Shotgun Proteomic Analysis of Long-distance Drought Signaling in

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Shotgun Proteomic Analysis of Long-distance Drought Signaling in Rice Roots Mehdi Mirzaei,† Neda Soltani,‡ Elham Sarhadi,‡ Dana Pascovici,§ Tim Keighley,§ Ghasem Hosseini Salekdeh,‡ Paul A. Haynes,*,† and Brian J. Atwell|| †

Department of Chemistry and Biomolecular Sciences, Macquarie University, North Ryde, NSW, Australia Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran, Karaj, Iran § Australian Proteome Analysis Facility, Macquarie University, North Ryde, NSW, Australia Department of Biological Sciences, Macquarie University, North Ryde, NSW, Australia

)

‡

bS Supporting Information ABSTRACT: Rice (Oryza sativa L. cv. IR64) was grown in split-root systems to analyze long-distance drought signaling within root systems. This in turn underpins how root systems in heterogeneous soils adapt to drought. The approach was to compare four root tissues: (1) fully watered; (2) fully droughted and split-root systems where (3) one-half was watered and (4) the other half was droughted. This was specifically aimed at identifying how droughted root tissues altered the proteome of adjacent wet roots by hormone signals and how wet roots reciprocally affected dry roots hydraulically. Quantitative labelfree shotgun proteomic analysis of four different root tissues resulted in identification of 1487 nonredundant proteins, with nearly 900 proteins present in triplicate in each treatment. Drought caused surprising changes in expression, most notably in partially droughted roots where 38% of proteins were altered in level compared to adjacent watered roots. Specific functional groups changed consistently in drought. Pathogenesis-related proteins were generally up-regulated in response to drought and heat-shock proteins were totally absent in roots of fully watered plants. Proteins involved in transport and oxidation reduction reactions were also highly dependent upon drought signals, with the former largely absent in roots receiving a drought signal while oxidation reduction proteins were strongly present during drought. Finally, two functionally contrasting protein families were compared to validate our approach, showing that nine tubulins were strongly reduced in droughted roots while six chitinases were up-regulated, even when the signal arrived remotely from adjacent droughted roots. KEYWORDS: Chitinases, drought signaling, label-free shotgun proteomics, pathogenesis-related proteins, plant proteomics, rice, split root

of water status.6 For example, maize root growth is enhanced in dry soils, presumably to improve water extraction;7 this was subsequently shown to be the result of ABA promoting root growth.8 The perception of ABA in roots and extent of the processes modified by it remain speculative, with major families of drought-inducible transcription factors up-regulated by water stress and ABA.9 Proteins that typically play a role in tissue drying, such as the late embryogenesis proteins, are induced as a result. The complexity with which root tissues respond to water stress at the cellular and molecular levels reflects the evolutionary pressure to survive water deficits in most terrestrial plants. The hierarchy of gene-level responses to drought10 12 must take into account interacting stress signaling systems.11 However, in spite of these highly mobile drought signals and subtle amplification

1. INTRODUCTION Water stress is the most serious limitation to plant productivity globally,1 with major droughts certain to impose ongoing threats to food security. Drought exerts its initial effect on leaves by disruption of plant hydraulics, but a complex series of secondary effects follow in which stomatal behavior is modified, causing reduced transpiration.2,3 This physiological acclimation necessarily requires regulation through long-distance signaling mediated by plant hormones. Abscisic acid (ABA) is widely accepted as the primary chemical signal transmitted to shoots when plants are droughted. Cytokinins released from growing roots have also been implicated as a possible antagonist to the effects of ABA on stomata.3 Thus, ABA is thought to emanate from roots and accumulate in leaf epidermal cells, although the origin of this ABA remains in question.4 In the past decade, it has become clear that the perception of ABA arriving in leaves determines part of the plant response to drought, with heterotrimeric G-proteins affecting downstream responses to water deficits.5 However, the analysis of drought effects has largely concentrated on above ground transpiring organs, while roots are clearly primary sensors r 2011 American Chemical Society

Special Issue: Microbial and Plant Proteomics Received: September 2, 2011 Published: November 03, 2011 348

