Proteomic changes in different growth periods of ginseng roots

Plant Physiology and Biochemistry 67 (2013) 20e32

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Research article

Proteomic changes in different growth periods of ginseng roots Rui Ma a, b,1, Liwei Sun b, *,1, Xuenan Chen b, Rui Jiang a, b, Hang Sun b, Daqing Zhao a, ** a b

Changchun University of Chinese Medicine, Jilin 130117, PR China College of Biology and Chemistry, Beihua University, 15 Jilin Street, Jilin, Jilin Province 132013, PR China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 3 November 2012 Accepted 27 February 2013 Available online 13 March 2013

For the first time, proteomics and biochemical variables have been employed to unravel the growth strategies for the different root growth periods of ginseng (Panax ginseng CA May., Araliaceae). Enzymatic activities and cellular contents, except for starch, related to defence and metabolism were significantly increased in the slow-growth period but decreased in the fast-growth period. Proteomic characterisation by two-dimensional gel electrophoresis (2DE) showed 83 differentially expressed spots; 62 spots were up-regulated and 21 spots were down-regulated in the slow-growth period when compared to the fastgrowth period. The identification of these spots indicated that the major groups of differential proteins were associated with energy metabolism (37%) and defence (17%), which was consistent with the changes observed in the biochemical measurements. These results clearly demonstrate that ginseng stores energy during its fast-growth period to promote root elongation, whereas it expends energy to improve the synthesis of secondary metabolites and stress resistance during its slow-growth period. The levels of many proteins were changed during the conversion period from fast to slow growth, providing new insights into ginseng proteome evolution. The proposed hypothetical model explains the interaction of metabolic proteins associated with the growth strategies of ginseng. Ó 2013 Published by Elsevier Masson SAS.

Keywords: 2DE Enzymatic activity Ginseng Growth period Metabolites Plant proteomics

1. Introduction Ginseng roots, which take at least five years to mature, have been widely used in traditional medicine approaches because of their various biological properties. The bioactivities of ginseng roots, which include hypotensive [1], anticancer [2], antioxidant [3], and anti-inflammatory activities as well as improving impaired memory [4,5], are facilitated by their main pharmacologically active components. Studies have shown that the content of these active components in ginseng increases every year during the fast-growth period (1e3 years of age) and remains relatively stable during the slow-growth period (>5 years of age). Thus, ginseng roots in the slow-growth period are believed to be the most valuable in clinical applications because they have optimal mass quality and consistently active components [6,7]. The developmental growth process of ginseng root has received widespread attention in an effort to improve its pharmacological

* Corresponding author. Tel./fax: þ86 432 64602992. ** Corresponding author. Tel.: þ86 431 86045317; fax: þ86 431 86172300. E-mail addresses: [email protected] (L. Sun), [email protected] (D. Zhao). 1 These authors contributed equally, all as the first authors. 0981-9428/$ e see front matter Ó 2013 Published by Elsevier Masson SAS. http://dx.doi.org/10.1016/j.plaphy.2013.02.023

effects. In this growth process, the series of the physiological and biochemical changes can be reflected in the differential expression of proteins. Therefore, it is necessary to understand root growth and development by examining protein expression in different growth stages of ginseng, especially in the transformation period from fast to slow growth. High-throughput and high-sensitivity proteomic techniques, such as two-dimensional gel electrophoresis (2DE) and mass spectrometry, allow the quantitative and qualitative separation of complex protein mixtures, which makes it possible to monitor dynamic protein expression in plant growth and metabolism. Yuzo et al. [8] have successfully compared the different growth stages of rice using the proteomics method to expound the roles of expressed proteins over the course of growth. Zeng et al. [9] have identified the proteomic changes in apple trees during their vegetative stages by 2DE and mass spectrometry. Recently, some proteomic studies have been performed on ginseng roots. Lum et al. [10] characterised the proteomic profiles of ginseng roots and identified several high-abundance proteins, thereby providing the first proteomic profile of ginseng. Most of the highly abundant proteins in the ginseng root are root-specific RNase-like proteins that function as vegetative storage proteins for survival in the natural environment [11,12]. Subsequently, proteomic analysis was used on different varieties of ginseng, such as Korean ginseng,

