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First published online November 14, 2008; 10.1104/pp.108.131300 Plant Physiology 149:719-734 (2009) © 2009 American Society of Plant Biologists OPEN ACCESS ARTICLE
Experimental Analysis of the Rice Mitochondrial Proteome, Its Biogenesis, and Heterogeneity1,[W],[OA]Australian Research Council Centre of Excellence in Plant Energy Biology, M316, University of Western Australia, Crawley, 6009 Western Australia, Australia
Mitochondria in rice (Oryza sativa) are vital in expanding our understanding of the cellular response to reoxygenation of tissues after anaerobiosis, the crossroads of carbon and nitrogen metabolism, and the role of respiratory energy generation in cytoplasmic male sterility. We have combined density gradient and surface charge purification techniques with proteomics to provide an in-depth proteome of rice shoot mitochondria covering both soluble and integral membrane proteins. Quantitative comparisons of mitochondria purified by density gradients and after further surface charge purification have been used to ensure that the proteins identified copurify with mitochondria and to remove contaminants from the analysis. This rigorous approach to defining a subcellular proteome has yielded 322 nonredundant rice proteins and highlighted contaminants in previously reported rice mitochondrial proteomes. Comparative analysis with the Arabidopsis (Arabidopsis thaliana) mitochondrial proteome reveals conservation of a broad range of known and unknown function proteins in plant mitochondria, with only approximately 20% not having a clear homolog in the Arabidopsis mitochondrial proteome. As in Arabidopsis, only approximately 60% of the rice mitochondrial proteome is predictable using current organelle-targeting prediction tools. Use of the rice protein data set to explore rice transcript data provided insights into rice mitochondrial biogenesis during seed germination, leaf development, and heterogeneity in the expression of nucleus-encoded mitochondrial components in different rice tissues. Highlights include the identification of components involved in thiamine synthesis, evidence for coexpressed and unregulated expression of specific components of protein complexes, a selective anther-enhanced subclass of the decarboxylating segment of the tricarboxylic acid cycle, the differential expression of DNA and RNA replication components, and enhanced expression of specific metabolic components in photosynthetic tissues.
As rice (Oryza sativa) is the one of the major food supplies for the expanding world population, especially in developing countries, exploiting a molecular understanding of rice biology has the potential to aid humanity in a profound way, as has been seen in the development and use of vitamin A-enhanced cv Golden Rice (Paine et al., 2005  ). Mitochondria are essential for all plant species as the energy production factory for ATP production via respiratory oxidation of organic acids and the transfer of electrons to O2. But the role and nature of mitochondria in rice take on special significance due to their early growth habitat in hypoxic or even anaerobic environments (Perata and Voesenek, 2007) and the need for mitochondrial biogenesis during the reoxygenation phase (Millar et al., 2004a; Howell et al., 2007). Rice seed embryos contain highly reduced protomitochondrial structures that mature to fully functional mitochondria through a complex biogenesis process involving induction of the general import pathway (Howell et al., 2006) and oxygen signaling of transcription (Howell et al., 2007). Furthermore, the farming practice of using hybrid rice production to boost crop yields relies on cytoplasmic male-sterile lines that have dysfunctional mitochondria in their pollen and restorer lines that recover mitochondrial function and thus fertility to the hybrid (Eckardt, 2006; Wang et al., 2006). Mitochondria in dicots are known to play critical roles in the synthesis of vitamins and cofactors important for human nutrition, including vitamin C (Bartoli et al., 2000; Millar et al., 2003), folate (Ravanel et al., 2001), biotin (Picciocchi et al., 2003), and lipoic acid (Yasuno and Wada, 2002), but there is little research in rice to confirm these roles or investigate these processes at the molecular level. Photorespiration in C3 plants like rice depends on the prevailing CO2 concentrations and involves a critical role of mitochondria in carbon recycling. But despite attempts to engineer C4 metabolism in rice and thus eliminate photorespiration (Ku et al., 1999), there has been little analysis of the photorespiratory machinery and related metabolism as integral components in rice mitochondrial function.