dx.doi.org/10.1021/pr2008779 | J. Proteome Res. 2012, 11, 348–358

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systems, there is also an argument that hydraulic signals from roots are the first to affect water loss in shoots.4 This would enable roots to detect subliminal dryness and elicit acclimatic changes in shoots such as reduced transpiration and growth. One approach to distinguishing the hydraulic and chemical signaling coming from drying roots is to investigate events at the level of gene expression. This strategy is best applied to split-root systems, where roots are partially dried and positive hydraulic signals combine with negative chemical signals to help separate their contribution to drought sensing. These experiments are not only informative with respect to drought signals to shoots: the possibility that long-distance signals could influence gene expression in contrasting zones of a root system with different water supply can also be studied in this manner. Apart from providing a better understanding of underlying events in drought, this study gives clues to the basis of restriction deficit irrigation, where dry roots induce water saving responses in plants which simultaneously have adequate water supplied by localized zones of irrigation. A proteomics approach was applied to analyze the effect of drought on the proteome of rice roots. One goal was to provide knowledge for molecular plant breeding programs under drought conditions, extending previous application of proteomics to drought stress studies.13 Traditional 2D-PAGE techniques have been the primary method for quantitative proteomic studies in many plant species exposed to environmental stresses, particularly drought stress, including rice,12,14,15 maize,16 sugar beet,17 banana,18 alfalfa19 and wheat.20 Nevertheless, certain limitations of 2D-PAGE techniques are undeniable, namely low representation of proteins with high molecular weights and pIs, hydrophobic membrane spanning proteins, due to poor solubility, and low-abundance proteins, due to limitation of total protein loading. Thus, alternative quantitative proteomics techniques such as stable isotope labeling and label-free approaches have been assessed by various groups. Among these techniques, labelfree quantitation based on spectral counting has become a popular and efficient approach for use in environmental stress studies involving comparison of multiple variables such as drought,15 heat stress21,22 and cold.23 In this study, we exposed rice seedlings to partial root drying, resulting in a substantial decrease in shoot dry weight, presumably by root-to-shoot communication. We analyzed the proteome of well-watered, droughted and partially dried root samples using a quantitative label free shotgun proteomics approach.

surface (well-watered, WW); same as well-watered until 14 d after transplanting, after which water was withheld from both compartments (water deficit, WD); same as well-watered until 14 d after transplanting, after which water was withheld from only one out of two compartments in each pot, with one drying root half (SpWD) and one well-watered root half (SpWW). Experiments were conducted in a glasshouse in the spring-summer period, with natural illumination. Nitrogen, phosphate and potassium were added as 2.73 g of urea, 1.84 g of Solophos, and 1.04 g of muriate of potash, to each pot, respectively. Roots from each compartment from each pot were sampled from three replicate pots. All analysis was performed on a randomized design with three replicates. Root tissues were immediately washed very briefly with purified water and lyophilized. 2.2. Relative Water Content Analysis

Relative water content (RWC) was calculated according to the method of Barrs and Weatherley.24 Leaf discs (1 cm in diameter) were sampled from a recently expanded leaf, weighed, and then floated on distilled water for 2 h so that they became fully turgid. Discs were weighed at full turgidity and again after drying at 70 °C for 24 h. The relative water content was calculated as [(fresh weight dry weight)/(turgid weight dry weight)] 100 = % relative water content. 2.3. Quantitative Analysis of Abscisic Acid

Abscisic acid (ABA) of rice leaf was extracted as described previously25 with some modifications.26 Briefly, leaf samples (0.5 1 g) were homogenized in 40 mL of 80% (v/v) aqueous methanol containing 0.25 g/L butylated hydroxytoluene and 0.44 g/L ascorbic acid (extraction buffer) with mortal and pestle. The suspension was incubated for 16 h in the dark at 4 °C and filtered through a Whatman filter, No 1, pore size 11 μm and washed with the extraction buffer. The methanol was evaporated under vacuum and 0.5 M phosphate buffer, pH 7, was added to the remaining mixture with the same volume, and the pH was adjusted to 8.5 with 0.2 N KOH and partitioned with ethyl acetate. After removal of the ethyl acetate phase under vacuum, the pH of the aqueous phase was adjusted to 2.5 with 1 N HCl. The solution was partitioned with ethyl acetate and the whole solution was stirred, but this time the ethyl acetate phase was kept. The sample was filtered with a 0.45 μm membrane syringe filter and then injected on to a HPLC Eurospher-100 C18 column (250 4 mm I.D.; 5 μm particle size, Knauer, Germany). The column was eluted isocratically with mobile phase (100% methanol and 0.2% acetic acid (50:50 (v/v)) at a flow rate of 0.7 mL/min. The ABA peak was measured at 257 nm at 40 °C and quantified using a known standard solution.

2. METHODS 2.1. Plant Material and Sampling

2.4. TCA-Acetone Protein Extraction and Separation by SDS-PAGE

Seeds of rice genotype, IR64, were obtained from the International Rice Research Institute (Los Ba~ nos, The Philippines). Surface sterilized seeds were pregerminated for 3 d, grown on Yoshida culture solution for 10 d, and then transplanted into pots for split-root culture. The pots were 26 cm in length, 20 cm in width and 15 cm in height. An internal wall divided each pot into two equal parts allowing for equal distribution of soil and water between the parts. A mixture of clay, sand and loam (1:2:1) was added to pots to within 5 cm from the top of both parts. Equal proportions of the root system of each seedling were distributed between the compartments. The following treatments were imposed for 14 d in randomized design with three replicates: watered daily and kept flooded to about 2.5 cm above the soil

Fifty milligrams of freeze-dried root powder was suspended in 1200 μL of 10% TCA in acetone, 0.07% β-mercaptoethanol, and incubated at 20 °C for 45 min. The extract was centrifuged for 30 min at 16000 g, and the pellet was collected and washed with 600 μL 100% acetone followed by centrifugation for 30 min at 16000 g. The acetone washing step was repeated three times, the colorless resulting pellet was lyophilized in a vacuum centrifuge and protein quantification was performed by Bradford assay. Extracted proteins in sodium dodecyl sulfate (SDS) sample buffer (120 μg per well) were separated on 10% bis-Tris polyacrylamide gels at 150 V for 1 h. After electrophoresis, proteins were visualized using colloidal Coomassie Blue. The gels 349

