Mass Spectrometry based Imaging in Plant Science

Mass Spectrometry based Imaging in Plant Science: Current Status and Perspectives Manuela PEUKERT1, Andrea MATROS1, Anke DITTBRENNER1, Udo SEIFFERT2, HansPeter MOCK1* 1

Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstrasse 3, 06466 Gatersleben, GERMANY 2 Fraunhofer-Institute IFF, Sandtorstraße 22, 39106 Magdeburg, GERMANY *Corresponding author: [email protected]

Abstract Mass spectrometry based imaging of metabolites and of proteins has been pioneered in medicine to detect novel clinical markers for better diagnosis or for pharmacological studies. In particular, MALDI MS imaging is frequently applied to obtain these data sets. Spatially resolved analysis of metabolites and proteins will also be a prerequisite to improve current models on plant metabolism. We will introduce recent developments in mass spectrometry imaging (MSI) techniques. Current achievements of MSI in plants will be shown by selected examples from the literature and from our own work on barley seed development. Challenges for the further development of the technique to analyse plant tissues will be discussed, such as sensitivity, spatial resolution, and identification of unknown compounds from the limited amounts available at the surface of tissue sections. Moreover, improvements in post-acquisition analysis will significantly contribute to the impact of MSI in plant biology.

Introduction In the recent decade, analytical techniques for the comprehensive analysis of metabolites and proteins in plants have made tremendous progress. The advancements in the multi-parallel analysis of small and large molecules were based on the development of suitable instrumentation for mass spectrometry allowing detecting a wide range of compounds in a sensitive manner. Plant researchers could hence join the fields of proteomics and metabolomics as seen in other areas of life science research. Information from all “omics”-techniques including transcriptomics provide a major route towards systems biology. Integration of multiple data sets will improve current models of cellular metabolism including signalling cascades and control mechanisms operating at various molecular levels. Most crop and model plants are composed of a multitude of tissues each with specific functions. Refinement of cellular and biochemical models will therefore request improved spatial resolution to adequately address the individual functions of particular tissues at a certain developmental stage. Spatial information however is lost when preparing extracts from organs or whole organisms. Specific mass spectrometry-based approaches have been designed which now allow for a spatially resolved detection of metabolites and proteins. First introduced in the context of medicinal research, mass spectrometry based imaging techniques are now making their way into plant research. We will first outline the basic techniques, address the specific technical challenges being faced using examples from our own work, and then discuss selected results from our own research and selected references. Finally we will describe how to integrate the date into biological context and outline perspectives for future applications.

Principles of Mass Spectrometry based Imaging (MSI) Matrix-assisted laser desorption/ionization (MALDI)-imaging The most frequently applied approach in MSI to date is based on MALDI- time-of-flight (TOF) MS. This type of instrument is frequently used for protein identification by typically applying a trypsinized protein sample together with a suitable matrix substance on a target. MALDI is a complex phenomenon involving multiple interacting physical and chemical processes, which are still not fully understood (Knochenmuss, 2006). Typically a focused laser beam is used to transfer energy to the matrix molecules. When surrounding matrix substance is evaporated, the sample molecules are also taken into the gas phase and thereby become accessible for subsequent MS detection. This principle can readily be adopted from a spot-wise application to scan larger areas such as flat surfaces or tissue sections (Fig. 1). MSI based on other Ionization Methods In addition to laser based techniques, also atmospheric ionization methods are used for MS imaging, among them desorption electrospray ionization (DESI) and secondary ion (SI) formation; see (Svatos, 2010; van Hove et al., 2010) for detailed overviews on MS imaging techniques. In contrast to MALDI, SIMS sputters the sample surface by means of a focussed Ar+, Ga+, or In+ beam and captures the ejected compound-specific secondary ions. However, despite its levels of spatial resolution, detection efficiency and surface sensitivity, and its high scan rate, SIMS has yet not make any significant impact within biological or biomedical research (Kaspar et al., 2011). The DESI approach extracts compounds from the sample surface by means of a gas/liquid jet. This technique has been primarily exploited for the

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Frontiers in Agriculture Proteome Research

rapid screening of small molecules, where detailed lateral resolution (BC=>NR(10.00)=>NR(10.00)[BP = 31461.6, 6791] 31460.26

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Useful Tool in Agricultural Diagnostics

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Fig.7. A typical protein profile of a barley variety.

Fig.8. Peptide profiles of three different sub-clover cultivars showing similar and different markers

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Fig.9. Peptide profiles of four different sub-clover varieties showing different and similar isotopic clusters. Table 1. A list of all molecular markes found in the varieties (top line) that have been analysed. Mass m/z Din Dwa Dal Jun Den Ger Nun Lar Gou Izm Dal Leu + 1428.55 + + 2165.38 + 2187.09 2471.88 + 2541.96 2585.32 + 2744.32 + 2801.11 + + 2946.3 + 3206.23 + + + + + 3430.64 + + + + + + 3716.69 + + + + + + + 3852.01 + + + + + + + 3903.98 + + + 3937.86 + + + + + + 4497.91 + + + + + + + + + + + + 5001.01 + + + + 5258.72 + + + + + + + + + + + 5529.62 + + + + + + + 5562.5 + 5625 + 6423.78 + + + + + + + + + + 6678.78 + + 6737.64 + 6811.57 + 7368.53 + + + + + + + + + + 8002.19 + + + + + + + + + + + 8954.26 + + + + + + + + + 10505.79 + + + + 10559.64 + + + + + + + + + + 11168.9

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Useful Tool in Agricultural Diagnostics

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Conclusion. The various molecular diagnostic tests that have been developed using MALDI-TOF-MS confirm that MS is a more powerful, much faster, more accurate, more high throughput and more cost effective than both SDS - PAGE methods and DNA analysis techniques. In wheat marker assisted breeding, the rapid differentiation of HMW-GS allele diversity at the Glu-B1 locus and the ability to discriminate protein subunits such as 7OE, 8a* and 8b* that are associated with superior flour quality, is of special value to wheat breeders, since it is not possible to discriminate the latter via the SDS-PAGE method. Its high resolution also has led to the identification of new HMW-GS. In cereal and sub-clover variety identification and seed purity analysis, MS makes possible high throughput testing, that is more accurate, very much faster and much more cost effective than either SDS-PAGE or DNA analysis. Overall, MALDITOF technology is a very powerful tool, used to carry out fast, high throughput, cost effective and accurate analysis of macromolecules in Agricultural research and related industries.

References. Hussain A, Larsson H, Kuktaite R, Prieto-Linde ML, Johansson E (2009) Protein content and composition in organically grown wheat: influence of genotype. Agronomy Res., 7, 599-605 Galova Z, Michalik I, Knoblochova H, Gregova E (2002) Variation in HMW glutenin subunits of different species of wheat. Rostlinná Výroba, 48, 15-19 Singh NK, Shepherd KW, Cornish GB (1991) A simplified SDS-PAGE procedure for separating LMW subunits of glutenin. J. Cereal Sci., 14, 203–208 Kussmann M, Nordhoff E, Rahbek-Nielsen H, Haebel S, Rossel-Larsen M, Jakobsen L, Gobom J, Mirgorodskaya E, Kroll-Kristensen A, Palm L, Roepstorff P (1997) MALDI-MS sample preparation techniques designed for various peptide and protein analytes. J. Mass Spectrom., 32, 593–601 Liu L, Wang A, Appels R, Ma J, Xia X, Lan P, He Z, Bekes F, Yan Y, Maa W (2009) A MALDI-TOF based analysis of high molecular weight glutenin subunits for wheat breeding. J. Cereal Sci., 50, 295–301 Nichols PGH, Collins WJ, Barbetti MJ (1996) Registered cultivars of subterranean clover - their characteristics, origin and identification. Agriculture Western Australia Bulletin,4327, 61

Cell-Free Protein Synthesis of Membrane-Integrated Proteins for Functional Analysis Yuzuru TOZAWA* Ehime University, Cell-Free Science and Technology Research Center, Matsuyama 790-8577, JAPAN

*Corresponding author: [email protected]

Abstract The genomes of living organisms encode many membrane-integrated proteins, a substantial proportion of these functions as solute transporters and ion channels. However, only a limited number of membrane proteins have been functionally characterized to date, mostly because of the experimental difficulties associated with their biochemical analysis. The reconstituted proteoliposome system is one of the most useful systems for exploring functional study of membrane proteins, especially for the functional analysis of solute transporters and ion channels. In this system, purified or recombinant proteins are reconstituted into artificial vesicles that consist of lipid bilayers, and the resultant proteoliposomes are subjected to analysis. However, overexpression of membrane proteins frequently interferes with the growth of host cells; thus, it is often difficult to obtain sufficient amounts of the membrane proteins for functional analysis. This limitation of expression of membrane proteins in cellular systems does not apply to cell-free protein expression systems, and such systems have recently been employed to the analysis of membrane proteins. I describe here a proteoliposome reconstitution system for functional analysis of membrane transporters that is based on a modified wheat germ cell-free translation system. We are able to produce sufficient amount of membrane proteins in overnight reaction and perform stable and reproducible functional analysis of a variety of solute transporters in vitro.

Introduction The genomes of plants encode various membrane proteins, and many of these belong to solute transporters (Arabidopsis Genome Initiative, 2000). However, a relatively small number of plant membrane proteins have been functionally characterized to date, because of the lack of efficient experimental methods for their biochemical analysis. The reconstituted proteoliposome system is one of the useful in vitro systems for the characterization of membrane transporters (Kasahara and Hinkle, 1976; Flügge at al., 1991; Flügge and Weber, 1994). In the system, proteins, directly purified from cell membranes, or recombinant proteins are reconstituted into artificial vesicles, and the resultant vesicle-protein complexes (proteoliposomes) are subjected to biochemical or sometimes electrophysical analysis. However, overexpression of membrane proteins often interferes with the growth of host cells, thereby it is frequently difficult to obtain sufficient amount of recombinant membrane proteins for their functional analysis. This limitation of membrane protein production in cell-based systems does not apply to cell-free protein synthesis systems (Katzen et al., 2005). Recently, the cell-free protein synthesis systems have been applied to analysis of membrane proteins in combination with the proteoliposome reconstitution system (Elbaz et al., 2004; Klammt et al., 2006; Klammt et al., 2007; Nozawa et al., 2007; Nozawa et al., 2011). There are now multiple choices of cell-free protein synthesis system, from Escherichia coli to human cells. The first cell-free protein synthesis system based on E. coli cell extract was reported by Spirin (Spirin et al., 1988). The prokaryotic cell-free system is now widely used for a variety of purposes as the base biochemical technology. Needless to say, E. coli is the best-characterized living organism. Therefore, we are able to modify the cell-free system by genetic modifications of the bacteria for preparing order-made extracts. Following to the Spirin’s cell-free system, Ueda’s group has established “pure-system”, which consists of purified components of E. coli translation machinery (Shimizu et al., 2001). In the case of eukaryotic systems, rabbit reticulocyte extracts and wheat germ extracts have been utilized for long time as mammalian and plant cell-free translation systems, respectively. But, the yields of protein production in those systems have remained to be low. Especially, preparation of sufficient amount of reticulocyte extract requires sacrifice of a large number of animals. Therefore it is not considered as a base technology for protein production in preparative scales. On the other hand, wheat germ extracts are derived from one of the two major crops in the world. One can expect stable supply of the source material. One of the frequently asked questions is “Why wheat germ?”. Normally, flour is the form for storage of wheat products. In contrast, seed itself is the form for food storage in the case of rice. Compared to rice seeds, which consists of crystal-type starch, wheat seeds are softer and larger, facilitating easy crash for making flour powder. This feature of wheat seeds makes isolation of embryo parts (germs) easy. In the case of third major crop, maize, embryo is hidden by endosperm that has also hard structure, making it difficult to take out intact embryo by physical treatment. Thus, only wheat embryo had been left as a suitable source for production of cell-free extracts. It has long been known that wheat germ extract shows relatively stable protein expression activity, and the in vitro translation system had been utilized as a biochemical tool for particular purpose such as preparation of precursor proteins in chloroplast import assay. The embryos contain all components necessary for starting-up new lives. Seeds

Cell-Free Protein Synthesis of Membrane-Integrated Proteins

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are dehydrated during maturation, resulting in low content of water in embryos. Vacuoles do not seem to be fully developed yet in dormant embryos, and this probably explains the reason why there are less degrading enzyme activities in the embryo extracts than extracts prepared from cultured cells. Turning point in the development of wheat germ translation system had come in the beginning of 21 century. Endo and his colleagues found that removal of inhibitory factors from isolated fresh embryo drastically stabilized activity of the cell-free translation system (Madin et al., 2000; Takai et al., 2009). The idea came from Endo’s experiences based on results from his past studies on ribosome-inactivation factors, such as ricin and alpha-sarcin, in eukaryotic cells (Endo et al., 1987; Endo and Tsurugi, 1987; Endo and Wool, 1982; Madin et al., 2000; Takai et al., 2009).

Vector design for producing proteins having uniform N-end in the wheat germ cell-free system Recent improvements in wheat germ cell-free protein synthesis resulted in a highly productive system for protein preparation (Madin et al., 2000; Sawasaki et al., 2001; Takai et al., 2009). To attain full potential of the cell-free system, it is important to monitor the quality of the end products. Especially, homogeneity of the produced proteins is critical for structural studies. To clarify N-terminal processing of the wheat germ cell-free system in a preparativescale, 20 mutant variants of maltose-binding protein (MalE), each having a different penultimate residue in the sequence Met-Xaa-Ile-Glu-, and 20 glutathione S-transferase (GST) variants, having Met-Xaa-Pro-Ile- sequence, were designed, synthesized, purified and characterized (Kanno et al., 2007). These investigations revealed that sequence specificity and efficiency of the N-terminal Met elimination in the cell-free system are similar to those reported from investigations in cellular systems or in the wheat germ cell-free protein expression system in analytical scale. The results clarified sequence-specific functions of the endogenous N-terminal processing machinery in the scaled-up wheat-embryo cell-free translation system. Cleavage of the N-terminal Met is basically determined by the penultimate amino acid in the polypeptide sequence (Kanno et al., 2007). Messenger RNA of eukaryotic cells requires 5’ cap structure and 3’ poly(A)-tail. But, in vitro preparation of capped and poly(A)-tailed mRNA is very costly. In the wheat germ cell-free system, a translation enhancer such as the omega sequence derived from tobacco mosaic virus, that allows cap-independent translation of the mRNA in the cell-free system, is required for low-cost preparation of template mRNAs (Madin et al., 2000; Sawasaki et al., 2001; Takai et al., 2009) (Fig. 1). However, the use of translational enhancer, omega sequence, often leads to unexpected byproducts (Ohta et al. 2010). Several AUU codons in the omega sequence can potentially function as translation initiators. We confirmed that the in-frame AUU in the omega sequence functions as a non-canonical start codon and results in the extension of the N-terminus of the target protein in some cases. Investigation of the selectivity of noncanonical initiation codon under the control of omega sequence in the wheat germ cell-free system revealed that seven non-AUG codons, CUG, AUA, AUU, GUG, ACG, AUC, and UUG, are recognized as translation initiators (Ohta et al., 2010). We found that the introduction of an in-frame stop codon just upstream of the target open reading frame is an efficient way to avoid unexpected byproducts. This minor but effective modification facilitates production of homogeneous proteins within the wheat germ cell-free protein expression system at the preparativescale (Ohta et al., 2010) (Fig. 2).

Fig. 1. Basic structure of a mRNA used for the wheat germ cell-free system.

Fig. 2. Modification for producing proteins with uniform N-end

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Cell-free synthesis and functional analysis of plastid transporters We describe here a novel proteoliposome reconstitution system for functional analysis of plant membrane transporters that is based on a modified wheat germ cell-free translation system. As a model membrane protein for the establishment of a functional reconstitution assay, we chose phosphoenolpyruvate (PEP)/phosphate translocator 1 of Arabidopsis thaliana (AtPPT1), which localizes to the inner membrane of chloroplasts (Fischer et al., 1997). AtPPT1 is a relatively small protein (30 kDa) whose activity can be measured by monitoring the incorporation of 32Plabeled Pi into proteoliposomes (Flügge and Weber, 1994; Fischer et al., 1997). We constructed a vector encoding the mature form of AtPPT1 for in vitro transcription, and the transcripts were subjected to cell-free translation for the production of AtPPT1 protein. Given that AtPPT1 synthesized by the conventional wheat germ cell-free system (Sawasaki et al., 2002) formed an insoluble precipitate that was not amenable to functional analysis, we needed optimization of the cell-free reaction mixture to allow the synthesis of a soluble form of AtPPT1. We screened various detergents at various concentrations as potential supplements to the cell-free protein synthesis mixture for improvement of the solubility of AtPPT1. Several detergents increased the solubility of AtPPT1 in the cell-free reaction mixture, and Brij35, Brij58, Brij78, Brij98, Brij97, and digitonin were found to be the most effective. The mature form of AtPPT1 was synthesized in the cell-free system in the presence of Brij35. After buffer exchange, the synthesized proteins were reconstituted into proteoliposomes and the phosphate/phosphate transport activity of reconstituted AtPPT1 was determined. The activity obtained was thus not sufficient for biochemical characterization of transporter function with this system. We hypothesized that Brij35 might negatively affect the reconstitution process as a result of its tight association with synthesized proteins. We therefore attempted cell-free protein synthesis in the presence of both liposomes and Brij35 to improve the reconstitution efficiency. In this approach, AtPPT1 was synthesized in the cell-free system supplemented with Brij35 (0.04%) and various amounts of liposome suspension prepared from asolectin. AtPPT1 synthesized under these conditions exhibited a greatly increased transport activity that was dependent on liposome concentration. The transport activity of AtPPT1 synthesized in the presence of liposomes at a concentration of 10 mg/mL was thus ~140 times that for the protein synthesized in the absence of liposomes; the background activity for GFP synthesized in the presence of liposomes did not differ substantially from that of GFP synthesized in their absence. These results indicated that the addition of liposomes to the cell-free system increased the yield of functional AtPPT1 produced in the presence of detergent. To further validate this new system, we isolated cDNAs encoding three putative PPT orthologs of rice as well as the triose phosphate/phosphate translocator (AtTPT) of Arabidopsis. The proteins produced with the modified cellfree system containing both Brij35 (0.04%) and liposomes (10 mg/mL) were analyzed for their substrate specificities by preloading the liposomes with various phosphorylated metabolites as exchangeable countersubstrates. The obtained results showed substrate specificity of each transporter (Nozawa et al., 2007). The biochemical characteristics of plant membrane proteins have often been analyzed with the use of proteoliposomes reconstituted with recombinant proteins purified from yeast cells. We compared our data with that in previous reports and confirmed that our method yields data similar to those obtained with the use of recombinant proteins purified from yeast cells. Thus, we have developed a method for the production and proteoliposome reconstitution of plant solute transporters that is based on a wheat germ cell-free protein synthesis system. Our modified cell-free protein synthesis system represents a valuable tool for the production of transporter proteins in a functional state.

Fig. 3. Plastid phosphate carrier proteins (left) and cell-free synthesis of PPT1 as proteomicelles (right)


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Cell-free synthesis and functional analysis of mitochondrial transporters As described above, the wheat germ cell-free system is a potent tool for functional analysis of plastid transporters. To present versatility of the system, we next describe the application to functional analysis of mitochondrial transporters. We chose transporters related to pathway of tricarboxylic acid (TCA) metabolism. Most organisms have evolved a canonical cyclic pathway of TCA metabolism, but there are some exceptions. For example, the malaria parasite, Plasmodium falciparum, has been shown to operate a noncanonical branched-type TCA metabolic pathway in its mitochondria (Olszewski et al., 2010). It was suggested that this protozoan does not depend on TCA metabolism for the generation of ATP, but rather relies on its unique TCA metabolism for more limited functions such as provision of a precursor, succinyl-CoA, for heme biosynthesis (Olszewski et al., 2010). The starting substrate and end product of the unique TCA metabolism were proposed to be oxoglutarate and malate, respectively. It is therefore important to clarify the functions of responsible transporter that facilitates efficient uptake of oxoglutarate and removal of malate across the mitochondrial inner membrane. The transport of molecules across the mitochondrial inner membrane is highly selective, so that an effective barrier exists between the cytosol and the mitochondrial matrix. Members of the mitochondrial carrier (MC) family of proteins, which is the largest family of transporters, operate the selective transport of most solutes across the inner membrane (Palmieri et al., 2011). One of the bottlenecks in biochemical analysis of P. falciparum proteins has been the lack of an efficient method for protein preparation. The parasite has one of the most A/T-rich genomes known (76.3% in exon regions) (Gardner et al., 2002), with the A/T-biased codon usage having been assumed to affect the expression of encoded proteins in bacterial recombinant systems. A wheat germ cell-free system was recently shown to be a promising alternative for the production of P. falciparum proteins (Tsuboi et al., 2008). An apicoplast phosphate translocator from P. falciparum has been synthesized and characterized with the use of a cell-free system (Lim et al., 2010). To gain insight into TCA metabolism in the mitochondria of P. falciparum, we isolated and characterized a predicted dicarboxylate-tricarboxylate carrier (DTC) homolog of this parasite with the use of a liposomesupplemented cell-free system. We clarified the substrate specificity of this protein, designated PfDTC, which has implications for the nature of the TCA pathway in the parasite (Olszewski et al., 2010, Nozawa et al., 2011) (Figs. 4 and 5).

Fig. 4. Proteoliposome reconstitution assay and substrate specificity of each transporter

Fig. 5. Suggested function of PfDTC in the branched type TCA pathway in malaria parasite

Cell-free synthesis of bacterial proton pump with unique detergent mixture Cell-free protein synthesis system is one potential approach to the production of functional membrane-integrated proteins. We have also examined various detergents as supplements to a wheat germ cell-free system in order to optimize the production and subsequent purification of a functional model membrane protein, bacteriorhodopsin, which is known as light-dependent proton pump of Halobacterium. As GFP is a useful visual marker for the

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synthesis of soluble protein, bacteriorhodopsin is a good candidate of visual marker for the synthesis of membraneintegrated protein. We found that Fos-choline and CHAPS detergents counteracted each other’s inhibitory effects on cell-free translation activity and thereby allowed the efficient production and subsequent purification of functional bacteriorhodopsin in high yield (Genji et al., 2010). Most modifications of the cell-free approach to the production of membrane proteins involve the addition of either vesicles (Kalmbach et al., 2007, Katzen et al., 2008, Nozawa et al., 2007, Shimono et al., 2009, Wuu and Swartz, 2008) or detergent (Klammt et al., 2007; Kaiser et al., 2008, Ishihara et al., 2005, Berrier et al., 2004, Klammt et al., 2005). Both additions allow the efficient production of certain membrane proteins in a functional state, but both still have some problems. In the case of vesicle-based systems, the insertion efficiency of the synthetic membrane protein depends completely on the spontaneous integration of the protein into the vesicle, which is a barrier for some membrane proteins. In the case of detergent-based systems, many detergents are not appropriate as supplements because they impair the translation activity. Detergents used for the purification of membrane protein are not necessarily applicable to cell-free protein synthesis systems. These limiting factors remain as hurdles in the development of a general method for the production of membrane proteins with a cell-free-based system. In seeking other effective modifications of the cell-free approach, we have focused on phospholipid-like detergents such as Fos-choline (FC), given that these detergents have been shown to be effective for solubilization and purification of functional forms of membrane proteins expressed in E. coli or wheat germ cell-free systems. We have examined the application of FC12 and FC14 to our wheat germ cell-free protein synthesis system in order to develop a method to supply membrane proteins in useful quantities. With the use of GFP as a reporter protein, we found that the wheat germ cell-free system retains sufficient translation activity in the presence of a unique combination of FC and CHAPS detergents (Genji et al., 2010). We went on to show that bacteriorhodopsin, one of the best characterized membrane proteins, can be efficiently synthesized with its functional fold in the presence of such mixed micelles. We have optimized the unique combination of detergents that allows efficient production of functional bacteriorhodopsin by cell-free translation in the wheat germ–based system (Genji et al., 2010). In addition, this detergent mixture allowed purification of the synthesized functional bacteriorhodopsin by a simple procedure based on immobilized metal affinity chromatography (Genji et al., 2010). The identification of this combination of detergents as a supplement for cell-free protein synthesis systems should provide a basis for the further development of such systems for the production of functional membrane-integrated proteins.

Fig. 6. Proteoliporomes and proteomicelles.

Fig. 7. CHAPS and Fos-Choline.


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As a biochemical tool for the identification of potential membrane associating proteins In addition to proteins that have transmembrane domain(s) in their polypeptides, proteins that are posttranslationally modified by acylation often acquire functions of membrane association. Protein N-myristoylation is one of the examples of protein-acylation that regulate destinations of synthesized proteins in living cells. Protein Nmyristoylation plays key roles in various cellular functions in eukaryotic organisms (Batistič et al., 2008; Resh, 1999). To clarify the relation between the efficiency of protein N-myristoylation and the amino acid sequence of the substrate in plants, we have applied a wheat germ cell-free translation system with high protein productivity to examine the N-myristoylation of various wild-type and mutant forms of A. thaliana proteins (Yamauchi et al., 2010). Evaluation of the relation between removal of the initiating Met residue and subsequent N-myristoylation revealed that constructs containing Pro at position 3 do not undergo N-myristoylation primarily because of an inhibitory effect of this residue on elimination of the initiating Met by methionyl aminopeptidase (Kanno et al., 2007; Yamauchi et al., 2010). Our analysis of the consensus sequence for N-myristoylation in plants focused on variability of residues at positions 3, 6, and 7 of the motif (Yamauchi et al., 2010). We found that not only Ser at position 6 but also Lys at position 7 affects the selectivity for the amino acid at position 3. The results of our analyses allowed us to identify several A. thaliana proteins as substrates for N-myristoylation that had previously been predicted not to be candidates for such modification with a prediction program. We have thus shown that a wheat germ cell-free system is a useful tool for plant N-myristoylome analysis. This in vitro approach will facilitate comprehensive determination of Nmyristoylated proteins in plants.

Fig. 8. Co-translational N-myristoylation in the wheat germ cell-free protein synthesis system

Conclusion We have developed a method for the production of functional membrane integrated proteins based on the wheat germ cell-free protein synthesis system. We are able to prepare membrane proteins in several different forms such as as protoeoliposomes or proteomicelles. The proteoliposome reconstitution system is a valuable tool for the functional analysis of transporters in vitro. Whereas proteomicelles system is useful for subsequent purification of cell-free synthesized membrane proteins. Further, N-myristoylation enzymes also active in the eukaryotic cell-free system, facilitating effective co-translational N-myristoylation of target protein. Given that the wheat germ cell-free system expands the scope for functional analysis of a wide variety of transmembrane proteins and membrane-associating proteins. Lastly, list of membrane protein that have been synthesized and characterized in our laboratory is shown below. Table 1. List of membrane integrated proteins synthesized and characterized based on the wheat germ system Name of protein PPT1 TPT1 OsPPT1 OsPPT2 OsPPT3 AtDTC1 PfDTC Bacterirhodopsin KAT1 OsOMT1 OsDCT1 OsDCT2 P450 reductase P450 C4H McPPT1 McTPT1 McGPT1 McGPT2

Cellular localization

Species

Reference

Arabidopsis thaliana Plastid inner membrane

Nozawa et al. 2007 Oryza sativa

Inner membrane Plasma membrane

Arabidopsis thaliana Plasmodium falciparum Halobacterium Arabidopsis thaliana

Plastid inner membrane

Oryza sativa

In preparation

Endoplasmic reticulum

Arabidopsis thaliana

In preparation

Plastid inner membrane

Mesembryanthemum crystallium (ice plant)

