Plant Science 230 (2015) 33–50

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Physiological and proteome studies of responses to heat stress during grain filling in contrasting wheat cultivars夽 Xiao Wang a,b,c,∗ , Burcu Seckin Dinler d , Marija Vignjevic b , Susanne Jacobsen c , Bernd Wollenweber b a Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture/Hi-Tech Key Laboratory of Information Agriculture of Jiangsu Province, Nanjing Agricultural University, Nanjing 210095, China b Aarhus University, Faculty of Science and Technology, Institute of Agroecology, Research Centre Flakkebjerg, DK-4200 Slagelse, Denmark c Enzyme and Protein Chemistry, Department of Systems Biology, Technical University of Denmark, Building 224, DK-2800 Kgs. Lyngby, Denmark d Department of Biology, Faculty of Arts and Sciences, Sinop University, Sinop, Turkey

a r t i c l e

i n f o

Article history: Received 29 September 2014 Received in revised form 22 October 2014 Accepted 26 October 2014 Available online 31 October 2014 Keywords: Antioxidant enzymes Leaf proteome Photosynthesis Wheat

a b s t r a c t Experiments to explore physiological and biochemical differences of the effects of heat stress in ten wheat (Triticum aestivum L.) cultivars have been performed. Based on the response of photosynthesis rates, cell membrane lipid peroxide concentrations and grain yield to heat, six cultivars were clustered as heattolerant (cv. ‘579 , cv. ‘810 , cv. ‘1110 , cv. Terice, cv. Taifun and cv. Vinjett) and four as heat-sensitive (cv. ‘490 , cv. ‘633 , cv. ‘1039 and cv. ‘1159 ). Higher rates of photosynthetic carbon- and light-use were accompanied by lower damage to cell membranes in leaves of tolerant compared to sensitive cultivars under heat stress. The tolerant cv. ‘810 and the sensitive cv. ‘1039 were selected for further proteome analysis of leaves. Proteins related to photosynthesis, glycolysis, stress defence, heat shock and ATP production were differently expressed in leaves of the tolerant and sensitive cultivar under heat stress in relation to the corresponding control. The abundance of proteins related to signal transduction, heat shock, photosynthesis, and antioxidants increased, while the abundance of proteins related to nitrogen metabolism decreased in the tolerant cv. ‘810 under heat stress as compared to the control. Collectively, the results indicate that primarily changes in both the amount and activities of enzymes involved in photosynthesis and antioxidant activities in leaves contributed to higher heat tolerance in the cv. ‘810 compared to the heat sensitive cv. ‘1039 . © 2014 Published by Elsevier Ireland Ltd.

1. Introduction

Abbreviations: A/Ci , curve, carbon assimilation versus intercellular CO2 concentration curve; APX, ascorbate peroxidase; Asat , saturated net photosynthetic rate; CAT, catalase; CPN60, chaperonin 60 proteins; DHAR, dehydroascorbate reductase; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; GR, glutathione reductase; gs , stomatal conductance; HSPs, heat shock proteins; Jmax , maximum photosynthetic electron transport rate; MDA, malondialdehyde; NPQ, non-photochemical quenching of chlorophyll fluorescence; Pn, photosynthetic rates; PSII, photosystem II; PSII, actual PSII photochemical efficiency; RCA, Rubisco activase; RLS, Rubisco large subunit; RSS, Rubisco small subunit; Rubisco, Ribulose-1,5-bisphosphate carboxylase/oxygenase; Vmax , maximum carboxylation rate of Rubisco; SAMS, Sadenosylmethionine synthase; SOD, superoxide dismutase; TR, transpiration rate; TPU, triose phosphate utilization. 夽 This paper is dedicated to the late Susanne Jacobsen. ∗ Corresponding author at: Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture/Hi-Tech Key Laboratory of Information Agriculture of Jiangsu Province, Nanjing Agricultural University, Nanjing 210095, China. Tel.: +86 25 84395478; fax: +86 25 84395478. E-mail addresses: [email protected], [email protected] (X. Wang). http://dx.doi.org/10.1016/j.plantsci.2014.10.009 0168-9452/© 2014 Published by Elsevier Ireland Ltd.

Increased frequency and duration of high temperature episodes during the last decade is becoming a limiting factor for plant growth [1,2]. In cereals, high temperature events especially occurring during the reproductive growth stage can significantly decrease both crop yield and quality [3,4]. Wheat, one of the most important crops, is sensitive to heat stress, which is considered to be one of the major limiting factors for wheat production in Europe [5]. The optimum temperature for wheat during grain filling is around 21 ◦ C [6,7], and higher temperatures have been shown to significantly decrease grain yield [8]. Thus, improvement of crop tolerance under more frequent heat stress conditions will become essential for food supply. The effects of heat stress on wheat production are quite complex [9]. Heat stress causes adverse effects for plant growth, development, crop yield and quality [10]. Photosynthesis as one of the most heat-sensitive physiological processes is significantly inhibited by high temperatures [11,12]. It has been reported that

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X. Wang et al. / Plant Science 230 (2015) 33–50

heat stress inhibits photosynthesis by decreasing the Rubisco activation state via inhibition of Rubisco activase [13,14]. The oxygen evolution complex in PSII is also considered to be vulnerable to heat stress [15]. Higher photochemical light-use efficiency and heat dissipation correlate with heat tolerance [16–18]. The disturbance of photosynthesis and other metabolic processes will result in the generation of reactive oxygen species (ROS), leading to cell membrane peroxidation, protein oxidation and DNA damage [19]. Antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), glutathione reductase (GR) and dehydroascorbate reductase (DHAR) play important roles in detoxifying ROS [20]. Both enhanced activity and synthesis of antioxidant enzymes correlate with heat tolerance in crops [12,18,21,22]. Proteome analysis is as a useful tool to investigate the mechanisms of plant response to abiotic stresses [23,24]. Previous studies found that proteins related to the electron transport chain, redox homeostasis, heat shock proteins (HSPs) and glycolysis may play critical roles in protecting leaves against heat stress [25]. Increased abundance of sucrose synthase, glutathione S-transferase, SOD and of HSPs could be important in protecting plants from heat stress [26]. Few studies have combined physiological and proteome analyses to elucidate changes in the abundance of and/or activity of relevant enzymes in response to heat stress. The hypothesis of this study has been that responses of physiological and proteomic parameters in tolerant and sensitive wheat cultivars will help to indicate possible thermo-tolerance mechanisms. The objective of this study was therefore to quantify the effects of a heat stress event during grain filling in ten different wheat cultivars followed by a detailed proteome analysis of differences to a heat stress event in the tolerant and the sensitive cultivar. 2. Material and methods 2.1. Plant material and experimental setup An outdoor pot experiment was done at the Research Centre Flakkebjerg, Aarhus University, Denmark in 2011. Ten kg soil (16:9:4 v/v/v mixture of peat moss, loamy soil and sand) was filled into each pot (18 cm height and 23 cm in diameter). Ten wheat (Triticum aestivum L.) cultivars were used in this study (Table 1) and for each cultivar 4 pots were used for each treatment. The plants were thinned to 4 seedlings per pot at the three-leaf stage. The phenology of each cultivar was carefully recorded according to Zadoks et al. [27]. The heat stress treatment started at 15 days after anthesis (determined individually for each cultivar as shown in Table 1) and lasted for 5 days. One half of the plants were moved into a climate chamber (PGV36; Conviron, Montreal, QC, Canada) with halogen lamps (HRI.BT 400W/D Pro daylight E40 (Radium Lampenwerk GmbH, Wipperfürth, Germany)) and with temperatures set to 35 ◦ C/26 ◦ C (day/night) and with a day length of 14 h. The photosynthetically active radiation was set to 400 ␮mol m−2 s−1 . The control plants were moved into a climate chamber with temperatures set to 20 ◦ C/12 ◦ C (day/night). The relative humidity was controlled around 60% in the control and 70% in the heat treatment chamber. After the heat stress treatment, all plants were moved outdoors again until maturity. 2.2. Gas exchange parameters and chlorophyll content After 5 days of heat stress treatment, flag leaves were used for the gas exchange measurements according to Wang et al. [12]. The LI-6400 system (LI-COR Biosciences, Lincoln, NE, USA) was used to measure photosynthesis rates from 8:30 a.m. to 11:30 a.m. with the light level set at 1200 ␮mol m−2 s−1 . The response curves of net