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and (0.2 Da, tolerance of 2 missed tryptic cleavages and K/R-P cleavages. Fixed modifications were set for carbamidomethylation of cysteine and variable modifications were set for oxidation of methionine.

were then washed twice in water (10 min per wash), before individual lanes were cut into 16 slices of equal sizes from top to bottom. 2.5. Trypsin In-gel Digestion

Each stained gel lane was cut into 16 equal size pieces and each piece was further chopped and placed into a well of a 96-well plate. To destain, the gel pieces were briefly washed with 100 mM NH4HCO3, then twice with 200 μL of ACN (50%)/100 mM NH4HCO3 (50%) for 10 min and finally dehydrated with 100% ACN. The samples were air-dried and reduced with 50 μL of 10 mM DTT/NH4HCO3 (50 mM) at 37 °C for 1 h before alkylating in the dark with 50 μL of 50 mM iodoacetamide/ NH4HCO3 (50 mM) at room temperature for 1 h. They were then briefly washed with 100 mM NH4HCO3, 200 μL of ACN (50%)/100 mM NH4HCO3 (50%) for 10 min, dehydrated with 100% ACN and then air-dried. Finally, samples were digested with 20 μL of trypsin (12.5 ng/mL 50 mM NH4HCO3) for 30 min on ice and then overnight at 37 °C. Peptides resulting from trypsin digestion of proteins were extracted twice with 30 μL of ACN (50%)/formic acid (2%), dried, vacuum centrifuge and reconstituted to 10 μL with 2% formic acid.

2.8. Data Processing and Quality Control

The three protein identification GPM output files from each of the replicates were combined into one joint data set to produce a single shotgun proteomic analysis for each condition. Only proteins which were identified in all three replicates were retained in the final data set for each condition, and reversed database hits and contaminants were excluded. An additional requirement was imposed of having a total spectral count of at least six for at least one condition.21,31 The protein false discovery rate was then calculated using the reverse database as decoy, hence protein FDR = (# Reverse proteins identified)/(Total protein identifications) 100;32 in addition the peptide false discovery rate was calculated as Peptide FDR = 2*(# Reverse peptide identifications)/(Total peptide identifications) 100.33

2.9. Quantitative Proteomic Analysis

Protein abundance data were calculated based on normalized spectral abundance factors (NSAF) as described previously.34 For each protein, k, in sample i, the number of spectral counts identifying the protein was divided by the estimated length of the protein. The protein length was determined as the protein molecular weight divided by the average amino acid molecular weight. The SpCk/Lengthk values normalized to the total by dividing by the sum (SpCk/Lengthk) over all proteins, yielding the NSAFi values for each sample i. When plotting or summarizing overall protein abundance for a particular condition the average of the NSAF values for all replicates was used as a measure of protein abundance. A spectral fraction of 0.5 was added to all spectral counts initially, to compensate for null values and allow for log transformation of the NSAF data prior to statistical analysis.35

2.6. Nanoflow Liquid Chromatography Tandem Mass Spectrometry

The tryptic digest extracts from 1DE gel slices were analyzed by nanoLC-MS/MS using a LTQ-XL ion-trap mass spectrometer (Thermo, Fremont, CA).27 Reversed phase columns were packed in-house to approximately 7 cm (100 μm i.d.) using 100 Å, 5 μM Zorbax C18 resin (Agilent Technologies, Santa Clara, CA) in a fused silica capillary with an integrated electrospray tip. A 1.8 kV electrospray voltage was applied via a liquid junction upstream of the C18 column. Samples were injected onto the C18 column using a Surveyor autosampler (Thermo, Fremont, CA). Each sample was loaded onto the C18 column followed by an initial wash step with buffer A (5% (v/v) ACN, 0.1% (v/v) formic acid) for 10 min at 1 μL/min. Peptides were subsequently eluted from the C18 column with 0%-50% Buffer B (95% (v/v) ACN, 0.1% (v/v) formic acid) over 58 min at 500 nL min 1 followed by 50 95% Buffer B over 5 min at 500 nL min 1. The column eluate was directed into a nanospray ionization source of the mass spectrometer. Spectra were scanned over the range 400 1500 amu. Automated peak recognition, dynamic exclusion window set to 90s28 and tandem MS of the top six most intense precursor ions at 35% normalization collision energy performed using the Xcalibur software (version 2.06) (Thermo, Fremont, CA).

Several t tests were performed to find the proteins up and down-regulated between conditions. In each particular comparison, only proteins identified reproducibly, meaning they were present in all replicates for at least one condition, were included in the data set. The 2-sample unpaired t tests were run on log transformed NSAF data, and proteins with a t test p-value less than 0.05 were considered to be differentially expressed. The resulting sets of up- and down-regulated proteins were then functionally annotated.