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Panax quinquefolium and ginseng hairy root [13e16]. However, to date, no systematic research has been reported for proteomic changes during different ginseng growth periods. Therefore, in this paper, a comparative 2DE analysis was performed in a time-course experiment designed for five different age groups of ginseng roots, and 11 biochemical parameters were also measured. These results provide insight into the biological functions and the biochemical status of developing ginseng roots and contribute to our overall understanding of ginseng root development. 2. Materials and methods 2.1. Plant materials Up to 40% of the world’s total supply of ginseng roots are grown in Jilin Province, which is the major ginseng farming region in China. Therefore, one- to five-year-old fresh ginseng roots (Panax ginseng) were collected from Jilin Province, China, during September 2011. Ginseng roots were washed and then transferred to a mortar. The dissected samples were immediately frozen in liquid nitrogen and stored at 80  C until protein extraction. 2.2. Enzymatic activity analysis Enzyme extract was prepared by sonication in lysis buffer under ice cold conditions. The sonicated sample was centrifuged at 15,000 g for 30 min at 4  C, and the resulting supernatant was used for assay of enzyme activity. Amylase (AMY, EC 3.1.1.2) activity was detected by the 3,5-dinitrosalicylic acid colorimetric method [17]. Malate dehydrogenase (MDH, EC 1.1.1.37) activity was determined as oxaloacetate reduction or malate oxidation, estimated by the decrease or increase in absorbance for NADH at 340 nm (ε ¼ 6.2 mM1 cm1) [18]. ATPase (EC 3.6.1.35) was determined according to the ATPase Activity Assay Kit (NanJing JianCheng Bioengineering Institute, China). Super oxygen dehydrogenase (SOD, EC 1.14.1.1) activity was assayed by monitoring the inhibition of NBT reduction according to the Gianopolitis’ and Ries’ method [19]. Catalase (CAT, EC 1.11.1.6) activity was determined using the method of Aebi [20]. Ascorbate peroxidase (APX, EC 1.11.1.11) activity was measured by the method of Nakano and Asada [21], which was defined as the conversion of 1 mM AsA into monodehydroascorbate in 1 min at 290 nm (ε ¼ 2.8 mM1 cm1). Peroxidase (POD, EC.1.11.1.7) activity was measured by the oxidation of guaiac-based phenol in the presence of hydrogen peroxide [22], which was defined as an absorbance change of 0.01 in 1 min at 470 nm. 2.3. Metabolite analyses 2.3.1. Starch determination Fat and soluble carbohydrates were removed from the ginseng roots, and starch was measured via an enzyme hydrolysis method. Starch was hydrolysed into dual sugars by amylase, then hydrolysed into monosaccharides by hydrochloric acid, and finally determined by reducing sugar, which could then be converted into starch [23].

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measured by spectrophotometer. A standard curve for calibration was obtained using sodium pyruvate as a reagent with a gradient of concentrations of pyruvic acid. Absorbance values were obtained to generate a standard curve to calculate the pyruvic acid concentration. 2.3.3. Lignin determination The samples were washed in 95% ethanol 3 times and then washed with normal hexane with 35% ethanol 3 times. The lignin content was measured according to the method reported by Morrison [25], with several modifications. The dried product was dissolved in acetic acid with 25% acetyl bromide and incubated for 30 min at 70  C; 0.9 ml 2 M NaOH was added to terminate the reaction. Acetic acid was added to the sample to reach a volume of 10 ml, and this solution was centrifuged at 1000 g/min for 7 min. The lignin content was determined as absorbance at 280 nm per gram fresh weight. 2.4. Protein extraction The ginseng root proteins were extracted using a phenol procedure [26] with modifications. Ground tissue was precipitated with cold acetone with 0.07% b-mercaptoethanol (at least three times). Residual acetone was allowed to evaporate at room temperature. The dry powder was resuspended in 4 volumes of lysis buffer [7 M urea, 2 M thiourea, 2% (w/v) CHPAS, 1% (w/v) plant protease inhibitor]. Then, an equal volume of Tris-saturated phenol was added; the mixture was shaken at 4  C for 30 min and centrifuged at 10000 rpm/min at 4  C for 15 min, and the water phase was discarded. Methanol containing 0.1 M ammonium acetate was added to the phenol phase at 20  C overnight and then washed with methanol containing 0.1 M ammonium acetate and acetone two and three times, respectively, to eliminate contaminants. After the complete evaporation of acetate, the proteins were dissolved in the appropriate volume of rehydration solution [5 M urea, 2 M thiourea, 2% (w/v) CHPAS, 2% (w/v) N-decyl-N,Ndimethyl-3-ammonio-1-propane-sulfonate (SB3-10)] [27]. The protein concentrations were measured using Bradford’s method [28]. 2.5. 2DE The protein samples were first separated by isoelectric focussing using linear precast IPG strips (24 cm, 3e10 liner pH gradients, GE Healthcare, UK). IPG strips with 1.2 mg of proteins were rehydrated for 12 h and focused on 72000 Vhs, as described previously [29]. First-dimension strips were equilibrated immediately or stored at 80  C. The first equilibration was carried out in 10 ml SDS equilibration solution (75 mM TriseHCl, pH 8.8, 6 M urea, 2 M thiourea, 30% glycerol, 2% SDS, 0.002% bromophenol blue) with 100 mg DTT for 15 min. The second equilibration was performed with 250 mg iodoacetamide for 15 min in the same volume. Second-dimension SDSePAGE was performed using 12.5% polyacrylamide gels at 2 W per gel for 30 min and 15 W per gel for 5e6 h in six EttanDalt systems (GE Healthcare, UK). Finally, the gels were stained using Coomassie Bright Blue R-250. 2.6. Image and data analysis

2.3.2. Pyruvic acid determination The contents of pyruvic acid in the sample were determined according to the methods of Mau-Wei Lin [24]. Protein was removed from the samples by TCA precipitation, and in the resulting sample, pyruvic acid reacted with 2,4nitrophenylhydrazine. The product turned red in the presence of an alkali solution, and the intensity of the colour change was

