Proteomic and Physiological Analysis of the Response of Oat (Avena sativa) Seeds to Heat Stress under Different Moisture Conditions

Plant material

Oat (“Triple crown”) seeds were supplied by the Forage Seed Laboratory of China Agricultural University, Beijing, China. The original MC and germination percentage of the oat seeds were 9.0 and 93%, respectively. The experiment was initiated in May 2014. Oat seeds were moistened and attained the safe MC (10%) and high MC (16%) according to the humid atmosphere method (Rodo and Filho, 2003). Samples were then immediately packaged in hermetically sealed aluminum foil bags with a high-power electric sealer (SINBO DZ-280/2SD, Hong Kong, China).

Heat-stress treatments

Seed samples with 10% MC in aluminum foil bags were placed in water baths (CU-600, Nanjing, China) at 35, 45, and 50°C, respectively, for 24 days. Seed samples with 16% MC were placed in water baths at 35, 45, and 50°C, respectively, for 2 days. All experiments were performed with three biological replicates. After the heat-stress treatments, the seed samples were frozen in liquid nitrogen immediately and stored at −80°C for further analysis.

Germination test

A germination test was performed within 1 h after the completion of the heat-stress treatment. Three replications of 50 seeds for each treatment were distributed in plastic boxes (11.5 × 11.5 × 2.5 cm) containing two sheets of filter paper moistened to saturation with distilled water. Plastic boxes were put in a germination chamber (GXZ, Ningbo, China) at a constant temperature of 20°C, 60% relative humidity, 8 h light and 16 h darkness. Normal seedlings were recorded every day following incubation until 10 days; germination percentage and germination index were evaluated according to criteria in the International Rules for Seed Testing (ISTA, 2013).

Determination of MDA and proline content

The MDA content was determined as described by Sofo et al. (2004). Powdered seeds (about 500 mg) were suspended in 5 mL of 5% (w/v) trichloroacetic acid, and the material was centrifuged at 10000 × g for 10 min at 4°C. Three milliliters of 0.06% (w/v) 2-thiobarbituric acid was added to the 3 mL of resulting supernatant, and the mixture was boiled for 15 min. The MDA content was quantified by measuring the absorbance at 450, 532, and 600 nm.

The proline content was determined as described by Momayezi et al. (2009). Powdered seeds (about 300 mg) were suspended in 3 mL of 3% (w/v) 5-sulfosalicylic acid, and the material was boiled for 10 min with shaking and centrifuged at 1000 × g for 10 min at room temperature. After the addition of 2.5% (w/v) acid ninhydrin, the supernatant was heated at 100°C for 30 min in a water bath; the reaction was then stopped by immersion in an ice bath. The mixture was extracted with toluene and the absorbance was measured at 520 nm.

Protein extraction

Total proteins were extracted by the phenol extraction method (Faurobert et al., 2007). Three individual seed samples (1 g) were homogenized in liquid nitrogen. The powdered seeds were suspended in 3 mL extraction buffer and then an equal volume of tris-buffered phenol was added. The phenolic phase at the top of the tube was recovered by centrifuging (6000 × g for 10 min at 4°C) and then precipitated overnight at −20°C with four volumes of cooled precipitation solution (methanol containing 0.1 M ammonium acetate). Following centrifugation (6000 × g for 10 min at 4°C), the pellet recovered was rinsed with cooled precipitation solution and 80% (w/v) acetone containing 0.07% (w/v) 2-mercaptoethanol. Finally, the pellet was air-dried and resuspended in solubilization buffer {7 M urea, 2 M thiourea, 40 mM Tris, 4% (w/v) 3-[(3-cholamidopropyl) dimethylammonio]-1-propane sulfonate (CHAPS), 1% (w/v) dithiothreitol (DTT), 1 mM EDTA}. Protein concentrations in extracts were determined by the Bradford method (Li et al., 2013), using bovine serum albumin as the standard. The quantified protein samples were stored at −20°C until further use.