The coordination of biochemical processes to perform the functions of mitochondria requires many hundreds of different proteins working together in protein complexes, in two membrane systems, and in several aqueous spaces. The majority of mitochondrial proteins are encoded in the nucleus and transported into mitochondria as cytosolic precursor proteins by the mitochondrial protein import machinery. Prediction tools based on N-terminal portions of protein sequences are unable to predict localization to a high fidelity (Heazlewood et al., 2005
The removal of contaminants is essential for accurate curation of subcellular organelle proteomes. While dual targeting of some proteins to multiple compartments occurs in plants (Peeters and Small, 2001
In this study, traditional differential and gradient centrifugation were combined with FFE separation to isolate rice mitochondria. Through the direct analysis of trypsin-digested mitochondrial peptides by LC-MS/MS and gel-based analysis of rice mitochondrial proteins and the removal of contaminants by quantitative comparison of mitochondria prior to FFE separation, a refined rice mitochondrial data set of 322 proteins is presented. The expanded rice mitochondrial data set is comparable in size and complexity to the previously published Arabidopsis data set (Heazlewood et al., 2004
Purification of Isolated Rice Mitochondria Using FFE
The integrity of the mitochondrial proteome is largely dependent on the purification of the isolated organelles away from other cellular contaminants. A two-Percoll gradient density separation technique to isolate mitochondria from dark-grown Arabidopsis cells (Millar et al., 2001
To confirm the distribution of organelles in different FFE fractions, an aliquot of every third fraction was separated by one-dimensional SDS-PAGE (Fig. 1A
). Western blotting was applied for analysis using antibodies raised against protein markers for mitochondria (mtHSP70), plastids (small subunit of Rubisco; RbcS), and peroxisomes (3-ketoacyl-CoA thiolase; KAT2; Fig. 1A). The mtHSP70 was present in fractions 27 to 36, which also contained the bulk of the protein content visible in colloidal Coomassie Brilliant Blue-stained gel lanes and in 280-nm absorbance measurements (Fig. 1A; Supplemental Fig. S1), indicating that those fractions constitute the mitochondrial portion of sample. The plastidic RbcS was mainly present in the fractions around 18, indicating that plastids were enriched in those fractions after FFE. The minor RbcS peak that copurified with mitochondrial fractions is most likely due to RbcS from ruptured plastids that adhere to the mitochondrial membrane, but it could be due to a very small proportion of chloroplast having the same surface charge as mitochondria. A similar bimodal distribution of RbcS is seen in Arabidopsis mitochondria purified by FFE (Eubel et al., 2007
The FFE-purified mitochondrial samples were compared with Percoll gradient-prepared mitochondria samples before FFE purification using differential two-dimensional IEF/SDS-PAGE by labeling proteins with fluorescent Cydyes (Fig. 2 ). The overall spot patterns were consistent with the rice mitochondrial profiles published previously (Heazlewood et al., 2003 ). Spots with the decreased abundance after FFE (indicated by arrows in Fig. 2) were selected for protein identification using LC-MS/MS. The proteins identified as putative contaminants are listed in Table I. Most of them are plastidic, peroxisomal, or cytosolic proteins but also include bovine serum albumin that was added in the mitochondrial extraction buffer.