In preparation

Mitochondrial inner membrane

Nozawa et al. 2011 Genji et al. 2010 In preparation

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References Arabidopsis Genome Initiative (2000) Analysis of he genome sequence of the flowering plant Arabidopsis thaliana. Nature, 408, 796-815 Batistič O, Sorek N, Schültke S, Yalovsky S, Kudla J (2008) Dual fatty acyl modification determines the localization and plasma membrane targeting of CBL/CIPK Ca2+ signaling complexes in Arabidopsis. Plant Cell, 20, 13461362 Berrier C, Park K, Abes S, Bibonne A, Betton J, Ghazi A (2004) Cell-free synthesis of a functional ion channel in the absence of a membrane and in the presence of detergent. Biochemistry, 43, 12585-12591 Endo Y, Mitsui K, Motizuki M, Tsurugi K (1987) The mechanism of action of ricin and related toxic lectins on eukaryotic ribosomes. The site and the characteristics of the modification in 28S ribosomal RNA caused by the toxins. J. Biol. Chem., 262, 5908-5912 Endo Y, Tsurugi K (1987) RNA N-glycosidase activity of ricin A-chain. Mechanism of action of the toxic lectin ricin on eukaryotic ribosomes. J. Biol. Chem., 262, 8128-8130 Endo Y, Wool IG (1982) The site of action of alpha-sarcin on eukaryotic ribosomes. The sequence at the alpha-sarcin cleavage site in 28S ribosomal ribonucleic acid. J. Biol. Chem., 257, 9054-9060 Elbaz Y, Steiner-Mordoch S, Danieli T, Schuldiner S (2004) In vitro synthesis of fully functional EmeE, a multidrug transporter, and study of its oligomeric state. Proc. Natl. Acad. Sci. USA, 101, 1519-1524 Fischer K, Kammerer B, Gutensohn M, Arbinger B, Weber A, Häusler RE, Flügge U (1997) A new class of plastidic phosphate translocators: A putative link between primary and secondary metabolism by the phosphoenolpyruvate/phosphate antiporter. Plant Cell, 9, 453-462 Flügge U, Weber A (1994) A rapid method for measuring organelle-specific substrate transport in homogenates from plant tissues. Planta, 194, 181-185 Flügge UI, Weber A, Fischer K, Lottspeich F, Eckerskorn C, Waegemann K, Soll J (1991) The major chloroplast envelope polypeptide is the phosphate translocator and not the protein import receptor. Nature, 353, 364-367 Gardner MJ, Hall H, Fung E, White O, Berriman M, Hyman RV, Carlton JM, Pain A, Nelson KE, Bowman S, Paulsen IT, James K, Eisen JA, Rutherford K, Salzberg SL, Craig A, Kyes S, Chan MS, Nene V, Shallom SJ, Suh B, Peterson J, Angiuoli S, Pertea M, Allen J, Selengut J, Haft D, Mather MW, Vaidya AB, Martin DM, Fairlamb AH, Fraunholz MJ, Roos DS, Ralph SA, McFadden GI, Cummings LM, Subramanian GM, Mungall C, Venter JC, Carucci DJ, Hoffman SL, Newbold C, Davis RW, Fraser CM, Barrell B (2002) Genome sequence of the human malaria parasite Plasmodium falciparum. Nature, 419, 498–511 Genji T, Nozawa A, Tozawa Y (2010) Efficient production and purification of functional bacteriorhodopsin with a wheat-germ cell-free system and a combination of Fos-choline and CHAPS detergents. Biochem. Biophys. Res. Commun., 400, 638-642 Ishihara G, Goto M, Saeki M, Ito K, Hori T, Kigawa T, Shirouzu M, Yokoyama S (2005) Expression of G protein coupled receptors in a cell-free translational system using detergents and thioredoxin-fusion vectors. Protein Expr. Purif., 41, 27-37 Kaiser L, Graveland-Bikker J, Steuerwald D, Vanberghem M, Herlihy K, Zhang S (2008) Efficient cell-free production of olfactory receptors: detergent optimization, structure, and ligand binding analyses. Proc. Natl. Acad. Sci. USA, 105, 15726-15731 Kalmbach R, Chizhov I, Schumacher M, Friedrich T, Bamberg E, Engelhard M (2007) Functional cell-free synthesis of a seven helix membrane protein: in situ insertion of bacteriorhodopsin into liposomes. J. Mol. Biol., 371, 639648 Kanno T, Kitano M, Kato R, Omori A, Endo Y, Tozawa Y (2007) Sequence specificity and efficiency of protein Nterminal methionine elimination in wheat-embryo cell-free system. Protein Expr. Purif., 52, 59-65 Kasahara M, Hinkle PC (1976) Reconstitution of D-glucose transport catalyzed by a protein fraction from human erythrocytes in sonicated liposomes. Proc. Natl. Acad. Sci. USA, 73, 396-400 Katzen F, Fletcher JE, Yang JP, Kang D, Peterson TC, Cappuccio JA, Blanchette CD, Sulchek T, Chromy BA, Hoeprich PD, Coleman MA, Kudlicki W (2008) Insertion of membrane proteins into discoidal membranes using a cell-free protein expression approach. J. Proteome Res., 7, 3535-3542 Klammt C, Schwarz D, Eifer N, Engel A, Piehler J, Haase W, Hahn S, Dötsch V, Bernhard F (2007) Cell-free production of G protein-coupled receptors for functional and structural studies, J. Struct. Biol., 158, 482-493 Klammt C, Schwarz D, Fendler K, Haase W, Hahn S, Dötsch V, Bernhard F (2005) Evaluation of detergents for the soluble expression of α-helical and β-barrel-type integral membrane proteins by a preparative scale individual cell-free expression system. FEBS J., 272, 6024-6038 Klammt C, Schwarz D, Löhr F, Schneider B, Dötsch V, Bernhard F (2006) Cell-free expression as an emerging technique for the large scale production of integral membrane protein. FEBS J., 273, 4141-4153 Lim L, Linka M, Mullin KA, Weber APM, McFadden GI (2010) The carbon and energy sources of the nonphotosynthetic plastid in the malaria parasite. FEBS Lett., 584, 549–554 Madin K, Sawasaki T, Ogasawara T, Endo Y (2000) A highly efficient and robust cell-free protein synthesis system prepared from wheat embryos: plants apparently contain a suicide system directed at ribosomes. Proc. Natl. Acad. Sci. USA, 97, 559-564


23

Nozawa A, Fujimoto R, Matsuoka H, Tsuboi T, Tozawa Y (2011) Cell-free protein synthesis, reconstitution and characterization of mitochondrial dicarboxylate-tricarboxylate carrier of Plasmodium falciparum. Biochem. Biophys. Res. Commun., 141, 612-617 Nozawa A, Nanamiya H, Miyata T, Linka N, Endo Y, Weber APM, Tozawa Y (2007) A cell-free translation and proteoliposome reconstitution system for functional analysis of plant solute transporters. Plant Cell Physiol., 48, 1815-1820 Nozawa A, Nanamiya H, Tozawa Y (2010) Production of membrane proteins through the wheat-germ cell-free technology. Methods Mol. Biol., 607, 213-218 Olszewski KL, Mather MW, Morrisey JM, Garcia BA, Vaidya AB, Rabinowitz JD, Llinás M (2010) Branched tricarboxylic acid metabolism in Plasmodium falciparum. Nature, 466, 774–778. Ohta T, Matsuoka H, Nomura Y, Tozawa Y (2010) Control of translational initiation in the wheat-embryo cell-free protein expression system for producing homogenous products. Protein Expr. Purif., 73, 15-22 Palmieri F, Pierri CL, De Grassi A, Nunes-Nesi A, Fernie AR (2011) Evolution, structure and function of mitochondrial carriers: a review with new insights. Plant J., 66, 161–181 Resh MD (1999) Fatty acylation of proteins: new insights into membrane targeting of myristoylated and palmitoylated proteins. Biochim. Biophys. Acta, 1451, 1-16 Sawasaki T, Ogasawara T, Morishita R, Endo Y (2002) A cell-free protein synthesis system for high-throughput proteomics. Proc. Natl. Acad. Sci. USA, 99, 14652-14657 Shimizu Y, Inoue A, Tomari Y, Suzuki T, Yokogawa T, Nishikawa K, Ueda T (2001) Cell-free translation reconstituted with purified components. Nature Biotechnol., 19, 751-755 Shimono K, Goto M, Kikukawa T, Miyauchi S, Shirouzu M, Kamo N, Yokoyama S (2009) Production of functional bacteriorhodopsin by an Escherichia coli cell-free protein synthesis system supplemented with steroid detergent and lipid. Protein Sci., 18, 2160-2171 Spirin AS, Baranov VI, Ryabova LA, Ovodov SY, Alakhov YB (1988) A continuous cell-free translation system capable of producing polypeptides in high yield. Science, 242, 1162-1164 Takai K, Sawasaki T, Endo Y (2009) Practical cell-free protein synthesis system using purified wheat embryos. Nature Protocol, 5, 227-238 Tsuboi T, Takeo S, Iriko H, Jin L, Tsuchimochi M, Matsuda S, Han ET, Otsuki H, Kaneko O, Sattabongkot J, Udomangpetch R, Sawasaki T, Torii M, Endo Y (2008) Wheat germ cell-free system-based production of malaria proteins for discovery of novel vaccine candidates. Infect Immun., 76, 1702–1708 Yamauchi S, Fusada N, Hayashi H, Utsumi T, Uozumi N, Endo Y, Tozawa Y (2010) The consensus motif for Nmyristoylation of plant proteins in a wheat germ cell-free translation system. FEBS J., 277, 3596-3607 Wuu J, Swartz J (2008) High yield cell-free production of integral membrane proteins without refolding or detergents. Biochim. Biophys. Acta, 1778, 1237-1250

“Parts Is Parts,” At Least from the Proteomics Perspective Ján A. MIERNYK1,2,3 * 1

USDA, Agricultural Research Service, Plant Genetics Research Unit, 2Interdisciplinary Plant Group, Department of Biochemistry, 102 Curtis Hall, University of Missouri, Columbia, MO 65211, USA *Corresponding author: [email protected] 3

Abstract A shot-gun proteomics strategy was used to compare leaves, developing pods, seedcoats, and cotyledons, and suspension-cultured cells of soybean (Glycine max (L.) Merr., cultivar Jack). A total of 3,500 proteins were identified and sorted into 11 categories. Unexpectedly, and with a few notable exceptions, distribution of proteins among the categories was more similar than dissimilar. In all instances the Primary Metabolism cluster was most populated, followed by Cellular Structure. The Stress Response cluster contained the smallest number of identified proteins. We speculate that the major differences in organ size, shape, and function are more reflective of posttranslational modifications than the overall bulk proteome.

Introduction No one would imagine questioning the observation that different plant parts/organs/tissues are specialized for distinct biological activities. The major function of leaves is photosynthesis, roots are specialized for H 2 O and nutrient uptake, flowers are essential for sexual reproduction, and seeds contain an embryo plus storage materials necessary to sustain the embryo until it achieves photosynthetic competence (Miernyk et al., 2011). Correspondingly, it is uniformly-accepted truism that the genome is identical in all nucleate cells. What then underlies specialization? The simplistic answer is that differences in the translated-proteome are responsible for specialization. Is it then feasible to use a simple proteomics strategy to test this assertion? While seeds have been the object of extensive study for many years (Miernyk and Hajduch, 2011), seed parts have only recently been examined from functional, molecular, and developmental perspectives (Weber et al., 2005). Seedpods encapsulate developing seeds and protect them from pests and pathogens. They are typically photosynthetically active and contribute the assimilates and nutrients that drive seed growth. More recently it has come to light that signals from the pod can act to coordinate seed filling (Bennett et al., 2011). The seedcoat, or testa, develops from the integuments of the ovule, and has multiple roles related to seed development, quiescence and/or dormancy, dispersal, and germination (Moise et al., 2005). Like pods, they also play an important nutritive role during seed development (Murray, 1987). The embryo comprises the storage organ(s) plus the embryonic axes. In the case of soybeans, the storage organs are cotyledons, while in other seeds they might be the endosperm, the hypocotyl, or specialized organs such as the megagametophyte (Costa et al., 2004) Leaves are the plant organ specialized for photosynthetic function (Braybrook and Kuhlemeier, 2010; Moon and Hake, 2011). The internal organization of leaves, the mesophyll with the palisade and spongy parenchyma, has evolved to maximise gas exchange and carbon fixation (Blein et al., 2010). Most leaves have stomata, which open or narrow to regulate the exchange of carbon dioxide, oxygen, and water vapour with the atmosphere (Dong and Bergmann, 2010). The most abundant protein in leaves/chloroplasts, the Calvin cycle enzyme ribulose-1,5bisphosphate carboxylase/oxygenase, is believed to be the most abundant protein on earth (Ellis, 1979). When plant cells/young embryos are aseptically-cultured in vitro with low levels of auxin there is a proliferation of dedifferentiated cells typically referred to as callus. The callus can be transferred to a nutritionally-complete liquid medium and grown with agitation sufficient to meet the requirements for aeration (Torrey and Reinert, 1961). If sterility is maintained and the cells are regularly transferred to fresh medium the cultures are essentially immortal, and will divide and grow forever. These suspension cultures are not autotrophic, and require a supply of reduced carbon and nitrogen, often along with vitamins and growth regulators. Plant cells are totipotent (Vasil and Vasil, 1972). After extended in vitro culture, cells typically lose their embryogenic capacity and become terminally dedifferentiated (Häsler et al., 2003). Herein we present the results from preliminary analyses of the whole soybean plant, in an attempt to better understand the bases of cell/tissue/organ differentiation.

Materials and methods Plants Soybean (Glycine max (L.) Merrill, cv. Jack) plants were glasshouse grown with supplemental lighting (16 h light/8 h dark, 26°C day/21°C night). Plants were not nodulated, and were treated weekly with an all-purpose fertilizer (Osmocote 14-14-14, Scotts-Sierra Horticultural Products, Marysville, OH). The staging of developing seeds is based on the fresh weight/color system first described by Meinke et al. (1981). For analysis of pods,

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seedcoats, and cotyledons, S4 seeds (green, 136 ± 12 mg) were used. Bright green, fully-expanded leaves, and suspension cells 5 days after transfer to fresh medium were harvested for comparisons. Plant materials were either extracted immediately or stored at -70oC until analysed. Reagents Unless otherwise noted, reagents were from the Sigma Chemical Company (St. Louis, MO USA). Sample preparation For each sample, a "total protein” protein fraction was isolated from 150 mg fresh weight of material using a phenol-based protocol (Hurkman and Tanaka, 1986) with minor modifications. Proteins were extracted with 100 mM tris-HCl, pH 8.8, containing 0.5% C7BZO, 2% SDS, 10 mM EDTA, and the HALT protease/phosphatase inhibitor cocktail (Pierce, Rockford, IL) with equal volume of tris, pH 8.8, buffered-phenol. Proteins were precipitated three times with 5 volumes of methanolic ammonium acetate containing 50 mM DTT, then washed twice with 80% acetone containing 20 mM DTT. The final pellet was suspended in 1 mL 80% acetone and stored at -20°. The acetone-insoluble pellet was dissolved in 200 μL of 8 M urea containing 0.2 % C7BZO (w/v). After the pellets were solubilized, the solutions were clarified by centrifugation, and protein levels estimated by A 280 readings. Proteins (100 μg) were reduced with 15 mM TCEP (Pierce; Rockford, IL) for 30 min at room temp, and then diluted to 4 M urea by 1:1 addition of 100 mM Hepes, pH 8.0, containing 50 mM iodoacetamide, followed by incubation for 30 min in the dark. Further dilution to 2 M urea was achieved by 1:1 addition of 40 mM N-acetyl-Cys which also quenched the unreacted iodoacetamide. Proteins were digested in solution by adding trypsin (Princeton Separations, Adelphia, NJ) in 25 mM Hepes-NaOH, pH 8.0, to a final concentration of 2.0% (w/v). Digestions proceeded at room temperature for approximately 16 h, then were stopped by adding trifluoroacetic acid to a final concentration of 0.1% (v/v). The tryptic peptides were processed by ZipTip (Millipore; Billerica, MA), following manufactures protocol. LC-MS/MS analysis ZipTipped-samples were loaded onto a C8 trap column (Michrom Bioresources, Auburn, CA). Bound peptides were eluted from this trap column onto a 10.5 cm, 150 µm i.d. pulled-needle analytical column packed with magic C18 reversed phase matrix (Michrom Bioresources). Peptides were separated and eluted from the analytical column with a continuous gradient of acetonitrile from 5 to 45% (in 0.1% formic acid) over 120 minutes. The Proxeon Easy nLC-II HPLC system is attached to an LTQ Orbitrap mass spectrometer (Thermo, Rockford, IL). Following a highresolution FTMS scan of the eluting peptides, each second, the 9 most abundant peptides were subjected to peptide fragmentation (CID in the ion-trap). Data across a total of 140 min of elution were collected and then searched against both the NCBInr all-species database and the Phytozome Glycine max database (updated August 8, 2009) using Sorcerer 2 IDA (a Sequest-based search algorithm). Identifications were examined using the Scaffold 3 program (Proteome Software, Portland, OR). For GeLC analysis (Graham et al., 2007), total proteins were separated by 1D SDS-PAGE on 12% (T) acrylamide gels. The abundant Coomassie-stained bands were excised with a razorblade, and the proteins subjected to in-gel trypsin digestion. The resultant tryptic-peptides were separated by nLC and identified by tandem MS.

Results Putative protein ID’s were accepted if more than one peptide was identified in at least two biological replicate analyses. The number of proteins meeting these criteria was: Seedcoats, 558; Cotyledons, 410; Pods, 513; Young Leaves, 529; and Suspension Cultures, 367. The protein ID’s were sorted into 11 clusters (Miernyk et al., 2011); Primary Metabolism, Secondary Metabolism, Cellular Structure, Stress Responses, Nucleic Acid metabolism, Protein Synthesis, Protein Folding, Protein Targeting, Hormones and Signaling, Seed Storage Proteins, and Proteins of Unknown Function . Clustering of the protein ID’s obtained by shotgun proteomic analyses of the various soybean parts/organs/tissues gave a series of very similar patterns (Fig. 1). In all instances the Primary Metabolism cluster contained the largest number of identified proteins and the Cellular Structure cluster contained the next largest group of ID’s. The Stress Response cluster contained the smallest number of identified proteins. The relatively small number of assignments to the Proteins of Unknown Function cluster belies the utility of the Phytozome database. The relatively uniform distribution of proteins identified by shotgun analyses was not anticipated, and raised the possibility that it represented only an “apparent similarity” that resulted somehow from the cluster assignment? This possibility was tested by 1D SDS-PAGE plus Coomassie Blue staining (Fig. 2). Overall the patterns of banding look more similar than dissimilar, and each sample has a small number of relatively abundant Coomassie-staining proteins at either the same or very similar gel mobility. The M r ~55,000 bands in all samples except the tissue cultures contained RuBisCO LSU (Glyma01g04090)(Table 1). The tissue culture band with approximately the same M r was EF-1α (Glyma19g07240.1). The Mr 41,000 band in all samples is NAD-glyceraldehyde-3-phosphate dehydrogenase isozyme C (Glyma06g18110.1), and the Mr 35,000 band is an annexin (Glyma15g38040.1). The Mr 37,000 band in seed pods and leaves is an acid phosphatase (Glyma07g01730.1). The abundant bands found only in the cotyledon samples are, from top to bottom, the SSP glycinin, beta-conglycinin acidic subunit, and beta-conglycinin basic subunit. The Mr 15,000 protein in all samples except the tissue cultures is RuBisCO SSU (Glyma13g07610.1)(Table 1).

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Fig. 1. Functional clustering of proteins identified during shot-gun LC-MS/MS analysis of soybean seedcoats (SC), pods, cotyledons (COT), leaves, and suspension-cultured cells.

Fig. 2. Analysis of soybean proteins by 1D SDS-PAGE with Coomassie-blue staining. The boxed protein bands were subjected to in gel-trypsin digestion, then analysed by GeLC MS/MS. The abundant bands visible on the 1D Coomassie-stained gels (Table 1), RuBisCO LSU and SSU, the SSP, acid phosphatase, the annexins, and GAPC are all known to be generally abundant proteins, so it is not surprising that they predominate. The annexins are Ca2+- and phospholipid-binding proteins known to be involved with vesicle trafficking, endo- and exocytosis, and calcium ion channel formation (Gerke and Moss, 2002). Acid phosphatases are the products of a mid-sized multi-gene family of secretory N-glycosylated phospho-monoesterases typically expressed in relation to phosphate nutrition (Miernyk, 1992). It has been reported that the GAP dehydrogenase proteins have, in addition to their function of converting 1,3-bisphosphoglycerate to glyceraldehyde 3-phosphate and inorganic phosphate as part of the Calvin cycle and glycolysis, at least 10 distinct moonlighting functions (Sriram et al., 2005).

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Table 1. Proteins from the gel in Figure 2 that were identified by GeLC-MS/MS. The attributed protein ID’s are based upon >10 peptides identified and >50% sequence coverage, in two biological replicates.

Protein band 1 2 3 4 5 6 7 8

A

B

C

D

E

nd LSU GAPC annexin nd nd nd SSU

nd LSU GAPC annexin nd AP nd SSU

glycinin LSU GAPC nd ASU nd BSU SSU

nd LSU GAPC nd nd AP nd SSU

nd EF-1α GAPC nd nd nd nd nd

Key: nd, not determined; LSU, Ribulose-1,5-bis-phosphate Carboxylase/Oxygenase large subunit; GAPC, glyceraldehyde-3-phosphate dehydrogenase isozymes C; ASU, β-conglycinin acidic subunit; BSU, β-conglycinin basic subunit; AP, acid phosphatase, and SSU, Ribulose-1,5-bis-phosphate Carboxylase/Oxygenase small subunit. Discussion Soybeans are a critically-important agricultural crop, and as a result have been subjected to extensive proteomic analyses (Sakata et al., 2009). In most instances, however, these studies have focused on limited physiological, developmental, or comparative differences (Agrawal et al., 2008; Ahsan and Komatsu, 2009; Kahn et al., 2009; Toorchi et al., 2009; Afroz et al., 2010). Even taking into consideration the background problem of dynamic-range extremes (Miernyk and Hajduch, 2011), it was not anticipated that results from both shotgun nLC-MS/MS and GeLC-MS analyses of “total proteins” isolated from different soybean cells/tissues/organs would yield such broadly similar patterns. Neither roots nor flowers were included in the present study. The Komatsu lab has published extensive results from proteomic analyses of soybean roots (Sataka et al., 2009; Kahn et al., 2009; Toorchi et al., 2009; Afroz et al., 2010), and additionally has recently published a proteomic comparison with soybean flowers (Ahsan and Komatsu, 2009). Overall the results from our analysis of the suspension cells are quite similar to the results from analysis of roots or flowers. In retrospect this is perhaps not surprising? All three “organs” might be considered heterotrophic; nutrients are supplied to the suspension cells in the liquid medium, nutrients are supplied to the roots by the rhizosphere and the leaves, and the flowers are supplied by the roots and leaves. Consistent with this idea, no RuBisCO was observed in roots, flowers, or suspension cells. There are both obvious and more subtle interpretations of our results showing global similarity in protein patterns. It might be that the major biological differences are the result of the activities of low-abundance proteins that would not be detected by the proteomic analysis methods employed. Alternatively, it is possible that it is the multitude of protein PTM’s, which would also not be detected by the methods used in these analyses, that comprises the underlying bases for the differences. While we favour the latter hypothesis, we can neither exclude the former nor the possibility that it is a combination of the two. Conclusion In an advertising conflict between two large American fast-food companies during the 1980’s, it was ungrammatically suggested that food preparation is critical because, “Parts is parts.” If the abundant proteins (“parts”) of leaves, pods, seedcoats, and cotyledons are the same, or at least very similar, then what is it that drives specialization? We hypothesize that the answer is within the myriad of protein PTM. A plethora of both reversible (phosphorylation, acetylation, N-methylation, Met-oxidation, etc.) and non-reversible (proteolytic processing, Nglycosylation, etc.) PTM’s are known to control protein activity, localization, stability, and interactions (Thelen and Miernyk, 2012). In order to extend our analysis of soybean proteins, we are currently studying reversible phosphorylation, acetylation, and Met oxidation in an attempt to define the bases for organ/tissue differentiation and specialization.

References Afroz A, Hashiguchi A, Khan MR, Komatsu S (2010) Analyses of the proteomes of the leaf, hypocotyl, and root of young soybean seedlings. Protein Pept. Lett., 17, 319-331 Agrawal GK, Hajduch M, Graham K, Thelen JJ (2008) In-depth investigation of the soybean seed-filling proteome and comparison with a parallel study of rapeseed. Plant Physiol., 148, 504-518 Ahsan N, Komatsu S (2009) Comparative analyses of the proteomes of leaves and flowers at various stages of development reveal organ-specific functional differentiation of proteins in soybean. Proteomics, 9, 4889-4907

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Bennett EJ, Roberts JA, Wagstaff C (2011) The role of the pod in seed development: strategies for manipulating yield. New Phytol., 190, 838-853 Blein T, Hasson A, Laufs P (2010) Leaf development: what it needs to be complex. Curr. Opin. Plant Biol., 13, 7582. Braybrook SA, Kuhlemeier C (2010) How a plant builds leaves. Plant Cell, 22, 1006-1018 Costa LM, Gutièrrez-Marcos JF, Dickinson HG (2004) More than a yolk: the short life and complex times of the plant endosperm. Trends Plant Sci., 9, 507-514 Dong J, Bergmann DC (2010) Stomatal patterning and development. Curr. Top Dev. Biol., 91, 267-97 Ellis RJ (979) The most abundant protein in the world. Trends Biochem. Sci., 4, 241-244 Gerke V, Moss SE (2002) Annexins: from structure to function. Physiol. Rev., 82, 331-371 Graham RLJ, Sharma1 MK, Ternan NG, Weatherly DB, Tarleton RL, McMullan G (2007) A semi-quantitative GeLC-MS analysis of temporal proteome expression in the emerging nosocomial pathogen Ochrobactrum anthropic. Genome Biol., 8, R110 Häsler J, Wüest J, Gaspar T, Crèvecoeur M (2003) Long term in vitro-cultured plant cells show typical neoplastic features at the cytological level. Biol. Cell, 95, 357-364 Hurkman WJ, Tanaka CK (1986) Solubilization of plant membrane proteins for analysis by two-dimensional gel electrophoresis. Plant Physiol., 81, 802-806 Khan NA, Takahashi R, Abe J, Komatsu S (2009) Identification of cleistogamy-associated proteins in flower buds of near-isogenic lines of soybean by differential proteomic analysis. Peptides, 30, 2095-2102 Ma F, Cholewa E, Mohamed T, Peterson CA, Gijzen M (2004) Cracks in the palisade cuticle of soybean seed coats correlate with their permeability to water. Ann. Bot., 94, 213-228 Meinke DW, Chen J, Beachy RN (1981) Expression of storage-protein genes during soybean seed development Planta, 153, 130-139 Miernyk JA (1992) purification and characterization of the major acid phosphatase isozyme secreted by maize endosperm cultures. Phytochemistry, 31, 2613-2616 Miernyk JA, Hajduch M (2011) Seed proteomics. J. Proteomics, 74, 389-400. Miernyk JA, Johnston M (2012) Digging deeper into the seed proteome: Pre-fractionation of total proteins. In Seed Development: OMICS Technologies toward Improvement of Seed Quality and Crop Yield, Ed., GK Agrawal, R Rakwal (in press) Miernyk JA, Preťová A, Olmedilla A, Klubicova K, Obert B, Hajduch M (2011) Using proteomics to study sexual reproduction in angiosperms. Sexual Plant Reprod., 24, 9-22 Moise JA, Han S, Gudynaite-Savitch L, Johnson DA, Miki BLA (2005) Seed coats: Structure, development, composition, and biotechnology. In Vitro Cell Dev Biol – Plant, 41, 620–644 Moon J, Hake S (2011) How a leaf gets its shape. Curr. Opin. Plant Biol., 14, 24-30 Murray DR (1987) Nutritive role of seedcoats in developing legume seeds. Amer. J. Bot., 74, 1122-1137 Sakata K, Ohyanagi H, Nobori H, Nakamura T, Hashiguchi A, Nanjo Y, Mikami Y, Yunokawa H, Komatsu S (2009) Soybean proteome database: a data resource for plant differential omics. J. Proteome Res., 8, 3539-3548 Sriram G, Martinez JA, McCabe ER, Liao JC, Dipple KM (2005) Single-gene disorders: What role could moonlighting enzymes play? Am. J. Hum. Genet., 76, 911–924 Thelen1 JJ, Miernyk JA (2012) The proteomic future: Where mass spectrometry should be taking us. Biochem, J. (in press) Toorchi M, Yukawa K, Nouri MZ, Komatsu S (2009) Proteomics approach for identifying osmotic-stress-related proteins in soybean roots. Peptides, 30, 2108-2117 Torrey JG, Reinert J (1961) Suspension cultures of higher plant cells in synthetic media. Plant Physiol., 36, 483-491. Weber H, Borisjuk L, Wobus U (2005) Molecular physiology of legume seed development. Annu. Rev. Plant Biol., 56, 253-279 Vasil IK, Vasil V (1972) Totipotency and embryogenesis in plant cell and tissue cultures. In Vitro, 8, 117-127

Contribution of ‘Omics’ Analysis to Gene Discovery for the Molecular Breeding of Drought Stress Tolerance Kazuo SHINOZAKI* Gene Discovery Research Group, RIKEN Plant Science Center, 3-1-1 Koyadai, Tsukuba 305-0074, JAPAN *Corresponding author: [email protected]

Abstract Drought has severe adverse effects on crop production, and plant drought tolerance is now one of the most important breeding targets. Understanding plant responses and tolerance at molecular and cellular levels is important for molecular breeding based on transgenic technology. Plants respond and adapt to water-deficit conditions through various complex physiological and molecular processes. Drought stress induces a variety of genes at the transcriptional level, and their gene products function in drought stress tolerance and response. Transcriptome analyses using various types of microarray and next-generation DNA sequencers have been demonstrated as being powerful tools for the discovery of useful genes. In this short introductory article, the importance of integrated analysis regarding the transcriptome, proteome, and metabolome for such discoveries is discussed based on our research over the past 20 years.

Introduction Abiotic stress responses and tolerances are important for immobile plants to cope with environmental changes. Abiotic stresses include drought, salinity, high temperature, freezing, and strong light. Among these, drought stress severely affects plant growth and crop yield, and therefore, understanding drought stress responses and tolerances is one of the most important current topics in plant science. Application of molecular biology and genomics has enhanced plant stress biology, and many stress-inducible genes with various functions have been isolated from model plants such as Arabidopsis and rice. The plant hormone abscisic acid (ABA) is known to play important roles in stress-induced gene expression, as well as in stomatal closure under drought stress conditions. Determination of highquality genome sequences of Arabidopsis and rice has also enhanced understanding in plant stress biology. In particular, microarray analysis has become a powerful tool for monitoring the expression profiles of many genes in response to various environmental stresses (see reviews by Shinozaki and Yamaguchi-Shinozaki, 2007; Hirayama and Shinozaki, 2010). Analysis of transcriptome data is necessary for the discovery of the many genes involved in drought stress responses. In this short introductory article, recent studies are reported from my group in RIKEN and from the group of Kazuko Yamaguchi-Shinozaki at the Japan International Research Center for Agricultural Sciences (JIRCAS) and The University of Tokyo as examples of ‘omics’ analysis of drought stress responses and tolerance and their applications in crop breeding. Review articles from our groups are mainly considered in this article. Integration of transcriptome and genome data provides information on the regulatory elements of each gene, such as the cis-regulatory element and trans factors involved in transcription. These analyses in relation to abiotic stress responses have revealed dynamic changes in transcription profiles (see reviews by Yamaguchi-Shinozaki and Shinozaki, 2006; Hirayama and Shinozaki, 2010). The information obtained from genomic data also allows us to identify metabolic pathways involved in abiotic stress responses. In addition, the genomic information provides methods to analyze the functions of polypeptides detected in mass spectrometry-based protein profiling and protein modification. Metabolite profiling also provides useful information on metabolites involved in stress tolerance. These combined ‘omics’ analyses are now essential to understand the whole range of plant stress responses, from perception of stress signals, through signal transduction, gene expression, and metabolite synthesis to achieve stress tolerance (Fig. 1). Here, progress in the dissection of plant molecular networks of drought stress responses and tolerances are reviewed based on our research results from the past 20 years.

Fig. 1. Integration of ‘omics’ for gene discovery.

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Drought-inducible gene expression Since 1989, many genes have been isolated that are induced in response to dehydration stress, particularly in Arabidopsis and rice as model plants (see reviews by Yamaguchi-Shinozaki and Shinozaki, 2006; Hiyarama and Shinozaki, 2010). We have shown that many genes having various functions are upregulated in response to dehydration stress, and most of their gene products function in stress tolerance and response. The stress-inducible genes are classified into two major groups: functional proteins involved in stress tolerance and regulatory proteins involved in gene expression and signal transduction. We have also analyzed the expression profiles of the droughtinducible genes and identified different regulatory systems in stress-responsive gene expression, one of which is ABA-dependent and the other is ABA-independent (see reviews by Yamaguchi-Shinozaki and Shinozaki, 2006; Hirayama and Shinozaki, 2010) (Fig. 2).

