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10

d

500

12

c

8

400 e

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6

Mean fruit diameter (mm)

2000

Mean fruit diameter (mm) Mean fruit fw (mg)

B

f

100

4 S1

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S6

Fruit maturity stage

Fig. 2. Developmental stages of blueberry (cv ‘Berkeley’ and cv ‘Bluecrop’) fruit used for molecular analyses. (A) Whole fruit separated into six stages. (B) Mean fresh fruit weight (Fw) and diameter of ‘Berkeley’ throughout development. (C) Mean fresh fruit weight (Fw) and diameter of ‘Bluecrop’ throughout development. Data are means of at least three replicates and different letters indicate significant differences (Duncan’s test, P < 0.05).

Fruit T-AsA (mg•100g-1 FW)

9

a a

Berkeley Bluecrop

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7

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6 c

c

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4

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more and more organisms by directly downloading from public databases. However, only MDHAR of blueberry are available to date. Thus, the other 9 objective genes were obtained from blueberry fruits using homologous cloning techniques. The sequences of genes predicted to encode GMP, GME, GGP, GPP, GDH, GLDH, APX, AO, and DHAR were cloned from both ‘Bluecrop’ and ‘Berkeley’ for the first time. The sequences of the homologous genes from the two cultivars shared 99.1–100% identity. Annotations of these blueberry genes were substantiated by performing BLASTX searches of the NCBI reference sequence protein database. In all cases, the top hits were orthologs from Arabidopsis, apple (Malus domestica), kiwifruit (Actinidia deliciosa), cacao (Theobroma cacao) or sesame (Sesamum indicum), whose function had been previously reported (Table 1).

S6

Fig. 3. Changes in AsA accumulation during blueberry fruit development. Values are means of three replicates and different letters indicate significant differences (Duncan’s test, P < 0.05).

The two blueberry cultivars had different patterns from the bilberry reported in Cocetta et al. (2012). Blueberry and bilberry belong to the large genus Vaccinium, however blueberries are originally from North American, while bilberry is native to Lithuanian forests. Moreover, Burdulis et al. (2009) have found there are some differences in fruit metabolism between blueberry and bilberry when comparing the anthocyanin composition, antimicrobial and antioxidant activity. The present results also supported this finding. 3.3. Identification of genes for blueberry AsA biosynthesis and recycling To gain insight into the molecular mechanisms underlying the AsA content change with blueberry fruit development and ripening, genes involved in AsA biosynthesis and recycling were identified in blueberry fruits. With the completion of the genome project, it has become convenient to obtain gene or EST sequences from

3.4. Expression analyses of AsA biosynthetic genes during blueberry fruit development To study the transcriptional regulation of AsA biosynthesis in highbush blueberry, the expression of six key genes involved in the L-galactose pathway, including GMP, GME, GGP, GPP, GDH, and GLDH, was profiled over the six stages of development by combining semi-quantitative RT-PCR with the qRT-PCR technique. Because of broad physiological and cellular changes occurring during fruit development, GAPDH and SAND were selected as simultaneous reference genes. According to Zifkin et al. (2012), the average relative transcriptional abundance of GAPDH and SAND was the most constant and did not differ statistically across the berry developmental stages. As shown in Figs. 4 and S1, the qRT-PCR and semi-quantitative RT-PCR results were consistent, and both might confirm each other. Among the 6 genes, the expression patterns of 3 genes (GMP, GPP, and GDH) in ‘Bluecrop’ and ‘Berkeley’ were similar during fruit development. For instance, in both ‘Bluecrop’ and ‘Berkeley’, GMP maintained a high expression level throughout fruit development, and no significant changes were observed in

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F. Liu et al. / Food Chemistry 188 (2015) 399–405 Table 1 BLASTX analyses of the objective gene sequences from blueberry genes.

a b

Gene

REFSEQ Match

Accession No.