To identify the proteins in FFE-purified rice mitochondria, preparative IEF/SDS-PAGE gels were run and analyzed. A set of 291 abundant spots from these gels (Supplemental Fig. S2) were excised and subjected to in-gel digestion followed by MS/MS-based analysis of the resultant peptides. Comparison of spot locations with the quantitative data in Figure 2 ensured that these spots were not decreased during the FFE process, indicating that they were retained or enriched by the mitochondrial purification. This analysis led to identification of a set of 146 nonredundant proteins from rice. We also reanalyzed a set of 89 spots excised from BN/SDS-PAGE gels to separate rice mitochondrial protein complexes as described by Heazlewood et al. (2003)
Non-gel-based LC-MS/MS of rice mitochondrial peptides allowed us to identify the highly hydrophobic, basic, and small or large molecular mass proteins excluded from polyacrylamide gel-based analysis. The whole mitochondrial samples before and after FFE purification were analyzed with three independent biological samples using LC-MS/MS. This analysis allowed us to quantitatively compare the ratio of peptide numbers found for each protein before and after FFE purification, which provided additional criteria to remove contaminants. There were a total of 357 nonredundant proteins found by LC-MS/MS from the samples before and after FFE purification (Fig. 3
). A set of 56 proteins were only found in the samples before FFE purification, and most of these proteins were contaminants from the plastids, cytosol, and peroxisomes (Supplemental Table S2A). For example, 17, 11, and 10 peptides were found for peroxisomal hydroxyacid oxidase 1 (Os07g05820), cytosolic Ala aminotransferase 2 (Os07g01760), and plastidic ATP synthase CF1 β-chain (Osp1g00410), respectively (Supplemental Table S2A). There were 262 proteins for which peptides were found in samples both before and after FFE purification. Nearly 71% of proteins were enriched (ratio of peptide number identified,
Broad Analysis of Mitochondrial Functions Identified in Rice
Combining the gel-based and non-gel-based approaches and after removal of contaminants, a nonredundant set of 322 proteins can be conservatively defined as rice mitochondrial proteins (Supplemental Table S3). In this set of rice mitochondrial proteins, 168 proteins were found using the gel-based method and 307 proteins were found using LC-based methods (Supplemental Table S3). Seventy-eight of the 122 nonredundant rice mitochondrial proteins reported previously using Percoll gradient centrifugation purification methods (Heazlewood et al., 2003 Each rice mitochondrial protein was assigned to one of 17 functional categories (Fig. 4 ; Supplemental Table S3). In this data set, known function proteins were highly represented by those involved in energy production (complexes I–V, 22%) and metabolism (TCA and general metabolism, 28%; Fig. 4), while the proteins with unknown function represented 17% of the mitochondrial protein set (Fig. 4). The numbers of proteins involved in energy production and metabolism are very similar in the rice and Arabidopsis mitochondrial data sets (Fig. 4). There are fewer proteins identified to be involved in electron transport chain assembly and signaling, stress defense, carriers and transporters, protein import/fate, and unknown proteins in the rice compared with the Arabidopsis mitochondrial data sets (Fig. 4).
Prediction of Rice Mitochondrial Proteins
This experimentally determined rice mitochondrial protein set provides an opportunity to test the sensitivity of different organelle-targeting prediction programs in rice. When our set of 313 nucleus-encoded rice mitochondrial proteins were analyzed, the accuracy of mitochondrial prediction by four leading targeting prediction programs ranged from 61% to 66% (Table II
), which was higher than the 40% to 50% prediction rate observed for the Arabidopsis mitochondrial protein set (Heazlewood et al., 2004
Global Analysis of Expression Pattern of the Identified Rice Mitochondrial Proteins
The plant mitochondrial proteome changes during development of plant organs as well as differing in various cell and tissue types. We have already shown in Arabidopsis that 40% of proteins change more than 2-fold in abundance when comparing mitochondrial proteomes from photosynthetic and nonphotosynthetic tissues (Lee et al., 2008
The Respiratory Apparatus and Its Expression