carbon assimilation rate versus intercellular CO2 concentration (A/Ci ) were determined in three biological replicates (flag leaves) using the LI-COR “A/Ci curve” program, with CO2 concentrations set to 400, 300, 200, 150, 100, 50, 400, 800 and 1500 ppm. The maximum carboxylation rate of Rubisco (Vmax ), maximum electron transport rate (Jmax ), triose phosphate utilization (TPU) and saturated net photosynthesis rate (Asat ) were determined according to Long and Bernacchi [28]. Chlorophyll content was measured on six biological replicates (leaves) with a chlorophyll meter SPAD502 (Soil Plant Analysis Development; Minolta, Japan). 2.3. Chlorophyll a fluorescence After 5 days of heat stress treatment, the plants were dark adapted for at least 20 min before measuring leaf chlorophyll fluorescence in the flag leaves (PAM chlorophyll fluorometer, M-series, Heinz Walz, Effeltrich, Germany). The actual PSII photochemical efficiency (PSII) and non-photochemical quenching of chlorophyll fluorescence (NPQ) were recorded. Three biological replicates (leaves from different plants in different pots) were done. 2.4. Cell membrane peroxidation and antioxidant enzyme activities The extract for determining the membrane lipid peroxidation was prepared according to Dhindsa et al. [29]. The extent of membrane lipid oxidation in flag leaves was determined by analyzing the malondialdehyde (MDA) content according to Heath and Packer [30]. Ascorbate peroxidase (APX) was assayed according to Nakano and Asada [31], glutathione reductase (GR) activity was measured according to Foyer and Halliwell [32], and dehydroascorbate reductase (DHAR) was determined according to Mishra et al. [33]. Soluble protein content was estimated by the method of Bradford [34]. The above measurements were done after 5 days of heat stress in three biological replicates (leaves). 2.5. Leaf proteomic analysis 2.5.1. Protein extraction and quantification After heat stress treatment, the flag leaves of cv. ‘810 and cv. ‘1039 were harvested for proteome analysis. Protein extraction was performed according to Rinalducci et al. [35]. Briefly, flag leaves were ground in liquid nitrogen, and then aliquots of 0.5 g were extracted with 5 mL 10% (w/v) trichloroacetic acid in acetone containing 0.07% (w/v) DTT and 1 tablet protease inhibitor cocktail (Roche, Basel, Switzerland) per 50 mL extraction solution, vortexed and incubated at −20 ◦ C overnight. The extraction was centrifuged at 35,000 × g for 1 h (4 ◦ C), and the pellet was washed three times with cold acetone containing 0.07% (w/v) DTT, incubated for 2 h and centrifuged at 20,000 × g for 30 min (4 ◦ C). The pellet was dried and then solubilised in lysis buffer containing 9 M urea, 4% (w/v) CHAPS, 1% (w/v) DTT, 1% (v/v) ampholytes pH 4–7 (GE Healthcare, Freiburg, Germany) and 35 mM Tris (Sigma). The mixture was centrifuged at 12,000 × g for 20 min (room temperature) and the supernatant was used for two-dimensional gel electrophoresis. The protein concentration was analysed according to Ramagli [36]. Three biological replicates were done. 2.5.2. Two-dimensional gel electrophoresis The IPG strips (linear pH 4–7, 18 cm, GE Healthcare) were rehydrated in 350 ␮L of solubilisation solution containing 1% ampholyte pH 4–7 (GE Healthcare), Orange G and 400 ␮g protein. After isoelectric focusing, the strips were subsequently equilibrated in 5 mL equilibration buffer (50 mM Tris–HCl pH 8.8, 6 M urea, 30% (v/v) glycerol, 2% (w/v) SDS, 0.01% (w/v) bromophenol blue) with 1%, w/v DTT for 15 min and then incubated in 5 mL equilibration buffer with

X. Wang et al. / Plant Science 230 (2015) 33–50

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Table 1 Wheat cultivars used for the heat stress screening. Cultivar origin

490 579 633 810 1039 1110 1159 Taifun Terice Vinjett

Denmark Germany Germany Afghanistan Pakistan Germany Turkey Denmark Denmark Denmark

Name

Anthesis

Balady 16 Postelberger Wechsel St.61 Hornings Grüne Dame 810 C518 Kloka WM1353 8156 White Taifun Terice Vinjett

54 69 84 53 56 57 61 58 58 59

GP Control

Heat

107 118 130 107 110 110 115 112 112 107

102 111 123 104 105 105 109 105 106 102

GP: growing period from sowing to harvest maturity (days).

2.5%, w/v iodoacetamide for 15 min. The second dimension was performed using EttanTM Daltsix Electrophoresis Unit (GE Healthcare). Strips and a molecular marker (Mark 12TM , Invitrogen, Denmark) were placed on the gels and overlaid with 0.5% molten agarose. Protein separation was set at 2 W per gel for 45 min, and then followed by 12 W per gel for around 4 h, when the dye front reached the gel bottom. After that, gels were fully stained by colloidal Coomassie Brilliant Blue G-250. 2.5.3. Image analysis The gels were scanned with a ScanMaker 9800XL, and the images were analysed using Progenesis SameSpots v 4.1 software (Nonlinear Dynamics Ltd., Newcastle, UK). ANOVA was carried out at a threshold of p ≤ 0.05, power ≥0.8 and ≥1.5-fold change in average spot volume between heat treatments and respective control were used for further MS analysis. 2.5.4. In-gel digestion and protein identification The differentially expressed spots between heat and control were subjected to in-gel trypsin digestion according to Yang et al. [37]. MALDI-TOF MS was used for the protein spot identification, then peptide mass fingerprinting data was acquired with flex analysis 3.0 software (Bruker-Daltonics, Bremen, Germany). Protein identification was performed by searching the NCBInr (National Center for Biotechnology Information, http://www.ncbi.nlm.nih.gov/) database using in-house Mascot server (http://www.matrixscience.com) integrated with BioTools v3.1 software (Bruker-Daltonics). Carbamidomethyl cysteine was chosen for global modification, variable modification, oxidation of methionine was chosen for variable modification; one missed cleavages was allowed; peptide tolerance, 80 ppm. 2.5.5. Statistical analysis Two-way ANOVA was applied to analyze differences between treatments and cultivars. Significant differences were determined by Duncan’s Multiple Range Test (Sigmaplot 11.0, Systat Software). Hierarchical clustering analysis of the ten wheat cultivars was done by SPSS Statistics (version 21). 3. Results 3.1. Effects of heat stress on gas exchange parameters and chlorophyll content The ten cultivars showed significant differences in gas exchange parameters and chlorophyll content under control and heat treatment (Table 2). Heat stress significantly decreased the rates of photosynthesis (Pn) in cv. ‘490 , cv. ‘579 , cv. ‘633 , cv. ‘1039 and cv. ‘1159 , increased Pn in cv. Taifun while no significant differences were found in cv. ‘810 , cv. ‘1110 , cv. Terice and cv. Vinjett. Stomatal