The stained gels were scanned by Image Scanner (GE Healthcare, UK) with 600 dpi. All spots were matched by gel-to-gel comparison using Image Master 2D Platinum Software Version 6.0 (GE Healthcare, UK). Volumes of every detected spot were normalised. After normalisation, the spots with statistically significant (Student’s t-test with a P-value <0.05) and reproducible

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changes in abundance were considered to be differentially expressed protein spots. Only those spots with reproducible changes (quantitative changes >1.5-fold in abundance) were considered for successive analyses. Significant differences were analysed through two-way hierarchical clustering methodology using the software PermutMatrix [30]. For this purpose, the data produced by the analysis of 2DE gels were converted into a binary matrix, replacing the missing values with zero. The row-by-row normalisation of data was performed using the classical zero-mean and unit-standard deviation technique. Pearson’s distance and Ward’s algorithm were used for the analysis. 2.7. Protein identification Protein spots were manually excised from the preparative gels, digested with trypsin and analysed using MALDI-TOF/TOF MS with a 4700 Proteomics Analyzer (Applied Biosystems, USA) as described previously [31]. The peptide mass fingerprint (PMF) was analysed with GPS (Applied Biosystems, USA) -MASCOT (Matrix Science, UK). The identified proteins were named according to the corresponding annotations in the NCBInr. For the proteins without functional annotations in the databases, homologues of these proteins were searched against the NCBI non-redundant protein database with BLASTP (http://blast.ncbi.nlm.nih.gov/) to annotate these identities. The experimental molecular mass of each protein spot was estimated by comparison with molecular weight standards, while the experimental pI was determined by the migration of protein spots on linear IPG strips. 2.8. Protein functional classification For functional classification, the differentially expressed proteins were entered into the iProClass Gene Ontology (GO) analysis tool in the Protein Information Resource (PIR) database (http://pir. georgetown.edu/) and assigned to three GO vocabularies, including biological processes, molecular functions and cellular components. 2.9. Statistical analysis Values in figures and tables were expressed as the mean  SD. Statistical analysis was carried out with three biological replicates for proteomic and biochemical analyses. The results of the spot intensities and physiological data were statistically analysed by one-way ANOVA and the Duncan’s new multiple range test (DMRT) to determine the significant difference between group means. A Pvalue 0.05 was considered statistically significant (SPSS for Windows, version 12.0).

3.1. Protein expression profiles of ginseng roots at different ages Proteomic technology provides a new vision and strategy for revealing patterns of biological activity at the molecular level; therefore, it is a powerful tool for researching the proteomic changes of ginseng roots during their growth process. A key aspect of proteomic studies is to establish an effective protein extraction method. In this study, the extraction method for ginseng root proteins was tested and improved on the basis of previously reported methods [33,34]. Our results demonstrate the enhanced efficiency of the phenol based protocol compared with other extraction methods. Nearly 1000 protein spots were obtained on a 2DE gel, which had more than twice the number of protein spots compared to other reported extraction methods [10]. This method represented a substantial reference map for further studies on ginseng proteomics. Representative gels from ginseng roots at different ages were analysed by ImageMasterÔ 2D Platinum software. The results revealed that the total numbers of protein spots on 2DE gels increased gradually with the age of the root [Fig. 1]. Notably, the total number of proteins in the five-year-old ginseng root, which had the best mass quality and consistency of essential ginseng bioactive components, was significantly higher than that of the younger roots. These data implied that the adult ginseng roots have a high capacity for protein synthesis. Based on the 2DE images from ginseng roots at different ages [Fig. 2], we have an outline of the expression profiles for the relatively abundant and soluble proteins. The distribution patterns of proteins spots with low abundance varied, while most of the proteins spots with intermediate and high abundance were similar in all 2DE images. Interestingly, eight of the high-abundance proteins that electrophoretically migrated to 27e28 kDa and were named ginseng major proteins (GMP) decreased progressively across the growth stages. These proteins originated from a 28-kDa ribonuclease-like protein [11] that is commonly found in Araliaceae Panax species such as P. quinquefolium and Panax pseudoginseng [15,35]. The volume percentages of each spot on the 2DE images in the fast- and slow-growth periods were estimated and compared. A total of 83 stained spots were found to have significant changes, with a minimum 1.5-fold difference in relative abundance. Among them, 62 spots were up-regulated and 21 spots were downregulated in the slow-growth period of the ginseng roots. Nine of the observed spots (F8, F15, F19, F20, F21, F25, F31, F33, F60) represented unique proteins. The magnified views of some differentially expressed protein spots are shown in Fig. 3.

3. Results and discussion During the growth process of ginseng the roots stretch and gain weight each year, and the rates of these morphology changes will decrease progressively after the third year [32]. Morphology studies defined the period from one to three years as the “fast-growth period”, when the ginseng roots grow fast with maximum changes in their structures. The period after five years was defined as the “slow-growth period”, when the root growth rate gradually decreases and tends towards stabilisation. Consequently, the stage between three and five years is a transition period for the growth rate and chemical composition of ginseng roots. Therefore, this stage is an important phase to study to elucidate the maturity mechanism in ginseng root growth.