The mitochondrion is an energy factory for ATP production coupled to the respiratory oxidation of organic acids and the transfer of electrons to O2. Over 71 proteins of the five electron transport chain complexes and 28 protein subunits of TCA cycle enzymes have been identified (Fig. 4), representing 31% of the rice mitochondrial protein set. Most of these proteins have orthologs in Arabidopsis, and most have also been experimentally shown to be mitochondrial proteins in Arabidopsis (Supplemental Table S3). This highlights that rice and Arabidopsis have a very conserved composition of the respiration chain complexes and the TCA cycle. Six proteins involved in alternative pathway respiration were also found, namely cytosol-facing NADH dehydrogenases that donate electrons to ubiquinone and bypass complex I and components of the electron-transfer flavoprotein pathway that reduces ubiquinone and is linked to the matrix branched-chain amino acid degradation pathway (Supplemental Table S3; Taylor et al., 2004
A series of genes encoding TCA cycle subunits were highly expressed in the anther; these were nearly all components of the pyruvate dehydrogenase complex (PDH) and the initial steps of the TCA cycle (citrate synthase, aconitase, and isocitrate dehydrogenase [ICDH]). In most cases, another isoform was also in our list of TCA cycle components and had a much more ubiquitous gene expression pattern (most notably, PDH E1
Plant mitochondria are also involved in synthesis of vitamins, cofactors, and lipids, metabolism of amino acids, photorespiratory Gly oxidation, and export of organic acid intermediates for other cellular biosynthesis. Rice mitochondrial proteins involved in these processes were also evident in our protein lists. In total, 64 proteins were identified as being involved in a range of metabolic pathways (Supplemental Table S3). Subdivision of this functional classification showed 16 proteins involved in amino acid metabolism, seven proteins involved in aldehyde/alcohol metabolism, six proteins involved in lipid synthesis, and six proteins involved in metabolism of nucleotides. Photorespiratory genes (Gly decarboxylase complex subunits and Ser hydroxymethyltransferase) were selectively expressed in leaf tissues (cluster 1, Fig. 6A), while components linked to C1 metabolism (glyoxylate, formate, and tetrahydrofolate metabolism) did not show leaf enhanced expression profiles (Supplemental Fig. S3). Two isoforms of the H protein of the Gly decarboxylase complex (Os06g45670 and Os02g07410) did not show leaf enhanced expression patterns but were broadly expressed with the C1 metabolism genes (Supplemental Fig. S3). The role of Gly decarboxylase in plant mitochondrial C1 metabolism outside of its photorespiratory role is still largely unexplored in plants. A 4-methyl-5-thiazole monophosphate biosynthesis protein (Os01g11880) predicted to be involved in thiamine biosynthesis was enriched after FFE purification (Supplemental Table S3), representing, to our knowledge, the first component of thiamine synthesis found in rice mitochondria.
There were 19 proteins in the DNA replication and transcription category (Supplemental Table S3). Among them, five were DAG-like proteins and eight were pentatricopeptide repeat (PPR) proteins. Genetic evidence shows that DAG proteins influence DNA synthesis and alter chloroplast differentiation (Bisanz et al., 2003
Fourteen proteins are listed in the group of proteins involved in translation. Six subunits of the putative mitochondrial ribosome were identified: L1, L27, and L30 of the 50S complex and S12, S18, and S19 of the 30S complex. Even with this small number of predicted subunits of the mitochondrial ribosome, clear differences between Arabidopsis and rice are apparent. The nucleus-encoded S12 protein in rice (Os12g33930) is most similar to the mitochondria-encoded S12 in Arabidopsis (AtMg00980), while the mitochondria-encoded S19 in rice (OsM1g00450) is orthologous to a nucleus-encoded ribosomal subunit in Arabidopsis (At5g47320). Extensive studies have been performed on ribosomal proteins shifting or swapping their location during recent evolution in plants (Adams et al., 2000
There were 19 proteins identified involved in protein import and fate (Supplemental Table S3). These included proteins involved in protein import and sorting, presequence cleavage, and proteolysis, and all of them had clear orthologs in the Arabidopsis mitochondrial proteome. The translocase of the outer membrane (TOM) was represented by TOM40, TOM20, and TOM22 subunits, while the only translocase of the inner membrane (TIM) components found were the intermembrane space members of the carrier import pathway, Tim8, Tim9, and Tim13 homologs. Lon, ClpX, and FtsH homologs were found, representing the three main classes of mitochondrial proteases in plants. The expression of genes encoding these proteins was mainly grouped into clusters 6 and 10, with notable expression in suspension cells, seeds, and embryos during the early stages of germination (Fig. 6; Supplemental Fig. S3). These results were consistent with our reports of the substantial mRNA pool in dry rice seeds for the genes encoding import components (Howell et al., 2006