conductance (gs) significantly decreased with heat in cv. ‘490 and cv. ‘1039 , and increased (or no significant differences were found) in the other cultivars. Transpiration rate (TR) significantly increased with heat in cv. ‘490 , cv. ‘579 , cv. ‘633 , cv. ‘810 , cv. ‘1110 , cv. Taifun, cv. Terice and cv. Vinjett, decreased in cv. ‘1039 , while no significant difference was found in cv. ‘1159 . Chlorophyll content significantly decreased as a result of heat stress in most of the cultivars, while no significant differences were found in cv. ‘810 and cv. ‘1110 under heat stress, as compared with the corresponding control (Table 2). 3.2. Effects of heat stress on parameters related to A/Ci in leaves The ten cultivars showed significant differences in maximum carboxylation rate of Rubisco (Vmax ), maximum photosynthetic electron transport rate (Jmax ), triose phosphate utilization (TPU) and saturated net photosynthesis rate (Asat ). Compared with the corresponding control, heat stress significantly increased Vmax and Jmax in cv. ‘490 , cv. ‘579 , cv. ‘810 , cv. Taifun, cv. Terice, cv. Vinjett, while no significant difference was found in cv. ‘633 , cv. ‘1110 and cv. ‘1159 . TPU significantly decreased in cv. ‘490 , cv. ‘633 and cv. ‘1159 , while increases or no significant changes were found in cv. ‘810 , cv. ‘579 , cv. ‘1110 , cv. Taifun, cv. Terice and cv. Vinjett under heat stress, compared to the corresponding control (Table 3). However, Asat significantly decreased in cv. ‘490 and cv. ‘633 , increased in cv. ‘810 and cv. Taifun, while no significant differences in the other cultivars were detected (Table 3). 3.3. Effects of the heat stress on antioxidant activities and cell membrane lipid peroxidation The ten cultivars showed significant differences in antioxidant enzyme activities and cell membrane lipid peroxidation measured as the malondialdehyde (MDA) content (Table 4). Heat stress significantly decreased the activities of ascorbate peroxidase (APX) only in cv. ‘579 . Glutathione reductase (GR) activities significantly decreased with heat stress in cv. ‘490 , cv. ‘633 , cv. ‘1039 and cv. ‘1159 . Dehydroascorbate reductase (DHAR) activities significantly decreased in cv. ‘490 , cv. ‘633 and cv. ‘1039 . MDA content significantly increased in cv. ‘490 , cv. ‘633 , cv. ‘1039 and cv. ‘1159 , while no significant differences were found in the other cultivars (Table 4). 3.4. Effects of heat stress on non-photochemical quenching (NPQ) and actual PSII photochemical efficiency (PSII) Heat stress increased NPQ in cv. ‘1039 and cv. ‘579 , decreased NPQ in Terice while no significant differences were detected in the other cultivars, compared to the corresponding control (Fig. 1). PSII significantly decreased with heat in cv. ‘490 , cv. ‘1039 , cv.

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Table 2 Effects of heat stress during grain filling on the gas exchange parameters (photosynthetic rates (Pn), stomatal conductance (gs), transpiration rate (TR), and chlorophyll content (SPAD value) in leaves of ten wheat cultivars. Cultivar

490 579 633 810 1039 1110 1159 Taifun Terice Vinjett Cultivars Treatments Cultivars × Treatments

Pn (␮mol CO2 m−2 s−1 )

gs (mol H2 O m−2 s−1 )

TR (mmol H2 O m−2 s−1 )

SPAD value

Control

Control

Control

Control

A

20.1a 13.5cA 13.5cA 17.4abA 15.2bcA 13.5cA 13.7cA 11.7cB 12.7cA 13.1cA

Heat B

Heat

A

12.0bcd 9.6dB 8.4dB 18.7aA 1.6eB 12.1bcdA 10.3cdB 15.6abA 11.4cdA 13.9bcA

B

0.74a 0.26bA 0.40bA 0.51abA 0.42bA 0.33bA 0.38bA 0.20bA 0.45bA 0.21bB

Heat

B

0.34b 0.35bA 0.59abA 0.74aA 0.03cB 0.36bA 0.25bcA 0.35bA 0.42bA 0.48abA

A

2.0cd 2.0cdB 4.2bB 5.9aB 2.6cdA 1.6cdB 3.0bcA 1.2dB 2.2cdB 1.8cdB

A

3.9fg 7.3bcA 8.0bA 11.9aA 0.8hB 3.3gA 4.3efgA 5.9cdeA 6.2bcdA 5.2defA

53.0a 49.2bA 39.8cA 49.9bA 48.7bA 48.4bA 49.8bA 53.8aA 54.3aA 49.2bA

***

**

***

***

ns

***

***

***

**

***

***

Heat 41.1dB 44.7cB 30.5eB 47.9bA 32.1eB 47.6bA 42.5dB 51.2aB 50.4aB 42.0dB

***

Data are means of the three biological replicates (n = 3). Different lowercase letters denote statistically significant differences (p < 0.05) among cultivars as analysed by Duncan’s Multiple Range Test. Different superscript uppercase letters indicate statistically significant differences (p < 0.05) between control and heat treatment within the same cultivar as analysed by Duncan’s Multiple Range Test. SPAD value: The value was detected by Soil Plant Analysis Development (SPAD) chlorophyll meter. ns: no significant difference. ** Significant difference at p < 0.01. *** Significant difference at p < 0.001. Table 3 Effects of heat stress during grain filling on the maximum carboxylation rate of Rubisco (Vmax ), maximum photosynthetic electron transport rate (Jmax ), triose phosphate utilization (TPU) and saturated net photosynthetic rate (Asat ) in leaves of ten wheat cultivars. Cultivar

490 579 633 810 1039 1110 1159 Taifun Terice Vinjett Cultivars Treatments Cultivars × Treatments

Vmax (␮mol m−2 s−1 )

Jmax (␮mol m−2 s−1 )

TPU (␮mol m−2 s−1 )

Asat (␮mol CO2 m−2 s−1 )

Control

Heat

Control

Heat

Control

Heat

Control

Heat

53abcB 54aB 41cA 42bcB 33c 38bcA 47abA 41bcB 45abcB 43bcB

80bA 71bA 38dA 103aA nd 53cA 54cA 81bA 79bA 68bcA

46abB 49aB 35cdA 38bcdB 29d 35cdA 43abcA 39abcB 43abcB 38bcdB

87bA 74bcA 39eA 107aA nd 55dA 57dA 85bcA 81bcA 70cdA

9.9abA 10.3aA 7.4cdA 7.7cdB 6d 7.3cdA 9.3abcA 8.2abcdA 9abcA 7.9bcA

7.6bcB 7.6bcA 4.1dB 12.1aA nd 6.3cA 6.2cB 9.2bA 9.2bA 7.7bcA

32.8aA 31.1abA 33cA 24.3cB 23.5c 22.8cA 27.1bcA 24.1cB 25.8bcA 25.5bcA

23.4bcB 24.1bcA 13.5dB 40.2aA nd 20.8cdA 20.3cdA 31.2bA 30bA 26.3bcA

***

***

**

***

***

***

**

ni

ni

ni

ns ni

Data were shown are means of three biological replicates (n = 3). Different lowercase letters denote statistically significant differences (p < 0.05) among cultivars as analysed by Duncan’s Multiple Range Test. The different uppercase superscripts means statistically significant differences (p < 0.05) between control and heat treatment in the same cultivar as analysed by Duncan’s Multiple Range Test. ns: no significant difference. nd: not detectable. ni: no interaction. ** Significant difference at p < 0.01. *** Significant difference at p < 0.001. Table 4 Effects of heat stress during grain filling on the activities of antioxidative enzymes and on MDA content in leaves of ten wheat cultivars. Cultivar

490 579 633 810 1039 1110 1159 Taifun Terice Vinjett Cultivars Treatments Cultivars × Treatments

APX

GR

DHAR

MDA

Control

Heat

Control

Heat

Control

Heat

Control

Heat

15.7abA 11.6abA 10.68abA 18.78aA 14.54abA 12.67abA 15.33abA 13.87abA 9.75bA 13.93abA

19.04aA 3.00cB 13.63abA 16.23aA 13.22abA 10.53abA 14.51abA 10.58abcA 8.48bcA 12.11abA

37.11bA 24.202bA 32.27bA 31.86bA 34.07bA 25.34bA 53.69aA 30.72bA 30.95bA 23.33bA

24.18abB 27.88abA 19.68bB 31.91abA 23.75abB 28.14abA 29.28abB 25.23abA 35.34aA 18.72bA

0.19bcA 0.14bcA 0.29aA 0.20abA 0.14bcA 0.11cA 0.23abA 0.18bcA 0.12cA 0.18bcA

0.11bcB 0.13bcA 0.12bcB 0.20abA 0.09cB 0.10bcA 0.16bcA 0.21aA 0.13bcA 0.21aA

65.4abB 70.1aA 50.0bcB 46.1cA 65.0abB 57.8abcA 47.9bcB 43.2cA 66.3abA 61.7abcA

89.2aA 69.2bcdA 75.3abcA 47.2eA 84.4abA 52.5eA 86.4abA 54.0deA 61.3cdeA 60.3cdeA

**

**

**

***

ns ns

**

**

***

**

**

**

APX (␮mol mg−1 protein min−1 ): Ascorbate peroxidases, GR (nmol mg−1 protein min−1 ): glutathione reductase, DHAR (␮mol mg−1 protein min−1 ): dehydroascorbate reductase, MDA (nmol mg−1 FW). Malondialdehyde. Data shown are means of three biological replicates (n = 3). Different lowercase letters denote statistically significant differences (p < 0.05) among cultivars as analysed by Duncan’s Multiple Range Test. The different uppercase superscripts means statistically significant differences (p < 0.05) between control and heat treatment in the same cultivar as analysed by Duncan’s Multiple Range Test. ns: no significant difference. ** Significant difference at p < 0.01. *** Significant difference at p < 0.001.