Two-dimensional electrophoresis

Proteins were first separated by isoelectric focusing (IEF). For preparative IEF, IPG strips (24 cm, pH 3-10, nonlinear; GE Healthcare, Uppsala, Sweden) were passively rehydrated overnight with 450 μl of rehydration buffer [7 M urea, 2% (w/v) CHAPS, 2% (w/v) DTT, 0.7% (v/v) IPG buffers at pH 3–10, 0.001% bromophenol blue] containing 1 mg of proteins. IEF was performed at 20°C in an Ettan IPGphor 3 IEF system (GE Healthcare) for a total run of 100 kVh (50 V for 6.5 h, 500 V for 2 h, 1 kV for 2 h, 3 kV for 2 h, 5 kV for 2 h and 10 kV for 9 h). After IEF, the IPG strips were incubated in equilibration buffer [1.5 M Tris-HCl (pH 8.8), 6 M urea, 30% (v/v) glycerol, 2% (w/v) sodium dodecyl sulfate (SDS), and 0.002% bromophenol blue with 1% (w/v) DTT or 2.5% (w/v) iodoacetamide]. The second-dimension electrophoresis was carried out using SDS-polyacrylamide gels (13%, w/v, acrylamide) in an Ettan DALTsix electrophoresis Unit (GE Healthcare) until the dye line reached the end of the gel.

Gels were stained overnight with Coomassie Brilliant Blue (PhastGel Blue R-350; GE Healthcare, Uppsala, Sweden) and scanned at 300 dpi resolution using an image scanner (ImageScanner III; GE Healthcare). Image analysis was carried out with Image Master 2D Platinum 7.0 software (GE Healthcare). Each sample was analyzed at three biological replicates. To compensate for subtle variability resulting from sample loading and gel staining, spot volumes were normalized as a percentage of the total volume of all spots on the gel. Only spots with a significant difference (p < 0.05) were considered as varying spots, and the protein spots with an abundance ratio of at least 1.5-fold between control and heat-treated samples were selected as differentially expressed proteins and identified by MS analysis.

Protein identification by nanoLC-MS/MS

The identified protein spots were excised from gels and distained with 50 mM ammonium bicarbonate in 50% acetonitrile, then dehydrated in 100% acetonitrile. The gels pieces were rehydrated with digestion solution (10 mg/ml trypsin in 50 mM ammonium) for 16 h or overnight at 37°C. The supernatant were vacuum-dried and dissolved in 30 mL 30% acetonitrile and 0.1% formic acid, shake for 30 min, and repeat with 60% acetonitrile. Dry the combined supernatant in vacuum concentrator, and add 10 mL 0.1% formic acid to reconstitute the residue. The digested fragments were analyzed using nanoelectrospray tandem mass spectrometry (nanoLC-MS/MS). The nanoLC separation was achieved with a Waters (Milford, MA, USA) nanoACQUITY Nano HPLC. Nanospray ESI-MS was then performed on a Thermo Q-Exactive high-resolution mass spectrometer (Thermo Scientific, Waltham, MA, USA). The MS/MS scans were acquired in data dependent mode. Survey scans (m/z 300–2000) were acquired with the resolution adjusted to 70,000 FWHM. The 10 most intensive peptide signals from the full scan were selected for MSMS scans. Analyses of MS/MS scans were performed with FWHM set at 17,500. The dynamic exclusion parameter was set to 10 s. Raw data from the mass spectrometer were preprocessed with Mascot Distiller 2.5 for peak picking. The resulted peak lists were searched against Swissprot database using Mascot 2.5 search engine compared against green plant EST database of the NCBInr protein database. The search parameters are as follows: fixed modifications: carbamidomethyl (C), variable modifications: oxidation (M); decoy database: yes; enzyme: trypsin; max missed cleavages: 2; MS mass tolerance: 10 ppm; MSMS mass tolerance: 0.02 Da. For all proteins, the best match was based on the one peptide sequences with an individual score above 21, and the coverage of the protein by the matching peptides must reach a minimum of 5%. Theoretical molecular masses and isoelectric points of the identified proteins were predicted by the ExPASy server (http://www.expasy.org/protparam).