There are 15 heat shock proteins and putative or well known molecular chaperones listed in our current data set (Supplemental Table S3). These included the classical 60/10-, 70-, and 80-kD chaperone classes. While these chaperone and heat shock protein classes are sometimes components induced by stresses with roles in stress tolerance (Schöffl et al., 1998
There were nine proteins with putative roles in stress response or oxidative stress in our data set (Supplemental Table S3). Mitochondria are often exposed to self-generated reactive oxygen species, primarily through the ubisemiquinone intermediate, formed by the NADH:ubiquinone oxidoreductase (complex I) or ubiquinone:cytochrome c oxidoreductase (complex III) of the electron transport chain, which can reduce O2 to O2– (Moller, 2001a
A total of 55 proteins were identified as proteins with unknown functions. Thirty-five of these rice unknown proteins were predicted as mitochondrially localized by at least one targeting prediction program, but only five of these unknown proteins have been identified in our previous study of the rice mitochondrial proteome (Heazlewood et al., 2004 The overall expression pattern of genes encoding proteins with unknown function was dispersed among other mitochondrial components, as shown in Figure 6, but some gene expression data could be grouped into different clusters or specific tissues. For examples, seven unknowns (Os05g08920, Os07g26700, Os04g41950, Os03g20860, Os05g01300, Os02g01450, and Os02g07910) are most highly expressed in the mature anthers (Fig. 6; Supplemental Fig. S3), which might be related to high mitochondrial metabolism in the same way as specific isoforms of TCA cycle enzymes show this distribution, as indicated above. Eight unknown function genes (Os10g40410, Os03g38520, Os03g48110, Os09g31260, Os05g46450, Os01g68030, Os06g33920, and Os02g35610) are coexpressed with genes encoding subunits of mitochondrial respiratory complexes (Fig. 6A; Supplemental Table S5), indicating that those genes might be involved in energy production or are associated with or are assembly factors for these complexes. Another five unknown function genes (Os06g22070, Os04g54410, Os08g34130, Os01g50310, and Os11g14990) are coexpressed with genes encoding proteins for DNA transcription and replication (Fig. 6A; Supplemental Table S5), indicating that those genes might be involved in similar functions, while Os01g05010 is tightly coexpressed with several mitochondrial ribosomal components. In cluster 7, comprising three genes (Fig. 6A; Supplemental Table S5), one unknown function gene (Os05g39390) was coexpressed with two genes encoding proteins involved in ubiquinone reduction, suggesting that this gene might have a related function.
In this study, the combination of FFE-based plant mitochondria separation (Eubel et al., 2007 ) and traditional differential and gradient centrifugations was applied to determine the rice mitochondrial proteome. This was achieved by organellar fraction selection using marker antibodies as well as differences in spot abundance in DIGE and peptide number ratios before and after FFE purification. The final rice mitochondrial data set provides evidence to confirm most of the fundamental biological processes in mitochondria previously uncovered in Arabidopsis (Fig. 4; Heazlewood et al., 2004). For example, the majority of mitochondrial proteins involved in energy production have highly conserved amino acid sequences between rice and Arabidopsis (Supplemental Table S3). A notable exception is the subunits of succinate dehydrogenase (SDH) or complex II. Differences between complex II in higher plants and mammals have been known for some time, most notably in the similarity of sequences for SDH1 and SDH2 but great divergence in sequences for the hydrophobic membrane anchor proteins SDH3 and SDH4 (Burger et al., 1996). In dicots, plant mitochondrial complex II appears to have four additional subunits in BN-PAGE-purified preparations, termed SDH5, -6, -7, and -8 (Millar et al., 2004b). In rice, we identified classical SDH1 and SDH2 subunits, but the SDH3 isoform we identified, Os02g02940, is very poorly related to SDH3 (At5g09600) in Arabidopsis. We did not identify the small SDH4 protein in rice, and the annotated SDH4 gene from rice (Os01g70980) bares little resemblance at all to the Arabidopsis SDH4. Furthermore, we found conserved homologs for SDH5, -6, and -7 (Supplemental Table S3) but no evidence for an SDH8 in rice analogous to the Arabidopsis SDH8. As BN-PAGE separation of mitochondrial membrane complexes from monocot mitochondria does not resolve complex II (Eubel et al., 2003; Heazlewood et al., 2003; Millar et al., 2004b), the potential differences in mitochondrial complex II between monocots and dicots requires further research.