2.7. Protein Identification

2.11. Functional Annotation

2.10. Statistical Analysis

Raw files were converted to mzXML format and processed through the global proteome machine (GPM) software using version 2.1.1 of the X!Tandem algorithm, freely available from http://www.thegpm.org.29,30 For each experiment, the 16 fractions were processed sequentially with output files for each individual fraction, and a merged, nonredundant output file was generated for protein identifications with log (e) values less than 1. Tandem mass spectra were searched against the NCBI O. sativa protein database within GPM containing 26938 protein sequences as of August 2010. The database also incorporated common human and trypsin peptide contaminants, and additional searching was performed against a reversed sequence database to evaluate the false discovery rate (FDR). Search parameters included MS and MS/MS tolerances of (2 Da

Gene ontology (GO) annotation was extracted from the Uniprot database and matched to the list of reproducibly identified proteins. In-house software was developed using the R statistical programming framework (http://www.r-project. org/) to process and summarize the gene ontology annotation.36 The resulting R package (PloGO) and documentation is available online at www.proteome.org.au/services/bioinformatics/ default.aspx. The available gene ontology annotation was summarized for each category of interest from a list of selected biological process categories, for the results of each comparison test (up, down-regulated proteins). For gene ontology categories of interest, NSAF abundance data was summed to obtain overall protein abundance change over time for biological process categories. Then gene ontology annotation and relative protein 350



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abundance was plotted side by side for the up and downregulated proteins for each comparison tests.

of the split-rooted plants was between those of WD and WW (data not shown). Therefore, even though protein loading for the shotgun proteomic analysis was equalized by protein weight, there may be some protein expression differences caused by subtle developmental stage differences between the plants.

3. RESULTS AND DISCUSSION 3.1. Physiological Measurements of Water Stress in Splitrooted Plants

3.2. Analysis of Label-free Shotgun Proteomics

A total of 1487 nonredundant proteins was identified in the four different root tissues. Table 1 represents a summary of proteins identified, and the details of all 1487 reproducibly identified proteins are provided in Supplementary Table S1 (Supporting Information). The number of proteins reproducibly identified ranged from a maximum of 1145 in roots of wellwatered plants (WW) to a minimum of 892 in the water-deprived roots of split-root systems (SpWD). There were 899 in wellwatered roots of split-root systems (SpWW) and 939 proteins in roots under complete water deficit (WD). Calculated levels of peptide FDR varied from 0.06 to 0.24%, while protein FDR was less than 1%, indicating that the data set was of sufficient stringency that further filtering was not required (Table 1). Supplementary Table S2 contains details of all the proteins identified in each drought condition, including their NSAF values (Supporting Information).

The relative water content (RWC) of leaves of both WD and split-root treatments were lower than in leaves of WW (Figure 1A). RWC of leaves when roots were split fell to 62%, indicating moderate stress. Water stress reduced RWC of shoots of split-root plants by 20% and that of WD plants by 36% compared with WW, demonstrating the benefit of supplying water to half the root system at the time of splitting roots. Consistent with this level of water deficit, ABA levels increased in both split-root and WD shoots but to a larger extent in WD. The measured ABA level of split-root and WD plants increased by 23 and 39%, respectively, compared with WW It is important to note that, as expected, the WW plants accumulated significantly more shoot biomass than the WD plants, and the shoot biomass

3.3. Qualitative and Quantitative Comparison of Differentially Expressed Proteins as Controlled by Drought Signals

Three separate t test comparisons were undertaken between treatment pairs in order to determine the statistical significance of fold-changes of proteins caused by long distance signaling from water-deprived roots. The primary comparison of SpWW vs SpWD was made first in order to establish the contrast between tissues caused by withholding water. However this difference is the result of both the hydraulic influence of SpWW on SpWD, as well as drought-inducible signals from SpWD influencing SpWW. Therefore these two distinct signaling phenomena were dissected by the two analyses described below in sections 3.3.2 and 3.3.3. The proteins identified as being significantly differentially expressed between treatments, sorted by biological function, are provided in Supplementary Table S3 (Supporting Information). 3.3.1. SpWW vs SpWD: Root-specific Effects of Drought on the Proteome. In the water-deprived roots of the split root Table 2. Number of Proteins Differentially Expressed between the Water-deprived and Well-watered Roots of Splitrooted Plants

Figure 1. Physiology measurements of leaf material taken from wellwatered, spilt-rooted and water-deprived rice plants. (A) Relative water content, (B) abscisic acid in microgram per gram of leaf tissue. In both panels, WW indicates well-watered plants, Sp indicates split-rooted plants and WD indicates water-deprived plants. In (A), Y-axis indicates percentage relative water content, and in (B), Y-axis indicates micrograms ABA per gram of leaf tissue.

student t test analysis WW vs SpWW SpWW vs SpWD SpWD vs WD Down-regulated

319

126

74

Up-regulated

197

90

72

Unchanged

835

863

923

Table 1. Summary of Numbers of Proteins Identified no. of identified proteinsa condition

a

protein FDRb (%)

peptide FDRb (%)

