Proteome Analysis of Early-Stage Soybean Seedlings under Flooding

Proteome Analysis of Early-Stage Soybean Seedlings under Flooding Stress Akiko Hashiguchi,† Katsumi Sakata,‡ and Setsuko Komatsu*,† National Institute of Crop Science, Tsukuba 305-8518, Japan, and Mitsubishi Space Software Company, Ltd., Tsukuba 305-0032, Japan Received December 7, 2008

Proteomic analyses of soybean seedlings responding to flooding were conducted to identify proteins involved in such response. Soybean was germinated for 48 h and then subjected to flooding stress for 6-48 h. Proteomic analysis of hypocotyl and root was used in a time-dependent manner, and altered proteins were identified using soybean protein data file constructed for this research. Under flooding stress, 35 proteins were up-regulated, whereas 16 proteins were down-regulated at a 24-h time point. Changes in energy generation was recognized because several glycolytic enzymes were up-regulated. General stress response was also shown to occur as various reactive oxygen species scavengers were up-regulated. Other identified proteins with diverse functional categories suggest that flooding stress includes not only hypoxic stress, but also other stresses such as weak light, disease, and water stresses. In addition, proteins with unknown functions were shown to be positioned as hubs which activate other proteins in system response networks by protein-protein interaction analysis, suggesting that this type of interaction analysis is useful for screening of important factors in plant response to environmental stresses. Keywords: Flooding • Proteome • Soybean • Protein-protein interaction

Introduction Transient flooding or irrigation is a common cause of plant hypoxia characterized by the soil having an impermeable clay base or consisting of cracking gray clays with poor drainage. This transient condition may be caused by weather with an extreme rainfall pattern or may be due to imperfect land planning. Higher plants are aerobic organisms that immediately die when oxygen availability is limited due to soil flooding.1 Flooding causes reduced gas exchange between the plant tissue and the atmosphere, because gases, particularly oxygen, diffuse 10 000 times more slowly in water than in air.2 In addition, other changes affecting soil chemical characteristics during flooding including variations in soil pH3 and redox potential4 are also induced by low oxygen concentration. Oxygen deprivation by flooding may not only become the main limiting factor for normal plant development, but may also serve as the prime signal triggering the flooding response.5 Gene expression studies on plants exposed to low oxygen concentration revealed the up-regulation of genes coding transcription factors,6 signal transduction components,7 nonsymbiotic hemoglobin,8 ethylene biosynthesis,9 nitrogen metabolism,10 and cell wall loosening.11 At the protein level, low oxygen concentration selectively induces the synthesis of proteins known as anaerobic proteins, most of which are enzymes involved in sugar me* To whom correspondence should be addressed. Dr. Setsuko Komatsu, National Institute of Crop Science, Kannondai 2-1-18, Tsukuba 305-8518, Japan. Fax: +81-29-838-8694. Tel: +81-29-838-8693. E-mail: [email protected]. † National Institute of Crop Science. ‡ Mitsubishi Space Software Co., Ltd.

2058 Journal of Proteome Research 2009, 8, 2058–2069 Published on Web 02/08/2009

tabolism, glycolysis, and fermentation pathways.12 Most of these findings have been obtained using model plants such as flood-intolerant species of the genus Arabidopsis, or a floodtolerant species, namely, rice. Despite knowledge on adaptive mechanisms and response regulation at the gene and protein levels, the understanding of mechanisms underlying plant response to flooding remains very limited. Even flood-intolerant species of the genus Arabidopsis switch on many genes generally associated with responses to flooding.13,14 These studies strongly suggest that the regulation of flooding tolerance in plants is far more complex than anticipated for many years.15 Various investigations of the mechanisms underlying responses to flooding stress using not only model plants, but also other plants have been carried out to generate flood-tolerant plants. Since flooding is one of the environmental constraints for the normal development of crop plants, additional studies using flooding stress-intolerant plants are required. Soybean is known as a flood stress-intolerant plant, and flooding is a major problem reducing soybean growth and grain yield in many areas of Japan and around the world. It was previously reported that flooding injury of soybean seeds before radicle protrusion was caused by physical disruption due to the rapid uptake of water, and this can be alleviated using seeds with high moisture content.16 The causes of flooding injury in the stages after radicle protrusion, however, have not been elucidated to date, although physiological factors include transcription factors and enzymes.17 On the other hand, protein analysis using highresolution, two-dimensional polyacrylamide gel electrophoresis (2-DE) is the most direct approach for defining gene function, 10.1021/pr801051m CCC: $40.75

 2009 American Chemical Society

Proteins in Flooding Response in Soybean and it has been employed for analyzing protein alterations in response to environmental changes.18 In this study, proteomic analysis was carried out at 5 time points over 48 h under normal and flooding conditions. Here, a catalog of the proteome changes occurring under flooding stress, as determined by proteome profiling, was constructed, and protein coordination inside the proteome was investigated. Data analysis allowed the reconstruction of the protein-protein network of mutual effects between differentially expressed proteins.