Evidence for the dual targeting of proteins to both mitochondria and chloroplasts has increased with the greater ease in GFP-tagging experiments and the increased interest in processes common to both organelles. In Arabidopsis, almost all organellar aminoacyl-tRNA synthetases are dual targeted, as shown by in vivo GFP and in vitro organelle import (Duchene et al., 2005
Glycolytic enzymes are traditionally regarded as cytosol-abundant proteins. Interestingly, 5% to 10% of the cytosolic isoforms of each glycolytic enzyme, at least in Arabidopsis, is associated with the outer membrane surface of the mitochondrion (Giegé et al., 2003
The relatively low levels of transcript abundance observed for the majority of genes in mature leaf tissue (last four columns in Fig. 6A), with the notable exception of genes encoding subunits of Gly decarboxylase, are in agreement with previous studies on the expression of genes encoding mitochondrial proteins in monocots. It has been previously shown that subunits of Gly decarboxylase were only detectable at the protein level in older regions of wheat (Triticum aestivum) leaf tissue (Rogers et al., 1991
A range of proteins identified that are involved in aldehyde/alcoholic metabolism might be related to alcoholic metabolism in rice mitochondria. Ethanolic fermentation is not only observed in anaerobic plant tissues but also in aerobic tissues such as anthers (Tadege et al., 1999
Thiamine (vitamin B1) synthesis in plants was thought at one time to be plastid specific (Belanger et al., 1995
The plant mitochondrial proteome is a changing entity over time and in different cells and tissues. This is evident by looking at mitochondria from photosynthetic and nonphotosynthetic plant tissues (Bardel et al., 2002
Growth of Rice Seedlings Batches of 200 g of rice (Oryza sativa ‘Amaroo’) seeds were washed in 1% (v/v) bleach for 10 min, rinsed in distilled water, grown in the dark in vermiculite trays (30 x 40 cm) at a constant 30°C, and watered daily, and the shoot tissues were harvested at 10 d for mitochondrial isolation.
Rice mitochondrial isolation was performed by differential centrifugation followed by Percoll gradients as described by Heazlewood et al. (2003)
FFE was performed using the BD FFE system (Becton Dickinson) with a separation chamber height of 0.5 mm. The separation and counterflow medium (10 mM acetic acid, 10 mM triethanolamine, 1 mM EDTA, and 280 mM Suc; medium inlets 2–6 and counterflow inlets 1–3) as well as electrode stabilization medium (100 mM acetic acid, 100 mM triethanolamine, 10 mM EDTA, and 200 mM Suc; medium inlets 1 and 7) were injected into the separation chamber at a speed of 200 mL h–1. Media for anode and cathode circuits consisted of 100 mM triethanolamine and 10 mM EDTA, respectively. A voltage of 600 V was applied. Before the FFE run, the sample (approximately 10 µg protein µL–1) was subjected to one stroke in a Potter-Elvehjem homogenizer. Sample injection speed was 3,000 to 3,500 µL h–1 depending on the sample and the level of contamination. Fractions were collected on 2-mL 96-well plates. The separation chamber was cooled to 5°C, and the sample and 96-well plates were cooled in an ice bath.