X. Wang et al. / Plant Science 230 (2015) 33–50

37

Fig. 1. Effects of heat stress on non-photochemical quenching (NPQ) and actual photochemical efficiency (PSII) in leaves of ten wheat cultivars. NPQ (A) and PSII (B) of cultivars ‘490 , ‘633 , ‘1039 and ‘1159 under control and heat-stress. NPQ (C) and PSII (D) of cultivars ‘579 , ‘810 and ‘1110 . NPQ (E) and PSII (F) of cultivars Taifun, Terice and Vinjett. Letters after cultivars indicate the treatments C: control; H: heat.

‘1159 , cv. ‘633 and cv. ‘579 , increased in cv. ‘1110 , while no significant differences were found in cv. ‘810 , cv. Terice, cv. Taifun and cv. Vinjett, compared to the corresponding control (Fig. 1).

3.5. Hierarchical clustering analysis Based on the photosynthesis rates (Pn), MDA content and grain yield (results showed in Vignjevic et al. [38]), the ten cultivars were classified into two groups (the squared Euclidean distance was 10 to 25), namely group I - relatively heat tolerant (cv. ‘810 , cv. ‘1110 , cv. ‘579 , cv. Terice, cv. Taifun and cv. Vinjett) and group II - relatively heat sensitive (cv. ‘633 , cv. ‘1159 , cv. ‘490 and cv. ‘1039 ) (Fig. 2). Based on the results, cv. ‘810 (heat-tolerant cultivar) and cv. ‘1039 (heat-sensitive cultivar) were chosen for further proteome analysis (Fig. 2).

3.6. Protein profiles in heat-tolerant cv. ‘810 and heat-sensitive cv. ‘1039 There were around 800 and 700 protein spots detected in cv. ‘810 and cv. ‘1039 , respectively. In the tolerant cv. ‘810 , 49 protein spots changed in abundance in response to the heat treatment compared with the control, 36 increased, and 13 decreased in abundance; 43 of 49 protein spots were identified (Fig. 3A and Table 5). In the sensitive cv. ‘1039 , 41 protein spots changed in abundance in response to the heat treatment compared with the control, 15 increased and 26 decreased in abundance; 33 of 41 protein spots were identified (Fig. 3B and Table 6). According to [39] these proteins were classified into the groups: energy, protein destination and storage, transport, defence, metabolism, second metabolism, signal transduction, cell structure and unknown function (Fig. 4).

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X. Wang et al. / Plant Science 230 (2015) 33–50

Table 5 List of proteins differently expressed in leaves of cv. ‘810 under heat stress analyzed by MALDI TOF-MS. Spots no. Accession no.

Protein name

Taxonomy

TMr/pIa

EMr/pIb

E-valuec

Match no.d SCe

Cluster

Spot abundance and FCf

Increased abundance under heat treatment

1e+7 206

gi|7960277

Rubisco activase B

Triticum aestivum

48/6.9

40/6.0

1.5E-14

28

49

Energy

2.3

5e+6 0 8e+6

227

gi|313574196

Rubisco activase small isoform

Hordeum vulgare

47/7.6

45/5.3

3.8E-11

23

49

Energy

1.5

4e+6 0

1e+7 240

gi|7960277

Rubisco activase B

Triticum aestivum

48/6.9

40/5.7

1.9E-12

25

39

Energy

1.8

5e+6 0 1e+7

224

gi|7960277

Rubisco activase B

Triticum aestivum

48/6.9

43/5.5

1.2E-07

25

48

Energy

1.5

5e+6 0

1e+7 235

gi|115392208

Rubisco activase

Triticum aestivum

40/6.5

40/5.6

0.0028

15

44

Energy

1.5

5e+6 0

4e+6 239

gi|62176930

Rubisco small subunit

Triticum durum

19/8.6

33/6.0

0.011

8

48

Energy

1.6

2e+6 0 4e+6

258

gi|12344

Rubisco large subunit

Triticum aestivum

47/6.6

28/6.5

7.6E-07

12

25

Energy

1.9

2e+6 0

2e+6 307

gi|32966580

Rubisco large subunit

Triticum aestivum

53/6.2

31/5.0

1.2E-05

14

25

Energy

1.7

1e+6 0

1e+6 281

gi|32966580

Rubisco large subunit

Triticum aestivum

53/6.2

75/5.1

1.5E-12

24

34

Energy

1.5

5e+5 0 6e+6

1.8 226

gi|32966580

Rubisco large subunit

Triticum aestivum

53/6.2

89/6.3

1.5E-07

17

29

Energy

3e+6 0

1e+6 291

gi|326487308

Oxygen-evolving Hordeum vulgare enhancer protein 1, chloroplastic

35/5.8

33/4.9

1.2E-04

11

38

Energy

5e+5 0

1.5

X. Wang et al. / Plant Science 230 (2015) 33–50

39

Table 5 (Continued) Spots no. Accession no.

Protein name

Taxonomy

TMr/pIa

EMr/pIb

E-valuec

Match no.d SCe

Cluster

Spot abundance and FCf

1e+7 204

gi|326509995

Glyceraldehyde-3phosphate dehydrogenase B, chloroplastic

Hordeum vulgare

47/6

46/5.9

1.9E-18

24

48

Energy

5e+6 0

4e+6 278

gi|326500100

Glyceraldehyde-3phosphate dehydrogenase A, chloroplastic

Hordeum vulgare

43/7.6

39/6.4

4.8E-06

12

31

Energy

gi|326507780

0

Glyceraldehyde-3phosphate dehydrogenase B, chloroplastic

Hordeum vulgare

Bp2A protein, partial

Triticum dicoccoides 26/5.9

47/5.9

45/6.0

3.8E-05

10

19

Energy

gi|133872436

1.6

2e+6 0 2e+6

306

1.6

2e+6

4e+6 285

1.6

67/5.6

4.8E-09

17

71

Energy

1.7

1e+6 0 2e+6

252

gi|326493350

Isocitrate dehydrogenase [NADP], chloroplastic

Hordeum vulgare

46/6.0

47/6.3

0.0012

12

35

Energy

1e+6 0

4e+6 202

gi|115466004

Os06g0114000 Oryza sativa (60 kDa chaperonin subunit beta)

64/5.6

60/5.3

2.9E-04

17

27

gi|115466004

Oryza sativa Os06g0114000 (60 kDa chaperonin subunit beta)

64/5.6

61/5.2

1.5E-06

14

28

gi|2493650

60 kDa chaperonin subunit beta

Secale cereale

54/4.9

60/5.3

3.8E-13

22

44

gi|134102

60 kDa chaperonin subunit alpha

Triticum aestivum

58/4.8

61/4.9

3.8E-18

19

32

Protein destination and storage 0

gi|134102

60 kDa chaperonin subunit alpha

Triticum aestivum

58/4.8

60/5.0

1.9E-07

16

27

gi|52075839

Putative chloroplast protease

Oryza sativa

51/4.9

68/5.5

3E-05

11

25

1.9

2e+6 Protein destination and storage 0 6e+6

201

1.9

1e+6 Protein destination and storage 0

4e+6 284

1.8

2e+6

2e+6 232

1.7

Protein 1e+6 destination and storage 0

4e+6 225

2.3

2e+6 Protein destination and storage 0

2e+6 260

1.5

3e+6 Protein destination and storage 0

1.5

40

X. Wang et al. / Plant Science 230 (2015) 33–50

Table 5 (Continued) Spots no. Accession no.