Fig. 2. The transcriptional regulatory network involved in drought, salinity, heat, and cold stress responses. In one of the ABA-independent pathways, the element DRE/CRT [(A/G)CCGACNT] and its binding proteins DREB1/CBF and DREB2 are, respectively, important cis- and trans-acting elements in stress-responsive gene expression (Fig. 2). Transcription factors belonging to the ERF/AP2 family, termed DREB1/CBF and DREB2, bind and transactivate DRE/CRT-regulated transcription. Overexpression of DREB1/CBF in transgenic plants increases tolerance to freezing, drought, and salt stresses, suggesting that the DREB1/CBF proteins function in the development of stress tolerance without further modification. However, overexpression of full-length DREB2 in transgenic plants does not improve stress tolerance, suggesting the involvement of posttranslational activation of the DREB2 protein. The DREB2 protein is unstable under normal growth conditions and is activated by osmotic stress through posttranslational modification in response to dehydration stress. One factor involved in the instability of the DREB2 protein has been isolated (see review by Qin et al., 2011).

ABA-regulated gene expression and its upstream signaling cascade In ABA-dependent pathways, ABRE is a major cis-acting element in ABA-responsive gene expression. Basic leucine zipper (bZIP) factors (AREB/ABF) function as major transcription factors after the accumulation of endogenous ABA (Fig. 2). The AREB/ABF transcription factors are activated through phosphorylation of SnRK2 PKase. Recently, a major ABA signaling pathway was elucidated that contains three components, a PYR/PYL/RCAR ABA receptor, PP2C PPase, and SnRK2 PKase (see reviews by Hirayama and Shinozaki, 2010; Umezawa et al., 2010) (Fig. 3). PYR1/RCAR1-type cytoplasmic ABA receptors resemble the bet-1v proteins at the amino acid sequence level. These proteins bind directly to clade A PP2C, such as ABI1 or HAB1, in an ABA-dependent manner and inhibit PP2C activity. Clade A PP2Cs interact with the ABA-activated SnRK2 protein kinases, and then PP2Cs dephosphorylate and inactivate SnRK2s. The SnRK2s phosphorylate and activate the AREB/ABF transcription factors (see reviews by Umezawa et al., 2010; Qin et al., 2011). Arabidopsis has three ABA-activated SnRK2 Class III protein kinases, namely, SRK2D, SRK2E, and SRK2I. Loss of all three SnRK2 genes (srk2dei) results in complete loss of the ABA response. We have carried out phosphoproteomic analyses to identify phosphorylated proteins produced in response to drought stress. About 5,000 phosphopeptides have been indentified in response to drought stress and ABA treatment. We are now using the SnRK2 triple mutant (srk2dei) to identify target phosphoproteins of SnRK2 PKase that are involved in ABA responses. Among them, we have identified AREB1 as a target of SnRK2 protein kinase. The SLAC1 channel involved in stomatal closure is also phosphorylated by SnRK2 (see review by Umezawa et al., 2010). Further target proteins have been identified using nontarget phosphoproteomic analyses (Fig. 3). Systematic analysis of SnRK2 target proteins will elucidate regulatory networks produced in response to ABA under drought stress conditions.

Plant Signal Transduction

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Fig. 3. The major ABA signaling cascade involved in gene expression and stomatal closure.

Metabolite profiling under drought stress conditions The endogenous ABA level is significantly increased in response to dehydration stress, which regulates physiological stress responses and gene expression. Drought-inducible NCED3 is an important gene in the dehydration-inducible biosynthesis of ABA. Integrated analysis of the metabolome and transcriptome of the dehydration stress response using GC-TOF/MS, CE/MS, and DNA microarray was carried out with an Arabidopsis knockout mutant of the NCED3 gene and the wild-type plant (see review by Urano et al., 2010). Metabolite profiling revealed that accumulation of various amino acids and sugars, such as glucose and fructose, is regulated by an increased ABA content during dehydration. More than 60% of drought-accumulated metabolites are regulated by ABA (Fig. 4). Accumulation of BCAAs (branch-chain amino acids: valine, leucine, and isoleucine), saccharopine, proline, and agmatine is correlated with the dehydration-inducible expression of their biosynthetic key genes BCAT2, LKR/SDH, P5CS1, and ADC2, respectively. These metabolites and genes are regulated by ABA. In contrast, droughtaccumulated raffinose and galactinol are not regulated by ABA, but through the DREB2 pathway in the drought stress response. These results reveal the important role of ABA-dependent regulation in dehydration stress metabolic changes (Fig. 4).

Fig. 4. Metabolites accumulated in response to drought stress: the ABA-dependent regulatory network.

Development of drought-tolerant crops using transgenic technology Application of drought-inducible genes is important for molecular breeding of drought-tolerant crops based on transgenic technology (see reviews by Umezawa et al., 2006; Hirayama and Shinozaki, 2010). Many genes have been tested for the improvement of drought tolerance using transgenic technology. We have succeeded in improving drought tolerance using the stress-inducible genes that we discovered and that function as transcription factors, for example, DREB and AREB proteins, not only in Arabidopsis but also in rice (see review by Umezawa et al., 2006). Since 2002, we have collaborated with CIMMYT (International Maize and Wheat Improvement Center) in Mexico to

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test these genes in transgenic wheat. Transgenic wheat plants that overexpress the rd29A promoter::DREB1 construct showed significantly improved drought tolerance (Pellegrineschi et al., 2004). In 2007, the Ministry of Agriculture, Fisheries and Forestry (MAFF) of Japan funded our project for the application of drought-inducible genes in breeding drought-tolerant rice and wheat, and their evaluation in test fields of a dry area. This project is known as the “The DREB project” for international collaboration with CIMMYT, IRRI (International Rice Research Institute), and CIAT (International Center for Tropical Agriculture). The JIRCAS and RIKEN groups have provided vector constructs with different combinations of genes and promoters for the transformations. Researchers at the IRRI, CIMMYT, and CIAT have used these to transform rice and wheat, and analyzed the plant stress tolerance in greenhouses, screen-houses, and finally in test fields. They found drought tolerance of transgenic rice and wheat in the greenhouse, and are now testing T 2 and T 3 transgenic plants in the test fields in a dry area. Some of the transgenic rice plants have shown tolerance to drought stress in field trials. In 2010, another project for the development of drought-tolerant transgenic soybean started in collaboration with Embrapa in Brazil, which is supported by JST (Japan Science and Technology Agency) and JICA (Japan International Cooperation Agency). Transgenic soybean lines with the rd29A promoter::DREB1A were selected to test for stress tolerance in greenhouses and test fields (Polizel et al., 2011). The hope is that some of the Arabidopsis and soybean genes will contribute to molecular breeding of drought stress tolerance in the future (Fig. 5).

Fig. 5. Application of basic knowledge obtained with model plants such as Arabidopsis and rice to other commercial crops. Comparative genomics is important for the discovery of candidate genes involved in stress responses and tolerance.

Conclusions Transcriptional regulation is a major molecular process essential to drought stress responses and tolerance. Many drought-inducible genes are involved in stress tolerance. Regulation of gene expression has been extensively studied and has revealed complex signal transduction cascades in drought stress responses. Transcriptome analyses have provided many stress-responsive genes. Recently, proteome and metabolome analyses have been extensively developed using high-quality mass spectrometry and related technological developments. Integration of the transcriptome and metabolome has established important metabolic networks in the responses to stresses, revealing important genes involved in stress-induced metabolic changes. Phosphoproteomics analysis has provided information on posttranslational regulation in stress signaling cascades. Gene discovery using ‘omics’ technology, together with comparative genomics, will be important for applications to edible crops and trees based on functional genomics knowledge from model plants.

References Hirayama T, Shinozaki K (2010) Research on plant abiotic stress responses in the post-genome era: past, present and future. Plant J., 61, 1041–1052 Pellegrineschi A, Reynolds M, Pacheco M, Brito RM, Almeraya R, Yamaguchi-Shinozaki K, Hosington D (2004) Stress-induced expression in wheat of the Arabidopsis thaliana DREB1A gene delays water stress symptoms under greenhouse conditions. Genome, 47, 493–500 Polizel AM, Medri ME, Nakashima K, Yamanaka N, Farias JR, de Oliveira MC, Marin SR, Abdelnoor RV, Marcelino-Guimarães FC, Fuganti R, Rodrigues FA, Stolf-Moreira R, Beneventi MA, Rolla AA, Neumaier N, Yamaguchi-Shinozaki K, Carvalho JF, Nepomuceno AL (2011) Molecular, anatomical and physiological properties of a genetically modified soybean line transformed with rd29A:AtDREB1A for the improvement of drought tolerance. Genet Mol. Res., 10 (on line) Qin F, Shinozaki K, Yamaguchi-Shinozaki K (2011) Achievements and challenges in understanding plant abiotic stress responses and tolerance. Plant Cell Physiol., 52,1569–1582 Shinozaki K, Yamaguchi-Shinozaki K (2007) Gene networks involved in drought stress response and tolerance. J. Exp. Bot., 58, 221–227 Umezawa T, Fujita M, Fujita Y, Yamaguchi-Shinozaki K, Shinozaki K (2006) Engineering drought tolerance in plants: discovering and tailoring genes to unlock the future. Curr. Opin. Biotechnol., 17, 113–122


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Umezawa T, Nakashima K, Miyakawa T, Kuromori T, Tanokura M, Shinozakai K, Yamaguchi-Shinozaki K (2010) Molecular basis of the core regulatory network in ABA responses: sensing, signaling and transport. Plant Cell Physiol., 51, 1821–1839 Urano K, Kurihara Y, Seki M, Shinozaki K (2010) Omics analyses of regulatory networks in plant abiotic stress responses. Curr. Opin. Plant Biol., 13, 132–138 Yamaguchi-Shinozaki K, Shinozaki K (2006) Transcriptional regulatory networks in cellular responses and tolerance to dehydration and cold stresses. Ann. Rev. Plant Biol., 57, 781–803

Update and Challenges on Proteomic Study of Plant Signal Transduction Zhi-Yong WANG1*, Wen-Qiang TANG2 1

Carnegie Institution for Science, Stanford, CA 94305, USA Institute of Molecular Cell Biology, College of Life Science, Hebei Normal University, Shijiazhuang, Hebei, 050016, CHINA *Corresponding author: [email protected] 2

Abstract Signal transduction is the molecular process of cellular regulation that allows a cell to respond to signals from neighbour cells or from the environment. It is a fundamental mechanism underlying virtually all developmental and physiological processes. Signal transduction involves protein-protein interaction and protein posttranslational modifications, which relay the signal from the receptor protein to downstream proteins that change gene expression or enzyme activities, leading to cellular responses. In principle, proteomics should be the best approach for studying signal transduction, however, in reality proteomic study of signal transduction is challenging and only limited success has been achieved. This is because the proteins involved in signal transduction are usually of low abundance. Protein fractionation and enrichment of target proteins are critical for successful proteomic study of signal transduction. We present examples of successful identification of components of specific signal transduction pathways using quantitative proteomic analysis of plasma membrane (PM) fractionations by 2-dimensional difference gel electrophoresis (2-D DIGE) and affinity purification of interacting proteins.

Introduction Signal transduction pathways provide the control circuits for cellular regulation. Signal transduction is particularly important for plants, because plants are sessile and rely on signal transduction pathways to regulate gene expression and to adapt to the changing environment. Signal transduction is the key molecular mechanism for nearly all developmental and physiological processes, including cell differentiation and morphogenesis, hormone responses, intercellular responses to biotic and abiotic stresses, and adaptation to the environment. Signal transduction involves protein-protein interactions and posttranslational modifications (PTMs) that change upon signal perception by a receptor protein. For example, an extracellular signal can be perceived by a specific receptor kinase, and the receptor kinase transduces the signal by initiating a chain of phosphorylation/dephosphorylation by kinases and phosphatase, which eventually regulates transcription factors and gene expression. Additional PTMs, such as ubiquitination, proteolysis, protein-protein interaction, and protein subcellular localization can be involved. RNA microarray can identify target genes controlled by a signal transduction pathway, but cannot reveal the components that perceive or transduce the signal. Quantitative analysis of signal-induced changes in protein abundance, modification, proteinprotein interactions, and subcellular localization, not only can identify the protein components of signal transduction pathways but also is essential for understanding the dynamics and molecular mechanisms of signal transduction. In addition, affinity purification of protein complexes containing a known signalling protein is another powerful approach to identification of new signalling proteins. Therefore, proteomics, the analysis of proteins at large scale, is particularly powerful for studying signal transduction. However, it is important to consider the low abundance nature of signalling proteins and to make best use of available knowledge about the pathway when choosing the proteomic methods and designing the experiments. Two-dimensional gel electrophoresis (2-DE), which separates proteins by charge using iso-electric focusing and then by size using SDS PAGE (O'Farrell, 1975), has been a powerful technique for proteomic analysis. In traditional 2-DE, each protein sample is analyzed in a separate gel, and quantitative comparison between samples in different gels is challenging and often unreliable due to gel-to-gel variation. A major improvement to 2-DE, called twodimensional difference gel electrophoresis (2-D DIGE) (Unlu et al., 1997; Tonge et al., 2001), allowed separation of multiple samples in the same gel and greatly improved quantitative comparison in 2-DE. In 2-D DIGE, two or three proteins samples are covalently labelled with molecular weight- and charge-matched fluorescence CyDyes (Cy2, Cy3, and Cy5; GE Healthcare), and then mixed together and analyzed in the same 2-DE gel. Each sample image is acquired based on the distinct emission wavelength of each fluorescent CyDye fluor. Thus identical image maps of samples to be compared can be obtained from the same gel, which significantly improves the reproducibility and accuracy of quantification. The intense fluorescence signals of the Cy Dyes also improve the detection sensitivity. 2D DIGE allows accurate comparison of spot signal intensities between samples based on the fluorescence images that have perfect matching patterns (Unlu et al., 1997; Tonge et al., 2001; Lilley and Dupree, 2006). While 2-DE and 2-D DIGE continue to be workhorse in proteomics, gel-free proteomics based on liquid chromatography followed by tandem mass spectrometry (LC-MS/MS) has gained tremendous popularity in the last decade. As new mass spectrometers are developed with more and more power and easier to maintain and use, LCMS/MS has become mainstream of proteomics in recent years. Gel-free proteomic methods analyze mixtures of


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peptides after tryptic digestion using multidimensional liquid chromatography followed by mass spectrometry. Quantitation is often achieved using one of the isotopic or isobaric labeling methods, including metabolic isotope labeling, in vitro labeling with isotope-coded affinity tag (ICAT) (Aebersold and Mann, 2003; Hansen et al., 2003) (Bindschedler et al., 2008), and the recently developed isobaric tags for relative and absolute quantitation (iTRAQ) (Ross et al., 2004). These methods have been widely used in recent years. For example, combining the differential profiling strength of the iTRAQ reagents with high sequence coverage provided by multidimensional liquid chromatography and tandem mass spectrometry (MS/MS), large numbers of novel proteins (>1,000), including those of low abundance, have been both identified and compared quantitatively among four different regions of postsynaptic density dissected from mouse brain (hippocampus, cerebellum, midbrain, and cortex) (Trinidad et al., 2006; Trinidad et al., 2008). Furthermore, label-free methods have recently been developed. Although gel-free approaches have become a popular choice for proteomic studies, gel-based and gel-free methods are highly complementary and neither method alone achieve complete coverage of a complex eukaryotic proteome. In particular, 2-D DIGE has many advantages for studying signal transduction.

Comparison between 2-D DIGE and gel-free approaches for quantitative proteomics Various proteomic methods have been developed for quantitative analysis of proteomic changes, and these methods belong to one of two groups based on whether protein or digested peptides are quantified. Gel-based approaches, namely 2-DE or 2-D DIGE, analyze intact proteins from biological samples; upon quantitative comparison, protein spots of interest are then excised from the gel and analyzed by mass spectrometry to determine the protein identity and possible presence of PTMs. In gel-free approaches, proteins are digested into peptides by tripsin or other site-specific proteases, and the mixture of peptides are then separated by online or offling liquid chromatography followed by mass spectrometry analysis, usually using LC-MS/MS. 2-D DIGE and LC-MS/MS each approach has its own advantages and limitations. To make effective use of either approach, it is important to keep in mind the unique strength and limitations of the methods. Which method is more powerful and analyzes more protiens? The main argument against gel-based approaches is that 2-DE cannot detect all proteins, because hydrophobic proteins and proteins with extreme charge (pI) and size (100 kD) are not effectively resolved in 2-DE gels. In contrast, LC-MS/MS is not biased against any protein type or class. But this observation is often misinterpreted as 2-DE detects fewer proteins than LC-MS/MS, or even LC-MS/MS can detect all proteins in a biological sample but 2-DE only detect a portion of the proteome. In reality, with current state-of-art instrumentations, the overall coverages of the proteome achieved by 2-DE and LCMS/MS are similar. A typical LC-MS/MS run only detect peptides representing hundreds of proteins, whereas a typical 2-DE run using large gels (24x20 cm) separates about 2000 protein spots. Extensive LC-MS/MS runs have achieved identificaiton of peptides of over 10,000 proteins, whereas high-resolution 2-DE using narrow pH ranges or large gels also can separate over 10,000 protein spots (Zabel and Klose, 2009). 2-D DIGE has several advantages compared to LC-MS/MS. First of all, by analyzing intact proteins, the complexity of sample to be quantified is reduced by at least an order of magnitude compared to the tryptic peptides. Secondly, 2-D DIGE is powerful in detecting changes in posttranslational modifications that alter the charge (e.g. phosphorylation) or size (e.g. partial proteolysis) of a protein. Modification forms that have different charge or size are resolved into separate spots in 2-DE. For example, phosphorylation increases negative charege of a protein and shift the protein spot to the acidic side along IEF dimension. Protein modification is common throughout the proteome, and it has been estimated that on average each protein is represented by about three protein spots in 2-DE (Klose et al., 2002). It is often argued as a weakness that coverage of the genome is smaller than the number of protein spots detected in 2-DE. However, different modification forms of the same protein often have different activities and functions, and separate quantitation of each modification form provides critical information for understanding the regulation mechanisms of the protein funciton and for studying signal transduction. In LC-MS/MS approaches, only a portion of the peptides of a protein is detected, and these peptides usually represent the sum of all modification forms of a protein; a change in posttranslational modification is only detected when the modified peptide is quantified. As such, phosphorylation of a protein at any one amino acid residue would cause a spot shift in 2-D DIGE, but will only be detected by LC-MS/MS if the peptide containing the phosphorylation is detected. Considering the partial peptide coverage of each protein in LC-MS/MS, one cannot conclude that a protein is not differentially phosphorylated based on negative data in LC-MS/MS, whereas lack of spot shift in 2-DE is a good indication of the absence of differential phosphorylation. Thus, the ability of 2-DE to resolve modification forms of protein make it a powerful approach for studying signal transduction. 2-DE also has its own limitations. First, certain types of proteins cannot be resolved in 2-DE. These include hydrophobic proteins, extremely acidic or basic proteins outside the pH range of IEF, or very small or large proteins with molecular weight out of the separation range of the SDS-PAGE gel (Chevallet et al., 1998; Santoni et al., 2000; Luche et al., 2003). For 2-D DIGE, fluorescence CyDyes are labelled on lysine (minimum labelling method) or cystine (saturation labelling), and therefore proteins lacking these amino acids would not be detected in 2-D DIGE (GE Healthcare). Another major limitation of 2-DE is that proteins of low-abundance often cannot be detected. This can be due to two possible reasons: either the staining/labeling signal is below detection sensitivity, or the signal is covered by more abundant overlapping protein spots. When using sensivity staining/detection methods, such as staining by silver or fluorescent dyes (e.g. Deep Purple) or labelling by CyDye in 2-D DIGE, the limitating factor is

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often insurficient spatial resolution that causes overlap between spots. Spot overlap not only masks low-abundance proteins, but also leads to errors in quantitation and protein identification because the signal and peptides from a spot may represent multiple proteins. Spot overlap can be reduced by using large gels with narrow pH ranges and by sample pre-fractionation, but would be exacerbated by increased amount of protein loaded in the gel. Despite the limitations, 2-D DIGE has been successfully used in studying signal transduction in plants. Using prefractionation before 2-D DIGE, we have detected BR-induced phosphorylation of the BAK1 and BSKs in the PM and dephosphorylation of BZR1 transcription factor in phosphoprotein fractions (Tang et al., 2008a; Tang et al., 2008b; Tang et al., 2010). In contrast, iTRAQ studies of a similar signaling pathway activated by a pathogen signal identified no previously-known component of that signaling pathway (Nuhse et al., 2007).

Proteomic study of brassinosteroid signal transduction using pre-fractionation followed by 2-D DIGE Brassinosteroids (BRs) are a class of steroidal hormone that promotes growth and regulates a wide range of developmental processes in plants. BR-deficient or insensitive mutants in both Arabidopsis and rice show multiple growth defects, including dwarfism, photomorphogenesis in the dark, and male sterility(Clouse, 2002; Kim and Wang, 2010). A recent study showed that in maize, BR deficiency causes a switch from male to female flowers (Hartwig et al., 2011). Altering BR synthesis or signaling has been shown to increase yield in rice (Sakamoto et al., 2006; Wu et al., 2008). A decade ago, molecular genetic studies identified the BRI1 receptor kinase and the BZR1 transcription factor as key components for brassinosteroid signal transduction, which suggested that downstream signal transduction involves protein phosphorylation (Wang et al., 2001; He et al., 2002). We therefore initiated a proteomic project aimed at identifying BR signaling proteins based on BR-induced phosphorylation changes, using 2-D DIGE (Deng et al., 2007; Tang et al., 2008a; Tang et al., 2008b). We initially analyzed total protein samples of BR-treated and mocktreated Arabidopsis seedlings using 2-D DIGE. No obvious changes were detected after three hours of BR treatment (Deng et al., 2007), althrough immunoblotting experiments showed BRI1 phosphorylation and BZR1 dephosphorylation within ten minutes of BR treatment (Tang et al., 2008a). With longer time of BR treatment up to 24 hrs, large numbers of responsive proteins were identified; however, these are mostly abundant enzymes and structural proteins that are regulated at the transcriptional level and mediate downstream cellular responses rather than signal transduction. Considering that the 2000 proteins detected in each 2-D DIGE gel represent the most abundant ~10% of the cellular proteins, it was not surprising that signaling proteins were not detected. We then tried to enrich protein fractions that most likely contain BR signaling proteins. First, phosphoproteins were enriched using immobilized metal affinity chromatography (IMAC) (Tang et al., 2008a). The method was optimized based on enrichment of phospho-BZR1 detected by immunoblotting. Upon 2-D DIGE comparison of phosphoprotein fractions between BR-treated and mock-treated samples, BR-induced BZR1 dephosphorylation was detected as two rows of green and red spots, which match the locations of BZR1 detected by immunoblotting. LCMS/MS analysis of several spots not only confirmed the presence of BZR1 in these spots but also identified two in vivo phosphorylation sites of BZR1 (Tang et al., 2008a). Considering that a major missing link of the BR signaling pathways was the substrate of the plasma membranelocalized BRI1 receptor kinase, we further performed 2-D DIGE analysis of plasma membrane proteins prepared using the two-phase partitioning method (Tang et al., 2008a). A great deal of variation between sample preparations were noticed in initial experiments. Even two samples prepared side-by-side sometimes showed variation that are not reproducible. Mass spectrometry analysis indicated that many of the variable spots contain chloroplast proteins, suggesting that variable amount of chloroplast contamination occured (Fig. 1A). By carefully controlling all experimental details, 2-D DIGE results with minimum variation were obtained; and these images show distinct changes of a small number of proteins (Fig. 1B, and (Tang et al., 2008b). Mass spectrometry analysis of these spots identified BAK1 and two new kinases we named BR-signaling kinase 1 and 2 (BSK1 and BSK2) (Tang et al., 2008a; Tang et al., 2008b). BAK1 was shown to be phosphorylated upon BR activation of BRI1 and functions as a coreceptor of BRI1. Our genetic and biochemical analysis further demonstrated that BSK1 and BSK2 are substrates of BRI1 kinase (Tang et al., 2008b), and they transduce the BR signal to downstream cytoplasmic component, the BSU1 phosphatase (Kim et al., 2009). Identification of BSKs filled a major gap in the BR signaling pathway (Fig. 2) (Kim and Wang, 2010). Fig. 1. Example preparation is critical for 2-D DIGE analysis of proteomic responses in subcellular fractions. Arabidopsis seedlings of the BR-deficient mutant det2-1 were grown in liquid culture and treated with 100 nM brassinolide (the most active form of BR) for 2 h. Plasma membrane proteins were prepared using the two-phase partitioning method. BR treated samples were labelled with Cy5 (red) and mock-treated controls were labelled with Cy3 (green). A and B show two biological repeat experiments, with different qualities. Panel A shows an example of excessive variation, and panel B shows a good reproducible preparation that reveals only specific BR-induced changes.


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Identification of BR-signaling proteins using tandem affinity purification Signal transduction requires protein-protein interaction, which facilitates protein modification or directly changes protein activity. To identify additional BR-signaling proteins, we performed affinity purification of the BZR1 complex (Tang et al., 2011). We transformed Arabidopsis with a construct that expresses a BZR1 fusion protein with both Myc and 6xHis tags, which allow affinity purification using anti-Myc antibody and nickel -agarose column, respectively. A transgenic line expressing a BZR1 fusion with green fluorescence protein (BZR1-GFP) was used as negative control. Tissue extracts were purified first using Ni-agrose beads, and the elute was further immunoprecipitated using anti-Myc-agarose beads. The final elute was separated in a SDS-PAGE gel and gel bands were anaylzed by in-gel digestion followed by LC-MS/MS. This experiment identified several isoforms of PP2A subunits as BZR1-interacting proteins (Tang et al., 2011), in addition to BZR1 itself and two known BZR1interacting proteins, i.e. members of the GSK3-like kinases and 14-3-3 proteins (He et al., 2002; Gampala et al., 2007). Further biochemical analysis confirmed that BZR1 directly interacts with several isoforms of the PP2A B’ subunit, which is known to mediate substrate selection. The PEST domain of BZR1 directly interacts with PP2A B’ and mutations in this domain consistently affect interaction with PP2A, BZR1 phosphorylation and BR-dependent growth. Therefore, our tandem affinity purification of BZR1 identified PP2A as another key component of the BR signaling pathway, mediating BZR1 dephosphorylation and activation (Tang et al., 2011) (Fig. 2).

Fig. 2. The BR signal transduction pathway. BSKs and PP2A were identified by proteomics, whereas other components were identified by molecular genetics. In addition, BR induced phosphorylation of BAK1 and dephosphorylation of BZR1 were detected in 2-D DIGE of PM and phospho-protein fractions, whereas PP2A, BIN2 homologs and 14-3-3 proteins were detected in purified BZR1 complex.

Conclusion While most proteomic studies have identified abundant response proteins that represent downstream targets or indirect effects of signal transduction, we have successfully used 2-D DIGE proteomics to identify several signaling components of the BR pathway (Fig. 2). Our proteomic studies made critical contributions to the complete BR signaling pathway, which is one of the best understood signaling pathways in plants. Our successes support the general believe that gel-free and 2-DE-based approaches for quantitative proteomics are highly complementary, with different limitations and advantages. Our study further demonstrate that pre-fractionation is essential for detecting signaling proteins using 2-D DIGE proteomics. Our experience emphasize the importance of good sample preparation and quality control of protein samples, supporting the widely-held notion of “garbage in, garbage out” in proteomic studies. In addition to 2-D DIGE quantitative proteomics, which requires no prior knowledge of the signaling pathway, affinity purification of known components of the signaling pathway is another powerful approach to identification of new components of signal transduction pathways. In conclusion, when combined with biochemical fractionation and purification, proteomics is powerful for studying plant signal transduction.