Precast gels with 12% (w/v) acrylamide and 1 mM Tris-HCl (Bio-Rad) were used for analytical purposes and western blotting. Protein assays (Bradford, 1976
Mitochondrial protein samples (700 µg) were extracted by addition of cold acetone (–20°C) to a final concentration of 80% (v/v). Samples were stored at –80°C for 4 h and then centrifuged at 20,000g at 4°C for 15 min. The pellets were resuspended in IEF sample buffer (7 M urea, 2 M thiourea, 4% [w/v] CHAPS, and 40 mM Tris, pH 8.5). Aliquots of 450 µL were used to reswell immobilized pH gradient strips pH3-10 NL (24 cm; GE Healthcare) according to the manufacturer's instructions. The strips were run for 24 h in Ettan IPGphor3 (GE Healthcare) according to the manufacturer's instruction. The strips were then transferred to an equilibration buffer (50 mM Tris-HCl [pH 6.8], 4 M urea, 2% [w/v] SDS, 0.001% [w/v] bromphenol blue, and 100 mM β-mecaptoethanol) and incubated for 20 min at room temperature with rocking. After a brief wash in 1x gel buffer, the strips were transferred to 12% acrylamide Gly gels and covered with 1.2% (v/w) agarose in gel buffer. Second-dimensional gels were run at 50 mA per gel for 6 h. Proteins were visualized by colloidal Coomassie Brilliant Blue (G250) staining.
Samples (50 µg) of pre- and post-FFE, as well as 50 µg of a 1:1 mixture of both samples, were acetone precipitated, resolubilized in lysis buffer (7 M urea, 2 M thiourea, 4% [w/v] CHAPS, and 40 mM Tris base, pH 8.5), and individually labeled with 400 mM of weight- and pI-matched fluorescent dyes Cy2, Cy3, and Cy5 (GE Healthcare). Samples were then combined and separated on IEF strips pH3-10NL (24 cm; GE Healthcare) according to the manufacturer's instructions. After first dimension running, the strips were then transferred to an equilibration buffer consisting of 50 mM Tris-HCl (pH 6.8), 4 M urea, 2% (w/v) SDS, 0.001% (w/v) bromphenol blue, and 100 mM β-mecaptoethanol and incubated for 20 min at room temperature with rocking. After a brief wash in 1x gel buffer, the strips were transferred to 12% (w/v) acrylamide Gly gels and covered with 1.2% agarose in gel buffer. Second dimensional gels were run at 50 mA per gel for 6 h. Proteins were visualized on a Typhoon laser scanner (GE Healthcare), and image comparison was performed using the DECYDER software package (version 6.5; GE Healthcare). Three independent experiments were performed, and each of the resulting three gel sets was first analyzed using differential in-gel analysis mode DECYDER prior to a comprehensive biological variance analysis including all three gel sets. Gel spots were filtered according to their presence and average abundance ratio. Gel images were electronically overlaid using ImageQuant TL software (GE Healthcare).