Fig. 1. The trend of total 2-DE spots of ginseng root in different ages. The total 2-DE spots were averaged from three parallel gels at each sample.

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Fig. 2. Comparison of the ginseng proteome pattern of different ages, which were one year old (A), two years old (B), three years old (C), four years old (D) and five years old (E) respectively. The arrows indicate the proteins of five-year ginseng. Down-regulated proteins (spots T1eT21) are indicated in the image of three-year ginseng. Up-regulated proteins and newly-induced proteins (spots F1eF62) are indicated in the image of five-year ginseng.

3.2. Hierarchical clustering analysis

3.3. Protein identification and functional classification

The differentially expressed protein spots were subjected to two way hierarchical clustering analysis using the PermutMatrix software [Fig. 4]. The clustering of columns mirrored the distances between the different growth stages of ginseng roots. It is evident that the cluster order reflected the sequential succession of the samples, whereas an obvious distinction existed between the first two and the third samplings. These results suggested that the most important changes in protein expression occur between the fastand slow-growth periods. As for the row clustering, two main trends were observed: the levels of some proteins increased during maturation and the levels of some proteins declined during root growth. Most of the spots exhibited the former trend (88.3%), in agreement with the observation that the number of proteins whose expression was switched on during growth stages was far greater than the number of proteins that were switched off.

A total of 83 differentially expressed spots were identified by searching against the viridiplantae protein database from NCBInr, and only matches with more than two peptide hits were accepted. As the sequence information on ginseng is limited, some proteins in our results were not included in the databases. Fifty spots matched the correct proteins, resulting in a 60.2% identification rate. The results of identification from MALDI-TOF/TOF MS are summarised in Table 1. To gain further knowledge of the functionality of growth regulated proteins, the identified proteins were analysed separately against the ontology of GOSlim in the PIR database with three sets of ontologies: biological processes (GOBP), molecular functions (GOMF), and cellular components (GOCC) [36]. Because one protein was sometimes grouped into multiple GO categories, the total number of proteins in each pie chart exceeded the input number.

Fig. 3. Expression pattern of selected proteins. 1, one year old; 3, three years old and 5, five years old was given to ginseng root. Numbers represent the spots no. on 2DE gel. Proteins showing significant and reproducible changes were subjected to MALDI-TOF/MS analysis. Details are given in Table 1.

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Fig. 4. Clustering analysis of the spots that resulted to change their relative volumes during the fast and slow growth periods. Two-way hierarchical clustering analysis of the 50 spots showed at least a 1.5-fold change in the relative spot volumes (ANOVA, P < 0.01) in the three different ages of ginseng root. The clustering analysis was performed with PermutMatrix graphical interface after Z-score normalisation of the averages of relative spot values (n ¼ 6). Pearson’s distance and Ward’s algorithm were used for the analysis.

The differentially expressed proteins were involved in diverse biological processes [Fig. 5A]. The most enriched GOBP category was energy metabolic processes (37% in total), which included glycolysis, tricarboxylic acid cycle, glucose catabolic process, proton transport, carbohydrate metabolism, and glycine and malate metabolisms, suggesting that these processes are functionally important for the growth and development of ginseng roots. The second most highly enriched GOBP category was stress response (17%). As for GOMF categories, binding activities represented the biggest portion (44%), including ATP, flavin adenine dinucleotide, haeme, metal ion, NAD, nucleotide, pyridoxal phosphate, RNA and protein binding activities [Fig. 5B]. When analysed on the basis of GOCC, the top category was cell wall synthesis (18%) [Fig. 5C]. 3.3.1. Proteins related to energy metabolism In this category, eleven proteins, such as phosphoglyceromutase (F7), phosphoglycerate kinase (PGK; F10), glyceraldehyde 3phosphate dehydrogenase (GAPDH; F25, F54), enolase (F46, F48), MDH (F55), ATP synthase (F43, F44, F45), and ATPase (F49), were up-regulated; and three proteins, including fructose-bisphosphate aldolase (FBA; T11) and pectinesterase (PME; T13), were downregulated in the slow-growth phase of ginseng roots. This result