Materials and Methods Plant Growth and Treatment. For growth analysis, seeds of soybean (Glycine max L.) cultivar Enrei were sterilized by sodium hypochlorite solution and germinated on sand for 2 days, followed by flooding for 12-48 h under white fluorescent light (600 µmol m-2 s-1, 12 h light period/day) at 25 °C and 70% relative humidity in a growth chamber. Seedlings were allowed to grow until the sixth day after germination. For protein expression analysis, 2-day-old seedlings were flooded for 0, 6, 12, 24, and 48 h. Experiments were done in triplicate with 20 seeds for each experiment of growth analysis and in four replications with 12 seeds for each experiment of protein expression analysis, respectively. Protein Extraction and 2-DE. A portion (200 µg) of hypocotyl and root was homogenized with 400 µL of lysis buffer19 containing 8 M urea, 2% Nonidet P-40, 0.8% Ampholine (pI 3.5-10, GE Healthcare, Piscataway, NJ), 5% 2-mercapthoethanol, and 5% polyvinyl pyrrolidone-40, using a grass mortar and pestle on ice. The homogenates were centrifuged twice at 15 000g for 5 min each. The supernatants (70 µL, 200 µg) were separated using 2-DE in the first dimension by isoelectric focusing (IEF) tube gel for low pI range (pI 3.5-8.0) or immobilized pI gradient (IPG) tube gel (Daiichi Kagaku, Tokyo, Japan) for high pI range (pI 6.0-10.0) and in the second dimension by SDS-PAGE. An IEF tube gel of 11 cm length and 3 mm diameter was prepared. IEF gel solution consisted of 8 M urea, 3.5% acrylamide, and 2% Nonidet P-40, 2% Ampholine (pI 3.5-10 and pI 5-8). Electrophoresis was carried out at 200 V for 30 min, followed by 400 V for 16 h and 600 V for 1 h. For IPG electrophoresis, samples were applied to the acidic side of gels. Electrophoresis using IPG tube gels (pI 6.0-10.0) of 11 cm length and 3 mm diameter was carried out at 400 V for 1 h, followed by 1000 V for 16 h and 2000 V for 1 h. After IEF or IPG, SDS-PAGE in the second dimension was performed using 15% polyacrylamide gels (160 × 140 × 1 mm) with 5% stacking gels.20 The gels were stained with Coomassie brilliant blue (CBB), and image analysis was performed. Gel Image Analysis. 2-DE images were obtained using a GS800 calibrated densitometer scanner (Bio-Rad, Hercules, CA) and the position of individual proteins on gels was evaluated with PDQuest software (version 7.1; Bio-Rad, Hercules, CA). The pI and molecular mass of each protein was determined using 2-DE marker (Bio-Rad). The amount of a protein spot was expressed as the volume of that spot which was defined as the sum of the intensities of all the pixels that make up the spot. To correct the variability due to CBB-staining and to reflect the quantitative variations in intensity of protein spots, the spot volumes were normalized as a percentage of the total volume in all of the spots present in the gel. Four biological replications were used for the analysis and spots which were up- or down-regulated in at least three physiological replications were considered reproducibly regulated. Spots assigned a fold-change cutoff at 1.5 for expression ratios were used. Two

research articles spots with 1.2- to 1.5-fold cutoff were also included to see the difference in their behavior from other spots (proteins 402 and 404). To determine which protein spots displayed a statistically significant quantitative difference in expression, the Fisher’s analysis of variance (ANOVA) method was used in Excel software. Cleveland Peptide Mapping. Following separation by 2-DE, gel pieces containing protein spots were excised and the protein was electroeluted from the gel pieces using an electrophoretic concentrator (Nippon-Eido, Tokyo, Japan) at 2 W constant power for 2 h. The protein solution was dialyzed against deionized water for 48 h and lyophilized. The protein was dissolved in 20 µL of SDS sample buffer containing 0.5 M TrisHCl (pH 6.8), 10% glycerol, 2.5% SDS, and 5% 2-mercaptoethanol, and applied to a sample well in an SDS-PAGE gel. The sample solution was overlaid with 20 µL of a solution containing 10 µL of Staphylococcus aureus V8 protease (0.1 µg µL-1; Pierce, Rockford, IL) and 10 µL of the SDS sample buffer. Electrophoresis was performed until the sample and protease were stacked in the stacking gel, interrupted for 30 min to digest the protein.21 Electrophoresis was then continued to separate the peptide fragments. N-Terminal and Internal Amino Acid Sequence Analyses. To analyze an N-terminal and internal-amino acid sequences following separation using 2-DE or Cleveland peptide mapping, the proteins were electroblotted onto a polyvinylidene difluoride (PVDF) membrane (Pall, Port Washington, NY) using a semidry transfer blotter (Nippon-Eido) and detected by CBB staining. The stained protein spots were excised from the PVDF membrane and directly subjected to Edman degradation on a gas-phase protein sequencer (Procise 494, Applied Biosystems, Foster City, CA). FASTA search service provided by National Institute of Agrobiological Sciences of Japan (NIAS) DNA bank (http://www.dna.affrc.go.jp) was used for searching Swiss-Prot or Uniprot-Sprot databases which cover various taxon containing sequences from other plants to find out novel proteins in soybean. Protein Identification by Mass Spectrometry. Protein spots were excised from CBB stained gels and destained with 50 mM NH4HCO3 for 1 h at 40 °C. Proteins were reduced with 10 mM DTT in 100 mM NH4HCO3 for 1 h at 60 °C and incubated with 40 mM iodoacetamide in 100 mM NH4HCO3 for 30 min. The gel pieces were minced and allowed to dry, then rehydrated in 100 mM NH4HCO3 with 1 pM trypsin (Sigma-Aldrich, St. Louis, MO) at 37 °C overnight. The tryptic peptides were extracted from the gel grains with 0.1% trifluioroacetic acid in 50% acetonitrile three times. The procedure described above was performed with DigestPro (INTAVIS Bioanalytical Instruments AG, Cologne, Germany). The peptide solution obtained was dried and reconcentrated with 30 µL of 0.1% trifluioroacetic acid in 50% acetonitrile and desalted with NuTip C-18 pipet tips (Glygen, Columbia, MD). Desalted peptide solution was analyzed by nanoliquid chromatography-tandem mass spectrometry (Ultimate3000, Dionex, Sunnyvale, CA; LTQ Orbitrap, ThermoFisher Scientific, Waltham, MA). The mass spectrometer was operated in data-dependent acquisition mode with the XCalibur software. Full scan MS spectra were acquired in the Orbitrap on the 150-2000 m/z with a resolution of 30 000. The three most intense ions at a threshold above 1000 were selected for collision-induced fragmentation in the linear ion trap at a normalized collision energy of 35% after acJournal of Proteome Research • Vol. 8, No. 4, 2009 2059