Protein samples to be analyzed were cut from the gels and were in-gel digested according to the method described by Taylor et al. (2005
Whole organelle protein extracts were digested overnight at 37°C in the presence of trypsin, and insoluble components were removed by centrifugation at 20,000g for 5 min. Samples were analyzed on an Agilent 6510 Q-TOF mass spectrometer with an HPLC Chip Cube source (Agilent Technologies). The chip consisted of a 40-nL enrichment column (Zorbax 300SB-C18; 5-µm pore size) and a 150-mm separation column (Zorbax 300SB-C18; 5-µm pore size) driven by the Agilent Technologies 1100 series nano/capillary liquid chromatography system. Both systems were controlled by MassHunter Workstation Data Acquisition for Q-TOF (version B.01.02, Build 65.4, Patches 1,2,3,4; Agilent Technologies). Peptides were loaded onto the trapping column at 4 µL min–1 in 5% (v/v) acetonitrile and 0.1% (v/v) formic acid with the chip switched to enrichment and using the capillary pump. The chip was then switched to separation, and peptides eluted during a 1-h gradient (5% [v/v] acetonitrile to 40% [v/v] acetonitrile) directly into the mass spectrometer. The mass spectrometer was run in positive ion mode, and MS scans were run over a mass-to-charge ratio range of 275 to 1,500 and at four spectra per second. Precursor ions were selected for auto MS/MS at an absolute threshold of 500 and a relative threshold of 0.01, with maximum three precursors per cycle, and active exclusion set at two spectra and released after 1 min. Precursor charge-state selection and preference was set to 2+ and then 3+, and precursors were selected by charge and then abundance. Resulting MS/MS spectra were opened in MassHunter Workstation Qualitative Analysis (version B.01.02, Build 1.2.122.1, Patches 3; Agilent Technologies), and MS/MS compounds were detected by Find Auto MS/MS using default settings. The resulting compounds were then exported as mzdata files, which when appropriate were combined using mzdata Combinator version 1.0.4 (West Australian Centre of Excellence in Computational Systems Biology; http://www.plantenergy.uwa.edu.au/wacecsb/software.shtml). Searches were conducted using Mascot Search Engine version 2.2.03 (Matrix Science) with mass error tolerances of ±100 ppm for MS and ±0.5 D for MS/MS, maximum missed cleavages set to 1, with variable modification of oxidation (M) and carbamidomethyl (C), instrument set to ESI-QUAD-TOF, and peptide charge set at 2+ and 3+. Results were filtered using mudpit scoring, maximum number of hits set to 400, and ion score cutoff at 20. The significance threshold P
Dehulled, sterilized rice seeds were grown under aerobic conditions in the dark at 30°C as described previously (Howell et al., 2006 In order to examine transcript abundance changes across different tissues and under different conditions and to compare these with the obtained germination transcript abundance profiles, rice array data were retrieved from the Gene Expression Omnibus within the National Center for Biotechnology Information database (GSE6901, GSE7951 GSE6908, GSE4438, GDS1383, and GSE7256). All data were MAS5.0 normalized and normalized against average ubiquitin expression for that array. These normalized array data were then compiled together, and for each probe set the maximum expression was set to 1.0, with all other data relative to this. This normalization allowed cross-comparison of arrays from all of the different studies at once. The arrays analyzed included all arrays from this study together with publicly available rice genome arrays carried out from different tissues/conditions. Hierarchical clustering across all of the arrays was carried out with average linkage clustering based on Euclidian distance using Partek Genomics suite software, version 6.3 (Supplemental Table S5).
The following materials are available in the online version of this article.
Received October 15, 2008; accepted November 12, 2008; published November 14, 2008.
1 This work was supported by the Australian Research Council (ARC) through the Discovery Programme (grant no. DP0664692 to A.H.M. and J.W.). N.L.T. and H.E. are supported as ARC Australian Postdoctoral Fellows (grant nos. DP0772155 and DP0773152), and A.H.M. is an ARC Australian Professorial Fellow (grant no. DP0771156).  The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: A. Harvey Millar (hmillar{at}cyllene.uwa.edu.au).
[W] The online version of this article contains Web-only data.
[OA] Open Access articles can be viewed online without a subscription. www.plantphysiol.org/cgi/doi/10.1104/pp.108.131300 * Corresponding author; e-mail hmillar{at}cyllene.uwa.edu.au.
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ABSTRACT
RESULTS
1.0) after FFE purification (
Os02g50620 versus Os12g08260, PDH E1β Os09g33500 versus Os08g42410, PDH E2 Os06g01630 versus Os02g01500, aconitase Os03g04410 versus Os08g09200, and ICDH Os04g40310 versus Os02g38200). In contrast to this, later steps of the TCA cycle, such as malate dehydrogenase (Os01g46070 and Os05g49880), were more evenly expressed across tissue types (Supplemental Fig. S3). Mature anthers might thus possess a very high metabolic activity for energy production during pollen formation, and potentially this is mediated by a specific highly expressed form of the TCA cycle in pollen. 