E value

IDa (%)

Region of ID

Covb

GMP GME GGP GPP GDH GLDH AO APX DHAR

GMP of Malus domestica GME of Arabidopsis thaliana GGP of Actinidia deliciosa GPP of Actinidia deliciosa GDH of Actinidia deliciosa GLDH of Actinidia deliciosa AO of Theobroma cacao APX of Theobroma cacao DHAR of Sesamum indicum

ACN88684 2C59A ADB85572 AAV49506 AAO18639 ADB85575 XP_007016684 ABR68691 ABB89210

6e148 4e149 3e75 2e94 3e149 2e77 2e125 2e118 2e112

82 96 91 89 93 84 76 80 81

54–330 102–311 92–231 43–194 49–282 82–218 135–393 40–229 15–206

99% 100% 100% 99% 100% 93% 91 99% 99%

Percentage sequence identity (ID), based on amino acid sequence. Percentage coverage, the percentage of total predicated protein length present in the gene sequences.

4

GMP

Berkeley Bluecrop

1.5

1.0

a

a

a

a

a

a

a

a

a

ab

a b

.5

Relative expression level

Relative expression level

2.0

Relative expression level

S2

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GME

a

Berkeley Bluecrop

a b

a bc

c

c

2 d

e cd

f

e

a c

bc cd

e

d

1 e

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S6

2.5

GDH

Berkeley Bluecrop

a

2.0

a

b

1.5

cd

1.0

e

bc

b

b

c c

d e

.5 0.0

GGP

S2

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S1 3.5

Berkeley Bluecrop

a

5 a

4

S6

b

ab

c

c

cd

3

c

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1 0

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0

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6

3

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Berkeley Bluecrop

b

0

0.0 4

a

GPP

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GLDH b c

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S6 Berkeley Bluecrop

c

1.5 1.0

S4 a

2.5 2.0

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b c

c

c

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Fig. 4. Expression analyses of genes involved in AsA biosynthesis during fruit development using qRT-PCR. Values are means of three replicates ± SD and different letters indicate significant differences (Duncan’s test, P < 0.05).

GMP expression levels at different stages. While for GPP, the highest expression level was observed at stage 4 in both cultivars (Figs. 4 and S1). There were obvious differences existing in the expression patterns of the other 3 genes, GME, GGP, and GLDH, between ‘Bluecrop’ and ‘Berkeley’. GME transcripts accumulated rapidly during early fruit development up to stage 3 in both cultivars. Afterward, the GME expression level decreased gradually and reached the minimum at stage 6 in ‘Bluecrop’. However, in ‘Berkeley’ GME expression levels dropped sharply at stage 4, and followed by a steady decrease. Although its transcripts peaked at stage 2 in both ‘Bluecrop’ and ‘Berkeley’, GGP was expressed at higher levels in ‘Bluecrop’ than in ‘Berkeley’, especially from stage

3 onward. Compared with ‘Berkeley’, the expression levels of GLDH were higher in ‘Bluecrop’. Moreover, the expression level of GLDH slightly fluctuated during fruit development in ‘Berkeley’, whereas in ‘Bluecrop’ expression showed an increasing trend until stage 4, and then declined (Fig. 4). Given that the L-galactose pathway is regarded as the main route of AsA biosynthesis, the present study focused on analyzing expression patterns of genes involved in the L-galactose pathway. Results showed that more GME, GGP and GLDH transcripts were detected in ‘Bluecrop’ than ‘Berkeley’, particularly from stage 4, which was in agreement with the higher AsA content in ‘Bluecrop’. GME, which converts GDP-D-mannose to