Protein name

Taxonomy

TMr/pIa

EMr/pIb

E-valuec

Match no.d SCe

Cluster

Spot abundance and FCf

2e+6 205

gi|357147646

Peptidyl-prolyl Brachypodium cis-trans isomerase distachyon CYP38

46/4.8

43/4.4

6.5E-07

13

30

Protein 1e+6 destination and storage 0

4e+6 266

gi|254211611

70 kDa heat shock protein

Triticum aestivum

74/5.0

70/4.8

7.6E-12

24

32

gi|14017579

ATP synthase CF1 beta subunit

Triticum aestivum

53/5.1

30/5.3

1.9E-06

20

45

1.5

Protein 2e+6 destination and storage 0

4e+6 243

1.5

Transport

1.5

2e+6 0

2e+6 267

gi|14017569

ATP synthase CF1 alpha subunit

Triticum aestivum

55/6.1

58/6.2

3.8E-22

25

41

Transport

1.5

1e+6 0 4e+6

246

gi|14017569

ATP synthase CF1 alpha subunit

Triticum aestivum

55/6.1

56/6.3

7.6E-16

25

44

Transport

2e+6 0

2e+6 264

gi|14017569

ATP synthase CF1 alpha subunit

1.6

Triticum aestivum

55/6.1

58/5.9

0.0035

12

24

Transport

1.7

1e+6 0

6e+6 262

gi|2499477

2-Cys Hordeum vulgare peroxiredoxin BAS1, chloroplastic

23/5.5

26/4.8

1.4E-04

8

47

Defence

3e+6 0 1e+6

221

gi|2565305

Glycine decarboxylase P subunit

x Tritordeum sp.

112/6.3

93/6.5

1.9E-12

26

26

Defence

gi|2443390

Ps16 protein

1.8

5e+5 0

4e+6 293

1.8

Triticum aestivum

32/4.6

30/4.5

0.0066

8

27

1.9

Metabolism 2e+6

0 8e+6 249

gi|42733490

BRI1-KD Oryza sativa interacting protein 114

17/5.8

18/5.8

1.2E-06

10

51

Signal transduction

1.7

4e+6 0

Decreased abundance under heat treatment

4e+7 218

gi|132107

Rubisco small chain clone 512

Triticum aestivum

13/5.8

14/6.2

4.8E-09

13

73

Energy

2e+7 0

0.4

X. Wang et al. / Plant Science 230 (2015) 33–50

41

Table 5 (Continued) Spots no. Accession no.

Protein name

Taxonomy

TMr/pIa

EMr/pIb

E-valuec

Match no.d SCe

Cluster

Spot abundance and FCf

1e+7 223

gi|11990901

Rubisco small subunit

Triticum aestivum

20/8.8

14/5.6

3.8E-06

8

44

Energy

5e+6 0

8e+6 270

gi|379036031

Rubisco large subunit, partial

0.6

Leymus arenarius

18/5.2

22/5.5

4.8E-08

8

38

Energy

0.6

4e+6 0 6e+6

214

gi|379031859

Rubisco large subunit, partial

Bromus ramosus

17/4.9

20/5.5

9.5E-07

7

32

Energy

0.5

3e+6 0 1e+6

230

gi|32966580

Rubisco large subunit

Triticum aestivum

53/6.2

65/5.0

7.2E-04

10

16

Energy

0.7

5e+5 0

4e+6

0.5 217

gi|54401456

Rubisco large subunit

Elymus sibiricus

53/6.2

15/4.9

0.0038

8

15

Energy

2e+6 0 2e+6

297

gi|326493350

Isocitrate dehydrogenase [NADP], chloroplastic

Hordeum vulgare

46/6.0

47/6.3

7.6E-09

17

44

Energy

0

4e+6 257

gi|121340

Plastid glutamine Triticum aestivum synthetase isoform GS2c

47/5.8

38/4.9

0.016

10

16

Metabolism

gi|71362640

Plastid glutamine Triticum aestivum synthetase isoform GS2c

0

47/5.8

37/5.0

4.8E-07

13

22

gi|122220777

SHordeum vulgare adenosylmethionine synthase 3

0.6

Metabolism 4e+6

0 4e+6

273

0.7

2e+6

8e+6 292

0.7

1e+6

43/5.5

48/5.8

7.6E-06

9

25

0.6

Secondary 2e+6 metabolism

0 2e+6

0.5 238

gi|326499510

Predicted protein

Hordeum vulgare

35/8.9

32/5.5

0.0052

10

26

unknown

1e+6 0

a b c d e f

Theoretical Mr/pI. Experimental Mr/pI values were calculated using the Progenesis SameSpots software. The expect value (E) lower than 0.05 can used to judge the significant match. Match no. means the number of peptides identified and matching with protein peptides in the database. Sequence coverage (%). white column stands for control and black column stands for heat. FC means the fold change in heat treatment compared with control.

42

X. Wang et al. / Plant Science 230 (2015) 33–50

Table 6 List of proteins differently expressed in leaves of cv. ‘1039 under heat stress analyzed by MALDI TOF-MS. Spots no. Accession no.

Protein name

Taxonomy

TMr/pIa

EMr/pIb

E-valuec

Match nod

SCe

Cluster

Spots abundance and FCf

Increased abundance under heat treatment

2e+7

1.6 39

gi|313574196

Rubisco activase small isoform

Hordeum vulgare

47/7.6

48/5.4

3.8E-13

27

54

Energy

1e+7 0 1e+7

34

gi|7960277

Rubisco activase B

Triticum aestivum

48/7.0

49/5.3

1.5E-10

21

41

Energy

5e+6

1.7

0

4e+6 65

gi|7960277

Rubisco activase B

Triticum aestivum

48/6.9

43/5.9

3E-07

17

30

Energy

3.4

2e+6 0 1e+6

3.7 72

gi|1173347

Sedoheptulose bisphosphatase

Triticum aestivum

43/6.0

38/5.2

0.037

13

26

Energy

5e+5 0 1e+7

30

gi|223018643

Chloroplast fructosebisphosphate aldolase

Triticum aestivum

42/5.9

40/5.7

2.4E-06

14

31

Energy

5e+6 0

2e+6 7

gi|134102

60 kDa chaperonin subunit alpha

Triticum aestivum

58/4.8

66/5.2

1.2E-06

15

33

Protein destination and storage

gi|134102

60 kDa chaperonin subunit alpha

Triticum aestivum

58/4.8

66/5.3

7.6E-13

16

30

Protein destination and storage

0

gi|134102

60 kDa chaperonin subunit alpha

Triticum aestivum

58/4.8

65/5.0

1.9E-21

32

52

Protein destination and storage

0

gi|134102

60 kDa chaperonin subunit alpha

Triticum aestivum

58/4.8

65/5.0

1.9E-09

21

35

Protein destination and storage

0

gi|115466004

Oryza sativa Os06g0114000 (60 kDa chaperonin subunit beta)

64/5.6

65/5.3

3E-07

23

39

Protein destination and storage

0

gi|326520756

Aspartate aminotransferase, chloroplastic

Hordeum vulgare

50/8.5

49/6.1

1.9E-09

12

26

Metabolism

2

2e+6 0

2e+6 97

2

1e+6

4e+6 44

1.9

1e+6

2e+6 98

1.9

2e+6

2e+6 60

1.8

1e+6

4e+6 8

1.5

1e+6 0

1.5

X. Wang et al. / Plant Science 230 (2015) 33–50

43

Table 6 (Continued) Spots no. Accession no.