R1

R2

R3

no of proteins common to all 3 replicates

WW

3604

3393

3100

1154

0.52

0.24

SpWW

2975

2808

3032

906

0.44

0.13

SpWD WD

2705 2892

2707 2605

3028 2559

896 948

0.22 0.63

0.06 0.22

R1, R2 and R3 denote replicate 1, replicate 2 and replicate 3, respectively. b FDR = False discovery rate. 351



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Figure 2. Qualitative and quantitative comparison of differentially expressed proteins obtained from each t test comparison. Up-regulated and downregulated proteins were classified in to 17 different biological process categories. Using PloGO, ontology annotation (number of proteins in each biological process) and corresponding relative protein abundance (sum of NSAF value of the same proteins) was plotted side by side for the up and down-regulated proteins. (A) Comparison of number and abundance of differentially expressed proteins in various biological processes obtained from t test comparison of SpWW against SpWD. (B) Comparison of number and abundance of differentially expressed proteins in various biological processes obtained from t test analysis of WW against SpWW. (C) Comparison of number and abundance of differentially expressed proteins in various biological processes obtained from t test analysis of SpWW against SpWD.

plants, 126 proteins were down-regulated compared to the levels in well-watered roots attached to the same shoot. However, 90 proteins were up-regulated, suggesting substantial numbers of drought-responsive proteins (Table 2). The following analysis of the processes in which these proteins participate excludes the large complement involved in “general metabolism”, even though some proteins in this category can co-occur in others. The major protein groups which were down-regulated in SpWD were associated with carbohydrate metabolism, biosynthesis, energy and protein metabolism, with a smaller number of proteins involved in oxidative reactions. Two key categories associated with growth, (biosynthesis and protein metabolism) were notably induced in droughted roots, suggesting that adaptive responses such as fine root proliferation or tuberized “resurrection” roots occurred in response to drought.37 A smaller number of proteins associated with lipid and amino acid metabolism, as well as stress response, increased under water deficit. In general, the abundance of proteins followed the numbers assigned to each category. That is, proteins contributed to upand down-regulation in various stresses in similar proportion to their abundance in the existing protein complement. Two categories deviated from this general observation, namely lipid metabolic process and response to stimulus: in the former,

10 proteins were up-regulated without any noticeable change in overall abundance while the up-regulation of the same number of proteins in the latter category was associated with a large increase in abundance of stress proteins (Figure 2A). 3.3.2. WW vs SpWW: Do Long-distance Signals from Droughted Roots Affect Gene Expression in Adjacent Well-watered Roots? Some 38% of proteins were either up- or down-regulated when we compared well-watered roots with and without a vascular connection to droughted roots (Table 2). This is a surprisingly large proportion of the total expressed genes. More than 300 proteins were down-regulated through apparent long-distance signals from the SpWD roots: this is likely to be in part due to drought-induced abscisic acid export but soluble carbohydrates were also likely to be more concentrated and could thus act as signals.38 However, this was not part of a general impairment of metabolism because a further 200 individual proteins were up-regulated in SpWW roots compared to WW roots. More than half of the reduction in protein numbers could be accounted for by processes associated with biosynthesis and protein metabolism, consistent with a reduction in root growth induced by drought signals (Figure 2B). The remaining reduction in the protein complement was spread across many processes, with transport substantially affected, albeit without a strong 352



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Figure 3. List of differentially expressed proteins in three different biological processes and comparison in their relative abundance (sum NSAF) across all treatments shown in bars. (A) Response to stimulus, (B) transport, (C) oxidation reduction. For (A), the upper shaded area highlights the seven pathogenesis-related proteins discussed in section 3.4.1.2, while the lower shaded area highlights the four small heat shock proteins discussed in section 3.4.1.3. For (B), the upper shaded area highlights the six small G proteins discussed in section 3.4.2.2, the middle shaded gray highlights the three nonsymbiotic hemoglobin proteins discussed in section 3.4.2.3, and the lower shaded area highlights the four mitochondrial import proteins discussed in section 3.4.2.4.

change in peptide abundance. Up-regulation involved fewer proteins but with a notable discrepancy between the low numbers of proteins affected and disproportionate abundances in three categories: carbohydrate metabolism, stress response and oxidative reactions (Figure 2B). These are further analyzed in section 3.4.

3.4. Drought-responsive Proteins

From gene ontology classification and categorization of differentially expressed proteins obtained using t tests, we identified functional categories which appeared to have responded generically and reproducibly to drought. The chosen categories discussed in this section are “response to stimulus”, “transport”, “oxidation reduction”, “lipid metabolic process” and “signaling”. We also performed a comparative analysis of contrasting cellular processes that rely on two key families of proteins, namely the expression of tubulins and chitinases.