research articles cumulation to a target value of 1000. Dynamic exclusion was employed within 30 s to prevent repetitive selection of the peptides. Data Analysis. Acquired MS/MS spectra were converted to single DTA files using Bioworks 3.3.1. The following parameters were set for creation of the peaklists: parent ions in the mass range with no limitation, one grouping of MS/MS scans, threshold at 100. Precursor ion tolerance was 10.00 ppm. Data were searched using an in-house licensed MASCOT search engine (Mascot version 2.2.04, Matrix Science, London, U.K.) against all entries in the soybean genome database version 4 (62 199 sequences), which was especially constructed for this research based on soybean genome preliminary sequences from Department of Energy Joint Genome Institute and Soybean Genome Sequencing Consortium. Namely, soybean genome sequences were downloaded from DOE database (http://www.phytozome.net, release date 24 January 2008) and were converted into FASTA format. Carbamidomethylation of cysteines was set as a fixed modification and oxidation of methionines was set as a variable modification. Trypsin was specified as the proteolytic enzyme and one missed cleavage was allowed. The mass tolerance of the precursor ion was set to 10 ppm and that of fragment ions was set to 1 Da. The instrument setting was specified as ‘ESI-Trap’. Protein hits were validated if the identification was with at least four top ranking peptides with p-value 3.5 were left and discussed as candidate interactions.

Results Growth of Soybean Seedlings Is Significantly Suppressed after 24 h of Flooding. In this study, a proteomic approach was used to identify soybean seedling proteins responding to flooding stress after radicle protrusion. Fourty-eight-hour-old 2060

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Hashiguchi et al. soybean seedlings were subjected to flooding for 12, 24, 48, and 96 h. The soaking water was drained and then the seedlings were allowed to grow until the sixth day after germination (Figure 1A). Changes in the hypocotyl length, main root length, hypocotyl fresh weight, and the fresh weight of total roots including lateral roots were measured on the sixth day after germination. Results showed that flooding stress affected the growth of soybean seedlings at all treatment durations. Morphological observation revealed that flooding-stressed seedlings have shorter hypocotyls and main roots with fewer lateral roots than control seedlings in which stress was not applied, and that hypocotyl pigmentation was also inhibited in floodingstressed seedlings (Figure 1B). Flooding stress also affected the fresh weight of hypocotyls and roots (Figure 1C), and treatment for 96 h was lethal. The extent of growth reduction was obvious in every aspect of growth characteristics under treatments longer than 24 h (40% decrease in hypocotyl length; 12% decrease in root length; 47% decrease in hypocotyl fresh weight; and 50% decrease in root fresh weight). Therefore, soybean seedlings stressed for 24 h were selected for investigating the proteome of the soybean seedlings stressed by flooding. Establishment of Two-Dimensional Reference Map and Expression Profiles of 48 h-old Soybean Seedlings. Prior to differential proteomic analysis, comprehensive analysis of soybean proteins from 48 h-old seedlings without flooding stress has been performed. A 2D reference map was obtained for soybean hypocotyls and roots, using both IEF and IPG gels (Figure 2, Supplemental Figure 1 in Supporting Information). The pI and Mr of these proteins ranged from 3.5 to 10.0 and 10.0 to 100.0 kDa, respectively (Figure 2). Eight hundred forty protein spots were detected on the 2-DE gels. These proteins were transferred to a PVDF membrane and their N-terminal or internal amino acid sequences were determined by direct protein sequencing. One hundred thirty protein spots were identified as landmark spots in 72 h-old soybean seedlings gels (Supplemental Table 1 in Supporting Information). Protein identifications were performed using the Swiss-Prot database or Uniprot-Sprot databases. Soybean protein data file was constructed using these proteins. To better characterize proteins expressed in 48 h-old soybean seedlings, putative protein functional classifications were assigned according to Bevan et al.24 and Tanaka et al.25 (Figure 3). All identified proteins were classified into 7 functional categories, that is, defense/disease, metabolism, protein synthesis, protein destination/storage, signal transduction, secondary metabolism, and transcription, showing that a broad range of cellular activities are taking place in the early stage soybean seedlings (Figure 3). Proteins involved in defense/ disease accounted for the largest portion (41 of 130, 32%), and those involved in metabolism including secondary metabolism were dominant (19 of 130, 15%). There were also a significant number of proteins of unclear classification. This is the first report of soybean proteins expressed in early stage germinating seedlings, although proteins in mature seeds have been described in depth by several studies.26,27 Fifty-One Proteins Are Differentially Expressed in Flooding Stress. To determine soybean proteins whose expression levels were changed due to submergence, 48 h-old soybean seedlings after germination were flooded for 24 h. Eight hundred forty proteins from the hypocotyls and roots were separated by 2-DE and stained with CBB (Figure 4). Fifty-one proteins were reproducibly changed between control and flooding-stressed seedlings in 3 physiologically independent