References Aebersold R, Mann, M (2003) Mass spectrometry-based proteomics. Nature, 422, 198-207 Bindschedler LV, Palmblad M, Cramer R (2008) Hydroponic isotope labelling of entire plants (HILEP) for quantitative plant proteomics; an oxidative stress case study. Phytochemistry, 69, 1962-1972 Chevallet M, Santoni V, Poinas A, Rouquie D, Fuchs A, Kieffer S, Rossignol M, Lunardi J, Garin J, Rabilloud T (1998) New zwitterionic detergents improve the analysis of membrane proteins by two-dimensional electrophoresis. Electrophoresis, 19, 1901-1909 Clouse SD (2002) Arabidopsis mutants reveal multiple roles for sterols in plant development. Plant Cell, 14, 19952000

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Deng Z, Zhang X, Tang W, Oses-Prieto JA, Suzuki N, Gendron JM, Chen H, Guan S, Chalkley RJ, Peterman TK, Burlingame AL, Wang ZY (2007) A proteomics study of brassinosteroid response in Arabidopsis. Mol. Cell. Proteomics, 6, 2058-2071 Gampala SS, Kim TW, He JX, Tang W, Deng Z, Bai MY, Guan S, Lalonde S, Sun Y, Gendron JM, Chen H, Shibagaki N, Ferl RJ, Ehrhardt D, Chong K, Burlingame AL, Wang ZY (2007) An essential role for 14-3-3 proteins in brassinosteroid signal transduction in Arabidopsis. Dev. Cell, 13, 177-189 Hansen KC, Schmitt-Ulms G, Chalkley RJ, Hirsch J, Baldwin MA, Burlingame AL (2003) Mass spectrometric analysis of protein mixtures at low levels using cleavable 13C-isotope-coded affinity tag and multidimensional chromatography. Mol. Cell. Proteomics, 2, 299-314 Hartwig T, Chuck GS, Fujioka S, Klempien A, Weizbauer R, Potluri DP, Choe S, Johal GS, Schulz B (2011) Brassinosteroid control of sex determination in maize. Proc. Natl. Acad. Sci., USA, 108, 19814-19819 He JX, Gendron JM, Yang Y, Li J, Wang ZY (2002) The GSK3-like kinase BIN2 phosphorylates and destabilizes BZR1, a positive regulator of the brassinosteroid signaling pathway in Arabidopsis. Proc. Natl. Acad. Sci. USA, 99, 10185-10190 Kim T-W, Guan S, Sun Y, Deng Z, Tang W, Shang J, Sun Y, Burlingame AL, Wang Z-Y (2009) Brassinosteroid signal transduction from cell-surface receptor kinases to nuclear transcription factors. Nat. Cell Bio., 11, 12541260 Kim TW, Wang ZY (2010) Brassinosteroid Signal Transduction from Receptor Kinases to Transcription Factors. Annu. Rev. Plant Biol., 61, 681-704 Klose J, Nock C, Herrmann M, Stuhler K, Marcus K, Bluggel M, Krause E, Schalkwyk LC, Rastan S, Brown SD, Bussow K, Himmelbauer H, Lehrach H (2002) Genetic analysis of the mouse brain proteome. Nat. Genet., 30, 385-393 Lilley KS, Dupree P (2006) Methods of quantitative proteomics and their application to plant organelle characterization. J. Exp. Bot., 57, 1493-1499 Luche S, Santoni V, Rabilloud T (2003) Evaluation of nonionic and zwitterionic detergents as membrane protein solubilizers in two-dimensional electrophoresis. Proteomics, 3, 249-253 Nuhse TS, Bottrill AR, Jones AM, Peck SC (2007) Quantitative phosphoproteomic analysis of plasma membrane proteins reveals regulatory mechanisms of plant innate immune responses. Plant J., 51, 931-940 O'Farrell PH (1975) High resolution two-dimensional electrophoresis of proteins. J. Biol. Chem., 250, 4007-4021 Ross PL, Huang YN, Marchese JN, Williamson B, Parker K, Hattan S, Khainovski N, Pillai S, Dey S, Daniels S, Purkayastha S, Juhasz, P, Martin S, Bartlet-Jones M, He F, Jacobson A, Pappin DJ (2004) Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell. Proteomics, 3, 1154-1169 Sakamoto T, Morinaka Y, Ohnishi T, Sunohara H, Fujioka S, Ueguchi-Tanaka M, Mizutani M, Sakata K, Takatsuto S, Yoshida S, Tanaka H, Kitano H, Matsuoka M (2006) Erect leaves caused by brassinosteroid deficiency increase biomass production and grain yield in rice. Nat. Biotechnol., 24, 105-109 Santoni V, Kieffer S, Desclaux D, Masson F, Rabilloud T (2000) Membrane proteomics: use of additive main effects with multiplicative interaction model to classify plasma membrane proteins according to their solubility and electrophoretic properties. Electrophoresis, 21, 3329-3344 Tang W, Deng Z, Wang ZY (2010) Proteomics shed light on the brassinosteroid signaling mechanisms. Curr. Opin. Plant Biol., 23, 27-33 Tang W, Deng Z, Oses-Prieto JA, Suzuki N, Zhu SW, Zhang X, Burlingame AL, Wang Z-Y (2008a) Proteomic studies of brassinosteroid signal transduction using prefractionation and Two-dimensional DIGE Mol. Cell. Proteomics, 7, 728-738 Tang W, Kim TW, Oses-Prieto JA, Sun Y, Deng, Z, Zhu S, Wang R, Burlingame AL, Wang ZY (2008b) BSKs mediate signal transduction from the receptor kinase BRI1 in Arabidopsis. Science, 321, 557-560 Tang W, Yuan M, Wang R, Yang Y, Wang C, Oses-Prieto JA, Kim T-W, Zhou H-W, Deng Z, Gampala SS, Gendron JM, Jonassen EM, Lillo C, De Long A, Burlingame AL, Sun Y, Wang Z-Y (2011) PP2A activates brassinosteroid-responsive gene expression and plant growth by dephosphorylating BZR1. Nat. Cell Bio., 13, 124-131 Tonge R, Shaw J, Middleton B, Rowlinson R, Rayner S, Young J, Pognan F, Hawkins E, Currie I, Davison M (2001) Validation and development of fluorescence two-dimensional differential gel electrophoresis proteomics technology. Proteomics, 1, 377-396 Trinidad JC, Specht CG, Thalhammer A, Schoepfer R, Burlingame AL (2006) Comprehensive identification of phosphorylation sites in postsynaptic density preparations. Mol. Cell. Proteomics, 5, 914-922 Trinidad JC, Thalhammer A, Specht CG, Lynn AJ, Baker PR, Schoepfer R, Burlingame AL (2008) Quantitative analysis of synaptic phosphorylation and protein expression. Mol. Cell. Proteomics, 7, 684-696 Unlu M, Morgan ME, Minden JS (1997) Difference gel electrophoresis: a single gel method for detecting changes in protein extracts. Electrophoresis, 18, 2071-2077 Wang ZY, Seto H, Fujioka S, Yoshida S, Chory J (2001) BRI1 is a critical component of a plasma-membrane receptor for plant steroids Nature, 410 380-383 Wu CY, Trieu A, Radhakrishnan P, Kwok SF, Harris S, Zhang K, Wang J, Wan J, Zhai H, Takatsuto S, Matsumoto S, Fujioka S, Feldmann KA, Pennell RI (2008) Brassinosteroids Regulate Grain Filling in Rice. Plant Cell, 20, 2130-2145 Zabel C, Klose J (2009) High-resolution large-gel 2DE. Methods Mol. Biol., 519, 311-338

Proteomics Approach to Study Metabolic Regulation Mediated by Ubiquitin-Proteasome System in Arabidopsis Shigetaka YASUDA, Shugo MAEKAWA, Takeo SATO, Junji YAMAGUCHI* Faculty of Science and Graduate School of Life Science, Hokkaido University, Sapporo 060-0810, JAPAN *Corresponding author: [email protected]

Abstract Carbon and nitrogen availability is one of the most important factors to regulate plant development. To utilize limited resource of carbon and nitrogen efficiently, plants enable to sense and respond to balance of carbon (C) and nitrogen (N) metabolites, called C/N response. To clarify the mechanisms for C/N sensing and signaling, we screened a large collection of FOX (Full-length cDNA OvereXpressor) transgenic Arabidopsis plants under the specific C/N stress condition. We identified the FOX plant showing suppressed sensitivity to C/N conditions, named cni1-D (carbon/nitrogen insensitive 1-Dominant). The CNI1 gene encoded a novel ubiquitin ligase CNI1/ATL31 and the protein was confirmed to have ubiquitin ligase activity in vitro. The knock-out mutant of this gene resulted in hypersensitivity to C/N conditions and furthermore removal of this ubiquitin ligase activity from the overexpressed protein resulted in the loss of the cni1-D phenotype. All these results indicated that the CNI1/ATL31 has essential role to regulate plant C/N response via the ubiquitin-proteasome system. We applied FLAG tag affinity purification and MS analysis to identify proteins targeted by ATL31, and thus likely involved in the phase transition checkpoint. This analysis revealed that 14-3-3 proteins associate with ATL31, and one of these, 14-3-3χ, was selected for detailed characterization. The interaction between ATL31 and 14-3-3χ was confirmed by yeast two-hybrid and co-immunoprecipitation analyses. In vitro assays showed that 14-3-3χ can act as a target of ATL31, which catalyzed ubiquitination of the recombinant protein. Degradation of 14-3-3χ in vivo was also shown to be correlated with ATL31 activity, and to occur in a proteasome-dependent manner. Furthermore, a reduction in 14-3-3 protein accumulation was induced by a typical shift to high C/N conditions in Arabidopsis seedlings, which was dependent on the presence of ATL31 and ATL6. These results indicated that ATL31 functions to target and ubiquitinate 14-3-3 proteins for degradation via the ubiquitin-proteasome system during the response to cellular C/N status.

Introduction The ubiquitin-proteasome system (UPS) plays a crucial role in the selective removal of short-lived target proteins, enabling fine-tuning of post-translation levels of the targets (Hershko and Ciechanover, 1998). The UPS controls multiple phenomena in plant growth and development by regulating the stability of target proteins that govern specific cellular events including photomorphogenesis, cell cycle, senescence, defense response and phytohormone response (Smalle and Vierstra, 2004). To achieve precise degradation of target proteins, ubiquitin ligases have an essential role in this system. The ubiquitin ligase (E3) interacts with the target protein and adds ubiquitin molecules derived from the ubiquitin activating enzyme (E1) and the ubiquitin conjugating enzyme (E2). The polyubiquitinated substrate is then degraded by a multi-subunit protease complex, the proteasome. Ubiquitin ligase is the key enzyme to specify the target protein for degradation via UPS. The Arabidopsis genome contains more than 1,200 genes encoding ubiquitin ligases. Some of the essential signaling factors for phytohormone response were identified as the target of each ubiquitin ligase and showed an impressive mechanism of phytohormone signaling. However, the physiological function of most ubiquitin ligase is still unknown. Our recent studies have revealed that UPS modulates plant development in response to carbon/nitrogen (C/N) balance conditions (Sato et al., 2009; Sato et al., 2011). Here we focus on proteomics approach to study on regulatory mechanism of carbon and nitrogen signaling via UPS.

Ubiquitin ligase ATL31 and ATL6 regulate plant C/N response Plant growth and development is controlled by the concerted actions of signaling pathways that are triggered by various environmental conditions and developmental cues. Nutrient availability, in particularly that of carbon and nitrogen, is one of the most important factors for regulating plant metabolism and development. In addition to independent utilization, the ratio of carbohydrate to nitrogen metabolites in the cell is also important for regulation of plant growth and is referred to as the ‘‘C/N balance’’ (Coruzzi and Zhou, 2001; Martin et al., 2002). However, little is known about the molecules involved in regulation of the C/N response and checkpoint for post-germinative growth arrest in plants. To further clarify the mechanism of C/N response, we previously identified and characterized a novel C/N response mutant, cni1-D (carbon/nitrogen insensitive 1-D), which showed to survive in the medium containing

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excessive glucose under limited nitrogen conditions (300 mM glucose/0.1 mM nitrogen) (Sato et al., 2009). The CNI1 gene encodes a RING-H2 type ubiquitin ligase and has been previously annotated as a member of the ATL family, ATL31 of which function was not understood (Serrano et al., 2006). ATL family proteins contain a transmembrane-like hydrophobic region at the N-terminus, a basic amino acid rich region, a region with highly conserved amino acid sequences (GLD), a RING-H2 type zinc finger domain and a non-conserved C-terminal region (Salinas-Mondragon et al., 1999). There are 80 members of the ATL family in Arabidopsis, with ATL2 the best characterized and shown to be involved in defense responses. Further experiments revealed that the cni1-D mutant, which is caused by over-expression of the ATL31 gene, leads to a less-sensitive phenotype while loss-of the function mutant for the ATL31 gene shows a hypersensitive phenotype to C/N stress conditions. In addition, the ATL31 shares high sequence similarity with another ATL family member, ATL6, and the ATL6 loss-of function mutant also showed C/N hypersensitivity (Sato et al., 2009). The ATL31 protein was confirmed to contain ubiquitin ligase activity using an in vitro assay system. Moreover, removal of this ubiquitin ligase activity from the overexpressed protein resulted in loss of the less-sensitive phenotype, suggesting that both ATL31 and ATL6 regulate plant C/N response via ubiquitination and following proteasome-dependent degradation of specific target proteins (Sato et al., 2009).

Proteomics approarch identified 14-3-3 protein as a target of ATL31 and ATL6 We recently identified 14-3-3 protein as interactor of ATL31 with proteomics analysis and demonstrated the ATL31 has ubiquitination activity to the 14-3-3 (Sato et al., 2011). ATL6 was also confirmed to interact and ubiquitinate the 14-3-3 protein. To identify proteins targeted for ubiquitination by ATL31 during the C/N response, a proteomics analysis of proteins associated with ATL31 was performed (Fig. 1). Transgenic Arabidopsis cultured cells overexpressing FLAG-tagged ATL31 containing a point mutation in the RING domain (35S-ATL31C143S-FLAG) were first generated. As the mutated ATL31C143S protein did not display ubiquitination activity (Sato et al., 2009), it was predicted that target proteins would remain bound to ATL31 without ubiquitination and immediate degradation (Fig. 1). Immunoprecipitation with anti-FLAG M2 affinity gel and mass spectrometry analysis revealed several specific bands which contained several 14-3-3 (or GF14) proteins with a high MS score.

Fig. 1. Immunoprecipitation of ATL31C143S-FLAG associated proteins for MS analysis. Arabidopsis suspension culcured cells MM2d were transformed with a construct containing ATL31C143S-FLAG under control of the CaMV 35S promoter, and transgenic MM2d cells were harvested at 5-days after subculture by centrifugation. Cell lysate was then incubated with anti-FLAG M2 affinity gel (Sigma) for 4 h at 4°C. After incubation and wash treatment, FLAG associating proteins were eluted using 3xFLAG peptide. Eluted proteins were separated by SDS-PAGE and specific bands were excised following detection with Silver Stain. Peptides for LCMS/MS analysis were then prepared by in-gel digestion using sequencing grade modified trypsin, and LC-MS/MS analysis was performed using a LTQ-orbitrap XL-HTC-PAL system (Thermo Fisher Scientific). The MS/MS spectra were compared against TAIR8 (The Arabidopsis Information Resource) using the MASCOT server (version 2.2).

14-3-3χ protein interacts with the ATL31 C-terminal domain in yeast To confirm the interaction between 14-3-3 and ATL31, yeast two-hybrid analysis (Y2H) was first applied. Two different ATL31 constructs which were prepared containing either the mutated RING domain and C-terminal region (ATL3187-368C143S) or the C-terminal domain only (ATL31169-368) were demonstrated to interact with 14-3-3χ,

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consistent with the expected role for this region to specify target proteins for ubiquitination by ATL family members. Similar results were also obtained for another 14-3-3 protein, 14-3-3λ, indicating that ATL31 may interact with multiple members of the 14-3-3 family. ATL31 shares high sequence similarity and shows functional redundancy with another ATL family member, ATL6. The potential interaction between ATL6 and 14-3-3χ was therefore also examined by Y2H. Positive β-galactosidase activity suggested that ATL6 as well as ATL31 interacted with 14-3-3χ in yeast cells.

ATL31C143S interacts with 14-3-3χ in vivo The in vivo interaction between ATL31C143S and 14-3-3χ in plant cells was tested further by coimmunoprecipitation analysis. FLAG-tagged ATL31C143S (ATL31C143S-FLAG) and myc-tagged 14-3-3χ (Myc14-3-3χ) were transiently over-expressed in Arabidopsis cultured cell protoplasts, and crude extracts subject to immunoprecipitation using anti-FLAG M2 affinity gel. Western blotting analysis with an anti-myc anitbody demonstrated that Myc-14-3-3χ was successfully co-immunoprecipitated with ATL31C143S . This was supported by further investigation using an anti-14-3-3 antibody that showed multiple bands corresponding to native 14-3-3 proteins in the immunoprecipitate.

ATL31 showed ubiquitination activity against 14-3-3χ protein To establish whether 14-3-3χ is an actual target protein of ATL31, in vitro ubiquitination of 14-3-3χ was tested in the presence of the ATL31. The recombinant protein MBP-ATL31 (maltose binding protein fused to ATL31) was previously shown to have autoubiquitination activity in vitro (Sato et al., 2009). In the current assay, MBP-ATL31 and recombinant His-tagged 14-3-3χ (Trx-His-14-3-3χ) were incubated with the required ubiquitination reaction enzymes and reagents. Western blotting analysis with anti-His antibody revealed a size shift corresponding to TrxHis-14-3-3χ that was dependent on incubation time and had higher molecular weight than input protein. This shift was not observed when Trx-His-14-3-3χ was incubated with MBP alone, or when the reactions did not include E1, E2 or ubiquitin components. These results confirmed that ATL31 has ubiquitination activity against 14-3-3χ protein in vitro. Similar activity was also observed for MBP-ATL6, which showed ubiquitination activity against 14-3-3χ in this in vitro assay.

14-3-3χ was degraded via the ubiquitin-proteasome system dependent on ATL31 ubiquitin ligase activity in plants The stability of 14-3-3χ in plant cells was next examined using a proteasome degradation assay. Myc-tagged 143-3χ protein (Myc-14-3-3χ) was transiently expressed in tobacco leaves together with ATL31-FLAG or mutant ATL31C143-FLAG using Agroinfiltration. Correct expression of ATL31 and 14-3-3χ, and the interaction between both proteins, was first confirmed in this system by co-immunoprecipitation. Protein extracts from infiltrated tobacco leaves were then incubated with proteasome inhibitor MG132 or DMSO (negative control) and stability of Myc-14-33χ tested. In the absence of the MG132 inhibitor, protein levels of Myc-14-3-3χ coexpressed with ATL31C143SFLAG decreased approximately 30% compared with that for MG132 treatment, suggesting Myc-14-3-3χ was degraded in a proteasome-dependent manner. Morevoer, this reduction of Myc-14-3-3χ in the absence of MG132 inhibitor was enhanced when coexpressed with active ATL31-FLAG and decreased approximately 60%, suggesting that enhanced activity of ubiquitin ligase ATL31 promoted degradation of Myc-14-3-3χ by the ubiquitin-proteasome system. Tobacco contain a paralogous protein of Arabidopsis ATL31, and thus the decrease of Myc-14-3-3χ coexpressed with mutated ATL31C143S was likely due to a native ATL31-like protein activity in tobacco. MG132 treatment was next carried out on intact tobacco leaves overexpressing ATL31-FLAG and Myc-14-3-3χ prior to protein extraction. In addition to accumulation of Myc-14-3-3χ with expected molecular weight, heterogeneous bands shifted to a higher molecular weight were detected in MG132 treated leaves. Similar shifted bands were also detected by western blot analysis of immunoprecipitated Myc-14-3-3χ protein, suggesting that ATL31 directly promoted poly-ubiquitination and degradation of 14-3-3χ via the 26S proteasome in plants. The stability of another 14-3-3 protein, Myc-14-3-3λ, was also influenced by ATL31 in a proteasome-dependent manner.

14-3-3χ protein accumulation responded to glucose amount in Arabidopsis seedlings To establish whether regulation of 14-3-3χ is part of the C/N response, accumulation of 14-3-3χ protein was next evaluated in Arabidopsis seedlings growing in medium containing different glucose amounts (0-300 mM Glc.) under low nitrogen (0.3 mM N) conditions. It was previously demonstrated that Arabidopsis seedlings show C/Ndependent growth inhibition in this condition and atl31 knockout mutant shows hypersensitivity compared with wildtype plant (Sato et al., 2009). Transgenic plants over-expressing FLAG-14-3-3χ mRNA in wild-type plant (FG in WT) were grown under different glucose conditions, and accumulation of the FLAG-tagged 14-3-3χ protein was examined by western blotting using anti-FLAG and anti-14-3-3 antibodies. The anti-FLAG antibody detected only a single band corresponding to recombinant FLAG-14-3-3χ, whereas the anti-14-3-3 antibody detected the recombinant FLAG-14-3-3χ protein and multiple bands corresponding to native 14-3-3 proteins. Accumulation of FLAG-14-3-3χ was increased in Arabidopsis plants according to glucose amounts., showing greatest accumulation at 300 mM Glc. /

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0.3 mM N, 276% compared with 0 mM glucose condition, while the seedling under each conditions showed similar exression level of FLAG-14-3-3χ mRNA. Similar increase was also observed for two major native 14-3-3 protein bands, suggesting that other 14-3-3 proteins in addition to 14-3-3χ respond to increase of glucose amount in medium. Furthermore, we examined the stability of costitutively expressed FLAG-14-3-3χ protein in atl31atl6 double knockout mutant background (FG in dKO). In contrast to FG in WT transgenic plants, the FLAG-14-3-3χ protein was hyper accumulated (or more stable) without addition of glucose (0 mM glucose) in FG in dKO plant and did not show further accumulation in respond to glucose addition. In addition, we tested the effect of proteolysis inihibitor for proteasome (MG132) to the stability of FLAG-14-3-3χ protein. As a result, FLAG-14-3-3χ protein was partially stabilized and accumulated by MG132 treatment in the 0 mM glucose condition. Taken together, it was demonstrated that the stability of FLAG-14-3-3χ protein was regulated in response to glucose amount in Arabidopsis seedling via UPS mediated by ubiquitin ligase ATL31/ATL6.

C/N response mediated by ATL31 and 14-3-3 protein ATL31 is a RING-type ubiquitin ligase essential for regulation of the C/N response in Arabidopsis thaliana. This role for ATL31 suggests that plants respond to changes in C and N availability by regulating levels of specific target proteins though the ubiquitin-proteasome system (UPS). In the current study, a proteomics approach using MS analysis identified several 14-3-3 proteins that bound to ATL31. 14-3-3 proteins bind phosphorylated motifs and function in multiple developmental processes by regulating the activity of a wide variety of target protein (Ferl et al., 2002; Chevalier et al., 2009). One of these 14-3-3 proteins, 14-3-3χ, was examined in detail and confirmed to interact with ATL31 in both yeast and plant cells. In vitro ubiquitination assays with purified recombinant proteins further confirmed that ATL31 was able to bind and ubiquitinate 14-3-3χ directly. Consistent with this, in vivo accumulation of 14-3-3χ in tobacco cells was reduced in response to increased ATL31 activity and this was dependent on the UPS. Moreover, stability of costitutively expressed 14-3-3χ protein was reduced as the glucose amounts decreased in Arabidopsis seedlings of wild-type background while the hyper-accumulation of 14-3-3χ in atl31atl6 double mutant background. The reduction of 14-3-3χ in wild-type background seedling was inhibited by proteasome inhibitor MG132. Taken together, these results suggested that the ATL31 regulates 14-3-3χ stability by direct polyubiquitination and targeting to the UPS, and that this is likely dependent on C/N conditions in Arabidopsis seedlings (Fig. 2). In mammalian cells, the stability of 14-3-3 proteins is regulated during the cell cycle by a RINGtype ubiquitin ligase Efp (Urano et al., 2002). A recent proteomics analysis in Arabidopsis using an affinity column against ubiquitin protein also reported that some 14-3-3 proteins are ubiquitinated protein candidates (Igawa et al., 2009). Although it had been expected that 14-3-3 proteins are degraded via the UPS in plants, the ubiquitin ligase that catalysed this ubiquitination and specific 14-3-3 protein targets were unknown. To our knowledge, this is the first report to identify a ubiquitin ligase that regulates the stability of 14-3-3 proteins in plants. Analysis of plant extracts with an antibody that detects native 14-3-3 proteins showed several bands that coimmunoprecipitated with ATL31 (Fig. 1). Accumulation of these multiple protein bands also responded to C/N conditions in wild-type Arabidopsis seedlings, which was partially promoted by atl31 and atl31atl6 double mutant background. Although this antibody did not enable individual 14-3-3 proteins to be identified or rule out the small possibility that each band contained only modified 14-3-3χ products, multiple 14-3-3 proteins were detected in the original MS analysis. Moreover, ATL31 was also confirmed to promote degradation of another 14-3-3 protein, 14-33λ, in a proteasome-dependent manner in plant cells. These data indicate that ATL31 likely functions to regulate the accumulation of multiple 14-3-3 proteins in addition to 14-3-3χ during the C/N response in Arabidopsis. ATL31 shares strong sequence homology with ATL6 and it is likely their functions are partially redundant for regulation of the C/N response (Sato et al., 2009). Consistent with this, ATL6 was found to interact with and ubiquinate 14-3-3χ in the current study. It is important for further understanding the plant C/N response to confirm affinity of interaction between ATL31/ATL6 and each 14-3-3 proteins and specificity of the 14-3-3 regulating C/N response. On the other hands, the both of atl31atl6 loss-of function and MG132 treatment did not completely inhibit the 14-3-3 proteins, suggesting the possibility of other degradation mechanism for 14-3-3 proteins mediated by other ubiquitin ligase including other ATL family and other protein degradation system. The Arabidopsis 14-3-3 protein family contains at least 13 members that show high amino acid sequence similarity (Ferl et al., 2002; Chevalier et al., 2009), and 8 members were detected as interactors of ATL31 by our MS analysis while the functional specificity of each member has remained unclear. The 14-3-3 proteins bind phosphorylated motifs and function in multiple developmental processes by regulating the activity of a wide variety of target protein X (Fig. 2). In particular, 14-3-3 has been reported to regulate primary carbon and nitrogen metabolism by direct interaction with essential enzymes such as the plasma membrane H+-ATPase, nitrate reductase, sucrose phosphate synthase, ADP-glucose pyrophosphorylase, and glutamine synthetase (Chevalier et al., 2009). In addition to direct regulation of enzyme activity, binding with the 14-3-3 protein changes the cleavage of some of these enzymes in response to nutrient conditions (Cotelle et al., 2000) and regulates the sub-cellular localization of target proteins (Ishida et al., 2004; Purwestri et al., 2009). On the other hand, the 14-3-3protein may act as an adaptor as well as a scaffold protein, which recruits the other target protein to be degraded, mediated by the ATL31/ATL6 ubiquitin ligase. Since the 14-3-3 protein forms a homo- or hetero-dimer and each 14-3-3 has a site to associate with a typical motif including phosphorylated Ser/Thr, the 14-3-3 protein complex binds with at least two different client proteins (Gokirmank et al., 2010).

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Fig. 2. Proposed model of ATL31 and ATL6 function to regulate plant C/N response during post-germinative growth. ATL31/ATL6 binds and ubiquitinates to the 14-3-3 protein to promote protein degradation via the 26S proteasome, which affects the activity of 14-3-3 client proteins and results in proper C/N response. Under high C/N stress conditions, over-accumulation of 14-3-3 proteins leads to growth arrest (red-colored arrow). Under low C/N ratios, the 14-3-3 proteins are degraded and post-germination growth continues through the phase transition checkpoint (green-colored arrow).

Conclusion Our recent studies have revealed that ubiquitin ligases ATL31 and ATL6 target 14-3-3 proteins and regulate the C/N response via UPS-mediated degradation, which suggests a novel regulatory mechanism for primary carbon and nitrogen metabolism. In the future studies, we will clarify the detailed mechanism of interaction between ATL31 and the 14-3-3 protein including up-stream signals such as the phosphorylation cascade. We should also reveal the dynamics of 14-3-3 proteins associated with target enzymes and how C/N metabolism is regulated. In addition, studies on other ubiquitin ligases indicated that plant UPS contributes extensively toward regulation of carbon and nitrogen response. Identification of the targets for these ubiquitin ligases will provide us with further information about the regulation of the signaling and metabolism. Furthermore, integrated studies on information between signaling mechanisms including UPS and metabolite dynamics will be needed to elucidate the complicated mechanisms of how plants coordinate development in response to nutrient environments.

Acknowledgements This work was supported by Grants-in-Aid for Scientific Research 2211450100 and 23380198 from the Ministry of Education, Culture, Sports, Science and Technology in Japan (http://www.mext.go.jp/english/).

References Chevalier D, Morris ER, Walker JC (2009) 14-3-3 and FHA domains mediate phosphoprotein interactions. Annu. Rev. Plant Biol., 60, 67-91 Comparot S, Lingiah G, Martin T (2003) Function and specificity of 14-3-3 proteins in the regulation of carbohydrate and nitrogen metabolism. J. Exp. Bot., 54, 595-604 Coruzzi GM, Zhou L (2001) Carbon and nitrogen sensing and signaling in plants: emerging 'matrix effects'. Current Opinion Plant Biol., 4, 247-253 Cotelle V, Meek SEM, Provan F, Milne FC, Morrice N, MacKintosh C (2000) 14-3-3s regulate global cleavage of their diverse binding partners in sugar-starved Arabidopsis cells. EMBO J.,19, 2869-2876 Ferl RJ, Manak MS, Reyes MF (2002) The 14-3-3s. Genome Biol., 3, 3010.1-3010.7 Gokirmak T, Paul AL, Ferl RJ (2010) Plant phosphopeptide-binding proteins as signaling mediators. Current Opinion Plant Biol., 13, 527-532 Hershko A, Ciechanover A (1998) The ubiquitin system. Annu. Rev. Biochem., 67, 425-479 Igawa T, Fujiwara M, Takahashi H, Sawasaki T, Endo Y, Seki M, Shinozaki K, Fukao Y, Yanagawa Y (2009) Isolation and identification of ubiquitin-related proteins from Arabidopsis seedlings. J. Exp. Bot., 60, 3067-3073 Ishida S, Fukazawa J, Yuasa T, Takahashi Y (2004) Involvement of 14-3-3 signaling protein binding in the functional regulation of the transcriptional activator REPRESSION OFSHOOT GROWTH by Gibberellins. Plant Cell, 16, 2641-2651 Martin T, Oswald O, Graham IA (2002) Arabidopsis seedling growth, storage lipid mobilization, and photosynthetic gene expression are regulated by carbon:nitrogen availability. Plant Physiol., 128, 472-481 Purwestri YA, Ogaki Y, Tamaki S, Tsuji H, Shimamoto K (2009) The 14-3-3 protein GF14c acts as a negative regulator of flowering in rice by interacting with the florigen Hd3a. Plant Cell Physiol., 50, 429-438

44


Salinas-Mondragon RE, Garciduenas-Pina C, Guzman P (1999) Early elicitor induction in members of a novel multigene family coding for highly related RING-H2 proteins in Arabidopsis thaliana. Plant Mol. Biol., 40, 579590 Sato T, Maekawa S, Yasuda S, Sonoda Y, Katoh E, Ichikawa T,Nakazawa M, Seki M, Shinozaki K, Matsui M, Goto DV, Ikeda A, Yamaguchi J (2009) CNI1/ATL31, a RING-type ubiquitin ligase that functions in the carbon/nitrogen response for growth phase transition in Arabidopsis seedlings. Plant J., 60, 852-864 Sato T, Maekawa S, Yasuda S, Domeki Y, Sueyoshi K, Fujiwara M, Fukao Y, Goto DV, Yamaguchi J (2011) Identification of 14-3-3 proteins as a target of ATL31 ubiquitin ligase, a regulator of the C/N response in Arabidopsis. Plant J., 68, 137-146 Serrano M, Parra S, Alcaraz LD, Guzman P (2006) The ATL gene family from Arabidopsis thaliana and Oryza sativa comprises a large number of putative ubiquitin ligases of the RING-H2 type. J. Mol. Evolution, 62, 434-45 Smalle J, Vierstra RD (2004) The ubiquitin 26S proteasome proteolytic pathway. Annu. Rev. Plant Biol., 55, 555590 Urano T, Saito T, Tsukui T, Fujita M, Hosoi T, Muramatsu M, Ouchi Y, Inoue S (2002) Efp targets 14-3-3σ for proteolysis and promotes breast tumour growth. Nature, 417, 871-875

Organelle Proteomics of Soybean under Flooding Stress Setsuko KOMATSU * National Institute of Crop Science, Tsukuba 305-8518, JAPAN *Corresponding author: [email protected]

Abstract As flooding injury is one of the major constraints for the cultivation of soybean, the improvement of flooding tolerance is important for increasing crop yields. To understand the response mechanism of soybean under flooding stress, various proteomics techniques have been conducted. Initially, the Soybean Proteome Database (http://proteome.dc.affrc.go.jp/ Soybean/) was constructed to serve as a data repository for the functional analyses of soybean responses to flooding injury. This database, which integrates the results of multiple “omics” approaches, including proteomics, transcriptomics, and metabolomics, allowed identification of the relationships among proteins, mRNAs, and metabolites that are up- and down-regulated under flooding stress. Examination of temporal expression profiles in seedlings confirmed that proteins related to glycolysis and alcohol fermentation were significantly increased in response to flooding. In addition, a number of flooding stress-responsive organelle proteins, including those of the cell wall, plasma membrane, and mitochondria, were identified using gel-based and -free proteomics techniques. The analyses provided three major insights into the response of soybean organelle proteins to flooding stress: (i) signaling-related proteins may regulate ion homeostasis; (ii) the decrease of cell wall proteins leads to suppression of lignification; and (iii) ATP synthesis is suppressed and apoptosis is induced in mitochondria. Finally, the identified proteins were characterized using molecular biological and biochemical techniques. Taken together, these data suggest that the early response of soybean seedlings to flooding may represent an important stress adaptation designed to ensure survival against not only hypoxia, but also from direct damage to cells.