3.3.3. SpWD vs WD: Do Hydraulic Signals Affect Gene Expression in Adjacent Droughted Roots? The smallest scale of change was seen in this comparison, with as many proteins (about 70) up-regulated as down-regulated (Table 2). Nevertheless, there is evidence that water supplied to adjacent roots in the split-root system was able to alter gene expression through long-distance effects which might have been positive hormonal signals (e.g., cytokinin) or direct hydraulic effects. The major reduction in numbers of proteins associated with growth in SpWD roots when compared with SpWW roots was seen again, this time with substantial down-regulation associated with total withdrawal of water (WD roots). Many other protein categories were down-regulated in WD roots but most were not associated with much lower protein abundances and appear to indicate a general suppression of metabolic and growth activity. By contrast, up-regulation in WD roots was restricted largely to those involved in carbohydrate metabolism and stress response; these two processes are known to be strongly associated with extreme levels of drought in all plant tissues.38 The other category to be upregulated to some degree was “cell wall macromolecule metabolic process”, which contains mainly chitinases (Figure 2C). Chitinases are pathogenesis related proteins (PR proteins) and have been reported to play a role in altering root system architecture in response to various environmental conditions.39

3.4.1. Response to Stimulus. Proteins involved in response to stimulus perform a variety of roles, with more than half participating in pathogenesis and heat shock response. This class of proteins was exceptional for the fact that it was the most highly responsive group of proteins that was consistently induced by drought. 3.4.1.2. Pathogenesis-related Proteins. Of the 15 differentially expressed pathogenesis related proteins (PR proteins) that were identified, seven were markedly more abundant when roots were droughted but almost absent during watering. Four PR proteins were identified in all drought treatments. These proteins included putative pathogen-induced proteins 2 4, Win1 pathogenesis-related protein, pathogenesis-related protein Bet v I family protein and root specific pathogenesis-related protein 10, which were most abundant in fully droughted roots (WD). Three other proteins, barwin-pathogenesis related protein, putative type I related protein and putative pathogenesis-related thaumatin-like protein, were equally expressed in SpWW roots, suggesting induction by drought signals (Figure 3A). Eight PR 353



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proteins also appeared in the “cell wall macromolecule metabolic process” category, six chitinases and two β-1,3-glucanases. Pathogenesis-related proteins (PR) are induced by multiple elicitors, playing an important role in plant defense against pathogenic constraints and in general adaptation to stress. These PR families are involved in various metabolic functions from cell wall rigidification to signal transduction and antimicrobial activity.40,41 PR proteins, despite their name, are not specific to pathogens but are also induced by different abiotic stresses such as drought42,43 salinity,44 cold,45 heat46 and heavy metals.47 3.4.1.3. Small Heat-shock Proteins. Heat-shock proteins (HSPs), like PR proteins, play a more general role in metabolism than their name suggests. The four heat-shock proteins identified were expressed even more distinctively than the PR proteins, with no expression seen in well-watered roots (WW) and minimal expression in SpWD roots (Figure 3A). HSPs are highly conserved and constitutively expressed as molecular chaperones involved in various functions such as protein folding, assembly, translocation and degradation. They are protective through stabilizing unfolded proteins and permitting repair and regeneration of damaged proteins.48 Small HSPs are differentially expressed in different stresses, principally heat and drought.21,49 52 3.4.2. Transport proteins. Because of the enormous diversity of transport activities in root cells, it is unsurprising that almost 40 transport proteins change in activity across all drought comparisons. This category included small GTPases, nonsymbiotic hemoglobin proteins and mitochondrial import proteins. Specifically, there were a high number of down-regulated proteins due to partial or complete drought (Figure 3B). 3.4.2.1. Small G Proteins. We identified six small GTP-binding proteins in WW roots but all were absent in drought treatments. Interestingly, five GTPases belonged to the Rab family; Rasrelated protein Rab11D, putative small GTP binding proteins Rab 7 D, Ras-related protein Rab11A, putative GTP-binding protein Rab11b and small GTP binding protein Rab 5 (Figure 3B). Small G proteins (signal transduction proteins) act as molecular switches and regulate a wide range of crucial cell physiological functions such as cell proliferation, cytoskeleton organization, intracellular trafficking and immunity response.53 Differential expression of small GTP binding proteins has been previously reported in various abiotic stresses, including drought.51,54 3.4.2.2. Nonsymbiotic hemoglobin proteins. We identified three hemoglobin proteins in the transport category: nonsymbiotic hemoglobin 1 (rHb1) and nonsymbiotic hemoglobin 2 (rHb2) were found in all treatments but significantly downregulated in drought conditions, whereas putative 2-on-2 hemoglobin was expressed only in WW roots (Figure 3B). Hemoglobins (Hbs) are heme-containing proteins found in most organisms including animals, bacteria, and plants. Plant nsHbs, particularly nsHb-1s, have been reported to be differentially expressed under various environmental stresses such as osmotic, nutrient deprivation, cold and oxidative stresses.55 Therefore, these proteins may play a role in signaling during environmental stresses, possibly by moderating the NO level and the ratio of H2O2/NO, in addition to modulating levels of ATP in the defense process. 3.4.2.3. Mitochondrial Import Proteins. We successfully identified four proteins associated with mitochondrial protein import machinery. From these proteins, mitochondrial import inner membrane translocase subunit Tim9 and mitochondrial import inner membrane translocase subunit TOM7-like protein were specific to well-watered plants, while subunit Tim13 was