Proteins in Flooding Response in Soybean

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Figure 1. Growth suppression of soybean seedlings after flooding. (A) Experimental scheme of flooding stress treatment. Soybean seedlings were germinated for 48 h and subjected to flooding stress for 12, 24, and 48 h. They were allowed to develop following water removal until the sixth day after sowing. Numbers indicate days after germination and numbers in parentheses indicate the duration of flooding treatment (days). (B) Photograph showing whole seedlings on the sixth day; flooding periods are given in parentheses. Morphological difference between normal and flooded soybean seedling are shown. Flooding-stressed seedlings have shorter roots with few lateral roots compared with control seedlings. (C) Effect of flooding on the early growth stage of soybean seedlings. Growth characteristics including hypocotyl length, hypocotyl fresh weight, root length, and root fresh weight were determined. Each value represents the average ( SE of 20 seedlings. Total root number, main root length, hypocotyl length, and hypocotyl and total root fresh weight were reduced significantly by flooding (p < 0.05).

experiments, indicating that a plethora of biological processes were affected; 35 proteins (69%) were up-regulated and 16 proteins (31%) were down-regulated (Figure 5). Along with the direct determination of the amino acid sequence of these proteins, the determination of the peptide masses of trypsinated spots by nanoLC MS/MS also led to the successful identification of proteins. The genomic sequence of soybean has recently been made available in public sequence databases, allowing the comprehensive definition of a theoretical soybean proteome including the tryptic peptides of all its components. However, these databases do not provide current annotation information on sequence homology. Therefore, all assignments were subjected to homology search using BLASTP

against the NCBI nonredundant database (Table 1). Peak lists of MS/MS data files were provided in Supplemental Table 2 of Supporting Information. Expression levels of proteins involved in glycolysis and fermentation pathways (protein 248, UDPglucose pyrophosphorylase; protein 383, fructose-biphosphate aldolase; and protein 402, phosphoglycerate kinase) were altered in response to flooding stress, suggesting that flooding stress also includes stress from oxygen limitation. Functional distribution of 35 up-regulated protein spots and 16 downregulated proteins were shown in Figure 6. Hierarchical Clustering of 51 Quantified Spot Groups Resulted in 6 Clusters. For further analysis, protein expression profiling of the 51 differentially expressed spots using 2-DE gels Journal of Proteome Research • Vol. 8, No. 4, 2009 2061

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Hashiguchi et al.

Figure 2. Reference map of soybean proteins. Merged gel image with pI and molecular weight indicators. Proteins (200 µg) were isolated from 48 h-old soybean hypocotyls and roots, and then separated by 2-DE in combination with CBB staining. Merged image of IEF gels ranging from pI 3.5-6.0 and IPG gels ranging from pI 6.0-9.0 is shown. Eight hundred forty protein spots were detected on the gels. Detected spots were numbered from the left upper direction to the right lower direction.

Figure 3. Functional distribution of proteins identified from 48 h-old soybean hypocotyls and roots. N-terminal or internal amino acid sequences of 130 proteins were determined using a protein sequencer and nanoLC-MS/MS. The chart shows the distribution of these proteins after functional classification.

was carried out at 5 time points over 48 h under normal and flooding conditions: 0, 6, 12, 24, and 48 h after flooding. Fiftyone proteins were analyzed by the UPGMA clustering method using the induction levels of the proteins (Supplemental Table 3 in Supporting Information) and 6 clusters of protein expression were recognized. The first cluster (cluster I) included proteins gradually down-regulated with flooding stress compared with the control. Cluster II encompassed proteins having the highest induction 12 h after flooding. Cluster III included early-responsive proteins up-regulated at the time point of 6 h 2062


after flooding. Members of clusters IV and V showed an upward trend during flooding treatment; particularly, proteins in cluster V were strongly induced 24 h after treatment. Cluster VI included proteins whose up-regulation is not remarkable compared with those assigned to other clusters (Figure 7). Down-regulated proteins tended to be classified into the same branches in the cluster, showing that clustering is valuable for evaluating protein function. All identified proteins were classified into functional subclasses, as originally established by Bevan et al.24 and Tanaka et al.25 Functional assignments are shown in Figure 6. Some of the proteins classified into the same functional categories tended to be located on the same branch of the tree (protein 799, 134, and 3501: late embryogenesisabundant protein, maturation polypeptide and albumin precursor, respectively; protein 724, 595, 596, and 649: Kunitz trypsin inhibitor, ascorbate peroxidases (APXs) and cp 10-like protein, respectively). Protein-Protein Interaction Analysis Revealed That Flooding Stress Changes Whole Interaction Network. To better understand the physiological process occurring in flooding-stressed soybean seedlings, time course expression data was used for estimating the interaction between proteins (Figure 8). In the control, 2 apparent interaction networks were recognized. The first network (network I) had 2 hubs centered around proteins 304 (S-adenosyl-L-methionine synthetase) and 799 (late embryogenesis-abundant protein). It also included proteins 784 (superoxide dismutase, SOD) and 586 (triosephosphate isomerase/unknown) downstream of protein 799. On the other hand, the second network (network II) consisted of protein interactions starting from upstream protein 654 (40S ribosomal protein) to downstream protein 577 (unknown) via protein 659 (beta-conglycinin), an intermediator. Proteins 596