Protein name

Taxonomy

TMr/pIa

EMr/pIb

E-valuec

Match nod

SCe

Cluster

Spots abundance and FCf

4e+6 106

gi|297849338

Hypothetical protein ARALYDRAFT 312058

Arabidopsis lyrata

21/9.2

20/6.2

0.011

9

71

Unknown

1.6

2e+6 0

Decreased abundance under heat treatment

4e+7 13

gi|32966580

Rubisco large subunit

Triticum aestivum

53/6.2

55/6.5

1.2E-12

20

28

Energy

0.5

2e+7 0

4e+6 54

gi|125380586

Rubisco large subunit (partial)

Agropyron cristatum

28/6.3

24/5.5

2.6E-04

8

24

Energy

0.5

2e+6 0

4e+6 59

gi|339742637

Rubisco large subunit

Triticum aestivum

22/7.5

21/5.5

0.0046

7

29

Energy

0.6

2e+6 0 2e+6

114

gi|32966580

Rubisco large subunit

Triticum aestivum

53/6.2

71/5.3

9.5E-07

14

29

Energy

0.5

1e+6 0

2e+6 111

gi|32966580

Rubisco large subunit

Triticum aestivum

53/6.2

82/5.3

0.021

10

21

Energy

0.3

1e+6 0

2e+6

0.5 2

gi|32400838

Pyruvate orthophosphate dikinase, partial

Triticum aestivum

33/5.0

95/5.5

0.0027

11

28

Energy

1e+6 0 2e+6

52

gi|326507780

Glyceraldehyde-3phosphate dehydrogenase B, chloroplastic

Hordeum vulgare

47/5.9

49/6

0.036

8

15

Energy

0 1e+6

94

gi|32400802

Phosphoglycerate mutase, partial

0.6

1e+6

Triticum aestivum

30/5.4

66/5.7

1.2E-09

15

60

Energy

0.5

5e+5 0

4e+6 61

gi|75114857

ATP-dependent zinc metalloprotease FtsH 2, chloroplastic

Oryza sativa

73/5.5

70/5.3

2.4E-07

23

32

Protein destination and storage

2e+6 0

0.5

44

X. Wang et al. / Plant Science 230 (2015) 33–50

Table 6 (Continued) Spots no. Accession no.

Protein name

Taxonomy

TMr/pIa

EMr/pIb

E-valuec

Match nod

SCe

Cluster

Spots abundance and FCf

2e+6

0.6 51

gi|326495158

ER molecular chaperone

Hordeum vulgare

73/5.1

81/5.3

7.6E-10

17

29

Protein destination and storage

1e+6 0 4e+6

5

gi|254211611

70 kDa heat shock protein

Triticum aestivum

74/5.0

82/5.3

3.8E-08

25

35

Protein destination and storage

0.5

2e+6 0

4e+5

0.5 67

gi|290131414

70 kDa heat shock protein

Triticum aestivum

74/5.0

77/5.1

3E-08

18

24

Protein destination and storage

2e+5 0

4e+6 15

gi|14017579

ATP synthase CF1 beta subunit

Triticum aestivum

54/5.1

33/5.3

9.5E-05

11

25

Transport

0.6

2e+6 0 2e+6

0.6 78

gi|14017569

ATP synthase CF1 alpha subunit

Triticum aestivum

55/6.1

63/5.8

7.6E-19

21

33

Transport

1e+6 0

2e+6 88

gi|14017569

ATP synthase CF1 alpha subunit

Triticum aestivum

55/6.1

60/6.3

2.4E-21

24

40

Transport

0.6

1e+6 0 1e+7

53

gi|115444771

Os02g0192700 (Peroxiredoxin IIE-2)

Oryza sativa

23/6.2

20/4.7

0.03

7

35

Defence

0

2e+6 101

gi|226897533

Ascorbate peroxidase

0.5

5e+6

Triticum aestivum

27/5.5

29/5.2

5.2E-05

15

40

Defence

0.7

1e+6 0 2e+6

62

gi|357134512

Dihydrolipoyl Brachypodium dehydrogenase 1, distachyon mitochondrial-like

53/6.9

67/5.1

0.04

8

13

Defence

1e+6

0.6

0 4e+6

0.4 118

gi|2565305

Glycine decarboxylase P subunit

x Tritordeum sp.

111/6.3

95/6.4

0.0028

16

11

Defence

2e+6 0

4e+6 56

gi|122220777

SHordeum vulgare adenosylmethionine synthase 3

43/5.5

52/5.8

0.0018

11

28

Secondary metabolism

2e+6 0

0.6

X. Wang et al. / Plant Science 230 (2015) 33–50

45

Table 6 (Continued) Spots no. Accession no.

Protein name

Taxonomy

TMr/pIa

EMr/pIb

E-valuec

Match nod

SCe

Cluster

Spots abundance and FCf

2e+6 37

gi|255684860

Actin

Triticum aestivum

28/5.3

49/5.5

6E-05

10

42

Cell structure

0.7

1e+6 0

a b c d e f

Theoretical Mr/pI. Experimental Mr/pI values were calculated using the Progenesis SameSpots software. The expect value (E) lower than 0.05 can used to judge the significant match. Match no. means the number of peptides identified and matching with protein peptides in the database. Sequence coverage (%). White column stands for control and black column stands for heat. FC means the fold change in heat treatment compared with control.

There were 54% of the protein spots in the energy group in cv. ‘810 , and 40% in cv. ‘1039 . In cv. ‘810 , 16 protein spots belonging to the energy group increased and 7 decreased in abundance. The proteins which increased in abundance included Rubisco activase (RCA, spots 206, 224, 227, 235 and 240), Rubisco small subunit (RSS, spots 239), Rubisco large subunit (RLS, spots 226, 258, 281 and 307), oxygen evolving enhancer protein 1 (OEE1, spot 291), glyceraldehyde-3-phosphate dehydrogenase (GAPDH, spots 204, 278 and 285), Bp2A protein (spot 306) and isocitrate dehydrogenase (spot 252). Nine spots identified as RSS (spots 218 and 223), RLS (spots 214, 217, 230 and 270) and NADP-isocitrate dehydrogenase (spot 297) decreased in abundance (Table 5). Identified proteins spots (228 and 307) have a lower size than the theoretical which could have been the result from spot degradation. Protein spots (239, 281, 226 and 217) that have a larger size than the theoretical could have been the result of posttranslational modification, spot 306 have a larger size than theoretical could because only a partial gene has been found. There were 5 protein spots that increased and 8 spots that decreased in abundance in the energy group in cv. ‘1039 . The increased proteins included RCA (spots 34, 39 and 65), sedoheptulose bisphosphatase (spot 72) and fructose-bisphosphate aldolase (spot 30). The decreased proteins included RLS (spots 13, 54, 59, 111 and 114), pyruvate orthophosphate dikinase (spot 2), GAPDH (spot 52), phosphoglycerate mutase (spot 94). Proteins spots (111

and 114) that have a larger size than the theoretical could have been the result from the posttranslational modification, spot 94 have a larger size than the theoretical could because only a partial gene has been found. There were 19% and 27% of the protein spots identified as protein destination and storage in cv. ‘810 and cv. ‘1039 , respectively. The 60 kDa chaperonin subunit CPN60 (spots 202, 225, 232, 260 and 284), chloroplast protease (spot 201), peptidyl-prolyl-cis-trans isomerase (spot 205) and 70 kDa heat shock protein HSP70, (spot 266) increased in abundance in cv. ‘810 . CPN60 (spots 7, 8, 44, 60 and 98) increased in abundance in cv. ‘1039 , while HSP70 (spots 5 and 67), ATP-dependent zinc metalloprotease FtsH 2 (spot 61) and ER molecular chaperone (spot 51) decreased in abundance in cv. ‘1039 . There were 9% of the spots identified as transport proteins in cv. ‘810 and cv. ‘1039 , respectively. The ATP synthase CF1 subunit (spots 243, 246, 264 and 267) increased in abundance in cv. ‘810 , while ATP synthase CF1 subunit (spots 15, 78 and 88) decreased in abundance in cv. ‘1039 . Protein spots 243 and 15 have a lower size than the theoretical which could have been the result from spot degradation. There were 5% and 12% of the spots identified as defence proteins in cv. ‘810 and cv. ‘1039 , respectively. 2-Cys peroxiredoxin BAS1 (spot 262), and glycine decarboxylase P subunit (spot 221) increased in abundance in cv. ‘810 under heat stress, compared with control. In cv. ‘1039 , proteins involved in defence, were decreased in abundance under heat stress, including Os02g0192700 (peroxiredoxin IIE-2, spot 53), ascorbate peroxidase (APX, spot 101), dihydrolipoyl dehydrogenase 1 (spot 62) and glycine decarboxylase P subunit (spot 118). There were 7% of the identified protein spots identified as metabolism group in cv. ‘810 and 3% in cv. ‘1039 . Glutamine synthetase (GS, spots 257 and 292) decreased in abundance in cv. ‘810 under heat stress. Ps16 protein (spot 293) increased in abundance in cv. ‘810 . Aspartate aminotransferase (spot 97) increased in abundance in cv. ‘1039 . BRI1-KD interacting protein 114 (spot 249) which involved in signal transduction increased in abundance in cv. ‘810 . Actin (spot 37) decreased in abundance in cv. ‘1039 . Spot 273 and spot 56, which both were identified as S-adenosylmethionine synthase 3 (SAMS), decreased in abundance in cv. ‘810 and cv. ‘1039 , respectively. Protein spot 37 has a larger size than the theoretical could have been the result of posttranslational modification. 4. Discussion 4.1. Physiological studies of heat stress in wheat

Fig. 2. Hierarchical clustering analysis of ten wheat cultivars based on leaf photosynthesis (Pn), malondialdehyde (MDA) content and grain yield (results showed in Vignjevic et al. [38]).