also identified in WD but with higher abundance in well-watered plants. Lastly, probable mitochondrial import receptor subunit TOM20 was expressed in WW and SpWD, revealing higher levels in WW than SpWD (Figure 3B). The mitochondrial protein import apparatus is responsible for importing hundreds of cytosolically synthesized proteins into mitochondria.56 These proteins are transported across the mitochondrial membranes via translocase complexes, termed TOM and TIM, situated in the outer and inner membrane, respectively. Previous studies have demonstrated differential expression of these proteins in response to various environmental stresses such as drought, chilling and herbicides.57 Therefore, based on our findings and previous studies, we hypothesize that these proteins may be involved in mechanisms of response to stimulus or adaptation to various unfavorable conditions. 3.4.3. Oxidation and Reduction. Antioxidative enzymes were largely up-regulated in all drought conditions as compared to well-watered plants. The effect of this would generally be to suppress levels of reactive oxygen species (ROS) such as superoxide (O2 ), hydrogen peroxide (H2O2) and the hydroxyl radical (OH ) under dry conditions. Antioxidant protection systems are divided into two separate categories; first, enzymes such as peroxidase, superoxide dismutases (SODs) and catalase which react with ROS in order to keep them at optimum levels, and second, ascorbate peroxidase (APX) and glutathione reductase, which regenerate antioxidants.58 From the first category, we identified superoxide dismutase [Mn] and dismutase [Cu Zn] which were up-regulated in all drought conditions but at higher levels in SpWW, while catalase isoenzyme A was more upregulated in WD. Furthermore, we identified four peroxidases: class III peroxidase 59 and 17 which were more abundant in SpWW, whereas class III peroxidase 22 and putative peroxidase were more expressed in fully droughted plants (WD). In the second category, we identified three ascorbate peroxidases, from which L-ascorbate peroxidase 1 was more abundant in SpWW but probable L-ascorbate peroxidase 7 and probable L-ascorbate peroxidase 6 were more expressed in WD (Figure 3C). These findings accord with a drought study performed on wheat, where the expression of SODs were enhanced at the early stage of drought but reduced at later stages of water deficit, while peroxidase activity greatly increased in response to water stress.59 3.4.4. Lipid Metabolic Process. Proteins engaged in lipid metabolism were significantly more abundant in root tissues associated with drought. Among these proteins, six were associated with isoprenoid biosynthetic pathways, including 4-hydroxy-3-methylbut-2-enyl diphosphate reductase, putative GCPE protein, 2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase, 1-deoxy-D-xylulose 5-phosphate reductoisomerase, geranylgeranyl diphosphate synthase and putative isopentenyl monophosphate kinase. Isoprenoid compounds (terpenoids) produced in the plastids are likely to be involved in plant response to drought stress. Through carotenoid metabolism, isoprenoids affect detoxification of free radicals and reactive oxygen species (ROS) during drought.60,61 In addition, we also identified allene oxide synthase 2 and lipoxygenase 2 associated with defense response62,63 and aldehyde oxidase 1 and 2 linked to ABA biosynthesis.64 Furthermore, we also identified aspartic proteinase, which was present in all conditions but more expressed in SpWD and WD. The physiological significance of plant aspartic proteinases (Aps) is not as well understood as those of the mammalian, microbial or viral counterparts.65 However, they are known to be involved in 354



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Figure 4. Abundance of proteins associated with cytoskeleton and macromolecule metabolic processes expressed at all four treatments. (A) Abundance of nine tubulins across all four treatments. (B) Abundance of six chitinases across all four treatments.

protein processing and degradation in different plant organs, as well as in plant senescence, stress responses, programmed cell death and reproduction. Several studies have demonstrated that plant proteases may play significant roles in responses to various environmental and developmental stimuli,66,67 as well as drought stress68 or metal stress.69 3.4.5. Signaling Proteins. We identified six isoforms of 143-3 proteins which were down-regulated in drought conditions. GF14-E, GF14-B, GF14-F and GF14-C followed a similar expression pattern; abundant in WW condition but downregulated in the other drought conditions, while GF14-A was exclusive to WW and SpWW, revealing down-regulation in SpWW in comparison to WW. Lastly, GF14-D was more abundant in WD compared to the other conditions. The 14-33 proteins form a highly conserved family of homodimeric and heterodimeric proteins and play a crucial role in signal transduction, subcellular targeting, and cell cycle control for growth regulation of plants as well as their responses to environmental stress.70,71 Various studies have reported the differential expression of 14-3-3 proteins in response to environmental stresses such as salinity,26,72 cold73 and drought stress.74,75

blocked when SpWW roots were influenced by SpWD roots. In contrast, chitinases became highly abundant in SpWW roots despite having been absent in WW roots, presumably induced by transmissible defense-inducing signals (Figure 4B). These findings provide insights into functional clusters and help validate the use of proteomics to define drought responses. The data we present show that signaling is a recurring theme in drought response. For example, the close interaction between microtubules and plasma membranes is targeted by several signaling pathways.76,77 Similarly, chitinases elicited by signals mount a defense response in compromised tissues such as dry roots. The implications for plant adaptation are broad, with no single protein class unaffected by stress. For example, tubulin transcript is frequently used as a common internal control for many expression studies. This study, and other recent reports of differential regulation of tubulin in response to cold stress in wheat,78 salt and osmotic stress in Arabidopsis,79 and drought stress in Piriqueta,80 establish that tubulin expression is dynamic.