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Figure 4. 2-DE overview map of proteins whose expression levels were affected by flooding stress for 24 h. Soybean seeds were germinated on sand for 48 h and subjected to water flooding for 24 h. The hypocotyls and roots of the seedlings were used for protein extraction. Proteins (200 µg) were separated by 2-DE followed by CBB staining. Protein spot expression level was calculated as the percent volume normalized for all detected spot intensities using four biological replications. Open circles indicate the spots where protein expression was changed by flooding treatment. Upward arrows show up-regulated spots, while downward arrows show downregulated spots.

(APX) and 781 (trypsin inhibitor) were under the control of protein 577 (Figure 8A). However, the interaction scheme was completely changed when soybean seedlings were subjected to flooding stress, in which a single large interaction network in flooding-treated soybeans appeared (Figure 8B, gray screened). This transformation was achieved by generating new interactions between the hubs observed in the 2 control networks (proteins 304 and 654, S-adenosyl-L-methionine synthetase and 40S ribosomal protein, respectively; proteins 586 and 654, triosephosphate isomerase/unknown and 40S ribosomal protein, respectively; proteins 586 and 659, triosephosphate isomerase/unknown and beta-conglycinin, respectively). Along with these changes, interactions within network I were also restructured (proteins 304 and 586; proteins 304 and 784; protein 784 is SOD). Thus, a hub complex consisting of proteins 304, 586, and 654 emerged, and protein 659 seemed to control the hub complex through protein 586. In the control, protein 659 controlled protein 577, which regulated downstream proteins 781 and 596 (network II). Interestingly, these downstream proteins controlled proteins in network I, dividing and integrating network II into network I (protein 304 controlled protein 781; protein 799 controlled protein 596). Proteins with relatively slight change (1.2- to 1.5-fold change: proteins 402 and 404) were not located on nodes.

Discussion A proteome reference map based on 2-DE is a prerequisite for evaluating changes in protein expression levels and for exact protein identification in genetic mutants, and biotically and abiotically challenged plants. Proteomics is a powerful tool for understanding physiological mechanisms of stress response in plants, uncovering key signaling molecules. To date, a proteome reference map of soybean has been constructed using developing seeds, and this development is important for human and animal nutrition.26 Proteome analyses of early-stage soybean seedlings have been performed to identify proteins responsible for defense against stresses such as those induced by flooding,28 salt,20 and alminium toxicity.29 However, a proteome reference map of soybean seedlings identifying which stage is sensitive to various environmental stresses has not been fully described to date. Here, a 48 h-old soybean seedling proteome reference map was constructed to serve as a platform for the analysis of early-stage soybean response to environmental stresses. The prevalence of proteins involved in metabolism and secondary metabolism indicated that various physiological processes occur in 48 h-old soybean seedlings to support radicle protrusion and growth. Because these processes should occur coordinately, this stage is extremely susceptible to environmental Journal of Proteome Research • Vol. 8, No. 4, 2009 2063

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Figure 5. Proteins differentially expressed in the control and flooding-stressed soybean seedlings. Protein expression levels were calculated using PDQuest software with 4 biological replications and plotted as the relative intensity of all spots detected on the gels. Values are the means of the protein values of gels from 3 physiologically independent experiments. Spots with 1.2-fold cutoff were shown. Asterisks indicate significant differences between control and flooding-stressed seedlings (*P < 0.05, **P < 0.01). SE is denoted by error bars. 2064


Hashiguchi et al. stresses. It is reasonable that proteins related to defense/disease were expressed in large numbers to protect these sensitive seedlings. Flooding stress for 24 h suppressed the growth of hypocotyls and roots. It also inhibited hypocotyl pigmentation. Complete submergence reportedly decreases light intensity, dampening photosynthesis.30 Inhibition of pigmentation suggested that soybean seedlings subjected to flooding stress are affected by not only hypoxic stress, but also light stress caused by attenuated weak light. Flooding stress is complex stress involving multiple stresses such as hypoxic, water, cold, and light stresses. There are several stress perceptions and responses, some of which are specific while others may cross-talk. To elucidate the mechanism of flooding tolerance, comprehensive expression analysis of genes or proteins is required. In response to flooding stress, 51 differentially expressed proteins were identified by high-throughput proteome profiling. These 51 proteins included proteins related to glycolysis (UDP-glucose pyrophosphorylase, fructose-biphosphate aldolase and nucleoside diphosphate kinase) (Supplemetal Table 3 in Supporting Information). Shift to alternative pathways of energy generation is crucial for plants to survive flooding stress because photosynthesis cannot be carried out under complete submergence due to scant light and low CO2 availability.31 Cells cope with this energy crisis by regulating glycolysis and fermentation processes. Among the identified glycolysis-related proteins, UDP-glucose pyrophosphorylase is positioned at the crossroads of sucrose synthesis and breakdown, producing UTPs used in the conversion of UDP-glucose to glucose-6P by fructokinase.31 Nucleoside diphosphate kinase recycles ATPs consumed by fructokinase. These lines of evidence that these enzyme expressions were up-regulated in flooding-stressed seedlings indicate that soybean seedlings can adjust their metabolic status and thus reduce energy consumption to cope with long periods of submergence. Limited underwater growth also supported this idea. Several reactive oxygen species (ROS) scavengers were found as flooding responsive proteins. ROS, such as superoxide radicals, hydroxyl radicals or hydrogen peroxide, play a dual role in plants, acting as a toxic product of normal cell metabolism and a regulatory molecule in stress perception and signal transduction.32 ROS scavengers such as 1-Cys peroxiredoxin, APX, glutathione peroxidase and SOD are stress indicators induced by various stress signals. They play roles in ROS removal to prevent oxidative damage in light- or heat-stressed plants.33 However, in flooding-stressed plants, the accumulation of toxic ROS is probably mild compared with light- or heatstressed plants because of low level of metabolism, as suggested by the induction of glycolytic enzymes. Consistently, one of the ROS scavengers, APX 2, has been discovered as a downregulated protein in flooding-stressed soybean seedlings.28 Two APXs were also down-regulated in our experiments. In contrast, most of these enzymes, except APXs, were up-regulated (Figure 5). Differences in response to flooding stress between APXs and other ROS scavengers appear to originate from the different positions of these enzymes in ROS scavenging pathways. APXs were shown to be located on the very upstream of the scavenging pathway so that they can sense the low ROS level in flooding-stressed soybean and negatively regulate their own expression levels. On the other hand, other enzymes were induced by the stress signal as general stress indicators. Proteins classified into the defense/disease category accounted for a major part of differentially expressed proteins