Functional annotation and classification

All the identified proteins were used for gene ontology (GO) and cluster of orthologous groups of proteins (COG) annotation to determine the functional classification and biological properties. GO annotation was performed using BLAST2GO (http://www.blast2go.com; Conesa and Götz, 2008). The identified proteins were classified into three functional categories: cellular component, biological process, and molecular function. COG analysis was conducted using the NCBI database (http://www.ncbi.nlm.nih.gov/COG/). In addition, pathway annotation was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.kegg.jp/kegg/pathway.html).

Hierarchical cluster analysis of protein abundance

Protein abundance values were estimated using Image Master 2D Platinum 7.0 software (GE Healthcare). Each sample was analyzed at three biological replicates. Hierarchical cluster analysis was performed using MeV (version 4.9) software after log2 transformation of the expression abundance values.

Statistical analysis

All experiments were replicated three times independently. Vigor parameter, physiological parameters and spot intensities were all analyzed statistically using analysis of variance (ANOVA) by SPSS 18.0. Treatment means were separated using Duncan's multiple range test taking p < 0.05 as significant.

Effect of heat-stress treatments on vigor of oat seeds with 10% and 16% MC

The germination percentage of oat seeds showed a trend toward decrease with temperature increase from 35 to 50°C (Figure 1A). Germination percentage of oat seeds with 16% MC declined significantly (p < 0.05) with increasing temperature of the heat treatments. For seeds with 10% MC, there was no significant difference (p > 0.05) in germination percentage between heat treatments of 35 and 45°C. The germination index of seeds with 10 and 16% MC showed a similar tendency to decline significantly (p < 0.05) under heat treatments from 35 to 50°C (Figure 1B).

Figure 1

Effect of heat-stress treatments on the vigor of oat seeds with 10 and 16% MC. (A) Germination percentage; (B) Germination index. Means with different lowercase letters show significant differences at the 0.05 level among treatments at the same MC, as determined by the Duncan's multiple range test. Each bar is the mean ± SE (n = 3) for each treatment.

Effect of heat-stress treatments on MDA and proline content of oat seeds with 10 and 16% MC

The results of MDA content analysis showed different tendencies under heat treatments for seeds with different MC. There was no significant (p > 0.05) difference in MDA content of seeds with 10% MC as the temperature increased from 35 to 50°C. However, the MDA content of seeds with 16% MC showed a significant (p < 0.05) decrease at temperatures of 45 and 50°C; there was no significant (p > 0.05) difference between these temperatures (Figure 2A). MDA content in 16% MC seeds was lower than that in 10% MC seeds under heat-stress treatment.

Figure 2

Effect of heat stress treatments on the MDA and proline content of oat seeds with 10 and 16% MC. (A) MDA content; (B) Proline content. Means with different lowercase letters show significant differences at the 0.05 level among treatments at the same MC, as determined by the Duncan's multiple range test. Each bar is the mean ± SE (n = 3) for each treatment.

The changes in proline content presented the opposite trend with heat treatments from 35 to 50°C (Figure 2B). The proline content of seeds with 10% MC decreased significantly (p < 0.05) as the temperature increased to 45°C, and no significant difference (p > 0.05) was found between 45 and 50°C. However, the proline content in seeds with 16% MC increased significantly (p < 0.05) as the temperature increased to 45°C. There was also no significant difference (p > 0.05) found between 45 and 50°C.

Changes in protein abundance of oat seeds with 10 and 16% MC under heat-stress treatments

From the three 2D-gel replicates, a total of 94 and 32 protein spots were detected in oat seeds with 10 and 16% MC, respectively, and these showed statistically significant differences at abundance ratios over 1.5-fold in relation to heat-stress treatment. Twenty-one proteins were successfully identified by searching against the MASCOT database (Table 1, Supplementary Figure 1). Most of these proteins covered the isoelectric points that ranging from 5 to 7, and their molecular masses ranged from 10 to 20 kDa, indicating that weakly acidic proteins with molecular masses of between 10 and 20 KDa play very important roles in the deteriorated oat seeds. Similar changes were observed between experimental and theoretical isoelectric point and molecular mass, except for spot 31 and spot 33 (Supplementary Figure 2).