Introduction Abiotic stress is the major constraint presently affecting global crop production. Various “omics” approaches, such as transcriptomics, proteomics, and metabolomics, have been used to study the abiotic stress responses of crops at the molecular level. Proteomics has been particularly useful for the comparative analyses of protein abundance between untreated and stress-treated, and stress-tolerant and -intolerant crops (Komatsu et al., 2003). Stress-induced alteration of gene expression leads to alteration of cellular protein abundance through the modulation of metabolic processes. Therefore, understanding how protein function is altered under stressful conditions is crucial for clarifying the molecular mechanisms underlying stress tolerance and crop injury (Komatsu et al., 2012). Proteomics has developed concurrently with technological advances in mass spectrometry (MS), which allows the identification of peptides derived from proteins following proteolytic digestion. Typically, peptides in solution or gel form are identified by liquid chromatography (LC)-MS (Nanjo et al., 2011), as this technique allows the identification of significantly more peptides from a complex mixture than can be identified using MS without LC separation. However, despite the remarkable technological advances in this field, the identification and quantification of all proteins present in any given biological system remains challenging. Among all abiotic environmental stresses affecting plants, flooding caused by heavy or continuous rainfall in areas with poorly drained soil is one of the most severe, as many types of crops cannot tolerate flooding. Under such conditions, oxygen deprivation may be the main factor limiting normal plant development, as well as the primary signal that triggers flooding responses (Jackson and Cormer, 2005). Previous studies examining gene expression responses under low oxygen conditions have found that plants up-regulate genes encoding transcription factors (Liu et al., 2005), signal transduction components (Baxter et al., 2002), nonsymbiotic hemoglobin (Dordas et al., 2004), ethylene signaling components (Reggiani, 2006), as well as genes involved in nitrogen metabolism (Mattana et al., 1994) and cell wall loosening (Saab and Sachs, 1996). Although metabolic acclimation to oxygen deprivation has been thoroughly reviewed by Bailey-Serres and Voesenek (2008), few reports to date have investigated the effects of flooding stress using proteomics technology. Furthermore, proteomics approaches have not been performed at the level of the organelle in plants subjected to soil flooding. However, the analysis of organelle proteins is anticipated to provide useful information to aid the understanding of cell behavior under flooding stress conditions. Flooding causes a marked reduction in the yields of several types of crops. Ahsan et al. (2007) investigated the response of roots and leaves of tomato to waterlogging stress using a proteomics approach and found that proteins involved in energy metabolism, secondary metabolic biosynthesis, and disease/defense were expressed in the roots, while proteins associated with photosynthesis were predominantly affected in leaves. Wheat seedlings respond to flooding stress by restricting cell growth to limit energy consumption, which is accomplished by coordinating methionine assimilation and cell wall hydrolysis (Kong et al., 2010). In aerenchymatous roots of wheat, soil hypoxia stress leads to the accumulation of proteins involved in alternative respiration and cell degeneration (Haque et al., 2011). Alam et al. (2010) profiled the proteome of soybean and analyzed the physiology of plants subjected to waterlogging stress during the vegetative stage and revealed that soybean copes with waterlogging by adjusting

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carbohydrate consumption and programmed cell death rates. Based on these findings, proteomics analyses of soybean plants in the young seedling stage under conditions of flooding stress were conducted in our study. The analysis of organelle proteins represents a powerful approach to elucidate cell behavior under abiotic stress conditions. Organelle proteins are primarily nuclear-encoded, although certain organelles, including mitochondria and chloroplasts, carry their own genetic material and are able to synthesize proteins (Hossain et al., 2012). However, because organelles and their respective proteins are in a dynamic state, elucidating the subcellular distribution and expression of organelle proteins remains challenging for proteomics researchers (Boisvert et al., 2010). In plant cells, abiotic stress alters interactions between organelles, which subsequently affects the regulation and secretion of proteins in cellular organelles and compartments. Several secretory pathways are involved in targeting proteins in plant cells (Carter et al., 2004; Furman et al., 2003; Mitoma and Ito, 1992). In addition, post-translational modifications, such as N-glycosylation and intramolecular disulfide bridge formation, are important determining factors for the correct folding and trafficking of target proteins from secretory pathway to chloroplasts (Buren et al., 2011; Kitajima et al., 2009; Nanjo et al., 2006; Villarejo et al., 2005). For example, Golgi-to-plastid trafficking of certain chloroplast resident proteins requires their glycosylation before entering chloroplasts. Together, these studies highlight the importance of identifying organelle proteins involved in stress responses, particularly proteins with regulatory or protein-targeting functions, to enhance the knowledge of cellular stress responses. To this end, our group is focused on the organelle proteomics of soybean seedlings subjected to flooding stress.

Construction of Soybean Proteome Database Soybean, a legume crop, is a significant source of fatty acids and proteins for both human and animal nutrition (Thelen and Ohlrogge, 2002). However, soybean production is sensitive to numerous environmental stresses, including temperature extremes (Ortiz and Cardemil, 2001; Strauss et al., 2007), salt (Luo et al., 2005), drought (Weisz et al., 1985; Gutierrez-Gonzalez et al., 2010), and flooding (Wuebker et al., 2001). Notably, soybean is a flood-intolerant crop, and its growth and grain yield are significantly reduced by flooding (Githiri et al., 2006). Thus, a better understanding of the flood-stress response mechanism in soybean is necessary for improving crop production and yields. Recently, the complete genome sequence of soybean was determined (Schmutz et al., 2010) and deposited into a publicly available database (http://www.phytozome.net/soybean). Access to such genomic information increases the feasibility of applying large-scale proteomics approaches to the investigation of stress-tolerance mechanisms in soybean. Unfortunately, functional genomics studies on soybean conducted to date have been limited by the presence of genome duplications, self-incompatibilities, and the long generation time of plants (Komatsu and Ahsan, 2009). Hajduch et al. (2005) constructed a soybean proteome database associated with the seed filling phase in soybean (Glycine max L. cultivar Maverick) (http://oilseedproteomics.missouri.edu) and used a high-throughput proteomics approach to determine expression profiles over time and the identities of hundreds of seed proteins after flowering. In our study, the Soybean Proteome Database (http://proteome.dc.affrc.go.jp/ Soybean/) was constructed to serve as a data repository for the functional analyses of soybean responses to flooding injury (Sakata et al., 2009). In the Soybean Proteome Database, the database contents, particularly the inclusion of numerous protein samples and their annotations from several organelles, have been markedly enhanced. The current release contains 23 reference maps of soybean (Glycine max L. cultivar Enrei) proteins collected from several organs, tissues, and organelles, and includes those for the plasma membrane, cell wall, chloroplast, and mitochondrion, based on proteins separated by twodimensional polyacrylamide gel electrophoresis (2-DE). Furthermore, proteins analyzed using gel-free proteomics techniques have been added to the database and are presently available online. In addition to proteins that exhibit fluctuations in expression under flooding stress, those associated with salt and drought stress have also been included in the current database release. The Soybean Proteome Database integrates the results of multiple “omics” approaches, including proteomics, transcriptomics, and metabolomics, and has allowed identification of the relationships among proteins, mRNAs, and metabolites that up- and down-regulated in response to flooding stress. Results from temporal expression profiles have confirmed that proteins related to glycolysis and alcohol fermentation are significantly up-regulated under flooding stress. The Soybean Proteome Database also includes proteins from organelles, including the cell wall, plasma membrane, and mitochondria. Proteins associated with the remaining organelles, such as the nucleus and endoplasmic reticulum, are planned to be added to the database in the future.

Organelle proteomics of soybean under flooding stress Organelle proteomic have led to a better understanding of the mechanism underlying tolerance to flooding stress in plants. Soybean seeds (Glycine max L. cultivar Enrei) were sterilized in a sodium hypochlorite solution, germinated on silica sand for two days, and the seedlings were then flooded with water for two days in a growth chamber. Three independent biological experiments were performed, in which the four-day-old seedling roots were collected for proteome analyses (Fig. 1). After the fractionation of organelles, including the cell wall, plasma membrane, and mitochondria, proteins were extracted, purified, and analyzed by both gel-based and gel-free proteomics techniques. For gel-based proteomics, purified proteins were first separated by 2-DE, and differentially

Organelle Proteomics of Soybean under Flooding Stress

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expressed protein spots were the excised, digested with trypsin, and analyzed by nanoLC-MS/MS. For gel-free proteomics, each protein solution was directly digested with trypsin, and analyzed by nanoLC-MS/MS. The resulting peptide sequence data for each technique were used to search the soybean peptide database, which was generated from the soybean genome database (Phytozome, version 7.0, http://www.phytozome.net/soybean), using the MASCOT search engine (version 2.2.04, Matrix Science, London, UK).

Fig. 1. Experimental design used in our organelle proteomics analysis of soybeans subjected to flooding stress. Soybean seedlings were either grown for four days under normal growth conditions (Control) or subjected to two days of flooding two days after germination (Flooding). Roots were collected from the control and flooded soybean seedlings, and cell wall, plasma membrane, and mitochondria were fractionated from the roots and used for gel-based and/or gel-free proteomics analyses. In higher plants, the cell wall is the first compartment to respond to stress signals, which are then transmitted to the cell interior where they modulate cellular responses. Komatsu et al. (2010a) isolated CaCl 2 -extracted cell wall proteins from flooding-stressed plants via sucrose gradient centrifugation and analyzed them using gel-based proteomic techniques. All of the identified cell wall proteins were related to lignification and included lipoxygenases, a germin-like protein precursor, 31-kDa stem glycoprotein, and superoxide dismutase [Cu-Zn]; the expression of which were decreased in response to flooding stress. Lignin staining confirmed that lignification is suppressed in the roots of flooding-stressed soybeans. Taken together, these findings suggest that the suppression of lignification in the roots of flooded soybean, resulting from decreased expression of lignification-related proteins, is related to the flooding-induced reduction of reactive oxygen species and jasmonate biosynthesis (Fig. 2).

Fig. 2. Pattern of lignin staining in the roots of soybean seedlings following flooding stress. Two-day-old seedlings were subjected to flooding for two days or left as untreated controls. The roots of seedlings were cut manually to give sections, and the sections were observed using a light microscope. The scale bar equals 100 µm. White stars show parts stained by phloroglucine. Komatsu et al. (2009) explored the effects of flooding stress on soybean plasma membrane proteins using an aqueous two-phase partitioning method in combination with gel-based and gel-free proteomics techniques. The findings from this study led to the following conclusions: (i) the increase of cell wall proteins in the plasma membrane of flooded plants suggests that the plasma membrane contributes to modifying the cell wall in response to flooding stress; (ii) the increased expression of superoxide dismutase indicates that the antioxidative system may play a crucial role in protecting cells from oxidative damage following exposure to flooding stress; (iii) heat shock cognate 70 kDa protein likely plays a significant role in protecting other proteins from denaturation and degradation during flooding stress; and (iv) signaling proteins might function cooperatively to regulate plasma membrane H+-ATPase and maintain ion homeostasis (Fig. 3).

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Fig. 3. Scheme summarizing the response of the plasma membrane proteome to flooding stress. Proteomics and metabolomics techniques were also used to examine whether flooding stress impacts mitochondrial function in soybeans (Komatsu et al., 2011b). In this study, mitochondrial fractions were purified from the roots and hypocotyls of four-day-old soybean seedlings subjected to flooding for two days. Mitochondrial matrix and membrane proteins were separated by 2-DE and blue-native PAGE, respectively, and differentially abundant proteins and metabolites were then identified using MS. This analysis revealed that proteins and metabolites of the tricarboxylic acid cycle and gamma-amino butyrate shunt are increased in response to flooding stress, whereas the abundance of inner-membrane carrier proteins and proteins related to complexes III, IV, and V of the electron transport chain are reduced. Notably, the levels of NADH and NAD+ increase in mitochondria; however, the concentrations of ATP decreases significantly. These results suggest that flooding directly impairs the electron transport chain, although mitochondrial NADH production increases through increased activity of the tricarboxylic acid cycle (Fig. 4).

Fig. 4. Scheme summarizing the response of mitochondrial proteins and metabolites to flooding stress (modified from Komatsu et al., 2010, J. Proteome Res., 10, 3993-4004).

Proteomics and confirmation experiments Gel-based proteomic analyses of young soybean seedlings have demonstrated that the expression of glycolytic proteins, including UDP-glucose pyrophosphorylase, fructose-bisphosphate aldolase, and nucleoside diphosphate kinase, is heavily impacted by flooding stress. Proteins associated with defense/disease resistance account for a major proportion of the proteins induced in soybeans experiencing flooding stress (Hashiguchi et al., 2009). A gel-free proteomic analysis of young soybean seedlings identified 81 proteins that are responsive to flooding stress, whereas only 32 such proteins were identified using a gel-based approach (Nanjo et al., 2010). Based on the number and function of proteins identified in these studies, it appears that glycolysis and fermentation enzymes, and inducers of heat shock proteins play key roles in the early response of soybean seedlings to flooding stress. Komatsu et al. (2010b) also examined the effects of nitrogen substitution with aeration on seedling during four days of flooding. Although nitrogen substitution did not alter the expression of many proteins that were affected by flooding stress, no differences in the expression of proteins classified into the protein destination/storage category were observed in response to flooding alone. The expression of alcohol dehydrogenase, which is the key enzyme in alcoholic fermentation, increased markedly in flooded plants subjected to nitrogen substitution compared to those treated with flooding alone. In addition, the abundance of the ROS scavenger 1-Cys peroxiredoxin increased in soybean undergoing flooding stress, but the levels of ascorbate peroxidase was reduced (Komatsu et al., 2010b). To understand how the proteins identified by proteomic approaches are involved in flooding stress responses in soybean, investigations have been conducted at the biochemical level. Analyses of the enzyme activities and carbohydrate content in flooded seedlings have shown that glucose degradation and sucrose accumulation are accelerated during flooding due to the activation of glycolysis and down-regulation of sucrose-degrading enzymes. It was also demonstrated that the methylglyoxal pathway, a detoxification system linked to glycolysis, is up-regulated


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during flooding in early-stage soybean seedlings (Nanjo et al., 2010). In addition, the function of proteins identified by the above-described proteomics analyses was clarified. In addition, both the normal and post-translationally modified forms of 1-Cys peroxiredoxin might remain as a result of growth retardation in seedlings suffering from flooding stress (Nishizawa et al., 2011). A decrease in ascorbate peroxidase at the protein and transcript levels, in conjunction with a decrease in ascorbate peroxidase enzyme activity, could provoke a large increase in ROS and induce oxidative damage that would impair plant development. Alternatively, ROS could be involved in signaling events related to reduced growth rates observed in flooded plants (Shi et al., 2008). Komatsu et al. (2011a) further examined soybean alcohol dehydrogenase expression in root tissue using a proteomics approach to clarify the role of this enzyme in response to flooding stress. Of six alcohol dehydrogenase isoforms, only alcohol dehydrogenase 2 was identified as a flooding-response specific gene expressed in the root tissue of soybean (Komatsu et al., 2011a).

Conclusion For organelle proteomics, two types of methods are currently available for quantitative investigations of the plant proteome: gel-based methods, including conventional 2-DE and 2D-fluorescence difference gel electrophoresis, and MS-based methods that involve label-based and label-free protein quantification. As 2-DE is not considered to be a truly global technique because of its limited usefulness in identifying low-abundance, hydrophobic, exceedingly large or small, and basic proteins (Nanjo et al., 2011), MS-based techniques are typically used to identify the widest range of proteins possible in a given sample. The identification and analysis of flood-responsive proteins using different proteomics methods may increase our understanding of how metabolic pathways, biological processes, and ubiquitinrelated systems are affected by flooding stress in soybean seedlings. Proteomic studies have generated a large amount of data regarding the expression of proteins in soybeans undergoing flooding stress. To verify the information generated through these studies, it will be necessary to use transgenic plants and/or marker-assisted breeding techniques, which have already been successfully applied to introduce the submergence-tolerance conferring sub1 (Xu et al., 2006) and SNORKEL1 and SNORKEL2 (Hattori et al., 2009) genes into selected rice cultivars. Our future research will focus on the use of proteomics and molecular breeding as tools for gene discovery and the development of flood-tolerant crops.

Acknowledgements We thank Drs. T. Nakamura, N. Nakayama, S. Shimamura, S. Hiraga, M. Tougou, Y. Nanjo and K. Nishizawa in National Institute of Crop Science for their critical comments and kind collaboration. This work was supported by a grant in Aid for Scientific Research (B) (19380015) of Japan Society for Promotion of Science.

References Ahsan N, Lee DG, Lee SH, Kang KY, Bahk JD, Choi MS, Lee IJ, Renaut J, Lee BH (2007) A comparative proteomic analysis of tomato leaves in response to waterlogging stress. Physiol. Plant., 131, 555-570 Alam I, Lee DG, Kim KH, Park CH, Sharmin SA, Lee H, Oh KW, Yun BW, Lee BH (2010) Proteome analysis of soybean root under waterlogging stress at an early vegitatibe stage. J. Biosci., 35, 49-62 Bailey-Serres J, Voesenek LACJ (2008) Flooding stress: Acclimations and genetic diversity. Annu. Rev. Plant Biol., 59, 313-339 Baxter-Burrell A, Yang Z, Springer PS, Bailey-Serres J (2002) RopGAP4-dependent Rop GTPase rheostat control of Arabidopsis oxygen deprivation tolerance. Science, 296, 2026-2028. Boisvert FM, Lam YW, Lamont D, Lamond AI (2010) A quantitative proteomics analysis of subcellular proteome localization and changes induced by DNA damage. Mol. Cell. Proteomics, 9, 457–470. Buren S, Ortega-Villasante C, Blanco-Rivero A, Martinez- Bernardini A, Shutova T, Shevela D, Messinger J, Bako L, Villarejo A, Samuelsson G (2011) Importance of post-translational modifications for functionality of a chloroplast-localized carbonic anhydrase (CAH1) in Arabidopsis thaliana. PLoS One, 6, e21021 Carter C, Pan S, Zouhar J, Avila EL, Girke T, Raikhel NV (2004) The vegetative vacuole proteome of Arabidopsis thaliana reveals predicted and unexpected proteins. Plant Cell, 16, 3285–3303 Dordas C, Hasinoff BB, Rivoal J, Hill RD (2004) Class-1 hemoglobins, nitrate and NO levels in anoxic maize cellsuspension cultures. Planta, 219, 66-72 Furman MH, Loureiro J, Ploegh HL, Tortorella D (2003) Ubiquitinylation of the cytosolic domain of a type I membrane protein is not required to initiate its dislocation from the endoplasmic reticulum. J. Biol. Chem., 278, 34804–34811 Githiri SM, Watanabe S, Harada K, Takahashi R (2006) QTL analysis of flooding tolerance in soybean at an early vegetative growth stage. Plant Breed., 125, 613-618 Gutierrez-Gonzalez JJ, Guttikonda SK, Tran LS, Aldrich DL, Zhong R, Yu O, Nguyen HT, Sleper DA (2010) Differential expression of isoflavone biosynthetic genes in soybean during water deficits. Plant Cell Physiol., 51, 936-948 Hajduch M, Ganapathy A, Stein JW, Thelen JJA (2005) A systematic proteomic study of seed filling in soybean. Establishment of highresolution two-dimentional reference maps, expression profiles, and an interactive proteome database. Plant Physioll. , 137, 1397-1419

50


Haque ME, Kawaguchi K, Komatsu S (2011) Analysis of proteins in aerenchymatous seminal roots of wheat grown in hypoxic soil under waterlogged conditions. Protein Peptide Let., 18, 912-924. Hashiguchi A.; Sakata K, Komatsu S (2009) Proteome analysis of early-stage seedling under flooding stress. J. Proteome Res., 8, 2058-2069 Hattori Y, Nagai K, Furukawa S, Song XJ, Kawano R, Sakakibara H, Wu J, Matsumoto T, Yoshimura A, Kitano H, Matsuoka M, Mori H, Ashikari M (2009) The ethylene response factors SNORKEL1 and SNORKEL2 allow rice to adapt to deep water. Nature, 460, 1026-1031 Hossain Z, Nouri M-Z, Komatsu S (2012) Plant cell organelle proteomics in response to abiotic stress. J. Proteome Res., 11, 37-48 Jackson MB, Colmer TD (2005) Response and adaptation by plants to flooding stress. Ann. Bot., 96, 501-505 Kitajima A, Asatsuma S, Okada H, Hamada Y, Kaneko K, Nanjo Y, Kawagoe Y, Toyooka K, Matsuoka K, Takeuchi, M, Nakano A, Mitsui T (2009) The rice alpha-amylase glycoprotein is targeted from the Golgi apparatus through the secretory pathway to the plastids. Plant Cell, 21, 2844–2858 Komatsu S, Ahsan N (2009) Soybean proteomics and its application to functional analysis. J. Proteomics, 72, 325336. Komatsu S, Hiraga S, Yanagawa Y (2012) Conceptual framework for the development of flooding tolerant crop using proteomics techniques. J. Proteome Res., 11, 68-78 Komatsu S, Kobayashi Y, Nishizawa K, Nanjo Y, Furukawa K (2010a) Comparative proteomics analysis of differentially expressed proteins in soybean cell wall during flooding stress. Amino Acids, 39, 1435-1449 Komatsu S, Konishi H, Shen S, Yang G (2003) Rice proteomics: A step toward functional analysis of the rice genome. Mol. Cell. Proteomics, 2, 2-10. Komatsu S, Sugimoto T, Hoshino T, Nanjo Y, Furukawa K (2010b) Identification of flooding stress responsible cascades in root and hypocotyl of soybean using proteome analysis. Amino Acids, 38, 729-738 Komatsu S, Thibaut D, Hiraga S, Kato M, Chiba M, Hashiguchi A, Tougou M, Shimamura S, Yasue H (2011a) Characterization of a novel flooding stress-responsive alcohol dehydrogenase expressed in soybean roots. Plant Mol Biol, 77, 309-322. Komatsu S, Wada T, Abelea Y, Nouri MZ, Nanjo Y, Nakayama N, Shimamura S, Yamamoto R, Nakamura T, Furukawa K (2009) Analysis of Plasma membrane proteome in soybean and application to flooding stress response. J. Proteome Res., 8, 4487-4499 Komatsu S, Yamamoto, A, Nakamura T, Nouri MZ, Nanjo Y, Nishizawa K, Furukawa K (2011b) A comprehensive analysis of mitochondria in roots and hypocotyls of soybean under flooding stress using proteomics and metabolomics techniques. J. Proteome Res., 10, 3993-4004. Kong FJ, Oyanagi A, Komatsu S (2010) Cell wall proteome of wheat roots under flooding stress using gel-based and LC MS/MS-based proteomics approaches. BBA-Protein Proteomics, 1804, 124-136. Liu F, Vantoai T, Moy L, Bock G, Linford LD, Quackenbush J (2005) Global transcription profiling reveals novel insights into hypoxic response in Arabidopsis. Plant Physiol., 137, 1115-1129. Luo Q, Yu B, Liu Y (2005) Differential sensitivity to chloride and sodium ions in seedlings of Glycine max and G. soja under NaCl stress. J. Plant Physiol., 162, 1003–1012 Mattana M, Coraggio I, Bertani A, Reggiani R (1994) Expression of the enzyme of nitrate reduction during the anaerobic germination of rice. Plant Physiol., 106, 1605-1608. Mitoma J, Ito A (1992) The carboxy-terminal 10 amino acid residues of cytochrome b5 are necessary for its targeting to the endoplasmic reticulum. EMBO J., 11, 4197–4203. Nanjo Y, Hiromasa O, Ikarashi N, Kaneko K, Kitajima A, Mitsui T, Jose Munoz F, Rodrıguez-Lope M, BarojaFernandez E, Pozueta-Romero J (2006) Rice plastidial N-glycosylated nucleotide pyrophosphatase/phosphodiesterase is transported from the ER-Golgi to the chloroplast through the secretory pathway. Plant Cell, 18, 2582–2592. Nanjo Y, Nouri MZ, Komatsu S (2011) Quantitative proteomics analyses of crop seedlings subjected to stress conditions; a commentary. Phytochemistry , 72, 1263-1272. Nanjo Y, Skultety L, Ashraf Y, Komatsu S (2010) Comparative proteomic analysis of early-stage soybean seedlings responses to flooding by using gel and gel-free techniques. J. Proteome Res., 9, 3989-4002. Nishizawa K, Komatsu S (2011) Characterization of soybean 1-Cys peroxiredoxin and its behavior in seedlings under flooding stress. Plant Biotech, 28, 83-88 Ortiz C, Cardemil L (2001) Heat-shock responses in two leguminous plants: a comparative study. J. Exp. Bot., 2, 711-1719 Reggiani R (2006) A role for ethylene in low-oxygen signaling in rice roots. Amino Acids, 30, 299-301. Saab IN.; Sachs MM (1996) A flooding-induced xyloglucan endotransglycosylase homolog in maize is responsive to ethylene and associated with aerenchyma. Plant Physiol., 112, 385-391 Sakata K, Ohyanagi H, Nobori H, Nakamura T, Hashiguchi A, Nanjo Y, Mikami Y, Yunokawa H, Komatsu S (2009) Sotbean Proteome Database: A data resource for plant differential omics. J Proteome Res, 8, 3539-3548 Schmutz J, Cannon SB, Schlueter J, Ma J, Mitros T, Nelson W, Hyten DL, Song Q, Thelen JJ, Cheng J, Xu D, Hellsten U, May GD, Yu Y, Sakurai T, Umezawa T, Bhattacharyya MK, Sandhu D, Valliyodan B, Lindquist E, Peto M, Grant D, Shu S, Goodstein D, Barry K, Futrell-Griggs M, Abernathy B, Du J, Tian Z, Zhu L, Gill N, Joshi T, Libault M, Sethuraman A, Zhang XC, Shinozaki K, Nguyen HT, Wing RA, Cregan P, Specht J, Grimwood J, Rokhsar D, Stacey G, Shoemaker RC, Jackson SA (2010) Genome sequence of the palaeopolyploid soybean. Nature, 463,178-183.


51

Shi F, Yamamoto R, Shimamura S, Hiraga S, Nakamura T, Yukawa, M, Hachinohe M, Matsumoto H, Komatsu S (2008) Ascorbate peroxidase 2 (Apx 2) involves in the response to submergence in soybean. Phytochemistry, 69, 1295-1303. Strauss AJ, Krüger GH, Strasser RJ, van Heerden PD (2007) The role of low soil temperature in the inhibition of growth and PSII function during dark chilling in soybean genotypes of contrasting tolerance. Physiol. Plant., 131, 89-105. Thelen J, Ohlrogge J (2002) Metabolic engineering of fatty acid biosynthesis in plants. Metab. Eng., 4, 12-21 Villarejo A, Buren S, Larsson S, Dejardin A, Monne M, Rudhe C, Karlsson J, Jansson S, Lerouge P, Rolland N, von Heijne G, Grebe M, Bako L, Samuelsson G (2005) Evidence for a protein transported through the secretory pathway en route to the higher plant chloroplast. Nat. Cell Biol., 7, 1224–1231 Weisz PR, Denison RF, Sinclair TR (1985) Response to drought stress of nitrogen fixation (acetylene reduction) rates by field-grown soybeans. Plant Physiol., 78, 525-530 Wuebker EF, Mullen RE, Koehler K (2001) Flooding and temperature effects on soybean germination. Crop Sci., 41, 1857-1861 Xu K, Xu X, Fukao T, Canlas P, Maghirang-Rodriguez R, Heuer S, Ismail AM, Bailey-Serres J, Ronald PC, Mackill DJ (2006) Sub1A is an ethylene-response-factor-like gene that confers submergence tolerance to rice. Nature, 442, 705- 708

Ubiquitin/Proteasome-Mediated Proteolysis is involved in the Response of Flooding Stress in Soybean Roots Yuki YANAGAWA1,2*, Setsuko KOMATSU1 1

National Institute of Crop Science, NARO, Tsukuba 305-8518, JAPAN Plant Science Center, RIKEN Yokohama Institute, Yokohama 230-0045, JAPAN *Corresponding author: [email protected] 2

Abstract Ubiquitin (Ub)/proteasome-mediated proteolysis is one of the highly conserved protein regulation from yeast to human. In plants, the proteolysis is known to play important roles in the response of several environmental stresses. Here we focus on the relationship between the proteolysis and flooding stress in soybean (Glycine max L. cultivar Enrei). In this work, immunoblot analyses revealed that the amount of ubiquitinated proteins decreased by flooded roots, while that of COP9 signalosome (CSN) increased, independent to oxygen limitation. We also revealed that no significant difference was observed in 2 subunits of 26S proteasome, Rpt5 and Rpn10, and the overall subunits of 20S proteasome between flooded and untreated roots, although 3 other subunits of 26S proteasome were up- or down-regulated by flooding stress in our previous proteomic analysis. Degradation assay following 2D-PAGE and LC-MS/MS analysis identified 6 proteins, those amounts changed significantly between flooding or untreated roots dependent to 26S proteasome-mediated proteolysis. Thus, our results suggest that Ub/proteasome-mediated proteolysis is involved in the response of flooding stress independent to oxygen limitation in soybean roots.

Introduction Plants are exposed to several environmental stresses. In soybean, especially, flooding is one of the major environmental stresses. Once soybean seedlings are submerged, growth would be delayed and many seedlings would be dead in severe case, causing decreased amount of agricultural productivity (Komatsu et al., 2009a; Komatsu et al, 2009b). In addition, no resistant cultivar against flooding stress has been found in soybean so far. Therefore, it is expected to elucidate the mechanism of the response of flooding stress in soybean. Ub is a highly conserved small protein composed of 76 amino acid polypeptide. It covalently attaches to a substrate protein as a signal molecule. The process of ubiquitination named by “Ub pathway” involves the sequential action of 3 enzymes: Ub-activating enzyme (E1), Ub-conjugating enzyme (E2 or UBC) and Ub ligase (E3) (Vierstra, 2003). In most widely known cases, the substrate proteins are polyubiquitinated through Ub pathway, and then the substrate proteins are degraded by a degradation machinery 26S proteasome. Ub/proteasome-mediated proteolysis is known to regulate the response of various biotic and abiotic stresses in plants (Kurepa et al., 2009; Biedermann and Hellmann, 2010). Our previous proteome analysis revealed that several Ub/proteasome-related proteins are up- or down-regulated in flooded soybean (Nanjo et al, 2010), implying the relationship of Ub/proteasome-mediated proteolysis in the response of flooding stress. Here, we show that the alteration of the amount of ubiquitinated proteins and a regulatory complex of ubiquitination, CSN, by the flooding stress in soybean roots. We also found 7protein spots were significantly changed in their amount with or without a proteasome inhibitor MG132 dependent to flooding stress.