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Proteins in Flooding Response in Soybean a

Table 1. Proteins Affected by Flooding Stress in Soybean Seedlings experimental theoretical MMc (kDa)

pIc

672

28.8

6.8

781 784

16.7 16.1

4.1 5.2

90

65.7

4.7

71.4

131

61.9

4.6

59

435

28.5

5.9

24.5

595

34.5

5.6

27.1

596

34.2

5.7

27.2

632

30.4

6.2

27.7

649

29.7

5.1

26.6

724

22.4

4.1

23.9

734

18.6

5.8

18.7

248

56.4

4.7

51.6

5.2

Metabolism UDP-glucose pyrophosphorylate [Amorpha fruticosa]

383

45.5

7.2

38.6

7.1

Fructose-biphosphate aldolase, cytoplasmic isozyme

402

45.5

5.7

42.4

6

586

35.8

5.1

32.8

6.2

792

14.1

6.2

16.5

6.3

248

56.4

4.7

72.5

5.5

613

33.8

4.3

72.5

5.5

659

30.9

4.3

72.5

5.5

509

37.9

4.2

24.4

4.5

654

30.5

8

30

770

16.9

5.6

17.7

no.b

MM (kDa)

pI

amino acid sequencesd

accession no.g

Defense/Desease Probable peroxiredoxin P52572 (EC1.11.1.15) N-DFVLDNEGNP Trypsin inhibitor B (Kunitz) P01071 I-VKAVAVLGSX Superoxide dismutase [Cu-Zn] 4A P23345 (EC 1.15.1.1) 5.1 70 kDa heat shock cognate Gm0112x00186 protein [Vigna radiata] AAS57912.1 5.1 Protein disulfide isomerase-like Gm0065x00031.3 protein BAD24712.1 6.4 1-Cys peroxiredoxin (thioredoxin Gm0022x00644.2 peroxidase)(Rehydrin) Q6E2E6 5.5 Ascorbate peroxidase [Glycine Gm0080x00023.2 max] AAA61779.1 5.7 Cytosolic ascorbate peroxidase 2 Gm0112x0276.2 [Glycine max] BAC92740.1 6.6 Cysteine proteinase inhibitor Gm0172x00066 [Glycine max] BAA19608.1 6.8 Cp 10-like protein Gm0010x00428.1 AAM77651.1 5.2 Putative Kunitz trypsin protease Gm0150x00108 inhibitor [Glycine max] ACA23205.1 6.6 Glutathione peroxidase [Malus x Gm0013x00705 domestica] AQ03092.1 N-PGLTIGDTIP

10.2 5.6

Eukaryotic translation initiation factor 5A isoform I

90

up

100 100

up up down

603 23/42%

down

624 14/62%

up

328 13/57%

down

814 18/67%

down

1028 17/64%

down

865 20/71%

down

420 5/35%

down

202 8/39%

up

Gm0040z0014

661 22/55%

down

AAL33919.1 Gm0036x00298

587 15/46%

up

Protein Destination/Storage Beta-conglycinin alpha prime Gm0052x00475 subunit [Glycine max] BAE02726.1 Beta-conglycinin alpha prime Gm0052x00475 subunit [Glycine max] BAE02726.1 Beta-conglycinin alpha prime Gm0052x00475 subunit [Glycine max] BAE02726.1

40S ribosomal S4 protein

matchf/ regulation by %cov flooding

951 24/42%

O65735 Cytosolic phosphoglycerate kinase Gm0054x00118 [Pisum sativum] AAF85975.1 Triosephosphate isomerase Gm0225x00011 NP_1797131.1 Nucleoside diphosphate kinase I Gm0072x00084 Q39839

Protein Synthesis Elongation factor 1B alpha-subunit 1[Arabidopsis thaliana]

homologye score

Gm0015x00664 NP_196772.1 Gm0104x00040 AAM93434.1 Gm0025x00905

1111 18/62%

down

470 9/34%

down

1067 11/62%

657 1%

up

down

1510 15/23%

up

988 17/19%

up

643 11/75%

up

135 4/15%

down

157 5/25%

up

AAQ08191.1 304

49.8

5.5

43.4

5.5

Secondary Metabolism S-adenosyl-L-methionine synthetase [Medicago sativa]