Among the differentially accumulated protein spots, there were 94 protein spots altered significantly (p < 0.05) and 12 protein spots further identified by nanoLC-MS/MS in 10% MC seeds (Table 1). According to their expression patterns, these 12 spots could be grouped into four types (Figure 3): type I, spots decreased slowly and then dropped rapidly with temperature increasing from 35 to 50°C (spots 33, 71, 78, 92, and 106); type II, spots first decreased rapidly and then slowly (spots 51 and 758); type III, spots were down-regulated consistently with temperature increases from 35 to 50°C (spots 46, 99, 362, and 515); type IV, spots were up-regulated as the temperature increased from 35 to 45°C and down-regulated from 45 to 50°C (spot 889). For oat seeds with 16% MC, a total of 32 protein spots were altered significantly (p < 0.05) and there were nine protein spots further identified by nanoLC-MS/MS analysis (Table 1). These nine spots grouped into three types (Figure 3): type I, spots increased with temperature from 35 to 45°C and decreased from 45 to 50°C (spots 15, 31, 95, and 446); type II, spots were down-regulated consistently with temperature increases from 35 to 50°C (spots 90, 96, 412, and 963); type III, spots were up-regulated consistently with temperature increases from 35 to 50°C (spot 100). Interestingly, three down-regulated spots (spots 31, 95, and 412) were also identified in oat seeds with 10% MC (spots 33, 78, and 362), and were also down-regulated as the temperature increased from 35 to 50°C (Figure 4).

Figure 3

Hierarchical cluster analysis of heat-resistance proteins in oat seeds with 10 and 16% MC. Dataset clustering was performed with MeV software after log2 transformation of the expression abundance values. Each colorized cell represents the spot quantity, according to the color scale at the top of the figure. (A, 10% MC; B, 16% MC).

Figure 4

Representative 2-DE pattern of the oat seed proteome under heat stress. Spot numbers indicate the protein spots analyzed by Image Master 2D Platinum 7.0 software. Zoomed images show the main differentially expressed protein spots in deteriorated oat seeds. Spot 446, up-regulation in oat seeds with 16% MC after heat-stress treatment; spots 31, 95, 412, down-regulation in oat seeds with 10 and 16% MC after heat-stress treatment. The three biological replicates of the 2-DE gels are shown in Supplementary Figure 1.

Functional annotation and classification of proteins identified in oat seeds with 10 and 16% MC

The functional categories of differential expression proteins were determined using GO analysis (Figure 5) and COG analysis (Figure 6). For oat seeds with 10% MC after heat treatment, a total of 10 proteins were divided into 22 GO terms to describe biological processes, cellular components, and molecular functions. The major functional categories in the biological processes were response to stimulus (7; 17.07%), cellular processes (6; 14.63%) and metabolic processes (6; 14.63%). Among cellular components, cell (8; 30.77%) and cell part (8; 30.77%) were the most abundant groups, whereas binding (5; 62.50%) and catalytic activity (2; 25.00%) accounted for the most abundant groups in terms of molecular functions (Figure 5A). Proteins were also aligned to the COG database to predict and classify possible functions. There were eight proteins distributed into five COG categories (Figure 6A, Supplementary Table 1), of which the COG category “posttranslational modification, protein turnover, chaperones” represented the largest group (3; 37.5%), followed by “general function prediction only” (2; 25%); the smallest groups were “nucleotide transport and metabolism” (1; 12.5%), “carbohydrate transport and metabolism” (1; 12.5%) and “translation, ribosomal structure and biogenesis” (1; 12.5%). A total of seven proteins were assigned to eight pathways by the KEGG analysis (Supplementary Table 2). Among these pathways, protein processing in endoplasmic reticulum and disease-related metabolic pathways were the highlighted pathways.

Figure 5

GO categories of the identified proteins in oat seeds with 10 and 16% MC under heat stress. Results are summarized under three main GO categories: biological process, cellular component, and molecular function. (A, 10% MC; B, 16% MC).

Figure 6

COG functional classification for the proteins identified in oat seeds with 10 and 16% MC under heat stress. (A, 10% MC; B, 16% MC).