The amount of ubiquitinated proteins decreased in flooded roots of soybean Since several regulatory factors of Ub/proteasome-mediated proteolysis are regulated by flooding stress in soybean (Nanjo et al., 2010), the profile of ubiquitinated proteins may change by flooding stress. To examine this hypothesis, soybean seedlings after 2 days of sowing were flooded for 1 day (Fig. 1). Immunoblot analyses were performed using 2 different antibodies against a monoclonal anti-Ub antibody capable of detecting ubiquitinated proteins but not free Ub (FK2; Nippon Bio-Test Laboratories) (Fujimuro et al., 1994), and a monoclonal antibody against lysine 48-mediated polyubiquitin chains (K48-Ub; Boston Biochem) (Newton et al., 2008). As shown in Fig. 1, the amount of ubiquitinated proteins decreased significantly by the treatment of flooding stress in roots by immunoblot analyses using both anti-Ub antibodies. K48-mediated polyubiquitination is famous signal for degradation by the 26S proteasome, and is thought to exist in the most widely in vivo, implying that the substrate proteins of 26S proteasome likely decreased by flooding stress in roots. Since flooding stress induces hypoxic response because of the reduced gas exchange from the atmosphere to plant tissues, low oxygen caused by flooding may be a key factor of the reduced amount of ubiquitinated proteins in flooded roots. Low oxygen leads the lower efficiency of ATP production because of the reduction of aerobic respiration. Ub/proteasome-mediated proteolysis needs ATP, however, no significant change was observed in the amount of ubiqutinated proteins by nitrogen substitution making the condition of low oxygen in flooded roots (Yanagawa et al., 2012). In addition, it was reported that the amount of ubiquitinated proteins accumulated again after removing water from submerged soybean seedlings

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(Yanagawa et al., 2012). These results imply that the amount of ubiquitinated proteins decreased by submergence independent of oxygen limitation.

Fig. 1. The effect of flooding treatment on soybean seedlings. (A) Soybean seeds were germinated on sand at 25oC under a 16/8 h light/dark cycle. Two-day-old seedlings were flooded with tap water for 1 day (Flooded), and then roots were harvested to prepare crude extracts. Crude extracts of soybean roots from untreated seedlings were used as a control (Control). (B) Immunoblot analyses were performed using antibodies against 2 types of Ub (FK2, K48-Ub), 20S proteasome (20S; Ozaki et al., 1992), Rpn10 (Yanagawa et al., 2002, Rpt5 (ENZO Life Sciences), CSN4 (ENZO) and CSN5 (ENZO).

Subunit proteins of CSN, but not 26S proteasome, increased in flooded roots of soybean Since the amount of ubiquitinated proteins decreased in flooded roots, regulatory factors of ubiquitination and/or degradation may change in the protein amount by flooding stress. A regulatory factor of ubiquitination, CSN, is composed of 8 subunits, CSN1-8. As shown in Fig. 1, both CSN4 and 5 proteins increased significantly by flooding treatment for 1day, although no significant change was found by nitrogen substitution (Yanagawa et al., in press). It was revealed that the CSN dissociates ubiquitinated proteins from neddylated cullin-based E3 ligase, bringing to promote the degradation of them in mammal (Miyauchi et al., 2008). Thus, it is likely that the reduced amount of ubiquitinated proteins by flooding stress is due to the increased amount of CSN proteins promoting capture of ubiquitinated proteins for the subsequent 26S proteasome-mediated proteolysis. Our previous proteomic analysis using the s extracts from hypocotyls and roots of soybean revealed that one of E1s was up-regulated by flooding stress (Nanjo et al., 2010), implying the promoted ubiquitination of the substrate proteins. However, the amount of ubiquitinated proteins decreased in flooded roots, suggesting that ability of the CSN may be stronger than that of E1. Next, to examine whether the protein level of 26S proteasome changes by flooding stress, immunoblot analyses were performed. The 26S proteasome consists of a core 20S proteasome and 19S/22S regulatory subcomplexes. The 20S proteasome is composed of 14 distinct subunits (α1-7 and β1-7), and three βsubunits carry catalytic activities of protein degradation (Bochtler et al., 1999). On the other hand, 19S/22S regulatory subcomplex consists of distinct Rpn (regulatory particle non-ATPase) and Rpt (regulatory particle ATPase) subunits (Glickman et al., 1998). No significant difference was found in the amounts of Rpt5 and Rpn10 proteins, or the overall amount of 20S proteasome subunits by flooding stress in soybean roots (Fig. 1), although our previous proteomic analysis showed that a αsubunit was up-regulated and another αsubunit and Rpt2 were down-regulated by flooding stress (Nanjo et al., 2010). It would be expected of further experiments in the contribution of each subunit protein in the response of flooding stress.

The amount of 6 proteins were changed significantly by the treatment of the proteasome inhibitor MG132 Since flooding stress changed in the amounts of a batch of ubiquitinated proteins and CSN subunits, the substrate proteins of 26S proteasome may change by flooded roots. In dead, several enzymes of Ub pathway are up- or downregulated by flooding stress in soybean seedlings (Nanjo et al., 2010), supporting this hypothesis. To identify those proteins which are regulated by flooding stress dependent to Ub/proteasome-mediated proteolysis, crude extracts from roots treated by flooding or none were incubated with MG132 or DMSO as a negative control for a protein degradation assay as described previously (Igawa et al., 2009), and then the samples were subjected by 2D-PAGE (Fig. 2). Since MG132 treatment prevents the degradation of certain proteins from their degradation by 26S proteasome, the comparison of the samples treated with MG132 or DMSO should give the information of the substrate proteins of Ub/proteasome-mediated proteolysis. Seven protein spots were observed in the significant difference of their amount on four gels (Control-DMSO, Control-MG132, Flooded-DMSO, and Flooded-MG132), indicating that they may be regulated by flooding stress dependent to Ub/proteasome-mediated proteolysis (Yanagawa et al., 2012). By LC-MS/MS analysis, six proteins were identified from 7 protein spots, including alkyl

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hydroperoxide reductase identified from 2 protein spots, implying certain modification such as phosphorylation. Further experiments will be expected to elucidate the relationships between the identified proteins and Ub/proteasome-mediated proteolysis.

Fig. 2. Degradation assay and 2DPAGE .Crude extracts of soybean roots treated (Flooded) or untreated (Control) with flooding for 1 day were incubated with MG132 or DMSO, and then analyzed using 2DPAGE. Only a gel from control sample treated with DMSO was showed to indicate the protein spots (arrowheads) that their signal intensities changed significantly among 4 gels; Control-DMSO, control-MG132, Flooded-DMSO, and Flooded-MG132 (Yanagawa et al., 2012).

Conclusion Recent our proteomic analysis has revealed that several regulatory proteins of Ub/proteasome-mediated proteolysis such as E1 and E3 ligases are regulated by flooding stress in soybean. In addition, immunoblot analyses showed the reduced amount of ubiquitinated proteins and CSN accumulation by flooding stress, independent to oxygen limitation. Furthermore, six proteins were identified as the regulated proteins by flooding stress, dependent to 26S proteasome-mediated proteolysis. Therefore, we suggest that the Ub/proteasome-mediated proteolysis is involved in the regulation of flooding stress in soybean. Further experiments will be necessary to elucidate the relationships between the response of flooding stress and the Ub/proteasome-mediated proteolysis.

Acknowledgements We thank Drs. Nanjo Y and Nouri MZ in National Institute of Crop Science, NARO, Japan for their technical help. This work was supported by a grant from National Agriculture and Food Research Organization, Japan.

References Biedermann S, Hellmann H (2010) WD40 and CUL4-based E3 ligases: lubricating all aspects of life. Trends Plant Sci., 16, 38-46 Bochtler M, Ditzel L, Groll M, Hartmann C, Huber R (1999) The proteasome. Anuu. Rev. Biophys. Biomol. Struct., 28, 298-317 Fujimuro M, Sawada H, Yokosawa H (1994) Production and characterization of monoclonal antibodies specific to multi-ubiquitin chains of polyubiquitinated proteins, FEBS Lett., 349, 173-180 Glickman MH, Rubin DM, Coux O, Wefes I, Pfelfer G, Cjeka Z, Baumeister W, Fried VA, Finley D (1998) A subcomplex of the proteasome regulatory particle required for ubiquitin-conjugate degradation and related to the COP9-signalosome and eIF3, Cell, 94, 615-623. Igawa T, Fujiwara M, Takahashi H, Sawasaki Y, Endo Y, Seki M, Shinozaki K, Fukao Y, Yanagawa Y (2009) Isolation and identification of ubiquitin-related proteins from Arabidopsis seedlings. J. Exp. Bot., 60, 3067–3073 Komatsu S, Yamamoto R, Nanjo Y, Mikami Y, Yunokawa H, Sakata K (2009a) A comprehensive analysis of the soybean genes and proteins expressed under flooding stress using transcriptome and proteome techniques. J. Proteome Res., 8, 4766-4778 Komatsu S, Wada T, Abaléa Y, Nouri MZ, Nanjo Y, Nakayama N, Shimamura S, Yamamoto R, Nakamura T, Furukawa K (2009b) Analysis of plasma membrane proteome in soybean and application to flooding stress response. J, Proteome Res., 8, 4487-4499 Kurepa J, Wang S, Li Y, Smalle J (2009) Proteasome regulation, plant growth and stress tolerance. Plant Signal. Behav., 4, 924-927 Miyauchi Y, Kato M, Tokunaga F, Iwai K (2008) The COP9 signalosome increases the efficiency of von HippelLindau protein ubiquitin ligase-mediated hypoxia-inducible factor-alpha ubiquitination. J. Biol. Chem., 283, 16622-16631 Nanjo Y, Skultety L, Ashraf Y, Komatsu S (2010) Comparative proteomic analysis of early-stage soybean seedlings responses to flooding by using gel and gel-free techniques. J. Proteome Res., 9, 3989-4002 Newton K, Matsumoto ML, Wertz IE, Kirkpatrick DS, Lill JR, Tan J, Dugger D, Gordon N, Sidhu SS, Fellouse FA, Komuves L, French DM, Ferrando RE, Lam C, Compaan D, Yu C, Bosanac I, Hymowitz SG, Kelley RF, Dixit VW (2008) Ubiquitin chain editing revealed by polyubiquitin linkage-specific antibodies, Cell, 134, 668-678

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Ozaki M, Fujinami K, Tanaka K, Amemiya Y, Sato T, Ogura N, Nakagawa H (1992) Purification and initial characterization of the proteasome from the higher plant Spinacia oleracea. J. Biol. Chem., 267, 21678-21684. Yanagawa Y, Hasezawa S, Kumagai F, Oka M, Fujimuro M, Naito T, Makino T, Yokosawa H, Tanaka K, Komamine A, Hashimoto J, Nakagawa H (2002) Cell-cycle dependent dynamic change of 26S proteasome distribution in tobacco BY-2 cells, Plant Cell Physiol., 43, 604–613 Yanagawa Y, Komatsu S (2012) Ubiquitin/proteasome-mediated proteolysis is involved in the response to flooding stress in soybean roots, independent of oxygen limitation. Plant Sci., (on line) Vierstra RD (2003) The ubiquitin/26S proetasome pathway, the complex last chapter in the life of many plant proteins, Trends Plant Sci., 8, 135-142

Involvement of Endomembrane-type Superoxide Dismutase in High Temperature Stress Tolerance during Grain Filling of Rice Toshiaki MITSUI1,2*, Takeshi SHIRAYA1, Taiki MORI2, Kentaro KANEKO2 1

Department of Applied Biological Chemistry, Niigata University, Niigata 950-2181, JAPAN Graduate School of Science & Technology, Niigata University, Niigata 950-2181, JAPAN *Corresponding author: [email protected] 2

Abstract The aim of our research is to isolate and identify the genes involved in high temperature tolerance during grain filling of rice. Gel-based comparative proteomic study with early rice cultivars which exhibit different sensitivities toward high temperature during grain filling strongly suggested that Mn-type superoxide dismutase (MSD1) should be a candidate responsible for the high temperature tolerance. The amino acid sequence deduced from the Oryza sativa MSD1 gene contained the signal sequence and N-glycosylation site predicted by PSORT and SignalP. To determine the actual subcellular localization of MSD1, the confocal imaging analysis of onion epidermal cells transiently expressed with MSD1-YFP was carried out. The obtained results showed the occurrence of MSD1-YFP in both the Golgi apparatus and the plastids, indicating that MSD1 is endomembrane-type plastid-targeting protein. In order to evaluate the involvement of MSD1 on the high temperature tolerance, we generated transgenic rice plants with either a constitutively high expression or suppression of MSD1 gene. The grain quality of rice overexpressing MSD1 grown at 33oC, 12h light / 28oC, 12h dark was markedly improved in comparison with that in the wild type. MSD1 knocked-down rice became more susceptible to high temperature stress. A series of quantitative shotgun proteomic analysis indicated that the overexpression of MSD1 up-regulated the reactive oxygen scavenging, chaperones, quality control systems and maintained the function of plastids in rice grains under the high temperature stress. Based on these results, we concluded that the endomembrane-type plastid-targeting MSD1 plays an important role to adapt to high temperature stress.

Introduction Global warming is one of the most serious environmental issues we face at the present. The Intergovernmental Panel on Climate Change (IPCC) is thinking several scenario concerning the greenhouse gas emission, but anyway, probably, the global surface temperature will further increase during the twenty-first century. In Japan excluding Hokkaido and a Tohoku region, abnormal high temperature during grain filling stage of rice causes a decrease in not only the grain size but also the grain quality. As shown Fig. 1, the normal grain is perfectly filled with normal starch granules. In the case of the white immature grains caused by the high temperature stress, abnormal and loose starch granules form in the part of grain, and this part is whitely seen by irregular reflection of the light. Probably, the white immature grains appeared by a shortage of starch deposition under high temperature stress.

Fig. 1. Normal and white immature grains of rice.

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Niigata prefecture is well known as the area that produces the high quality of rice grains, however, a decrease trend of grain quality of Niigata rice has been observed in the last 20 years. Particularly, in the last year 2010 which was the hottest summer in thirty years, the production of 1st class grain (the normal grain with full round and transparency accounts for equal to or more than 70 %) of Niigata brand rice “Koshihikari” severely decreased. Ongoing global warming will further damage the rice production. Frequent occurring of damaged grains by high temperature stress influences the income of rice farmers directly, and also, it is capable of losing the brand image of the high quality rice. Therefore, the development of high temperature tolerant cultivars of rice is very important and urgent research task.

Results and Discussion We examined high temperature susceptibilities of several rice cultivars during the grain filling period from 2004 to 2008. The rice cultivars including “Yukinkomai”, “Yukinosei” and “Todorokiwase” were treated in a field with irrigation of 35 oC warm water at a flow rate of 80L/min during heading and milky stages. The average temperature in the irrigating field was increased to 1.4 to 1.9 oC compared with that of the normal field (25.4 oC). The evaluation of the grain qualities with or without the irrigating treatment indicated that “Yukinko-mai” exhibited a tolerant of high temperature, while “Todorokiwase” was susceptible to high temperature stress. Therefore, we were searching the genes involved in high temperature tolerance of cultivar “Yukinkomai” by the gel-based proteomic approach. Fig. 2 shows the 2D-PAGE separation profiles of proteins extracted from the grains of 4 day-after-flowering (DAF) of “Yukinkomai”, “Yukinosei” and “Todorokiwase”. The quantities of protein spots in the 2D-gels stained with Coomassie brilliant blue (CBB) were determined using image analysis software, Image Master 2D Elite and PDQuest (Asakura et al., 2007), and the protein identification was performed by the analysis of MALDI-TOF/TOF-MS (Azwan et al., 2010). We observed the changes in the expression of heat shock protein 70 (HSP70) and 16.9 (HSP16.9), 20S proteasome αF, ABA-inducible protein (R40g2), ascorbate peroxidase (APX), alcohol dehydrogenase (ADH), protein disulfide isomerase (PDI) and superoxide dismutase (SOD), etc., by the treatment of high temperature stress. We had a great interest in a SOD protein characteristically and highly expressed in developing seeds of “Yukinkomai” (Fig. 2A).

Fig. 2. 2D-PAGE separation profiles of proteins extracted from the grains of 4 day-after-flowering (DAF) of “Yukinkomai” (A), “Yukinosei” (B) and “Todorokiwase” (C). An aliquot of each protein extract was subjected to isoelectric focusing (pH 3.5-10), followed by SDS-PAGE. HSP70 (66 kDa, pI 4.8), 20S proteasome aF (46 kDa, pI 5.7), PDI (40 kDa, pI 5.3), R40g2 (38 kDa, pI 6.8), APX (36 kDa, pI 5.2), ADH (28 kDa, pI 5.0), SOD (28 kDa, pI 5.6), HSP16.9 (18 kDa, pI 5.6).

SODs convert superoxide anion to oxygen and hydrogen peroxide (H 2 O 2 ), and H 2 O 2 is further detoxified to H 2 O and O 2 by catalase and peroxidases. The enzymes are thought to be an important antioxidant defense in nearly all cells exposed to O 2 . The SOD protein identified in the developing grain of high temperature tolerant cultivar was a manganese-type superoxide dismutase, MSD1. SOD has been reported to diversely distribute in Arabidopsis cells. Ferrous type FSD1, 2 and 3 localize in chloroplasts, copper/zinc-type CSD1, 2 and 3 localize in cytosol, chloroplasts and peroxisomes, and Mn-type MSD1 localizes in mitochondria (Kliebenstein et al., 1998). Mn-type pea SOD has been also shown to localize in mitochondria (del Río et al., 2003). Fig. 3 shows the amino acid sequence alignments of the deduced proteins of rice, Arabidopsis, maize, wheat and pea MSD genes. It has been described that the Mntype SOD (MSD1) from rice has the mitochondria presequence (Sakamoto et al., 1993; Li et al., 2009), though Computer-assisted analyses using SignalP (http://www.cbs.dtu.dk/services/SignalP/) and PSORT (http://psort.ims.utokyo.ac.jp/) algorithms revealed that the Oryza sativa MSD1 has the signal sequence rather than the mitochondria transit peptide in addition to an N-glycosylation site. To examine the actual localization of MSD1, we carried out the experiments of transient expression of MSD1-YFP using onion epidermal cells. The confocal laser scanning microscopic observation revealed that a large portion of MSD1-YFP fluorescence overlapped with both the Golgi bodies and the plastids visualized by ST-mRFP and WxTP-DsRed (Kitajima et al., 2009), respectively. We next examined the effects of dominant negative and constitutive active mutants of AFR1 and SAR1 GTPases on the plastid-targeting of MSD1-YFP. Sar1 and Arf1 GTPases have been shown to be necessary for the membrane traffic

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between the ER and Golgi apparatus in plant cells (Takeuchi et al. 2002, Kitajima et al. 2009). The plastid-targeting of MSD1-YFP was perfectly prevented in the cell expressing AFR1 and SAR1 mutants, and both MSD1-YFP and ST-mRFP Golgi marker distributed in the ER network in the cells. Overall, results strongly suggest that MSD1 is an endomembrane-type SOD, and is targeted and functioned to the interior of plastid from the ER-Golgi system through the secretory pathway (Fig. 4), like rice α-amylase I-1 (AmyI-1) and nucleotide pyrophosphatase/phosphodiesterase 1 (NNP1) (Nanjo et al., 2006; Kitajima et al., 2009).

Fig. 3. Alignments of predicted amino acid sequences of the deduced MSD1 proteins of possible orthologous genes from Oryza sativa, Arabidopsis thaliana, Zea mays, Triticum aestivum and Pisum sativum. Conserved amino acids are boldfaced. Underlines represent mitochondria transit peptide predicted by PSORT. In rice MSD1, open and closed arrowheads show possible cleavage sites of the signal peptide predicted by PSORT and signalP, respectively. An N-glycosylation site is boxed.

Fig. 4. A hypothetical model for plastid-targeting of Oryza sativa MSD1 from the Golgi apparatus through the secretory pathway.


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To test the involvement of MSD1 in high temperature stress tolerance, the transgenic rice plants with Ubi::MSD1 were generated using Agrobacterium-mediated transformation. We confirmed the overexpression of MSD1 in the transgenic rice plants by evaluating the expression profiles of the MSD1 mRNA in different organs of wild type (WT) and transgenics (USD1-1 and USD1-2). When rice plants of USD1 and WT were incubated under high temperature condition (33oC for 12h in the light and 28oC for 12h in the dark) during heading and grain filling, the grain quality of USD1 was markedly improved in comparison with those of WT. While, the MSD1 knocked-down rice became more susceptible to the high temperature stress. Thus, we conclude that the constitutively high expression of MSD1 overcomes the grain quality decreasing by high temperature stress. Why did the overexpression of MSD1 bring out the high temperature stress tolerance? To clarify the mechanism, we carried out the quantitative shotgun proteomic analysis of ripening seeds. The ripening seeds of USD1 and WT grown in normal (28oC for 12h in the light and 23oC for 12h in the dark) and high temperature stress (33oC for 12h in the light and 28oC for 12h in the dark) conditions were subjected to protein extraction, trypsin digestion and iTRAQ labeling, then applied to MS/MS analysis with LTQ-Orbitrap XL. Fig. 5 shows the summary of the results of quantitative shotgun proteomic analyses, revealing that 79 proteins including storage and allergen proteins were down-regulated and 219 proteins were up-regulated in the ripening seeds of USD1 under the high temperature stress compared to those in WT.

Fig. 5. Characteristic protein expression in the ripening seeds of transgenics with MSD1 overexpression under high temperature stress. When examining the contents in detail, the reactive oxygen species (ROS) scavenging system including peroxiredoxins, thioredoxins, ascorbate peroxidases, monodehydroascorbate reductase, and so on, were markedly upregulated in the transgenics with MSD1 overexpression under the high temperature condition in comparison with those in the wild-type. Under the normal condition, the change in such scavenging system was silent (Fig. 6). We considered that the highly expressed MSD1 actively converts ROS caused by high temperature stress to H 2 O 2 , and H 2 O 2 probably serves as a trigger for enhancing ROS scavenging system, since it is known that H 2 O 2 functions as signaling molecules and activates the MAPK cascade (Neill et al., 2002; Apel and Hirt, 2004). Actually, H 2 O 2 induced ascorbate peroxidase in embryo of germinating rice seed (Morita et al., 1999), Arabidopsis leaves (Karpinski et al., 1999), tobacco leaves (Gupta et al., 1993), and peroxiredoxin in thyroid cells (Kim et al., 2000). It is likely those peroxiredoxin and ascorbate peroxidase are the main regulators of the intracellular H 2 O 2 concentration. In addition to ROS scavenging system, chaperones, chaperonins, several heat shock proteins, a component of quality control calreticulin and proteasome components of programmed proteolysis systems were also up-regulated under the high temperature condition (Fig. 7). As MSD1 was targeted to the plastids, we looked at changes in the plastid proteomes by the shotgun analysis. Photosystem I and II chlorophyll apoproteins, chlorophyll a/b binding protein, oxygen evolving protein, and Rubisco, Rubisco activase and binding protein, chaperonin, chloroplastic aldolase, triose phosphate isomerase and glyceraldehydes-3-phosphate dehydrogenase were up-regulated in the transgenics with MSD1 overexpression under the high temperature condition, that was similar to those of ROS detoxifying and chaperon and quality control systems. As described before, the white immature grains are thought to be appeared by abnormal starch accumulation and granule formation. Starch metabolism-related genes are actively expressed during the milky stage of grain filling.

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Yamakawa et al. (2007) have reported that high temperature stress reduces the gene expression of starch synthesisrelated enzymes such as ADP-glucose pyrophosphorylase, ADP-glucose translocator (Bt1), starch synthase, starch branching enzyme, etc., whereas increases those of starch degrading enzymes in the grain of rice. Thus, the changes in starch metabolism will be related to occurring of white immature grains. Noteworthy, our present data of proteomics indicated that the overexpression of MSD1 just slightly affected the expression of starch synthesis-related enzymes, but strongly lowered the abnormal high expression of starch degrading enzymes such as α-amylase and αglucosidase by under the high temperature condition. From the overall results, we concluded that the overexpression of MSD1 maintains the formation and accumulation of starch granules by controlling the expression of starch degrading enzymes in the grain under high temperature stress.

Fig. 6. Expression of ROS scavenging system in the transgenics overexpressing MSD1 under high temperature stress. The developing seeds at 4 and 10 DAF were subjected to the quantitative shotgun analysis. MSD1ox, MSD1 overexpresion; WT, wild type. Hot condition, 33oC for 12h in the light and 28oC for 12h in the dark; control, 28oC for 12h in the light and 23oC for 12h in the dark.

Fig. 7. Expression of chaperone, quality control and programmed proteolysis systems in the transgenic overexpressing MSD1 under high temperature stress.


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Conclusion The constitutively high expression of MSD1 improves the grain quality decreasing by high temp stress. MSD1 is targeted to the plastid from the ER-Golgi system through the secretory pathway. MSD1 up-regulates stress response, and maintains the plastid functions including light reaction, carbohydrate metabolism and starch accumulation.

References Apel K, Hirt H (2004) Reactive oxygen species: metabolism, oxidative stress, and signal transduction. Annu. Rev. Plant Biol., 55, 373-399 Asakura T, Hirose S, Nanjo Y, Nakaizumi T, Itoh K, Hori H, Komatsu S, Mitsui T (2007) Proteomic characterization of tissue expansion of rice scutellum stimulated by abscisic acid. Biosci. Biotech. Biochem., 71, 1260-1268 Azwan A, Karim R, Mitsui T (2010) Proteomic Analysis of Teobroma cacao Pod Husk. J. Applied Glycoscence, 57, 245-264 del Río LA, Sandalio LM, Altomare DA, Zilinskas BA (2003) Mitochondrial and peroxisomal manganese superoxide dismutase: differential expression during leaf senescence. J. Exp. Bot., 54, 923-933 Gupta AS, Webb RP, Holaday AS, Allen RD (1993) Overexpression of Superoxide Dismutase Protects Plants from Oxidative Stress (Induction of Ascorbate Peroxidase in Superoxide Dismutase-Overexpressing Plants). Plant Physiol., 103, 1067-1073 Karpinski S, Reynolds H, Karpinska B, Wingsle G, Creissen G, Mullineaux P (1999) Systemic signaling and acclimation in response to excess excitation energy in Arabidopsis. Science, 284, 654-657 Kim H, Lee TH, Park ES, Suh JM, Park SJ, Chung HK, Kwon OY, Kim YK, Ro HK, Shong M (2000) Role of peroxiredoxins in regulating intracellular hydrogen peroxide and hydrogen peroxide-induced apoptosis in thyroid cells. J. Biol. Chem., 275, 18266-18270 Kitajima A, Asatsuma S, Okada H, Hamada Y, Kaneko K, Nanjo Y, Kawagoe Y, Toyooka K, Matsuoka K, Takeuchi M, Nakano A, Mitsui T (2009) The rice α-amylase glycoprotein is targeted from the Golgi apparatus through the secretory pathway to the plastids. Plant Cell, 21, 2844-2858 Kliebenstein DJ, Monde RA, Last RL (1998) Superoxide dismutase in Arabidopsis: an eclectic enzyme family with disparate regulation and protein localization. Plant Physiol., 118, 637-650. Li W, Qi L, Lin X, Chen H, Ma Z, Wu K, Huang S (2009) The expression of manganese superoxide dismutase gene from Nelumbo nucifera responds strongly to chilling and oxidative stresses. Journal of Integrative Plant Biol., 51, 279-286 Morita S, Kaminaka H, Masumura T, Tanaka K (1999) Induction of rice cytosolic ascorbate peroxidase mRNA by oxidative stress, the involvement of hydrogen peroxide in oxidative stress signalling. Plant Cell Physiol., 40, 417422 Nanjo Y, Oka H, Ikarashi N, Kaneko K, Kitajima A, Mitsui T, Muñoz FJ, Rodríguez-López M, Baroja-Fernández E, Pozueta-Romero J.(2006) Rice plastidial N-glycosylated nucleotide pyrophosphatase/phosphodiesterase is transported from the ER-Golgi to the chloroplast through the secretory pathway. Plant Cell, 18, 2582-2592 Neill SJ, Desikan R, Clarke A, Hurst RD, Hancock JT (2002) Hydrogen peroxide and nitric oxide as signalling molecules in plants. J. Exp. Bot., 53, 1237-1247 Sakamoto A, Nosaka Y, Tanaka K (1993) Cloning and sequencing analysis of a complementary DNA for manganese-superoxide dismutase from rice (Oryza sativa L.). Plant Physiol., 103, 1477-1478 Takeuchi M, Ueda T, Yahara N, Nakano A (2002) Arf1 GTPase plays roles in the protein traffic between the endoplasmic reticulum and the Golgi apparatus in tobacco and Arabidopsis cultured cells. Plant J., 31, 499-515 Yamakawa H, Hirose T, Kuroda M, Yamaguchi T (2007) Comprehensive expression profiling of rice grain fillingrelated genes under high temperature using DNA microarray. Plant Physiol., 144, 258-277

Quantitative Label-Free Shotgun Proteomics of Abiotic Stress in Rice Paul A. HAYNES1*, Mehdi MIRZAEI1, C. Gayani GAMMULLA1, Dana PASCOVICI2, Karlie A. NEILSON1, G. Hosseini SALEKDEH3, Brian J. ATWELL4 1

Department of Chemistry and Biomolecular Sciences, Macquarie University, North Ryde, NSW 2109, AUSTRALIA 2 Australian Proteome Analysis Facility, Macquarie University, North Ryde, NSW 2109, AUSTRALIA 2 Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran, Karaj, IRAN 4 Department of Biological Sciences, Macquarie University, North Ryde, NSW 2109, AUSTRALIA *Corresponding author: [email protected]

Abstract We have pursued a series of studies in recent years examining the effects of abiotic stress on rice plants. This has included analysis of cell suspensions and leaf and root tissues, looking at how protein expression changes in response to temperature stress and drought stress. We have developed a quantitative label-free shotgun proteomics analysis pipeline that allows us to generate thousands of protein expression level data points across multiple sampling points within a stress imposition regime. This has enabled us to reveal richly detailed information about how rice plants respond at a molecular level when faced with external abiotic stress conditions.