481

42

5.7

37.8

6

Aldo/keto reductase AKR [Manihot esculenta]

609

29.7

5.5

29

6.3

Acid phophatase

spot b

44.3

6.9

38.6

6

Peroxidase [Glycine max]

404

43.8

6.7

36

6.3

Signal Transduction TGF-beta receptor-interactiong protein-1 [Phaseolus vulgaris]

Gm0065x00008.1

1778 23/76%

ABO77438.1 Gm0018x00048.1

969 15/43%

up

507 11/49%

down

AAX84672.1 Gm0146x00211.2 CAA11075.1 Gm0307x00010 AA37376.1 Gm0138x00015

down

1463 17/37%

up

574 16/65%

up

AAK49947.1

Journal of Proteome Research • Vol. 8, No. 4, 2009 2065

research articles

Hashiguchi et al.

Table 1. Continued experimental theoretical no.b

412

MMc (kDa)

pIc

MM (kDa)

pI

44.1

6.8

36

6.3

TGF-beta receptor-interactiong protein-1 [Phaseolus vulgaris]

5.5

Transcription Glycine-rich RNA-binding protein [Glycine max]

amino acid sequencesd

accession no.g

homologye score

Gm0098x00037

matchf/ regulation by %cov flooding

633 15/58% up

AAK49947.1 796

14

4.9

16.7

Gm0248x00047

1119 7/50%

up

198 4/15%

up up up up

AAA33985.1 Gm0200x00034

271 11/24%

up

AAA33985.1 Gm0200x00034

789 27/40%

up

1689 28/56%

up

542 19/40%

up

1041 35/63%

up

956 26/47%

up

564 10/58%

up

735 16/48%

down

980 17/57%

down

509 13/50%

down

720 22/65%

down

ABK93363.1 Gm0113x00271.1

730 13/50%

down

P10743 Gm0107x00278.2

1616 20/54%

up

P15490 Gm0030x00410

780 14/36%

up

AAD49719.1 Gm0030x00410

281 9/29%

up

AAD49719.1 Gm0030x00410

136 4/23%

up

AAD49719.1 Gm0015x00336.1

494 9/44%

up

1683 14/89%

up

796 27/56%

up

AAD48471.1 Unclear Classification N-ADXNGAXSPF Albumin precursor (A1) N-ADXNGAXSPF Albumin precursor (A1) N-ADXNGA Albumin precursor (A1) 6.3 Maturation polypeptide [Glycine max]

3501 spot a spot c 134

37.3 47.6 40.7 61.5

6.9 6.9 6.9 6.2

50.6

135

61.7

6.5

50.6

6.3

Maturation polypeptide [Glycine max]

136

54.2

7

49.5

7.1

Late embryogenesis-abundant protein [Glycine max]

219

55.1

6.2

47.8

6

Maturation polypeptide

222

55.3

6

47.8

6


237

54.9

6.4

47.8

6


244

55.2

6.7

49.5

7.1


450

42

4.4

24.4

4.8

Unknown [Populus trichocarpa]

576

35.1

5.8

29.4

6.7

Stem 31 kDa glycoprotein precursor

577

35.4

5.5

27.5

5.6


586

35.8

5.1

25.6

5.5


589

33.6

6

29.4

6.7


647

29.6

7.7

29.2

8.8


675

26.8

5.1

25.6

5.5

Maturation protein pPM32 [Glycine max]

684

26.7

5

25.6

5.5


720

22.3

4.8

25.6

5.5


770

16.9

5.6

22.8

8.7

Unnamed protein product [Vitis vinifera]

773

18.5

4.5

18.6

4.9

Unnamed protein product [Vitis vinifera]

799

11.8

5.1

11.5

5.5


spot d

52.6

5.9

47.8

6


N.D.h 771

19.1

4.3

N.D.

Q9FRT8 Q9FRT8 Q9FRT8 Gm0294x00005

AAA33985.1 Gm0025x00312 CAA80491.1 Gm0294 × 00005 AAA33985.1 Gm0294x00005 AAA33985.1 Gm0294x00005 AAA33985.1 Gm0025x00312 CAA80491.1 Gm0131x00054 ABK92744.1 Gm0113x00272.1 P10743 Gm0023x00091.2 ABK95918.1 Gm0011x00193.1

CAO21273.1 Gm0011x00008 CAO63869.1 Gm0050x00138 AAB68027.1

80 80 83

up

a Proteins were identified by protein sequencer and LC-MS/MS from soybean subjected to flooding stress for 24 h and nontreated control. Proteins were sequenced or identified by analysis of tryptic peptides following searching Swiss-Prot or Uniprot-Sprot databases for sequences and soybean genome database for MS/MS data, respectively. Annotations were obtained by BLAST search using soybean protein against the NCBI nonredundant database. b The spot numbers as given in Figure 4. c Molecular mass (MM) and pI as calculated from the gel in Figure 4. d N-terminal (N-) and internal (I-) amino acid sequences as determined by Edman degradation. e The homology for the identity of protein sequences for Edman degradation. f Number of unique peptides identified. g Accession numbers in database of Uniprot-Sprot or soybean genome database. h N.D. means the proteins whose amino acid sequence or MS/MS were not determined.