Photosynthesis is known to be significantly affected by heat stress [40]. In the present study, photosynthesis rates significantly

46

X. Wang et al. / Plant Science 230 (2015) 33–50

Fig. 3. Representative 2-DE gels from control of wheat leaf proteins in cv. ‘810 (A) and cv. ‘1039 (B). Representative 2-DE gel analysed using Progenesis Samespot software comparing control and heat- stress treatments in cv. ‘810 (A) and cv. ‘1039 (B). Proteins changing in abundance as a result of heat stress are indicated by arrows and descriptions of them are listed in Tables 5 and 6. Mr: relative molecular mass; pI: isoelectric point.

decreased in cultivars belonging to group II (cv. ‘633 , cv. ‘1159 , cv. ‘490 and cv. ‘1039 ) and cv. ‘579 belonging to group I, while photosynthesis rates increased or showed no significant change in the other cultivars in group I (cv. ‘810 , cv. ‘1110 , cv. Terice, cv. Vinjett and cv. Taifun) (Table 2). Plant chlorophyll content is an important factor in determining photosynthetic capacity [41]. Chlorophyll content is positively correlated with the stability of the thylakoid membrane under heat stress, and can be used for screening for heat stress in wheat [42]. Here, leaf chlorophyll content was decreased by heat stress in most of the cultivars, except in cv. ‘810 and cv. ‘1110 , which is related to the higher photosynthetic activity in these cultivars under heat stress (Table 2).

Vmax , the maximum carboxylation rate of Rubisco, is known to increase with increasing temperature [43]. The photosynthesis rate is limited by photosynthetic electron transport rate (Jmax ) under high temperature stress [44]. Decreased TPU indicated that photosynthesis is inhibited by increased oxygen concentration [45]. Vmax and Jmax were not significantly different or increased in all cultivars under heat stress, while TPU significantly decreased in cv. ‘490 , cv. ‘633 and cv. ‘1159 (Table 3). This may indicate that increased oxygen concentration caused oxidative stress in sensitive cultivars. In a previous experiment we have shown that the decrease in photosynthesis rates in wheat as a result of heat stress was mainly due to damage to PSII [12]. PSII significantly decreased in cv. ‘490 , cv. ‘633 , cv. ‘1159 and cv. ‘1039 in group II and cv. ‘579

X. Wang et al. / Plant Science 230 (2015) 33–50

47

showed higher activities of CAT and SOD, contributing to the higher efficiency of ROS scavenging capability in primed than non-primed plants under heat stress [12]. GR and DHAR regulate the cellular ascorbic acid redox state and help to scavenge excess ROS [22]. We have recently shown that GR activity in both chloroplasts and mitochondria decreased significantly with heat stress, and that increased GR activity in mitochondria is consistent with lower MDA content in wheat seedlings [18]. DHAR and GR can be significantly inactivated by severe heat stress, while higher activities of DHAR and GR in transgenic plants contributed to the decreased oxidative damage [48]. Here, the significantly increased MDA content in cv. ‘490 , cv. ‘633 , cv. ‘1039 and cv. ‘1159 indicated cell membrane peroxidation by heat stress, which in accordance with decreased activities of GR and DHAR in cv. ‘490 , cv. ‘633 and cv. ‘1039 , and the decreased activities of GR in cv. ‘1159 , under heat stress (Table 4). Thus, we propose that the alleviated oxidative damage through increasing activities of antioxidant enzymes contributed to the thermo-tolerance of the cultivars in group I in response to heat stress. 4.2. Proteomic studies of heat stress effects in wheat

Fig. 4. Functional classification and distribution of the proteins changing in abundance in cv. ‘810 (A) and cv. ‘1039 (B) under heat stress during the grain filling stage. Proteins are categorized according to Bevan et al. (1998).

in group I, while PSII increased or showed no significant differences in the other cultivars in group I (Fig. 1). We have reported that the decrease in PSII under heat stress results from both the decreased rate of open reaction centres and from increased nonphotochemical quenching (NPQ) [12]. Here, the increase of NPQ in the cv. ‘579 is in accordance with decreased PSII and photosynthesis under heat stress (Fig. 1). In cv. ‘499 , cv. ‘633 and cv. ‘1159 , the decrease of PSII (and no significant differences of NPQ) under heat stress, indicated that the reaction centres were partly closed under heat stress. The significantly highest NPQ and the lowest PSII in cv. ‘1039 might be indicative of damage to the PSII caused by heat stress. Low electron transport efficiency due to malfunction of PSII can lead to increased generation of ROS [12]. In addition, ROS generated by heat stress induced oxidative damage, as exemplified by increase of the MDA content as an indicator of lipid peroxidation [12,18,46]. APX, GR and DHAR play important roles in removing H2 O2 through the ascorbate glutathione redox cycle [20]. The activity of APX can be induced by exogenous H2 O2 [47], and decrease in response to heat stress [48]. However, in other studies it was also found that APX activities did not change significantly under heat stress [49,50]. The activity of APX decreased significantly only in cv. ‘579 under heat stress compared with the corresponding control, while no significant differences of MDA content were found in cv. ‘579 (Table 4). This indicates that in this cultivar other enzymes involved in scavenging ROS, such as catalase (CAT) or superoxide dismutase (SOD) might be involved in decreasing the increased ROS production with heat stress. In wheat, heat stress significantly decreased both the gene expression and enzyme activity of CAT and SOD, while primed (pre-exposure to mild heat stress) plants

4.2.1. Increased abundance of signal transduction proteins and of heat-shock proteins after heat stress in the heat-tolerant cultivar BRI1-KD interacting protein 114 which contains nucleoside diphosphate kinases (NDKs) group I like domain may be involved in signal transduction [51,52]. It has been reported that NDKs play a role in generating nucleoside triphosphates, including GTP, which mediates ROS signalling pathways via interaction with catalases [53,54]. Previous studies showed that increased abundance of BRI1KD interacting protein 114 play roles in alleviating effects of salt stress in a tolerant wheat cultivar [55]. Here, BRI1-KD interacting protein 114 was increased in abundance in cv. ‘810 (Table 5) and may play a protective role against heat stress. Heat-shock proteins (HSPs) act as molecular chaperones to repair stress-damaged proteins, and can be induced by abiotic stresses such as drought [56], chilling [57] and heat [58]. Overexpression of HSP70 genes resulted in higher tolerance under heat stress [59,60]. In addition, HSP70 is also involved in regulating genes involved in signal transduction [61]. We found that HSP70 increased in cv. ‘810 while decreased in cv. ‘1039 in relation to the corresponding control (Tables 5 and 6). Thus the increase in abundance of the heat-shock protein in cv. ‘810 may have helped in protecting cells against heat stress. 4.2.2. Increased abundance of proteins related to photosynthesis after heat stress in the heat-tolerant cultivar The abundance of Rubisco subunits, which play an important role in the Calvin cycle, will be significantly reduced under heat stress [62,63]. RCA is one of a new type of chaperone, which play important roles in maintaining the catalytic activity of Rubisco [64], was amongst the limiting factors of photosynthesis under heat stress [65,66]. In this study, several spots identified as RLS and RCA, may have been related to transcriptional modifications or protein degradation (Table 5). Previous studies found that RCA was significantly increased in abundance by heat stress, presumably to protect the photosynthetic machinery from heat [67,68]. In our study, both the protein amount of the RCA and the RCA activity increased in abundance in tolerant cv. ‘810 under heat stress. In addition, sedoheptulose bisphosphatase and chloroplast fructose-bisphosphate aldolase are important enzymes involved in RuBP regeneration [69,70]. In the current study, sedoheptulose bisphosphatase and fructose-bisphosphate aldolase increased in abundance in cv. ‘1039 (Table 6). The OEE1 is involved in the regulation of PSII [71]. The downregulation of OEE was due to inhibition of photosynthesis under