Introduction Our planet faces an uncertain future in terms of both climate and food security. Rice is one of the most important crops in the world as it feeds a large percentage of the human population, yet global supply struggles to keep up with demand. Global mean temperatures are expected to rise by 2 - 4.5ºC by 2100, accompanied by an increase in frequency and amplitude of extreme temperature events. Greater climatic extremes and an expanded range of cultivation will expose rice to increasing stress in the future. These climatic changes and expansion of boundaries of cultivation due to population growth will expose rice to more extreme temperatures in future. High temperature stress decreases grain filling rate, seed setting rate, grain weight, pollen fertility, yield (Cao et al., 2006; Peng et al., 2004; Tang et al., 2005) and also grain quality (Zhang et al., 2008). Mechanisms of tolerance to temperature stress and drought are complex, interacting and polygenic. This is why we believe it is important to learn all we can about how rice adapts to environmental changes. The core technology at the heart of our shotgun proteomics analysis pipeline is the ion trap mass spectrometer. We are currently using a Thermo LTQ-XL ion trap, but will be using a recently acquired next generation Thermo Velos Pro Linear ion trap from next year. Shotgun proteomics involves large scale fractionation at either the peptide or protein level, prior to identification of peptides using CID fragmentation and database searching software. There are many different fractionation approaches used, including SDS-PAGE, HPLC, free flow electrophoresis and isoelectric focussing of proteins, and isoelectric focussing, HPLC and strong cation exchange (SCX) chromatography of peptides (Gilmore and Washburn, 2010). The majority of our recent work has been performed using SDS-PAGE of proteins as a front-end for shotgun proteomics experiments. This approach has several advantages; first, it is very simple, inexpensive and robust; second, SDS-PAGE sample buffer is an excellent protein solubilizing agent; third, it can often can work better than a mudpit experiment when you have one or two proteins that are far more abundant than anything else, as they are isolated in separate gel slice fractions and so cause less interference in the other fractions (Jones et al., 2008). The main quantitation approach we use is label-free quantitation of proteins based on spectral counting (Zybailov et al., 2005). The applicability of this in other systems has been demonstrated widely, but our work is some of the first to apply it successfully to plants. We have used this approach to generate quantitative data for individual proteins, but also, more recently, for whole categories or pathways of proteins. Quantitation of protein categories provides new information as it can interpolate some missing details and reveal information that would otherwise have escaped notice (Friso et al., 2010).

Results and discussion In the following sections we present a summary of our recent published works on abiotic stress in rice. Temperature stress in rice cell suspension cultures In this study we investigated the proteomic responses of rice (Oryza sativa cv. Nipponbare) cell suspension cultures to sudden temperature changes. Cell cultures grown at a controlled temperature of 28°C were subjected to 3day exposure to 12ºC or 20ºC for low temperature stress, and 36ºC or 44ºC for high temperature stress. Quantitative

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label-free shotgun proteomic analysis was performed on biological triplicates of each treatment and over 1900 proteins were reproducibly identified in one or more temperature treatments. More than 850 of these were found to be responsive to either of the temperature extremes. These temperature-responsive proteins included 40 novel stressresponse proteins and more than 300 proteins which were uniquely expressed at either 12ºC or 44ºC. We also observed that switching between the classical and alternative pathways of sucrose metabolism occurs in response to extremes of temperature (Gammulla et al., 2010). Overall, it was very clear that the molecular level changes observed at 44ºC were qualitatively and quantitatively very different to what was observed at any of the other temperature points. The protein expression patterns observed at low temperature stress were consistent with expectations, with many stress response proteins up-regulated. The protein expression patterns seen at very high temperature stress seemed indicative of a metabolic shutdown rather than stress response. This is perhaps best summed up as were able to ‘visualize cellular panic’. Temperature stress in rice seedlings This study was a follow-up to the one described above, where we investigated the proteomic responses of leaves of rice (Oryza sativa cv. Doongara) seedlings to sudden temperature changes (Gammulla et al., 2011). This was modelled on a similar temperature regime, but the experimental design was complicated by the need to maintain a viable diurnal temperature range. Hence, rice seedlings grown at 28/20°C (day/night) were subjected to three-day exposure to 12/5 or 20/12°C (day/night) for low-temperature stress, and 36/28 or 44/36°C (day/night) for hightemperature stress, followed by quantitative label-free shotgun proteomic analysis on biological triplicates of each treatment. Out of over 1100 proteins expressed in one or more temperature treatments, more than 400 were found to be responsive to temperature stress. Of these, 47, 135 and 50 proteins were exclusively found at 12/5, 20/12 and 44/36°C, respectively. In this study we identified over 20 novel stress-response proteins, and, consistent with the previous study, observed that sucrose and starch metabolism show significant responses to temperature stress. Perhaps the most interesting observation from this study was that the most dramatic protein changes were seen at the 20/12°C conditions, not at either of the extreme temperatures. We speculate that this may be the result of the plants being forced to switch repeatedly between stress and non-stress conditions, rather than maintaining a stress response. Clearly, the growing plants were better able to cope with temperature extremes than the cells in suspension culture were. In a further study focussed on rice cold stress we showed that our label-free quantitative proteomics approach generated considerably more useful information than analysis of the same tissue samples using isobaric labelling with iTRAQ quantitation (Neilson et al., 2011). Drought stress in rice seedlings This study described in gene expression at precise physiological stages of drought in 35 day-old seedlings of Oryza sativa cv. Nipponbare (Mirzaei et al., 2011a). Drought was imposed gradually for up to 15 days, causing abscisic acid levels to rise and growth to cease, and plants were then re-watered. Proteins were identified from leaf samples after moderate drought, extreme drought, and 3 and 6 days re-watering. Label-free quantitative shotgun proteomics resulted in the identification of 1548 non-redundant proteins. More proteins were down regulated in early stages of drought but more were up-regulated as severe drought developed. After re-watering, there was a noticeable reduction in the total number of expressed proteins, suggesting that stress-related proteins were being degraded. Proteins involved in signaling and transport became dominant as severe drought took hold but decreased again on rewatering. One of the most interesting findings of this study was a co-ordinated response in aquaporin expression. A whole suite of aquaporins were found to be strongly down-regulated in response to moderate drought stress, and then strongly up-regulated as the drought continued to a more extreme stage, and then even more strongly down-regulated once re-watering began. Also, nine G-proteins appeared in large amounts during severe drought and dramatically degraded once plants were re-watered. We speculate that water transport and drought signaling are critical elements of the overall response to drought in rice and might be the key to biotechnological approaches to drought tolerance. Drought stress in rice split-rooted seedlings Rice (Oryza sativa L. cv. IR64) was grown in split-root systems in order to answer a particular question, namely whether long-distance drought signals could be transmitted within root systems (Mirzaei et al., 2011b). 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 one half was watered (3) and the other half was droughted (4). This was aimed at identifying how droughted root tissues altered the proteome of adjacent wet roots by hormone signals and secondly, how wet roots reciprocally affected dry roots hydraulically. Quantitative label-free shotgun proteomic analysis of four different root tissues resulted in identification of 1487 non-redundant 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. Notably, 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 specifically address the question raised. Nine tubulins were strongly reduced in droughted roots while six chitinases were upregulated, and the same expression pattern was observed in well-watered split-roots where the drought signal arrived remotely from adjacent droughted roots. This study provide firm evidence that well-watered root tissues can receive, and act upon, a drought signal from adjacent root tissues connected to the same shoot.

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Conclusion We have performed a series of studies employing a quantitative label-free shotgun proteomics approach to examine protein expressions changes in rice exposed to complex abiotic stresses. This includes wide ranging temperature stress in cells and seedlings, and progressive drought and re-watering in seedlings. We have revealed a number of insights into the molecular level response of rice plants to abiotic stresses. For example, we have seen pathway switching and a generalized panic response caused by very high temperature, co-ordinated regulation of a suite of aquaporins during drought progression, and evidence of long-distance drought signalling using split-rooted plants. In order to analyze such a large amount of data we have relied on several open source software tools that we have written and implemented in-house. These include a program known as Scrappy, which sorts, combines, compares and quantifies spectra counting data from shotgun proteomics experiments, and a program known as PloGo which was developed to aid with the bioinformatics analysis of multi-condition label-free proteomics experiments using quantitation based on spectral counting (Pascovici et al., 2011). These software tools are an essential part of our analysis pipeline and have greatly facilitated the process of biological discovery. Understanding dramatic gene expression changes in response to wide-ranging thermal and drought stress regimes is important for the engineering of rice cultivars with tolerance to non-optimal temperatures. Developing rice cultivars better adapted to non-optimal temperatures is essential in order to increase rice yield in future, and it is this which makes understanding the molecular response of rice to temperature stress necessary

References Cao Y, Song F, Goodman RM, Zheng Z (2006) Molecular characterization of four rice genes encoding ethyleneresponsive transcriptional factors and their expressions in response to biotic and abiotic stress. J. Plant Physiol., 163, 1167-1178 Friso G, Majeran W, Huang M, Sun Q, Van Wijk KJ (2010) Reconstruction of metabolic pathways, protein expression, and homeostasis machineries across maize bundle sheath and mesophyll chloroplasts: large-scale quantitative proteomics using the first maize genome assembly. Plant Physiol., 152, 1219-1250. Gammulla CG, Pascovici D, Atwell BJ, Haynes PA (2010) Differential metabolic response of cultured rice (Oryza sativa) cells exposed to high- and low- temperature stress. Proteomics, 10, 3001-3019. Gammulla CG, Pascovici D, Atwell BJ, Haynes PA (2011) Differential proteome response of cultured rice (Oryza sativa) leaves exposed to high- and low- temperature stress. Proteomics, 11, 2839-2850. Gilmore JM, Washburn MP (2010) Advances in shotgun proteomics and the analysis of membrane proteomes. J. Proteomics, 73, 2078-2091 Jones RC, Deck J, Edmondson RD, Hart ME (2008) Relative quantitative comparisons of the extracellular protein profiles of Staphylococcus aureus UAMS-1 and its sarA, agr, and sarA agr regulatory mutants using onedimensional polyacrylamide gel electrophoresis and nanocapillary liquid chromatography coupled with tandem mass spectrometry. J. Bacteriol.,190, 5265-5278 Mirzaei M, Pascovici D, Atwell BJ, Haynes PA (2011a) Differential regulation of aquaporins, small GTPases and VATPases proteins in rice leaves subjected to drought stress and recovery, Proteomics, In Press. Mirzaei M, Soltani N, Sarhadi E, Pascovici D, Keighley T, Salekdeh GH, Haynes PA, Atwell BJ, Shotgun proteomic analysis of long-distance drought signalling in rice roots (2011b). J. Proteome Res. (on line) Neilson KA, Mariani M, Haynes PA (2011) Quantitative proteomic analysis of cold-responsive proteins in rice. Proteomics, 11, 1696 - 1706 Pascovici D, T. Keighley T, M. Mirzaei M, Haynes PA, Cooke B (2011) PloGO: Plotting Gene Ontology annotation and abundance in multi-condition proteomics experiments. Proteomics, In Press. Peng S, Huang J, Sheehy JE, Laza RC, Visperas RM, Zhong X, Centeno GS, Khush GS, Cassman KG (2004) Rice yields decline with higher night temperature from global warming. Proc. Natl. Acad. Sci. USA, 101, 9971-9975 Tang RS, Zheng JC, Chen, LG, Zhang, DD, Jin ZQ, Tong HY (2005) Effects of high temperature on grain filling and some physiological characteristic in flag leaves of hybrid rice. Zhi Wu Sheng Li Yu Fen Zi Sheng Wu Xue Xue Bao 31, 657-662 Zhang GF, Wang SH, You J, Zhang YX, Wang QS, Ding YF (2008) Effects of relatively high temperature at grainfilling stage on rice grain's starch viscosity profile and magnesium and potassium contents. Ying Yong Sheng Tai Xue Bao. 19, 1959-1964 Zybailov B, Coleman MK, Florens L, Washburn MP (2005) Correlation of relative abundance ratios derived from peptide ion chromatograms and spectrum counting for quantitative proteomic analysis using stable isotope labelling. Anal. Chem., 77, 6218-24

Cold Stress Modulates Brassica juncea Nitrosoproteome, Inhibits RuBisCO Activity Culminating In Photosynthetic Down Regulation Ankita SEHRAWAT, Jasmeet K. ABAT, Renu DESWAL* Molecular Plant Physiology and Proteomics Laboratory, Department of Botany, University of Delhi, Delhi-11007, INDIA *Corresponding author: [email protected]

Abstract Stress whether biotic or abiotic contributes to nitric oxide (NO) production in plants. Recently, NO has emerged as an important signaling molecule regulating plethora of physiological processes by modifying all major biomolecules whether it is protein, lipids or nucleic acids. Present focus is on understanding S-nitrosylation, a post translational modification of proteins. B.juncea is an important oil seed crop. India is still not self sufficient in oil production due to losses incurred by biotic and abiotic stress. It is very well established that stress down regulates photosynthesis but the mechanism is still obscure. To know, if nitrosylation has any role in the process, nitrosoproteome was analyzed by biotin switch technique (BST), Neutravidin affinity purification followed by 2DMS in total proteins after S-nitrosoglutathione (GSNO, NO donor) treatment. The probable targets belong to various metabolic pathways including Calvin cycle. Cold stress mediated nitrosylation led to RuBisCO degradation and its significant (40%) inhibition. Photosynthetic measurements using portable photosynthesis measuring system (LICOR) showed 32.3% higher electron transport rate (ETR) in cold stress. This enhanced ETR could contribute to higher nitrosative and oxidative stress, which could either activate or inhibit enzymes including RuBisCO. In fact, cold stress inhibited RuBisCO carboxylase activity showed similar (39%) extent of inhibition. This inhibition would translate to lower CO 2 fixation leading to photosynthesis down regulation. To summarize, present investigation has clearly established a correlation between cold induced nitrosylation and photosynthesis in cold stress.

Introduction All stress whether biotic or abiotic have two major common effects on plants, one is the down regulation of photosynthesis and second is the evolution of reactive oxygen and nitrogen species contributing to oxidative and nitrosative stress. Oxidative stress can be due to chemically reactive species like reactive oxygen species (ROS) such as superoxide radical (O 2 .- ), hydrogen peroxide (H 2 O 2 ), hydroxyl radical (OH.) and singlet oxygen (1O 2 ) while reactive nitrogen species (RNS) such as nitrogen dioxide (·NO 2 ), peroxynitrite (ONOO- ), S-nitrosothiols (RSNOs), S-nitrosoglutathione (GSNO), dinitrogen trioxide (N 2 O 3 ) contribute to the nitrosative stress. ROS and RNS are highly reactive and can oxidize biological molecules like proteins, carbohydrates, unsaturated lipids and nucleic acids. Proteins being the most abundant constitute the major targets (68%) of oxidative species (Rinalducci et al., 2008). Role of several components of nitric oxide (NO) signaling during abiotic stress was analyzed in pea plants exposed to low temperature (LT, Corpas et al., 2008). Increase in NO content and L-arginine dependent generation of NO (NOS activity) was shown in LT. RSNOs content also showed 5-fold increase by LT stress. Brassica juncea seedlings also showed maximum SNO content in LT (1.4 fold) in comparison with drought (1.2 fold), salinity and HT (1.1 fold each) (Abat and Deswal, 2009). These reports clearly show the differential production of NO in abiotic stress. ROS are produced due to an imbalance between the reducing equivalent and the photosynthetic consumption capacity (Baker, 1994). This imbalance in turn leads to photoinhibition of photosynthesis. Cold stress is reported to affect photosynthesis by down-accumulating many photosynthetic proteins (Rinalduccia et al., 2011). A marked decrease in the abundance of proteins like oxygen evolving enhancer protein (OEE1 and 2) and ribulose 1,5-bisphosphate carboxylase/oxygenase (RuBisCO) was observed in cold stress along with their scattering either due to fragmentation or posttranslational modifications (PTMs, Rinalduccia et al., 2011). Thus, the current literature suggests that cold stress causes photosynthetic inhibition (Yan et al., 2006) which contributes to reduced crop yield. Brassica juncea is an important oil yielding crop and is known to be affected by biotic and abiotic stress. Abiotic stress meditated photosynthetic loss is well known but the mechanism is still not understood. NO is reported to be generated in the chloroplast (Jasid et al., 2006). Protein abundance of many photosynthetic proteins like photosystem II (PSII) oxygen-evolving complex (OEC), RuBisCO subunit binding protein β-subunit, RuBisCO activase and sedoheptulase bisphosphate precursor are known to be altered on sodium nitroprusside (SNP, NO donor) treatment. One of the mechanisms by which abiotic stress mediated photosynthetic loss occurs could be due to S-nitrosylation. Snitrosylation is a NO based PTM which involves reversible attachment of NO to the free thiols of cysteines in a protein. Proteins of light reactions of photosynthesis like PSII P680 protein, PSII D2 protein, Rieske Fe-S protein, PSII OEC 33, PSII OEC protein 3 like, OEE3 precursor-like protein and 23 kDa subunit of oxygen evolving system of PSII (Alconada et al., 2010) are reported to be S-nitrosylated. Like light reaction, many proteins involved in the Calvin cycle (dark reactions of photosynthesis) are also S-nitrosylated. Both large and small subunit of RuBisCO (Abat et al., 2008; Alconada et al., 2010), glyceraldehyde-3-phosphate dehydrogenase β subunit (Alconada et al.,

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2010) and RuBisCO activase (Alconada et al., 2010) are S-nitrosylated (Fig. 1). RuBisCO is one of the most important protein in CO 2 assimilation. Cys 449 and Cys 459 residues are known to be involved in oxidative inactivation of RuBisCO (Moreno et al., 2008) indicating the role of cysteines in maintaining catalytic efficiency of RuBisCO.

Fig. 1. S-nitrosylated targets in the Calvin cycle. Enzymes depicted in boxes are reported to be S-nitrosylated. Recent reports of S-nitrosylation of photosynthetic proteins support the significant role of this PTM in regulating photosynthesis. To know how S-nitrosylation might playing a role in stress mediated photosynthetic inhibition, Snitrosylation was analyzed in Brassica juncea seedlings with major focus on RuBisCO as S-nitrosylation target in cold stress (6 h) as firstly, it is the most abundant plant protein. Secondly, it is a key enzyme of Calvin cycle and thirdly it was already validated to be S-nitrosylated earlier by Abat et al., 2008. Also, the effect of cold stress on its carboxylase activity was studied to determine a correlation between stress, S-nitrosylation and its activity. This work is further linked with the photosynthetic efficiency of B.juncea by measuring electron transport rate (ETR) in cold stress (6 h) treated seedlings.

Material and method Plant material and growth conditions Brassica juncea var. varuna seeds were obtained from Indian Agricultural Research Institute, New Delhi, India. Seeds were germinated in germination paper and grown in biological oxygen demand incubator (BOD) at 25ºC under 2000 lux light for 16/8 h light and dark photoperiod. Cold stress was given to 7 days seedlings in ice cold buffer for 6 h.

Purification of S-nitrosylated proteins, 2-DE, data analysis, MS identification and western blotting For detection of S-nitrosylation of RuBisCO in Brassica juncea, biotin switch technique (BST) was used (Jeffery and Snyder, 2001; Abat and Deswal, 2009) coupled with Neutravidin agarose chromatography for purification. For 2DE, proteins in rehydration buffer were loaded onto IPG strip (13 cm, pH 3-10) and kept for overnight rehydration. Isoelectric focusing was carried out using an IPGphor (GE Healthcare, Uppsala, Sweden) at 27,500 V for 8.3 h at 20°C with a limiting current of 50 μA/ strip. Strips were equilibrated in 1% (w/v) DTT and alkylated with 2.5% (w/v) iodoacetamide in the equilibration buffer. The second dimension was carried out at 10 mA for 1 h and then 20 mA using Hoefer SE 600 (GE Healthcare). ImageMaster 2-D Platinum software (version 6.0 GE Healthcare) was used for spot detection and pattern matching. For protein identification, PMF and LC-MS/MS was done using Ultra Flex (Bruker Daltonics, Bremen, Germany) and Agilent 1100 2D nano LC-MS/MS respectively. For western blotting, proteins were transferred onto a nitrocellulose membrane (NC) membrane and probed with anti-RuBisCO antibody (a kind gift from Norm Huner) at 1:2000 dilution for 2 h and alkaline phosphatase-conjugated antibodies (Santa Cruz, CA, USA) at 1:2000 dilution for 30 min with nitro blue tetrazolium (NBT) and 5-Bromo-4-chloro-3-indolyl phosphate (BCIP) as substrate. Experiments were repeated three times.

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RuBisCO carboxylase activity assay and ETR measurement Validation of RuBisCO as S-nitrosylation target in cold stress was done by performing RuBisCO carboxylase activity following Garcia-Ferris and Moreno, 1993. Experiments were repeated four times in duplicate. ETR was measured using LI-6400XT portable photosynthesis system (LI-COR).

Results and Discussions To know the in vivo modulation of S-nitrosylation by cold stress, S-nitrosylated proteins were identified in LT (6 h) stress treated seedlings. S-nitrosylated proteins detected using BST, purified using Neutravidin affinity chromatography and identified by MS showed differential S-nitrosylation of many photosynthetic (RuBisCO, transketolase-like protein and sedoheptulose-bisphosphatase), metabolic (fructose-bisphosphatase aldolase, triosephosphate aldolase and ACC synthase 4), stress related (glutathione S-transferase and hsp70) and signaling (elongation factor EF-2) proteins. Detailed analysis of RuBisCO on 2-D gels showed both an increase (spot 1, 3 and 5) as well as a decrease (spot 2 and 4) in S-nitrosylation after cold stress (Fig. 2A and B). RuBisCO is known to fragment in cold stress (Yan et al., 2006). To investigate whether protein fragmentation also occurs after Snitrosylation, purified S-nitrosylated proteins from control and cold stress seedlings were resolved on 2-D gels and probed with anti-RuBisCO antibody. After cold stress, abundance of large subunit of RuBisCO decreased (shown with a single arrow, Fig. 2D). This was confirmed by an increase in the RuBisCO fragmentation (shown in a box, Fig. 2D) and later confirmed by MS where more than one spot were identified as RuBisCO. Comparison of 2-D gels of purified S-nitrosylated proteins (Fig. 2A and B) with 2-D blots (Fig. 2C and D) showed increased S-nitrosylation (Fig. 2B) as well as protein accumulation (Fig. 2D) of spot 1. Spot 2 showed a decrease in S-nitrosylation (Fig. 2B) whereas the amount of protein remained same on the blot (Fig. 2D). S-nitrosylation (Fig. 2B) as well as accumulation (Fig. 2D) of spot 6 remained constant. These results suggest cold stress mediated differential S-nitrosylation of RuBisCO.

Fig. 2. 2-DE (A and B) and western blotting (using anti-RuBisCO antibody, C and D) of purified S-nitrosylated proteins in control and cold stress to show cold stress induced differential S-nitrosylation and fragmentation of RuBisCO. E) Effect of NO donor on the purified RuBisCO activity. (F) RuBisCO activity in control and cold stress treated seedlings extracts. The GSNO and cold stress inhibited activity is recovered by reducing agents (DTT and GSH) suggesting similar mechanism of activity inhibition. RuBisCO activity in untreated control was taken as 100%. To further confirm S-nitrosylation mediated RuBisCO regulation, its activity was analyzed in the presence of GSNO (a NO donor, Fig. 2E) as well as in cold stress (Fig. 2F). RuBisCO carboxylase activity was inhibited by GSNO in a dose-dependent manner. Addition of DTT (a thiol specific reductant) to GSNO treated extract restored the RuBisCO carboxylase activity indicating specificity/reversibility of the reaction. A 39% decrease in carboxylase activity was found in cold stress in comparison with the control. Also, addition of DTT restored the activity reflecting cold stress induced reversible thiol modification of RuBisCO protein. Cys 172 and 459 identified as redox sensitive cysteines could probably be involved in cold stress induced S-nitrosylation of RuBisCO. An increase in ETR is reported in cold stress as a protective mechanism against photoinhibition. To confirm, ETR was measured which showed a 32.3% increase in cold stress treated seedlings in comparison with the control (data not shown).

Conclusion and future prospects The present study showed in vivo validation of S-nitrosylation of RuBisCO in cold stress. Further it is shown that cold stress induced S-nitrosylation of RuBisCO is responsible for its inactivation. On the basis of the results, a putative model is presented which shows that cold stress increases the ETR which further enhances RNS responsible

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for nitrosative stress (Fig. 3) and might be responsible for S-nitrosylation of RuBisCO. S-nitrosylation causes inhibition of its activity. Abiotic stress alters the abundance of many transcripts and proteins by regulating gene expression as well as protein turnover (Saibo et al. 2009). Also, during environmental stress the CO 2 availibility reduces in the leaf and/or the ATP sythesis is impaired. LT also enhances ROS production which further causes lipid peroxidation, protein denaturation, photo-oxidative damage and initiation of scavenging mechanism (superoxide dismutase and glutathione ascorbate cycle). All these factors reduces photosynthesis and might contribute to crop yield loss. Effect of all S-nitrosylated targets need to be analyzed to have a complete picture of the nitrosylation mediated yield loss. Further work on identification of regulatory pathways involved in this novel mechanism is required. Also, similar work on field grown plants needs to be undertaken to know the in vivo effect of abiotic stress mediated S-nitrosylation on crop yield.

Fig. 3. A putative model showing cold stress induced photosynthetic inhibition. LT stress perceived by plants can initiate signal transduction which can further increase ETR. Increased ETR in chloroplast contributes to enhanced RNS and ROS generation. These are known to inhibit photosynthesis by limiting CO 2 , impairing ATP production and photo-oxidative damage along with other effects leading to crop yield loss.

References Abat JK, Mattoo AK, Deswal R (2008) S-nitrosylated proteins of a medicinal CAM plant Kalanchoe pinnata – ribulose-1,5-bisphosphate carboxylase/oxygenase activity targeted for inhibition. FEBS J., 275, 2862–2872 Abat JK, Deswal R (2009) Differential modulation of S-nitrosoproteome of Brassica juncea by low temperature: Change in S-nitrosylation of Rubisco is responsible for the inactivation of its carboxylase activity. Proteomics, 9, 4368–4380 Alconada AM, Zomeno SE, Lindermayr C, Lopez IR, Durner J, Jorrn J (2010) Proteomic analysis of Arabidopsis protein S-nitrosylation in response to inoculation with Pseudomonas syringae. Acta Physiol. Plant, 33, 1493-1514 Baker NR (1994) Chilling stress and photosynthesis. In Causes of Photooxidative Stress and Amelioration of Defense System in Plants. Edited by Foyer, C.H. and Mullineaux, CRC Press, Boca Raton, FL. Corpas FJ, Chaki M, Fernańdez-Ocan˜ A, Valderrama R, Palma J M, Carreras A, Begara-Morales J C, Airaki M, Rio L A D, Barroso J B (2008) Metabolism of reactive nitrogen species in pea plants under abiotic stress conditions. Plant Cell Physiol., 49, 1711–1722 Garcıá-Ferris C, Moreno J (1993) Redox regulation of enzymatic activity and proteolytic susceptibility of ribulose-1,5-bisphosphate carboxylase/oxygenase from Euglena gracilis. Photosynth. Res., 35, 55–66 Jaffrey SR, Snyder SH (2001) The biotin switch assay for the detection of S-nitrosylated proteins. Sci. STKE, PL1. Jasid S, Simontacchi M, Bartoli CG & Puntarulo S (2006) Chloroplasts as a nitric oxide cellular source. Effect of reactive nitrogen species on chloroplastic lipids and proteins. Plant Physiol, 142, 1246–1255 Moreno J, Garcıá-Murria MJ, Marıń-Navarro J (2008) Redox modulation of Rubisco conformation and activity through its cysteine residues. J. Exp. Bot., 59, 1605–1614 Rinalducci S, Murgiano L, Zolla L (2008) Redox proteomics: basic principles and future perspectives for the detection of protein oxidation in plants. J. Exp. Bot., 59, 3781–3801 Rinalduccia S, Egidia MG, Mahfoozib S, Godehkahrizc JS, Zollaa L (2011) The influence of temperature on plant development in a vernalization-requiring winter wheat: A 2-DE based proteomic investigation, J. Proteomics, 74, 643 – 659 Saibo NJ, Lourenco T, Oliveira MM (2009) Transcription factors and regulation of photosynthetic and related metabolism under environmental stresses. Ann Bot., 103, 609-623 Yan SP, Zhang QY, Tang, ZC, Su WA, Sun WN (2006) Comparative proteomic analysis provides new insights into chilling stress responses in rice. Mol. Cell. Proteomics, 5, 484–496

Proteomic Analysis of Oil Palm Leaves with High and Low Proliferation Rate in Callusing Tan HOOI SIN1*, Susan LIDDELL2, Meilina ONG ABDULLAH3, Wong WEI CHEE4,5, Choo CHIN NEE4, Chin CHIEW FOAN1 1

School of Biosciences, Faculty of Science, University of Nottingham, Malaysia Campus, Jalan Broga, 43500 Semenyih, Selangor, MALAYSIA 2 School of Biosciences, Faculty of Science, University of Nottingham, UNITED KINGDOM 3 Malaysian Palm Oil Board, P.O. Box 10620, 50720 Kuala Lumpur, MALAYSIA 4 Advanced Agriecological Research Sdn Bhd, ½ km Jalan Sg Buloh/Subang,47000, Sg Buloh, Selangor, MALAYSIA 5 AAR-UNMC Biotechnology Research Centre, Jalan Broga, 43500 Semenyih, Selangor, MALAYSIA *Corresponding author: [email protected]

Abstract Oil palm is an important commercial crop in Malaysia which is the world’s second largest producer and exporter of palm oil. In order to meet the increasing demand for oil palm plantlets to produce palm oil, the oil palm plantation companies have used in vitro micropropagation techniques through somatic embryogenesis to promote the growth and yield of oil palm. However, many issues hamper the progress of the oil palm embryogenesis technique, such as a low rate of embryogenesis and clonal abnormality. This study deploys proteomic technology to compare differential protein expression in leaves from high and low proliferation rate of callusing in oil palm tissue culture. Total protein of oil palm leaves was successfully extracted using trichloroacetic acid /acetone precipitation technique. The proteins were separated on two-dimensional gel electrophoresis. A total of 200-300 spots were reproducibly detected. Out of these 14 distinct protein spots that differentially expressed in these two categories namely high and low proliferation of callusing leaves, 8 proteins were found to be lower in abundance, 1 protein was higher in abundance in low proliferation rate samples compared to the higher proliferation rate samples, while 5 protein spots were found to present only in the high proliferation rate samples. The variant proteins were subsequently sent for identification using mass spectrometric analysis.