induced by flooding stress. It is reported that disease reaches epidemic proportions when plants are grown during the rainy season under highly humid conditions.34 One of the constraints reducing crop yield of soybean is the spread of diseases. The changes in protein levels involved in defense/disease mechanisms could partly explain the harmful effects of flooding stress. 2066


The largest portion of flooding-affected proteins is composed of proteins with unclear classification. Most of them are maturation proteins, late embryonic abundant proteins, and glycoprotein precursors. Although their exact function has not yet been fully described, they are shown to be associated with drought tolerance,35,36 salt tolerance37 and wounding.38 Hier-


research articles works switches intermediator proteins as induced by flooding stress. In the control, protein 659 controlled protein 577 (unknown) to affect proteins 596 (APX) and 781 (Kunitz trypsin inhibitor) (Figure 8A, network II). When stressed, protein 659 recruited protein 586 as its new intermediator and discarded protein 577, enabling it to affect proteins 304 and 654 (Figure 8B). Proteins 577 and 586 are both unknown proteins without any functional annotations (Supplemental Table 2 in Supporting Information). From these results, comprehensive proteomic studies are thus useful for identifying unknown proteins as stress-responsible factors and for reconstructing system response networks of mutual effects. The above-mentioned data suggest that the soybean response to flooding stress includes not only anaerobic protein induction, as suggested by changes in the expression levels of glycolytic enzymes and ROS scavengers, but also a certain defense system involving maturation proteins. In addition, there were other response

Figure 6. Functional distribution of proteins affected by flooding stress for 24 h. (A) Thirty-five up-regulated protein spots were determined using a protein sequencer and nanoLC-MS/MS. The chart shows the distribution of these proteins after functional classification. (B) Sixteen down-regulated protein spots were determined using a protein sequencer and nanoLC-MS/MS. The chart shows the distribution of these proteins after functional classification.

archical clustering showed that these proteins tend to be located in the same branch, for example, cluster IV. This cluster of 7 proteins includes 2 proteins associated with defense (protein 632, cysteine proteinase inhibitor; protein b, peroxiredoxin). A coexpression study is one of the means for estimating protein function because proteins located in the same biological pathways are likely to group together. The reliability of the clustering is confirmed by the fact that downregulated proteins with the same functional assignment were grouped in a certain branch in cluster VI (proteins 649, cp 10like protein, 596 and 595, APX, and 724, Kunitz trypsin inhibitor). Thus, it can be assumed that proteins such as maturation proteins, late embryonic abundant proteins, and glycoprotein precursors in cluster IV can receive functional assignments of defense. Protein-protein interaction analysis clearly showed that flooding stress affected the overall protein interactions occurring in the soybean seedlings (Figure 8). New interactions generated by flooding stress showed a hub in the network where 3 proteins (proteins 304, S-adenosyl-L-methionine synthetase; 586, triosephosphate isomerase/unknown; and 654, 40S ribosomal protein) are centered. These 3 proteins belong to cluster I whose expression levels decrease with flooding stress. It is intriguing that these proteins showing dramatically reduced expression as induced by flooding stress play central roles in response to stress. Some pathways suppressed in normal conditions may be activated in flooding-stressed soybean seedlings for survival. Another interesting discovery is that an upstream protein, protein 659 (beta-conglycinin), in the net-

Figure 7. Summary of the significant clusters. Significant clusters are indicated by black rectangles. Expression profile patterns are shown on the right side of the figure. Protein ratios were transformed into log scale, and the temporally changed profiles of 51 differentially expressed proteins were divided into 6 clusters. Downward arrows beside the protein numbers show down-regulated proteins. Functional classification is denoted. Functional classifications of proteins with multiple protein assignments are also placed side by side. Journal of Proteome Research • Vol. 8, No. 4, 2009 2067

research articles

Hashiguchi et al. Organization, Japan. The authors thank Dr. S. Kuroda for his kind support to the research. We thank Mr. T. Sugimoto for his support to this work. We also thank Dr. T. Nakamura, Dr. R. Yamamoto, and Dr. S. Shimamura for helpful discussions.

Supporting Information Available: Supplemental Table 1, proteins identified in early-stage soybean seedlings; Supplemental Table 2, peak lists of MS/MS data for identified proteins; Supplemental Table 3, proteins expression levels of 51 differentially identified spots; Supplemental Figure 1, reference map of soybean proteins without spot numbers. This material is available free of charge via the Internet at http:// pubs.acs.org. References

Figure 8. Interactions of proteins regulated by flooding stress for 24 h. The figure shows a network of proteins for which associated proteins are connected. Green circles indicate each protein. Red arrows show inductive interactions and blue Ts demonstrate suppressive interactions. (A) Interaction networks in control seedlings. There are 2 major interaction networks (networks I and II). (B) Interaction networks in flooding-treated seedlings. Networks were integrated to generate a large interaction network (gray screened).

pathways involving proteins of unknown functions that were newly identified as flooding-responsive proteins in this research. Abbreviations: APX, ascorbate peroxidase; CBB, Coomassie brilliant blue; PBS, phosphate-buffered saline; PVDF, polyvinylidene difluoride; ROS, reactive oxygen species; SOD, superoxide dismutase; 2-DE, two-dimensional polyacrylamide gel electrophoresis.

Acknowledgment. This work was supported by the grants 2068

from

National

Agriculture

and

Food


Research

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Proteome Analysis of Early-Stage Soybean Seedlings under Flooding

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