was interpreted as explicit evidence of an adaptive strategy for ginseng root growth. Starch is a type of stored energy in plants and represents the start of the energy metabolism pathway. Our results showed that the contents of starch declined with the age of the ginseng roots [Fig. 6A]. AMY is the first enzyme in the process of starch decomposition, and its activity increased for each year of age [Fig. 6B]; for instance, activity in the fifth year is 2.4 times that of the third year roots and 2.8 times that of the first year. This finding suggests that the decomposition of starch could provide energy for the maturation of ginseng roots, and it may be an indication of an alteration in energy metabolism, as previously reported for the maize endosperm [37]. Starch is broken down into glucose, which enters the glycolytic pathway. In glycolysis, the demarcation between the preparatory and payoff phases is glyceraldehyde 3-phosphate, before which the breakdown of each molecule of glucose costs two ATP and after which four ATP will be gained. FBA (T11) is involved in energy preparation and was up-regulated during the fast-growth period. This result indicates that ginseng mainly absorbs energy for storage and that GMP functions as a vegetative energy storage protein for ginseng root survival [12]. FBA and GMP had higher abundances in the fast-growth phase according to the 2DE gels [Fig. 2]. On the contrary, GAPDH (F25, F54), phosphoglyceromutase (F7) and enolase (F46, F48), which are a series of enzymes involved in the catabolism of glyceraldehyde-3-phosphate to pyruvate in the payoff phase, had higher abundances in the slow-growth period. This finding shows that active glycolysis releases energy to provide the required energy for ginseng root maturation in the slowgrowth period. The final product of the glycolytic pathway is pyruvate. It can be converted into carbohydrates (such as glucose) via gluconeogenesis or into fatty acids through acetyl-CoA, and pyruvate can also be used to construct the amino acid alanine, which has a role in several metabolic pathways. We detected an increase in pyruvate content along with ginseng growth [Fig. 6C] when the fifth year roots had 2.16 times more pyruvate than third year roots and 2.68 times than first year roots. This result verified that the glycolysis in the slowgrowth period is more active than that in the fast-growth period, presumably because it provides the necessary energy for ginseng maturation processes such as synthesis and stress resistance. Pyruvate is oxidised to acetyl-CoA during the citric acid cycle. MDH (F55) catalyses the regeneration of oxaloacetate to maintain this cycle. In our study, its expression and activity increased in the over the course of the growth phase [Fig. 6D], indicating that ginseng is not only active in glycolysis but also enhances the citric acid cycle to generate large quantities of ATP during the maturation process. Accompanied with increased generation of ATP during the slowgrowth period, ATPase (F49), which hydrolyses ATP to release energy, was up-regulated in the ginseng slow-growth period. Our assays also showed that ATPase activity increased during ginseng growth; the fifth year roots had 1.7 times the ATPase activity compared to the third year roots and 3.6 times the ATPase activity of the first-year roots [Fig. 6E]. This result indicates that the demand for energy (ATP) by the ginseng roots during the slow-growth period was greater than the energy demand during in the fastgrowth period. In summary, we speculate that ginseng enhances sugar metabolism in the growth and maturation process to produce acetylCoA, which, in turn, enters the mevalonate pathway that results in the increased production of mevalonate. AMP, which results from ATP hydrolysis, and mevalonate are both cytokinin precursors [38]. Therefore, the production of cytokinin increased to promote the root enlargement and weight gain during the slow-growth

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Table 1 Identification of different expressed proteins from ginseng root in different growth periods. Spots no.a

Protein name

Accession no.b

Species

pI/MW Theoc

pI/MW Expd

Pep. counte

Energy metabolism F7 Cofactor-independent phosphoglyceromutase

Q9SDL3

Apium graveolens

5.26/60.9

6.07/62.3

10

F10

Phosphoglycerate kinase

B4G0K4

Zea mays

5.65/42.4

6.11/40.3

9

F15

Malic enzyme, putative

B9RS07

Ricinus communis

6.43/60

7.17/64.6

12

F25

Glyceraldehyde-3-phosphate dehydrogenase

Q3LRW8

Panax notoginseng

8.46/22.3

8.6/32.4

9

F43

ATP synthase subunit beta, mitochondrial-like

F6GTT2

Vitis vinifer

5.9/59.1

5.44/52.0

21

F44

ATP synthase beta chain

B6SVV9

Zea mays

5.9/58.9

5.53/52.0

14

F45

ATP synthase subunit beta, mitochondrial-like

F6GTT2

Vitis vinifer

5.9/59.1

5.63/52.9

20

F46

Enolase 1

Q9LEJ0

Hevea brasiliensi

5.57/47.8

5.76/52.9

7

F47

ACT1

A7YVW7

Actinidia deliciosa

5.31/41.6

5.43/44.1

19

F48

Enolase

Q6W7E8

Brassica rapa subsp. Campestris

5.46/47.3

6.01/53.4

15

F49

F1 ATPase a-subunit

O47412

Panax ginseng

5.93/54.9

6.39/50.1

20

F54

Glyceraldehyde 3-phosphate dehydrogenase

Q2KMF3

Crypteronia paniculata

6.81/13.1

6.62/31.8

8

F55

Malate dehydrogenase, mitochondrial

P17783

Citrullus lanatus

8.88/36.2

6.78/29.57

7

F62

Ribonuclease-like storage protein

P83618

Panax ginseng

5.87/27.3

6.72/18.3

6

T11

Fructose-bisphosphate aldolase

D1MY57

Phyllostachys edulis

7.57/38.8

7.2/35.5

8

T13

Pectinesterase 2.2

Q96575

Solanum lycopersicum

8.64/60.4

7.4/25.0

8

T15

Os12g0137900

C7J9E9

Oryza sativa Japonica group

8.2/39.7

8.3/27.7

13

Q43497

Solanum lycopersicum

5.77/47.0

6.3/42.5

8

Sports intensities Fast

Slow

ROS scavenging and defence

F11

Monodehydroascorbate reductase

(continued on next page)