4. CONCLUDING REMARKS Our quantitative label-free shotgun proteomic analysis of water stress in split-root systems provides novel molecular insights into heterogeneous translation patterns in wet and dry zones of rice plants subject to drought. By analyzing proteins in well-watered root tissues and adjacent droughted roots, we provide quantitative evidence that the water supplied was able to alter gene expression remotely. This may be attributable to either hormonal signals or direct hydraulic effects. We have identified and quantified a large number of proteins associated with specific water regimes; these will provide an excellent basis for further detailed study into a complex environmental signaling response.

3.5. Response Patterns: Contrasting Effects of Drought on Two Protein Families

Cytoskeletal development and plant defense are distinct and largely unrelated processes in plant development. Plant microtubules (actins and tubulins) are central elements of cell growth, division and morphogenesis, and are involved in regulation of various cellular processes such as signaling, translation, and metabolism, while chitinases participate in defense. Accordingly, one might expect that drought would inhibit cytoskeletal activity but enhance the defense response. Therefore, we analyzed the effects of drought and long-distance signaling on these families to establish whether they were regulated in this manner. Figure 4A shows that nine α- and β-tubulins were highly expressed in WW roots but significantly down-regulated in SpWW tissues as well as in roots experiencing full drought. This pattern was distinctive and repeatable, suggesting a core role in cell generation that was

’ ASSOCIATED CONTENT

bS

Supporting Information Supplementary Table S1. The complete set of 1487 proteins identified reproducibly from all four treatments in this study,

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including numbers of peptides assigned to each protein in each replicate experiment. Also includes protein identification data from individual replicates, with measured and corrected percent coverage values for each protein. Supplementary Table S2. Proteins identified in each drought condition, including NSAF values. Supplementary table S3. Biological classification of differentially expressed proteins (up-regulated, down-regulated) obtained from t test analysis of WW vs SpWW, SpWW vs SpWD and SpWD vs WD, including NSAF value for each protein. This material is available free of charge via the Internet at http://pubs. acs.org.

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’ AUTHOR INFORMATION Corresponding Author

*Professor Paul A. Haynes, Department of Chemistry and Biomolecular Sciences, Macquarie University, North Ryde, NSW 2109, Australia. E-mail: [email protected]. Phone: 61-2-9850 6258. Fax: 61-2-9850 6200.

’ ACKNOWLEDGMENT M.M. acknowledges support from Macquarie University in the form of a MQRES scholarship. P.A.H. acknowledges funding support from the New South Wales Government Office of Science and Medical Research and the Australian Research Council and wishes to thank Henry Holmes for continued support and encouragement. ’ ABBREVIATIONS ABA, abscisic acid; APX, ascorbate peroxidase; CAT, catalase; FDR, false discovery rate; GO, gene ontology; GPM, global proteome machine; GPX, glutathione peroxidase; GR, glutathione reductase; nanoLC-MS/MS, nanoflow liquid chromatography tandem mass spectrometry; NCBI, National Center for Biotechnology Information; NSAF, normalized spectral abundance factor; PloGO, Plotting Gene Ontology annotation; PRD, partial root drying; ROS, reactive oxygen species; RWC, relative water content; SDS, sodium dodecyl sulfate; sHsps, small heat shock proteins; SOD, superoxide dismutase; SpWW, split root well-watered; SpWD, split root water deficit; TCA, tricarboxylic acid; WD, water deficit; WEGO, web gene ontology annotation plot; WW, well-watered ’ REFERENCES (1) Boyer, J. S. Plant productivity and environment. Science 1982, 218 (4571), 443–448. (2) Hsiao, T. C. Plant responses to water stress. Annu. Rev. Plant Physiol. 1973, 24 (1), 519–570. (3) Blackman, P. G.; Davies, W. J. Root to shoot communication in maize plants of the effects of soil drying. J. Exp. Bot. 1985, 36 (1), 39–48. (4) Christmann, A.; Weiler, E. W.; Steudle, E.; Grill, E. A hydraulic signal in root-to-shoot signalling of water shortage. Plant J. 2007, 52 (1), 167–174. (5) Nilson, S. E.; Assmann, S. M. The α-subunit of the arabidopsis heterotrimeric G protein, GPA1, is a regulator of transpiration efficiency. Plant Physiol. 2010, 152 (4), 2067–2077. (6) Gollan, T.; Richards, R. A.; Passioura, J. B.; Rawson, H. M.; Munns, R.; Johnson, D. A. Soil water status affects the stomata. Aust. J. Plant Physiol. 1986, 13 (4), 459–464. (7) Sharp, R. E.; Davies, W. J. Root growth and water uptake by maize plants in drying soil. J. Exp. Bot. 1985, 36 (9), 1441–1456. 356



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