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heat stress [72]. Here, the increased abundance of OEE1 (Table 5) consistent with the higher photosynthesis rate and higher PSII in cv. ‘810 (Fig. 1). Peptidyl-prolyl-cis-trans isomerase is required for the assembly and stabilization of PSII [73]. The chloroplast protease, ATP-dependent zinc metallo-protease FTSH complexes and ER molecular chaperone play critical roles in maintaining the normal function of chloroplasts under abiotic stress [74–76]. The peptidyl-prolyl-cis-trans isomerase and chloroplastase were significantly increased in cv. ‘810 (Table 5), while ATP-dependent zinc metalloprotease FTSH and ER molecular chaperone decreased in abundance in cv. ‘1039 (Table 6) in relation to the corresponding control, probably corresponding to the higher thermo-stability of PSII in cv. ‘810 than in cv. ‘1039 , which is also consistent with the higher actual photochemical efficiency in cv. ‘810 than in cv. ‘1039 (Fig. 2). 4.2.3. Increased abundance of proteins related to ROS scavenging after heat stress in the heat-tolerant cultivar In this study, proteins involved in stress defence increased significantly in cv. ‘810 (Table 5) and decreased in cv. ‘1039 under heat stress (Table 6). For counteracting ROS damages, APX and 2-Cys peroxiredoxin play important roles in scavenging H2 O2 [77], and peroxiredoxin IIE-2 is also involved in chloroplast redox homeostasis [78]. In this study, 2-Cys peroxiredoxin BAS1 increased in cv. ‘810 (Table 5), while APX and peroxiredoxin IIE-2 decreased in cv. ‘1039 (Table 6) in relation to the corresponding control. Dihydrolipoyl dehydrogenase (DHLD) is part of the glycine cleavage system. P- and L-proteins of the glycine cleavage system are responsible for the conversion of glycine to serine in the photorespiratory cycle [79,80]. It has been suggested that the decrease in glycine decarboxylase P subunit indicates oxidative stress [81]. In the current study, relative to the corresponding control, glycine decarboxylase P subunit increased in abundance in cv. ‘810 (Table 5), while glycine decarboxylase P subunit and dihydrolipoyl dehydrogenase decreased in abundance in cv. ‘1039 (Table 6) which may suggest that cv. ‘810 could better maintain photorespiration and alleviate oxidative stress. These results indicate that proteins involved in the ROS scavenging system increased in abundance in the heat-tolerant cv. ‘810 (Table 5) and decreased in abundance in the heat-sensitive cv. ‘1039 (Table 6), which is consistent with the higher MDA content in cv. ‘1039 , compared to cv. ‘810 , under heat stress (Table 4). Furthermore, the analysis of antioxidative enzyme activities suggest that APX activities decreased in cv. ‘1039 under heat stress is in accordance with the decreased expression of APX protein abundance in cv. ‘1039 (Table 6) under heat stress. Thus, the expression of both the protein amount and of the enzyme activities added to the higher efficiency of ROS scavenging, which contributed to the higher heat tolerance in cv. ‘810 . 4.2.4. Increased abundance of energy metabolism-related proteins after heat stress in the heat-tolerant cultivar ATP synthase CF1 increased in abundance under heat stress [25]. CF1 subunits of ATP synthase play central roles in energy transduction and are related to abiotic stress tolerance [82]. In this study, the increase in abundance of ATP synthase CF1 subunits in cv. ‘810 (Table 5), and its decrease in cv. ‘1039 (Table 6), indicated that these proteins may be involved in protecting ATP synthesis from heat stress, thereby sustaining energy production under heat stress. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), which catalyses the conversion of glyceraldehyde 3-phosphate to 1,3bisphosphoglycerate, is involved in the glycolytic pathway. Previous studies found that GAPDH was enhanced under heat stress in rice seedlings [68]. In this study, GAPDH significantly increased in abundance in cv. ‘810 (Table 5) and decreased in abundance in cv.

‘1039 (Table 6). Phosphoglycerate mutase is involved in glycolysis [83], and the increase in abundance of phosphoglycerate mutase under cold stress in rice leaves suggested increased glycolysis and energy production, which is needed by the defence processes [84]. In the present study, the induction of the proteins involved in glycolysis significantly decreased in abundance under heat stress in heat-sensitive wheat cv. ‘1039 (Table 6), and increased in abundance in heat-tolerant cv. ‘810 (Table 5). 4.2.5. Decreased abundance of proteins related to nitrogen metabolism after heat stress in heat-tolerant cultivar Glutamine synthetase (GS) plays an important role in the nitrogen metabolism by catalysing the assimilation of ammonium to glutamine [85]. GS was decreased by heat stress in roots of two grasses species [26]. In the present study, GS significantly decreased in cv. ‘810 (Table 5) which may indicate decreased nitrogen metabolism under heat stress. Aspartate aminotransferase, which transfers an ␣-amino group between aspartate and glutamate, is an important enzyme in amino acid metabolism [86]. Aspartate aminotransferase increased in abundance under heat stress in alfalfa [87]. In the current study, aspartate aminotransferase increased in abundance in cv. ‘1039 (Table 6) in relation to corresponding control, indicating the increased amino acid metabolism in sensitive cultivar under heat stress. 4.2.6. CPN60 and SAMS as heat stress markers The chaperonin 60 protein (CPN60) is involved in protecting Rubisco activase from heat denaturation [88]. In the present study, protein spots identified as CPN60 all increased in abundance in cv. ‘1039 and cv. ‘810 , indicating that CPN60 can be used as a heat stress marker. S-Adenosylmethionine synthase (SAMS) decreased in abundance in both cv. ‘810 and cv. ‘1039 . SAMS is involved in the biosynthesis of S-adenosyl-l-methionine from L-methionine and ATP [26]. SAMS is a methyl donor in lignification reactions and is also the precursor for ethylene and polyamines biosynthesis. SAMS protein increased in abundance under cold stress [89], and decreased in abundance under heat stress [26,68], indicating that lignification or polyamine accumulation was enhanced by cold stress [84] but inhibited by heat stress. 5. Conclusions Ten cultivars of wheat were used to study the effects of heat stress. Based on photosynthesis rates (Pn), cell membrane lipid peroxide (MDA) content and grain yield, six cultivars were clustered as heat-tolerant (cv. ‘810 , cv. ‘1110 , cv. ‘579 , Terice, Taifun and Vinjett) and four as heat-sensitive (cv. ‘633 , cv. ‘1159 , cv. ‘490 and cv. ‘1039 ). Proteomic analyses performed on leaves of the tolerant cv. ‘810 and the sensitive cv. ‘1039 showed increases in proteins related to signalling transduction, heat shock protein, photosynthesis, antioxidant enzyme, ATP synthase and GAPDH, while proteins related to nitrogen metabolism decreased in the tolerant cv. ‘810 compared to the sensitive cv. ‘1039 . These differently regulated proteins might play important roles in tolerance to heat stress during grain filling. Acknowledgements This paper is dedicated to the memory of our co-author Susanne Jacobsen, who died suddenly during the writing of the manuscript. We thank Bettina Viola Hansen and Ulla Andersen for their help in setting up the pot experiment, and Anne Blicher and Birgit Andersen for technical assistance The Ministry for Food, Agriculture and Fisheries of Denmark is acknowledged for a research grant (HeatWheat) to Bernd Wollenweber. The Chinese Scholarship Council is

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acknowledged for supporting Xiao Wang for her Danish PhD. We thank Centre for Advanced Food Studies (LMC) for financial support to the MS instrument. The authors have declared no conflict of interest.

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