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R. Ma et al. / Plant Physiology and Biochemistry 67 (2013) 20e32

Table 1 (continued ) Spots no.a

Protein name

Accession no.b

Species

pI/MW Theoc

pI/MW Expd

Pep. counte

F20

Catalase

B9H662

Populus trichocarpa

7.09/56.9

7.59/52.9

12

F21

Catalase

B9H662

Populus trichocarpa

7.09/56.9

7.78/52.9

15

F22

Catalase

B9H662

Populus trichocarpa

7.09/56.9

7.98/52.9

14

F23

Glutamate dehydrogenase

A7YVW4

Actinidia chinensis

6.28/44.8

7.0/42.5

6

F24

Monodehydroascorbate reductase

A5JPK7

Vitis vinifera

5.93/47.2

7.12/42.5

7

F58

Glutathione peroxidase

A9NKE6

Picea sitchensis

7.6/18.6

4.81/19.1

4

T16

1,3-Beta-D-glucanase

Q4JGN7

Phaseolus vulgaris

8.51/37.0

8.73/26.0

4

Amino acid and secondary metabolism

F18

Serine hydroxymethyltransferase 2

C6ZJY7

Glycine max

8.22/54.5

7.11/54.4

13

F19

Serine hydroxymethyltransferase 1

F6HCS8

Vitis vinifera

7.17/51.9

7.36/53.9

10

F51

Isoflavone reductase homologue Bet v 6.0101

O65002

Betula pendula

7.82/33.1

6.31/31.8

14

F52

Aldo/keto reductase, putative

B9RTJ8

Ricinus communis

5.69/39.2

6.40/32.4

4

Protein synthesis

F31

Peptidyl-prolyl cisetrans isomerase

A5APT3

Vitis vinifera

8.76/19.7

8.50/24.4

7

F35

Luminal-binding protein 1

Q9LKR3

Arabidopsis thaliana

5.08/73.6

5.16/71.4

19

F36

Luminal binding protein 2

Q39043

Arabidopsis thaliana

5.08/73.4

5.20/71.4

15

F37

Luminal binding protein 2

Q39043

Arabidopsis thaliana

5.08/73.4

5.28/71.4

20

F38

Heat shock protein Hsp70

Q2HT97

Medicago truncatula

5.11/71.0

5.15/67.7

22

F50

Pterocarpan reductase

Q05JY0

Lotus japonicus

5.94/34.0

5.93/34.2

4

T4

Retrotransposon protein

Q53LX4

Oryza sativa Japonica group

9.07/149.8

8.2/65.8

36

P42652

Solanum lycopersicum

4.69/29.3

8.5/27.4

8

Transcription

Signal transduction

F60

14-3-3 protein 4

Sports intensities Fast

Slow

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Table 1 (continued ) Spots no.a

Protein name

Accession no.b

pI/MW Theoc

Species

pI/MW Expd

Pep. counte

Sports intensities Fast

Slow

Hypothetical protein

F30

Hypothetical protein

XP_002265030.2

Vitis vinifera

9.64/29.9

8.22/24.6

10

F33

Hypothetical protein

XP_002265030.2

Vitis vinifera

9.64/29.9

8.37/24.6

9

T12

Hypothetical protein SORBIDRAFT_01g018770

C5WXH3

Sorghum bicolor

8.69/134.4

7.4/35.8

25

Predicted protein

F5

Putative uncharacterised protein

D8T4G9

Selaginella moellendorffii

9.02/38.2

5.9/62.3

13

F8

Putative uncharacterised protein

D7KS87

Arabidopsis lyrata subsp. lyrata

5.07/73.0

4.42/46.6

12

F9

Putative uncharacterised protein

D7KS87

Arabidopsis lyrata subsp. lyrata

5.07/73.0

4.49/46.6

12

F34

Predicted protein

B9N0E2

Populus trichocarpa

5.35/75.2

4.82/75.0

16

F39

Putative uncharacterised protein

B8LRY5

Picea sitchensis

5.07/71.3

5.2/67.03

23

F40

Putative uncharacterised protein

B8LRY5

Picea sitchensis

5.07/71.3

5.29/67.03

20

F41

Unnamed protein product

XP_002274296.1

Vitis vinifera

5.38/118.7

5.0/45.8

25

T7

Predicted protein

B9IK65

Populus trichocarpa

6.63/203.7

4.68/28.5

30

T18

Predicted protein

C1MMF6

Micromonas pusilla CCMP1545

5.34/189.2

4.53/11.8

33

T20

Predicted protein

C1MHC5

Micromonas pusilla CCMP1545

8.87/34.5

7.92/27.5

12

a b c d e

The numbering corresponds to the 2-DE gel in Fig. 2: F1eF62 are up-regulated proteins and T1eT21 are down-regulated in slow growth period. Accession number in NCBI database. Theoretical pI and molecular weight. Experimental pI and molecular weight. Number of matched peptides.