For oat seeds with 16% MC, there were eight proteins to be classified into 18 GO terms to describe biological processes, cellular components, and molecular functions. The major functional categories in the biological processes were response to stimulus (5; 33.33%), cellular processes (2; 13.33%) and metabolic processes (2; 13.33%). Among cellular components, cell (5; 29.41%) and cell part (5; 29.41%) were the most abundant groups, whereas binding (2; 40.00%) and catalytic activity (2; 40.00%) accounted for the most abundant groups in terms of molecular functions (Figure 5B). According to COG function annotation, five proteins were distributed into three COG categories (Figure 6B, Supplementary Table 1), among which COG category “posttranslational modification, protein turnover, chaperones” represented the largest group (3; 60%), followed by “energy production and conversion” (1; 20%) and “amino acid transport and metabolism” (1; 20%). Notably, these five proteins, including ATP synthase subunit alpha, argininosuccinate synthase (ASS), and 17.3, 17.9, and 18.3 kDa class I heat shock proteins, were also mapped in the 10 KEGG pathways (Supplementary Table 2). This indicated that most of these related proteins might be playing an important role in the deterioration of oat seeds.

High temperature and seed MC accelerated SD

Temperature and MC are two important environmental factors that influence seed longevity. For the longevity of orthodox seeds in storage, the optimal MC was shown to be 10–11% with a temperature lower than 25°C (Ellis et al., 1989). In this experiment, the decrease of seed germination percentage and germination index in oat seeds with 10 or 16% MC as temperature was raised from 45 to 50°C confirmed the occurrence of SD. Furthermore, seed vigor at 16% MC declined much faster than that at 10% MC under heat stress (Figure 1). This meant that there was a synergy between higher temperature and MC affecting seed vigor during storage. Xia et al. (2015) observed that the germination percentage of oat seeds decreased gradually during seed aging, and the extent of the declining rate of germination was related to seed MC. Moreover, Kong et al. (2015) observed that the germination percentage of oat seeds decreased with increasing seed MC. When in storage for 12 months, the germination percentage of oat seeds with 4% MC did not change significantly, but decreased significantly in oat seeds with 16% MC and reached zero in seeds with 28% MC. In this study, similar results were obtained in oat seeds during heat stress.

Although, the biochemical mechanisms of SD are not yet fully understood, several studies identified oxidative free radical attack as one of the main causes of SD during seed storage (Galleschi et al., 2002). In addition, some researchers found that vigor loss or seed death was well correlated with accumulation of MDA in plant species such as neem (Azadirachta indica) (Kumar and Mishra, 2014), cotton (Goel and Sheoran, 2003) and onion (Allium cepa) (Rao et al., 2006). However, MDA content declined under the combination of higher temperature and MC conditions in this study; there were no significant (p > 0.05) differences in MDA content among heat treatments in oat seeds with 10% MC. A significant decrease in MDA content was observed at 45°C in 16% MC seed (Figure 2A). Similar results have been reported for wheat (Triticum aestivum) (Lehner et al., 2008). These results indicated that the loss of seed vigor might not be attributed to lipid peroxidation at higher MC (16%). Meanwhile, proline accumulation during heat treatments was only evident in 16% MC seeds. The changes in proline content between 10 and 16% MC showed the opposite tendency with temperature alteration from 35 to 50°C (Figure 2B). The accumulation of proline could be regarded as a signal of response to abiotic stress (Floyd and Nagy, 1984). It has been demonstrated that proline accumulates as plants suffer from environmental temperature stress in species such as alfalfa (Medicago sativa) (Li et al., 2013), chickpea (Cicer arietinum) leaves (Kaushal et al., 2011) and Phylanthus emblica seeds (Li et al., 2009). This suggests that lipid peroxidation was affected by the level of oat seed MC during storage and that MC was a primary factor in causing SD.

Proteome expression of oat seeds with different MC under heat stress

In this study, there were 21 proteins differentially expressed in oat seeds under heat stress, and these were mainly involved in stress/disease responses, energy metabolism, carbohydrate and amino acid transport and metabolism, posttranslational modification, etc. among all heat-responsive proteins.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.