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GDP-L-galactose, was suggested as a key rate-limiting enzyme in AsA biosynthesis by analyzing transgenic tomato lines in which GME were RNAi-silenced (Gilbert et al., 2009). Previous studies have shown that the expression of GME correlated with AsA content in apple fruit, as well as the flesh of radish root (Li et al., 2010; Xu, Zhu, Chen, Gong, & Liu, 2013). Not only that, GME also played an important role in the biosynthesis of cell wall polysaccharides. Thus, it represents a significant linkage between the two metabolic pathways (Gilbert et al., 2009). In the present study, the expression pattern of GME also appeared to have the best correlation with the changing profile of AsA content in both cultivars during fruit development. GGP appeared to be positively correlated with AsA content in the two blueberry cultivars, although the relationship was not close. GGP, which catalyzes GDP-L-galactose to release L-galactose-1-P, is considered another significant rate-limiting enzyme in the production of AsA (Ishikawa et al., 2006; Linster & Clarke, 2008). Stable over-expression of GGP in Arabidopsis resulted in increased leaf AsA up to 4-fold (Dowdle, Ishikawa, Gatzek, Rolinski, & Smirnoff, 2007; Laing, Wright, Cooney, & Bulley, 2007). Further, GLDH, the last enzyme in the

development (Supplementary Fig. S1). Even though AsA accumulation was low in stage 1 and 6, high expression levels of GMP were detected. This indicates that, except for the biosynthesis of AsA, GMP might be required for other biological metabolism processes, such as the previously reported biogenesis of cell walls and protein glycosylation (Li et al., 2010). Taken together, the above results indicate that the L-galactose pathway is also the predominant route of AsA biosynthesis in highbush blueberry, and higher expression levels of GME, GGP and GLDH were associated with higher AsA content in ‘Bluecrop’, compared with ‘Berkeley’. 3.5. Expression analyses of AsA recycling genes during blueberry fruit development In addition to the main AsA biosynthesis pathway, the recycling pathway impacts AsA levels in plant tissues. To obtain more data about the molecular mechanisms of AsA accumulation in blueberry fruit, expression patterns of AsA recycling genes, including AO, APX, MDHAR and DHAR, were compared between the two blueberry cultivars (Fig. 5). As for either AO or APX, ‘Bluecrop’ had similarly fluctuated trends with ‘Berkeley’ during fruit ripening. In contrast, different from that in ‘Berkeley’, the MDHAR expression level had two peaks in ‘Bluecrop’ at stage 4 and stage 6, respectively. Similarly, DHAR expression showed some differences between ‘Bluecrop’ and ‘Berkeley’. The expression level of DHAR showed an increasing trend and reached the highest level at stage 2 in the two cultivars. Thereafter, the DHAR transcripts maintained the high levels until stage 4 and then reduced sharply, whereas in ‘Bluecrop’ the DHAR transcripts fell more obviously from stage 3. It has been shown that AsA consumption and recycling is mainly determined by oxidation of AO and APX, and reduction of MDHAR and DHAR. Either lower oxidizing activities, higher recycling activities, or both could result in AsA accumulation in plant tissues (Yang et al., 2011). In the present study, the expression patterns of AO and APX showed little differences between the two blueberry cultivars, and there was no clear association with AsA

L-galactose

pathway, catalyzes the oxidation of L-galactono-1, 4-lactone to AsA. At the same time, it also might participate in a

D-galacturonic acid pathway. The role of GLDH in AsA biosynthesis has been elucidated by inhibition or overexpression of GLDH in tobacco BY-2 cells. However, no clear correlation between AsA content and GLDH expression level has been identified in a range of species, such as kiwifruit and tomato, during fruit ripening (Alhagdow et al., 2007; Li et al., 2010). The present study showed that the changes in GLDH expression and AsA content were not inconsistent in both blueberry cultivars. However, a higher expression level of GLDH was observed in ‘Bluecrop’ than ‘Berkeley’, which might help to produce more AsA. Compared with the above mentions genes, less correlation appeared to exist between the expression of the other three genes (GMP, GPP and GDH) and AsA accumulation in blueberry fruit. It is worth mentioning that GMP had a consistently high expression level throughout fruit

3.5

AO

Berkeley Bluecrop

2.5 2.0

a

1.5

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ab

c

c

ab

c

c

1.0 d

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.5

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Berkeley Bluecrop

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APX

Berkeley Bluecrop

2.5

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b b

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Berkeley Bluecrop

a a

ab ab

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Fig. 5. Expression analyses of genes involved in AsA recycling during fruit development using qRT-PCR. Values are means of three replicates ± SD and different letters indicate significant differences (Duncan’s test, P < 0.05).