period, while reduced cytokinin elongates the root during the fastgrowth phase. These results verified the previous morphologic study on ginseng roots [32]. We propose a hypothetical model to explain the interaction of proteins involved in metabolic processes in the context of growth strategies of ginseng roots during different phases of growth [Fig. 7]. Pectins are involved in the cell wall structure, and the changes in the structure/chemistry of cell walls directly affect the ripening and senescence of plants [39,40]. PME controls the assembly and disassembly of pectin through the de-esterification process, which increases the density and the compactness of the cell wall. In our study, the protein level of PME (T13) in the fast-growth period was much higher than that in the slow-growth period, indicating that PME may play an important biological role in the elongation

process of ginseng root, which was supported by previous reports on pea plants [41] and Solanum tuberosum L. [42]. Furthermore, optimally limited energy and matter was allocated to defence of the plant. This consumption was higher than that of the primary metabolism during the fast-growth period. Proteins related to energy metabolism, such as GAPDH, ATPase and MDH, can change in abundance in response to stress. Studies have shown that low temperature stress can cause the up-regulation of ATPase in plants, leading to the release of more energy (mainly for heat) to resist the effects of low temperatures [43]; on the contrary, ATPase was down-regulated by heat treatment [44]. GAPDH could provide plants with metabolic flexibility for the facilitation of their development [45] and acclimation to environmental stresses [46], such as hypoxia, iron deficiency [47], heat [43] or cold [48]. MDH (F55)

28

R. Ma et al. / Plant Physiology and Biochemistry 67 (2013) 20e32

Fig. 5. Functional analyses of proteins among different gene ontology (GO) categories in ginseng root during slow growth period. All identified proteins were included and presented in biological process (A), molecular function (B) and cellular component (C). Percentage distributions of the GO terms were calculated by iProClass GO tool in PIR database.

was detected as a cell wall protein that was covalently bound to the apoplast compartment, which participates in primary growth processes and the detoxification of heavy metals during the ripening of ginseng and is consistent with a report on maize roots [49,50]. Therefore, we hypothesised that the ginseng root suffered from greater biotic and abiotic stresses during the slow-growth period, leading to an increase in the levels of these enzymes, which may provide the energy necessary to respond appropriately to such environmental stressors. 3.3.2. Proteins related to ROS scavenging and defence Reactive oxygen species (ROS) cause damage to cellular components during times of stress [51,52]. Cells have developed a wide

range of antioxidant systems to scavenge excessive ROS or ROSinduced toxic substances to protect against oxidative damage [53]. During stress conditions, stress-related proteins are induced and play an important role in protecting cells against damage [54]. The proteins associated with ROS scavenging pathways, including CAT (F20-22), monodehydroascorbate reductase (MDAR; F11, F24), glutamate dehydrogenase (GDH; F23) and glutathione peroxidase (GPX; F58), were over-expressed during the slow-growth period. These results were in agreement with the results of our biochemical assays. CAT (F20-22) catalyses the decomposition of hydrogen peroxide in cells [55]. This proposition is supported by the up-regulation of CAT under salt stress [56,57] and water stress [58]. The activities of

R. Ma et al. / Plant Physiology and Biochemistry 67 (2013) 20e32

29

Fig. 6. Starch contents (A), AMY (B), pyruvic acid contents (C), MDH (D) and ATPase (E) of ginseng root in different ages. 1e5, one to five years old were given to ginseng root. Bars indicate SD.

Fig. 7. Schematic overview of the enzymes involved in energy metabolism and their connection with some intermediary activities that changed in expression in ginseng root during slow growth period. The expression was evaluated by measuring relative spot volumes in the 2-DE analysis. Arrows indicate whether the abundance of the identified proteins decreased or increased during slow growth period, respectively.

30

R. Ma et al. / Plant Physiology and Biochemistry 67 (2013) 20e32

Fig. 8. CAT (A), SOD (B), APX (C), POD (D) and lignin contents (E) of ginseng root in different ages. 1e5, one to five years old were given to ginseng root. Bars indicate SD.

CAT were increased during the slow-growth period relative to the fast-growth period in our study [Fig. 8A]. MDAR (F11, F24) and GPX (F58) were also previously identified as oxidants in the glutathioneeascorbate cycle, which is a major plant antioxidant system that protects cells against ROS [59]. Our assays showed that the activities of some other enzymes involved in the antioxidant reaction system, including SOD and APX, were higher during the ginseng slow-growth period than during the fast-growth period [Fig. 8B, C]. In addition, POD activity is positively correlated with stress resistance, and it plays an important role in plant resistance to disease; additionally, it is used as a physiological and biochemical marker for some plant disease resistance indices. We detected that POD activity increased year by year in ginseng roots [Fig. 8D], indicating that ginseng stress resistance is enhanced during the growth process. POD is also a key enzyme for synthetic lignin, which is a secondary metabolite in plant growth and development. We accordingly detected a yearly increase in the lignin content [Fig. 8E]. POD biosynthesis can also be induced upon various biotic and abiotic stress conditions, such as wounding, pathogen infection, metabolic stress, and perturbations in the cell wall structure [60,61]. Notably, the root is a major component of a plant’s response to disease. The up-regulation of these antioxidant proteins and metabolites could increase the adaptive ability of roots to adverse growth environments. 3.3.3. Proteins related to protein synthesis All of the proteins suppressed and expressed de novo during ginseng growth belong to the protein synthesis category, which may redirect protein metabolism to aid in plant survival under stressful conditions. The protein content increased with ginseng root age [Fig. 9], indicating that protein synthesis enhanced the ginseng maturation at different metabolic levels. Peptidyl-prolyl cis/trans isomerases (PPIases) (F31) are enzymes that accelerate the energetically unfavourable cis/trans isomerisation of the peptide bond preceding a proline. The overexpression of this protein during the slow-growth period is thought to be essential for protein synthesis during normal growth. This finding was also supported by reports on wheat cultivars [62] and Bacillus subtilis [63].