F. Liu et al. / Food Chemistry 188 (2015) 399–405

accumulation during fruit development. However, compared with that in ‘Berkeley’, more transcripts of MDHAR and DHAR were variably detected in ‘Bluecrop’. These results indicate that the higher efficiency of AsA regeneration was partially responsible for the higher AsA accumulation in ‘Bluecrop’. Moreover, expression of MDHAR basically exhibited a rising trend, whereas that of DHAR a declining trend, with the fruit ripening, which implied that MDHAR are important for regenerating AsA from the oxidised form contents at later stages, while DHAR at earlier stages, and they have a complementary relationship in maintaining a redox state of AsA. Similar observations have been reported during other fruit development, such as kiwifruit, tomato and bilberry (Cocetta et al., 2012; Li et al., 2010). In conclusion, AsA content and expression profiles of genes involved in AsA biosynthesis, as well as recycling, were compared between ‘Bluecrop’ and ‘Berkeley’. Results indicated that the L-galactose

pathway is the predominant route of AsA biosynthesis in highbush blueberry. Moreover, the higher expression levels of the AsA biosynthetic genes GME, GGP and GLDH, as well as the recycling genes MDHAR and DHAR, were associated with the higher AsA content in ‘Bluecrop’, compared with ‘Berkeley’, indicating that a higher efficiency of AsA biosynthesis and regeneration is responsible for the more AsA accumulation in ‘Bluecrop’. Conflict of interest The authors declare no competing financial interest. Acknowledgments This work was supported by the National Natural Science Foundation (Nos. 31470661; 31200248), the Natural Science Foundation of Shandong Province (Nos. ZR2013CM018; ZR2014CM004), and the Scientific Technology Development Project of Shandong province (No. 2012GSF12110). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.foodchem.2015. 05.036. References Alhagdow, M., Mounet, F., Gilbert, L., Nunes-Nesi, A., Garcia, V., Just, D., et al. (2007). Silencing of the mitochondrial ascorbate synthesizing enzyme L-galactono-1,4lactone dehydrogenase affects plant and fruit development in tomato. Plant Physiology, 145(4), 1408–1422. Badejo, A. A., Fujikawa, Y., & Esaka, M. (2009). Gene expression of ascorbic acid biosynthesis related enzymes of the Smirnoff-Wheeler pathway in acerola (Malpighia glabra). Journal of Plant Physiology, 166(6), 652–660. Bulley, S. M., Rassam, M., Hoser, D., Otto, W., Schünemann, N., Wright, M., et al. (2009). Gene expression studies in kiwifruit and gene over-expression in Arabidopsis indicates that GDP-L-galactose guanyltransferase is a major control point of vitamin C biosynthesis. Journal of Experimental Botany, 60(3), 765–778. Burdulis, D., Sarkinas, A., Jasutiené, I., Stackeviciené, E., Nikolajevas, L., & Janulis, V. (2009). Comparative study of anthocyanin composition, antimicrobial and antioxidant activity in bilberry (Vaccinium myrtillus L.) and blueberry (Vaccinium corymbosum L.) fruits. Acta Poloniae Pharmaceutica – Drug Research, 66(4), 399–408. Cocetta, G., Karppinen, K., Suokas, M., Hohtola, A., Häggman, H., Spinardi, A., et al. (2012). Ascorbic acid metabolism during bilberry (Vaccinium myrtillus L.) fruit development. Journal of Plant Physiology, 169(11), 1059–1065. Cruz-Rus, E., Amaya, I., Sanchez-Sevilla, J. F., Botella, M. A., & Valpuesta, V. (2011). Regulation of L-ascorbic acid content in strawberry fruits. Journal of Experimental Botany, 62(12), 4191–4201. Cruz-Rus, E., Botella, M. A., Valpuesta, V., & Gomez-Jimenez, M. C. (2010). Analysis of genes involved in L-ascorbic acid biosynthesis during growth and ripening of grape berries. Journal of Plant Physiology, 167(9), 739–748.

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