Moreover, Heat shock proteins (Hsps) play a crucial role in protecting plants against stress by re-establishing normal protein conformation and maintaining cellular homoeostasis. Heat shock protein 70kD (Hsp70; F38), which is involved in almost every step of protein biogenesis, was identified in our samples. There was enhanced expression of the predicted proteins F8, F9, F34, F39 and F40 with 95%, 95%, 92%, 90% and 91% homology, respectively, with Hsp70. These proteins play essential roles as molecular chaperones, assisting with the correct folding of nascent polypeptide chains as they emerge from the ribosome, participating in transmembrane protein transport, and limiting cellular damage following stress by their ability to prevent protein aggregation and restore the function of denatured proteins [64,65]. Luminal binding protein (BiP) (F35-37), a member of the Hsp70 family, localises to the endoplasmic reticulum (ER) of eukaryotic cells, where it functions as a chaperone and is believed to support proper protein folding and protein translocation into the ER lumen [66]. Hsp70 and BiP were over-expressed during the slowgrowth period to ensure proper protein folding under (a)biotic stress, and similar results were found in resistance to drought stress [67].

Fig. 9. Protein contents of ginseng root in different ages. 1e5, one to five years old were given to ginseng root. Bars indicate SD.

R. Ma et al. / Plant Physiology and Biochemistry 67 (2013) 20e32

3.3.4. Proteins related to amino acid and secondary metabolism The proteomic analysis performed in this study revealed a differential increase in the abundance of several enzymes devoted to amino acid and prosthetic group metabolism in ginseng during the slow-growth period. For example, serine hydroxymethyltransferase (SHMT; F18, F19), a key enzyme in amino acid production and plant photorespiration that catalyses the reversible interchange between serine and glycine, played a role in amino acid metabolism in the slow-growth period. This observation supports previous observations of Malus domestica in vegetative phase and Citrus sinensis L. (Osbeck) flesh at ripening time [9,68]. Flavonoid biosynthesis enzymes were also altered in the ginseng growth period. Flavonoids are involved in defence, pigmentation and the control of enzyme activity in plants [69]. They can modulate the activity of auxin transport proteins [70,71], modify the architecture of roots [72] and play roles in redox control as antioxidants [73]. The expression of isoflavone reductase (F51), which is an enzyme involved in the (iso)flavone biosynthesis, increased during the ginseng growth and it may ensure the survival of ginseng in response to its environment. 3.3.5. Other proteins Finally, some proteins characterised in this study were involved in transcription (F50, T4) and signal transduction (F60). The 14-3-3 protein (F60), which was specifically expressed in the slow-growth period, has been reported to be induced in response to various stressors such as salinity [74] and drought [75]. The highly conserved phosphopeptide-binding protein may play a role in stress responses by regulating target proteins with functions of either signal transduction or regulatory processes [76,77]. Retrotransposon protein (T4) has been studied in the plant genome in the context of gene regulation, phylogeny and biodiversity assessment [78]. Reports have shown that retrotransposon protein was activated by tissue culture, cold stress, and salicylic acid to control plant growth and development. Meanwhile, some reports demonstrated that the expression of this protein changed during the maturation process of the litchi [79]. Further work is necessary to define the roles of many other proteins in ginseng root growth and development processes. 4. Conclusions This work provides new insight into the proteome evolution of ginseng root during different growth periods, which contributes to filling the gaps in the knowledge of Chinese traditional medicinal plant root growth and development. According to the protein expression patterns of different ginseng growth periods, it can be concluded that many of the differentially expressed proteins were likely the result of ginseng growth phase transitions. In particular, the changes in the expression of energy-related proteins reflected the preparatory phase for promoting the elongation of the fast-growth ginseng root, the energy payoff phase for the root thickening and weight gain, the synthesis of secondary metabolites and the resistance to stress of the slow-growth root. These variations were accompanied by increased levels of other primary metabolites. Acknowledgements This research was financially supported by two national key technology R&D programs (No. 2011BAI03B01 and No. 2012BAI29B05), two foundations of National Natural Science (No. 81041091 and No. 21173108), the National Science and Technology Major Project (No. 2010ZX09401-305-02) and Jilin Provincial Scientific and Technological Development Project (No. 2012142).

31

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