Introduction Oil palm (Elaeis guineensis Jacq.) is an important commercial crop in Malaysia. It is a diploid monocotyledon with single vegetative apex (Low et al., 2008). Due to the long life cycle and single growing apex of the oil palm perennial crop, somatic embryogenesis has become one of the alternatives in clonal propagation of oil palm to supply the elite oil palm plantlets (Thuzar et al., 2010). Young leaves of oil palm will be chosen as a starting material for tissue culture to induce callus. The nodular appearance of callus will form along the cut edges of leaves. Callus remains compact and undergoes embryogenesis (Rohani et al., 2000). Somatic embryogenesis is a process by which somatic cells can be regulated to differentiate into embryos with similar morphological appearance as parental plant by the use of plant growth regulators. There are three main developmental stages of somatic embryogenesis, namely, induction of conversion callus, maturation of somatic embryo, and plantlet regeneration. However, the callus could develop into soft, granular and translucent tissues which do not have embryogenic potential and incapable of regeneration into a new plantlet. The callus formation and development of somatic embryos become one of the major bottlenecks in oil palm tissue culture as well as the clonal abnormality problem. A very low rate approximately 19% of callogenesis of oil palm have been reported by Corley and Tinker (2003) and an average rate of embryogenesis in leaf derived callus is only 6% (Wooi, 1995). To date, there are little that has been known about the molecular changes associated with callogenesis and embryogenesis in oil palm. Malaysia Palm Oil Board (MPOB) has been actively working on the gene expression studies in both embryogenesis and clonal abnormality. Some potential gene markers have been identified but functionality of these proteins associated with embryogenesis is still unknown (Sambanthamurthi et al., 2009). The aim of this experiment is to employ a proteomic approach to determine the protein expression profile in the low and high proliferation rate of callus in oil palm tissue culture.

Material and Methods Plant material Young (cabbage) and old leaves of oil palm (Elaeis guinensis Jacq.) were collected from Applied Agriculture Resource (AAR) and MPOB, Malaysia. All samples were stored at –80°C until use. Leaves were transferred to a prechilled mortar, frozen in liquid nitrogen and ground into a 0.2g fine powder. Total proteins were extracted using a trichloroacetic acid (TCA)/acetone method. TCA/acetone precipitation method


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Proteins were extracted according to a protocol modified from Gómez-Vidal et al. (2008). Four volumes of icecold 10% (v/v) TCA in acetone containing 20 mM dithiothreitol (DTT) were added to 0.2 g leaf tissues fine powder. Proteins were precipitated for one hour at –20ºC and centrifuged at 20,000 rpm for 30 minutes at 4ºC. The pellet was washed twice for 30 min each time with ice-cold acetone containing 20 mM DTT. The pellet was air dried and dissolved in 2D electrophoresis rehydration solution consisting of 8 M urea, 4% CHAPS, 0.2% carrier ampholytes, and 18 mM DTT. Two-dimensional gel electrophoresis The protein content was measured using the Bradford method. For 2D electrophoresis, isoelectric focusing (IEF) dimension was conducted on 7 cm IPG strips with a linear pH gradient of 4-7. The IPG strips were rehydrated and focused using the PROTEAN®IEF System (BioRad) at maximum of 50 µA per strip at 20ºC. The program used was a linear increase from 0 to 250 V over 20 min, 250 to 4000 V for 2 h and then a rapid gradient from 4,000 V up to total focusing of 10,000 Vh. After IEF, the IPG strips were equilibrated in an equilibration buffer (50 mM Tris-HCl, pH 8.8, 6 M Urea, 30% w/v glycerol, 2% w/v SDS) containing 2% w/v DTT for 15 min, followed by incubation for 15 min in the same buffer containing 135 mM iodoacetamide instead of DTT. The strips were transferred to 12% SDSPAGE gels for the second dimension separation using SDS electrophoresis buffer (250 mM Tris-HCl, pH 8.3, 1.92 M glycine, 1% SDS) with 150 V applied for approximately 1.5 h. The gels were stained with Coomassie blue and digital images captured on a densitometer (BioRad) and analysed using PDQuest software 8.0.1 (BioRad).

Results and Discussion Two categories of the oil palm leaves samples have been identified as high and low proliferation rate based on previously recorded tissue culture performances. Sample AN 25 and AN 28 were categorized as high proliferation rate, while AN 27 and AN 29 were grouped as low proliferation rate. Proteins were extracted from the four samples and separated using two-dimensional gel electrophoresis. Images of the 2D gel protein profiles were captured digitally and analysed using dedicated protein 2D gel analysis software. kDa 200

pI 4

pI 7

pI 4

pI 7

a

b

c

d

100 70 50 40 30 25

10 kDa 200 100 70 50 40 30 25

10

Fig. 1. 2D gel images for AN 25 (a), AN 28 (b) which were high proliferation rate samples, AN 27 (c) and AN 29 (d) which were low proliferation rate samples Fig. 1 shows the 2D gel images for the two categories namely, the high proliferation rate (Fig. 1a and b) and low proliferation rate (Fig. 1c and d) samples. Each sample was run in triplicate. All the gel images were subjected to PDQuest software for automated spot detection, matching, normalization and quantification. After matching all the protein spots, the gels were analyzed for statistically significant in fold change differences between samples. A total of 14 spots exhibited a statistically significant difference of at least a 2 fold change between the high and low proliferation rate samples. Finally, each of the selected spots was checked manually on every gel. Of the 14, 8 proteins were found to be lower in abundance, 1 protein was higher in abundance in low proliferation rate samples compared to higher proliferation rate samples, and 5 protein spots are present only in the high proliferation rate samples (Table 1, Fig. 2).

Proteomic Analysis of Oil Palm Leaves with High and Low Proliferation Rate in Callusing

kDa

pI 4

71

pI 7

200 100 70 4501

50

3401 3402 4403

40 30

6201 2201

3205

25

6203 2202 2203

5204 2104 6103

1113

10

Fig. 2. Protein spots that exhibit significant differences between high and low categories are shown. Table 1. Fourteen protein spots from the low and high proliferation gels exhibit statistically significant differences. Categories

Spots number

Value Differences

pI/ MW

Lower protein abundance in low proliferation samples

SSP3401 SSP4403 SSP4501 SSP2201 SSP 2202 SSP3205 SSP6201 SSP6203 SSP6103

2.525 2.325 1.375 1.125 1.425 6.925 9.105 4.305 3.094

4.90/46.1 5.40/44.1 5.30/55.9 4.62/27.5 4.63/25.0 5.20/26.0 5.90/26.5 6.20/26.7 6.00/14.3

SSP1113 SSP2104 SSP2203 SSP3402 SSP5204

8.475 2.625 3.375 3.175 6.225

4.50/16.8 4.90/19.2 4.75/15.0 5.20/45.6 5.80/19.5

Higher protein abundance in low proliferation samples Present in only the high proliferation rate samples

Conclusion In this study, we used oil palm leaves as explant materials to study the protein profiles between high and low proliferation rate in callogenesis. A total of 14 protein spots were founds to be statistically different between the two conditions. These 14 protein spots are very promising for our future work in identifying proteins that are associated with the process of embryogenesis in oil palm.

References Corley RHV, Tinker PB (2003) The oil palm. 4th Ed. Oxford, Blackwell Science Ltdp 562. ISBN 0-632-05212-0 Gómez-Vidal S, Tena M, Lopez-Llorca LV, Salinas J (2008) Protein extraction from Phoenix dactylifera L. Leaves, a recalcitrant material, for two-dimensional electrophoresis. Electrophoresis., 29,448-456 Low ET, Alias H, Boon SH, Shariff EM, Tan CY, Ooi LCL, Cheah SC, Raha AB, Wan KL, Singh R (2008) Oil palm (Elaeis guineensis Jacq.) tissue culture ESTs: Identifying genes associated with callogenesis and embryogenesis. BMC Plant Biol., 8, 62 Rohani O, Sharifah SA, Rafii MY, Ong M, Tarmizi AH, Zamzuri I (2000) Tissue culture of oil palm. In Advances in Oil Palm Research. Edited by: Basiron Y, Jalani BS, Chan KW. Bangi: Malaysian Palm Oil Board, 238-283 Sambanthamurthi R, Singh R, Kadir APG, Abdullah MO, Kushairi A (2009) Opportunities for the Oil Palm via Breeding and Biotechnology. In Breeding Plantation Tree Crops: Tropical Species. (Eds. Jain SM and Priyadarsham PM) Springer Science+ Business Media, LLC 377-421 Thuzar M, Vanavichit A, Tragoonrung S, Jantasuriyarat C (2010) Efficient and rapid plant regeneration of oil palm zygotic embryos cv. ‘Tenera’ through somatic embryogenesis. Acta Physiol. Plant., 33, 123-128 Wooi KC (1995) Oil palm tissue culture - current practice and constraints. In: Rao V, Henson IE, Rajanaidu N. Eds. Recent developments in oil palm tissue culture and biotechnology. Malaysia, Malaysian Palm Oil Board, pp 2132

Proteomics Analysis of Soybean and Flax Adaptation in Radioactive Chernobyl Area Katarína KLUBICOVÁ1, Maksym DANCHENKO1,4, Ludovit SKULTETY2,3, RASHYDOV4, Martin HAJDUCH1*

Namik M.

1

Institute of Plant Genetics and Biotechnology, Slovak Academy of Sciences, Nitra, SLOVAKIA Institute of Virology, Slovak Academy of Sciences, Bratislava, SLOVAKIA 3 Center of Molecular Medicine, Slovak Academy of Sciences, Bratislava, SLOVAKIA 4 Institute of Cell Biology and Genetic Engineering, National Academy of Sciences of Ukraine, Kyiv, UKRAINE * Corresponding author: [email protected] 2

Abstract The recent tragedy at the Fukushima Nuclear Power Plant is sadly reminiscent of the nuclear disaster at Chernobyl, Ukraine, 25 years ago. Unexpectedly, plants grow and successfully reproduce in Chernobyl area that remains substantially contaminated with long-lived radioisotopes such as 90Sr and 137Cs. The aim of our work is to investigate the mechanisms underlying plant adaptation to these conditions. For this purpose, seeds of local varieties of soybean (Soniachna) and flax (Kyivskyi) were grown in Chernobyl region. Total protein fractions have been isolated annually from mature and developing seeds, and analyzed using 2-dimensional electrophoresis and tandemmass spectrometry. Based on the results, the working models for plant adaptation in radioactive Chernobyl area were proposed.

Introduction The accident at Chernobyl Nuclear Power Plant (CNPP) was the most serious nuclear disaster in the history. The accident released large number of radioactivity. Now, 25 year after the accident, the long living isotopes such as 137Cs or 90Sr still persists in the environment (Møller and Mousseau, 2006). Surprisingly, plants grow and successfully reproduce in radioactive Chernobyl area and the United Nations (UN) report on Chernobyl have officially stated that the ecosystem was rebound (Chernobyl forum, 2005). However, this unexpected ability of plants to adapt to a radioactive environment is not well understood. Only partial information is available from genomic and proteomics analyses. For instance it is known, that plants that grow in radioactive Chernobyl area are significantly hypermetylated to protect their genome (Kovalchuk et al., 2003). Strikingly, this not prevent mutations in wheat grow (Kovalchuk et al., 2000). Additionally, it was observed that progenies of plants from radioactive Chernobyl are resisting higher levels of mutagens (Kovalchuk et al., 2004). The aim of our research is to elucidate plant adaptation in radioactive Chernobyl using a postgenomic methodology, proteomics. For this purpose, the experimental fields were established in Chernobyl area (Fig. 1). Since 2007, soybean and flax are grown in radioactive and control fields developing seeds are harvested along with mature seeds on yearly basis. This provides unique opportunity to follow plants during their adaptation toward radioactive conditions and elucidate changes in seed proteome through generations.

Fig. 1. The location of experimental fields in Chernobyl area. Radioactive field is located 5 km from Chernobyl Nuclear Power Plant and have radioactivity 20650±1050 Bq/kg of 137Cs and 5180±550 Bq/kg of 90Sr. Control field is located in remediated are of Chernobyl town and have radioactivity 1414±71 Bq/kg of 137Cs and 550±55 Bq/kg of 90Sr.

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Materials and Method Plant material and experimental fields Soybean (Glycine max [L.] Merr.; variety Soniachna) and flax (Linum ussitatissimum, L.; variety Kyivskyi) were grown in two locations near the CNPP (Fig. 1). The radioactive field is 5 km from CNPP, near the village Chystogalivka (Fig. 1). The soil contained 20650 ± 1050 Bq kg-1 of 137Cs and 5180 ± 550 Bq kg-1 of 90Sr. The control field is in a remediated area of Chernobyl town, where the soil contained 1414 ± 71 Bq kg-1 of 137Cs and 550 ± 55 Bq kg-1 of 90Sr. Both fields have similar agrochemical properties and contain sod-podzol soil (pH 5.5), that includes 12% clay and 2% of organic material. Radioactivity Measurements The 137Cs in the samples was quantified using γ-spectrometry as described previously (Methodical recommendation, 1980). Measurements were performed using semi-conductivity coaxial detector of superpure germanium, with an energetically resolved 1332.5 keV peak of 60Co with 60% γ-quantum efficiency (Canberra, Meriden, CT, USA). Instrument calibration used a standard, loose gauge EM66 with poured consistence of 1.1 g cm3, and after validation yielded an uncertainty value for 137Cs of 7% for 2σ. 90Sr was quantified using β-radiometry and a low-background UMF-1500M instrument as previously described (Berlizov et al., 2005). Protein analysis by two-dimensional electrophoresis Seeds (500 mg) were ground to a fine powder with liquid N using a mortar and pestle and proteins were extracted in biological triplicate as described earlier (Danchenko et al., 2009). Isolated proteins were quantified using the Bradford Reagent (Sigma-Aldrich, Saint Louis, MO) with BSA as the standard. Prior isoelectric focussing, proteins were dried under reduced pressure, resolubilized in 0.5 mL of immobilized pH gradient (IPG) buffer containing 8 M urea, 2 M thiourea, 2% CHAPS, 2% Triton X-100, and 50 mM DTT with gentle agitation for 30 min at 4°C. Insoluble material was removed by centrifugation for 20 min at 14000g at 4°C. Protein samples (700 µg) were stored at -80°C until the analysis. Prior to isoelectric focusing (IEF), 2% (v/v) of pH 4-7 carrier ampholytes were added and the samples were loaded onto IPG strips (pH 4 to 7; 17 cm; Bio-Rad, Hercules, CA). The volumes of the samples containing 700 µg protein were adjusted with IPG buffer to 340 µL. Samples were vortexed, then centrifuged at 24,000 g for 5 min at 4°C. Supernatants were transferred to the focusing trays, and the dehydrated strips were placed onto the sample. After 1 h of passive rehydration, strips were overlayed with mineral oil and placed into the IEF unit (Protean IEF Cell, Bio-Rad, Hercules, CA). The unit was programmed for active rehydration for 10 h at 50V, followed by a three-step focusing protocol with current limit 50 µA per line with rapid slope in every step: a) 100 Vh at 100 V, b) 500 Vh at 500 V, c) 70000 Vh at 8000 V. After IEF excess mineral oil was removed and the strips were equilibrated for 15 min in 4 ml of reduction solution (2% DTT in equilibration buffer containing 1.5 M Tris, pH 6.8, 6 M urea, 30% glycerol, and 5% SDS), and for 15 min in 4 mL of 2.5% iodoacetamide in equilibration buffer. The strips were rinsed in running buffer (25 mM Tris, 192 mM glycine, 0.1% SDS), placed on top of a SDS-gel (4% stacking and 12% separation gel), and overlaid with sealing solution (0.5% (v/w) agarose in running buffer with 0.002% bromphenol blue as the tracking dye). Second dimension separations were carried out using Protean II xi Cell (Bio-Rad), at 10 mA current for approximately 14 h until dye migrated off of the gel. After completion of two-dimensional electrophoresis (2-DE), the gels were washed three times for 15 min in deionized water, and stained overnight in Colloidal Coomassie (20% ethanol, 1.6% phosphoric acid, 8% ammonium sulfate, 0.08% Coomassie Brilliant Blue G-250). The 2-D gels were digitalized using a GS-800 Calibrated Densitometer (Bio-Rad) at 300 dpi and a 16 bit grayscale. Digitalized gels were analyzed using ImageMaster software 4.9 (GE Healthcare, Uppsala, Sweden) that include spot detection, quantification, background subtraction, and spot matching between multiple gels. To compensate for minor differences in sample loading and gel staining, the volume of each spot (spot abundance) was normalized as relative volume. This normalization method divides each spot volume value by the sum of total spot volume values in order to calculate relative volumes for individual spots. The volumes of spots excluded from the analysis were not considered. Each analyzed gel was matched to the reference gel, and expression profiles were created. Protein identification For protein identification, 2-DE spots were excised, washed at least 3 times for 15 min with 500 µL of 50% acetonitrile in 50 mM ammonium bicarbonate, until the Coomassie dye was completely removed. The gel plugs were then dehydrated in 100 µL of 100% acetonitrile for 5 min and rehydrated in 20 µL of digestion solution (20 µg of lyophilized modified sequencing grade trypsin (Promega) per 1 mL of 50 mM ammonium bicarbonate). Following overnight digestion at 37°C, the tryptic peptides were extracted twice with 50 µL of 60% acetonitrile containing 1% formic acid with continuous agitation for 10 min. Extracts were pooled, transferred to a microplate and lyophilized. Tryptic peptides were separated by automated nanoflow reverse-phase chromatography using a nanoAcquity UPLC system coupled to a Q-TOF Premier (Waters, Milford, MA, USA) instrument and analyzed by MS/MS. Samples were injected onto the column (nanoAcquity UPLC column BEH 130 C18, 100 µm x 150 mm, 1.7 µm particle size); the mobile phase was an acetonitrile gradient (3-50% B in 15 min; A = water with 0.1% formic acid, B = acetonitrile containing 0.1% formic acid) at a flow rate of 350 nL/min. The column was connected to the PicoTip emitters (New Objective, New Objective, MA, USA) mounted into the nanospray source. A nano-electrospray voltage of 3.5 kV was applied, with the source temperature set to 70°C. The spectral acquisition scan rate was 0.6 s, with a 0.1 s interscan delay. In the low energy MS mode, data were collected at constant collision energy of 3 eV. In

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the elevated energy MS mode the collision energy was ramped from 20 eV to 35 eV during each integration. The MS spectra obtained at different collision energies were stored separately. During data acquisition the quadrupole analyzer was not mass selective but operated in the radio-frequency only mode. Thus, all ions were passed to the TOF analyzer. This yielded exact mass fragment ions that were potentially observed for every peptide precursor ion present in the low-energy TOF dataset. All the samples were analyzed in triplicate. The MS/MS data were processed using the ProteinLynx Global Server v. 2.4 (Waters, Milford, MA, USA) that includes background-subtraction, smoothing, centroiding, and deisotoping. All data were lockspray calibrated against GFP using data collected from the reference line during acquisition. The lockmass-corrected data were charge-state reduced to produce a single accurately mass measured monoisotopic mass for each peptide and the associated fragment ion. The initial correlation of precursor and fragment ions was achieved by means of time alignment. The resulting data were searched against non-redundant UniProt Glycine max database (March 1 2011; 15,416 entries) and UniProt Linum database (April 14 2011; 389 entries). Unidentified MS spectra were searched against non-redundant UniProt Viridiplantae database (March 1 2011; 811,908 entries). The variable modifications of carbamidomethyl-C, oxidation M, deamidation Q, deamidation N, acetylation N -terminus were specified. One missed cleavage site was allowed. Parameters for accepting the protein identification were; i) detection of at least three fragment ions per peptide, ii) a minimum of two peptides matched to the protein sequence, and iii) a 50 ppm tolerance of databasegenerated theoretical peptide ion masses.

Results and Discussion To closely investigate changes in seed proteome of plants grown in radioactive Chernobyl area, soybean and flax mature seeds were harvested from experimental fields in Chernobyl area (Fig. 1) and subjected to comparative quantitative proteomics study. Proteins isolated were firstly analyzed by 2-DE (Fig. 2).

Fig. 2. Protein 2-DE gels of soybean and flax mature seeds harvested form control and radioactive Chernobyl area. Resulted 2-DE gels were analyzed by computer-assisted approach to detect differentially abundant proteins between seeds harvested from control and radioactive field. Based on the identity of differentially abundant soybean proteins, a working model of soybean response toward contaminated conditions was proposed (Danchenko et al., 2009). Seed storage proteins (SSP) changed their abundance in response toward radioactive conditions (Fig. 3). It is known that SSP respond to various stresses by undergoing changes in their composition. For instance, the application of salicylic acid caused mobilization of SSP during seed germination of A. Thaliana (Rajjou et al., 2006) and the abundance of alfa subunit of beta conglycinin was changed upon salt stress (Aghaei et al., 2008). Seed Storage Proteins have additional roles besides seed storage reserves (Sales et al., 2000). Surprisingly, 2S albumin can function as a defence protein (Regete et al., 2001). Comparative proteomics study of mature soybean seed proteins revealed that around 50% of the proteins that were found differentially abundant were SSP. Seed Storage Proteins produce a high number of 2-DE species during seed development (Agrawal et al., 2008) that their abundance profiles are of complex nature (Hajduch et al., 2005). The complex behaviour of SSPs in mature soybean seeds harvested from radioactive Chernobyl area supports additional roles of SSP behind storage reserves. Soybean grown in radioactive Chernobyl area exhibited also “heavy metal stress”-like response. Cysteine synthase was found to be three times higher abundant in the seeds from radioactive area. This suggests increase in cysteine production that plays important role in adaptation toward heavy metal stress (Steffens, 1990). Transgenic tobacco plants over-expressing a cysteine synthase gene increase their tolerance against heavy metals stress (Harada et al., 2001). Additionally, transgenic rice over-expressing cysteine synthase gene increase their tolerance against cadmium, selenium, nickel, lead, and copper (Kawashima et al., 2004). Importantly, over-expression of cysteine synthase in transgenic tobacco plants had also protective effect toward sulfur-containing environmental pollutants (Noji et al., 2001). Soybean study also detected four differential abundant dehydrins that are stress-inducible proteins, that accumulate in vegetative plant tissues (Ingram and Bartels, 1996; Rorat, 2006). Dehydrins role in plant protection against heavy metals was confirmed on Phaseolus vulgaris (Zhang et al., 2006) and other transgenic plants (Xu et al., 2008). Soybean study also revealed differential abundance of peroxisomal betaine aldehyde

Proteomics Analysis of Soybean and Flax Adaptation in Radioactive Chernobyl Area

75

dehydrogenase exhibited in the seeds harvested from contaminated field. Betaine aldehyde dehydrogenase catalyzes the last step in glycine betaine synthesis (Nakamura et al., 2001) Interestingly, glycine betaine have a protective effect against radiation-induced damage in human blood in vitro (Monobe et al., 2005).

soybean Chernobyl contaminated conditions mobilization of SSPs

adaptation toward heavy metals

protection against radiation damage

Fig. 3. Working model for soybean response toward radioactive Chernobyl area. This model suggest that Seed Storage proteins (SSP), adaptation toward heavy metals and protection toward radiation damage are important for soybeans response toward radioactive conditions. Involvement of glycine betaine in response toward radioactive Chernobyl conditions was detected also in flax mature seeds harvested form radioactive area (Klubicova et al., 2010). Choline monooxygenase, which catalyzes the first step of the glycine betaine biosynthetic pathway in plants (Burnet et al., 1995), was differentially abundant. Based on the identity of differentially-abundant proteins in flax seeds harvested from the radio-contaminated Chernobyl area, working model for flax response toward radioactive Chernobyl environment was constructed (Fig. 4).

Fig. 4. Working model for flax response toward Chernobyl radioactive conditions. This model suggest involvement of Signalling (1), Stress response (2), Transcription (3), Translation (4), Secretion (5), Phosphorylation (6), Hormones (7), Alarmones (8), Betaine (9), and Respiration (10) in flax response toward radio-contaminated environment. The working model suggest involvement of signalling, protein phosphorylation, and hormones/alarmones; transcription, translation, the secretory pathway, stress, respiration, and glycine betaine metabolism. These pathways present an interacting network, where signalling, the stress response, and transcription are considered primary events (Armengaud, 2010). The changes in signalling are transduced via protein phosphorylation and phospho-protein interactions, which then lead to hormone and alarmone production. We speculate, that activation of the stress response (Fig. 4) might lead directly to changes in glycine betaine synthesis and in respiration. The network might be either more or less branched. For example, signalling might directly involve the ubiquitin/26S proteasome component without any prior or subsequent involvement of protein phosphorylation or hormones/alarmones. Likewise, an increase in respiration might precede changes in transcription/translation/secretion. This initial network is effected substantially by the numbers of proteins assigned to the functional clusters and the decision to consider the most populated clusters as primary hubs (Guimerà and Nunes Amaral, 2005).

Conclusion Comparative proteomics analyses of first generations of mature seeds harvested from Chernobyl experimental fields revealed different response of soybean and flax toward radioactive conditions. While soybean response was based on mobilization of SSP, flax responded with changes of abundance in proteins associated with Signalling and Transcription. However, both plants exhibited changes in proteins associated with Disease/Defence as response toward radioactive conditions. The analyses of next generations of soybean and flax plants grown in Chernobyl area are in progress and will refine these studies.

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References Agrawal GK, Hajduch M, Graham K, Thelen JJ (2008) In-depth investigation of the soybean seed-filling proteome and comparison with a parallel study of rapeseed. Plant Physiol., 148, 504-518 Aghaei K, Ehsanpour AA, Shah AH, Komatsu, S (2008) Proteome analysis of soybean hypocotyl and root under salt stress. Amino Acids, 7, 4858-4868 Armengaud J (2010). Proteogenomics and systems biology: quest for the ultimate missing parts. Expert Rev. Proteomics, 7, 65-77 Berlizov AN, Sajeniouk AD, Tryshyn VV (2005) A Technique for Stronsium-90, Plutonium and Americium Isotope Content Determination in Environmental Samples. J. Radioanal. Nucl. Chem., 263, N 2, 307 Burnet M, Lafontaine PJ, Hanson AD (1995) Assay purification and partial characterization of choline monooxygenase from spinach. Plant Physiol., 108, 581-588 Chernobyl Forum. (2005). Chernobyl: The True Scale of the Accident. 20 Years Later a UN Report Provides Definitive Answers and Ways to Repair Lives, IAEA, WHO, UNDP. Danchenko M, Skultety L, Rashydov N, Berezhna V, Matel L, Salaj T, Pretova A, Hajduch M (2009) Proteomic analysis of mature soybean seeds from the Chernobyl area suggests plant adaptation to the contaminated environment. J. Proteome Res., 8, 2915-2922 Guimerà R, Nunes Amaral LA (2005) Functional cartography of complex metabolic networks. Nature, 433, 895-900 Hajduch M, Ganapathy A, Stein JW, Thelen JJ (2005) Systematic proteomic study of seed filling in soybean. Establishment of high-resolution two-dimensional reference maps, expression profiles, and an interactive proteome database. Plant Physiol., 137, 1397-1419 Harada E, Choi YE, Tsuchisaka A, Obata H, Sano H (2001) Transgenic tobacco plants expressing a rice cysteine synthase gene are tolerant to toxic levels of cadmium. J. Plant Physiol., 158, 655–661 Ingram J, Bartels D (1996) The molecular basis of dehydration tolerance in plants. Annu. Rev. Plant Physiol. Plant Mol. Biol., 47, 377-403 Kawashima CG, Noji M, Nakamura M, Ogra Y, Suzuki KT, Saito K (2004) Heavy metal tolerance of transgenic tobacco plants over-expressing cysteine synthase. Biotechnol. Lett., 26, 153-157. Klubicová K, Danchenko M, Skultety L, Miernyk JA, Rashydov NM, Berezhna VV, Pret'ová A, Hajduch M (2010) Proteomics analysis of flax grown in Chernobyl area suggests limited effect of contaminated environment on seed proteome. Environ. Sci. Technol., 44, 6940-4946 Kovalchuk O, Burke P, Arkhipov A, Kuchma N, James SJ, Kovalchuk I Pogribny I (2003) Genome hypermethylation in Pinus silvestris of Chernobyl-a mechanism for radiation adaptation? Mutat. Res., 529, 13-20 Kovalchuk O, Dubrova YE, Arkhipov A, Hohn B, Kovalchuk I (2000) Wheat mutation rate after Chernobyl. Nature, 407, 583-584 Kovalchuk I, Abramov V, Pogribny I, Kovalchuk O (2004) Molecular aspects of plant adaptation to life in the Chernobyl zone. Plant Physiol., 135, 357-363 Methodical recommendation on sanitary control of radioactivity substance in the objects environmental. M., MH USSR, 1980, 356 Møller AP, Mousseau TA (2006) Biological consequences of Chernobyl: 20 years on. Trends Ecol. Evol. 21, 200-207. Nakamura T, Nomura M, Mori H, Jagendorf AT, Ueda A, Takabe T (2001) An isozyme of betaine aldehyde dehydrogenase in barley. Plant Cell Physiol., 42, 1088-1092 Monobe M, Uzawa A, Hino M, Ando K, Kojima S (2005) Glycine betaine, a beer component, protects radiationinduced injury. J. Radiat. Res. Tokyo, 46, 117-121 Noji M, Saito M, Nakamura M, Aono M, Saji H, Saito K (2001) Cysteine synthase overexpression in tobacco confers tolerance to sulfur-containing environmental pollutants. Plant Physiol., 126, 973-980 Rajjou L, Belghazi M, Huguet R, Robin C, Moreau A, Job C, Job D (2006) Proteomic investigation of the effect of salicylic acid on Arabidopsis seed germination and establishment of early defense mechanisms. Plant Physiol., 141, 910-923 Regente M, De La Canal L (2001) Are storage 2S albumins also defensive proteins? Physiol. Mol. Plant Pathol., 59, 275-276 Rorat T (2006) Plant dehydrins--tissue location, structure and function. Cell Mol. Biol. Lett., 11, 536-556 Sales MP, Gerhardt IR, Grossi-De-Sá MF, Xavier-Filho J (2000) Do legume storage proteins play a role in defending seeds against bruchids? Plant Physiol., 124, 515-522 Steffens JC (1990) The heavy metal-binding peptides of plants. Annu. Rev. Plant Physiol. Plant Mol. Biol., 41, 553– 575 Xu J, Zhang YX, Wei W, Han L, Guan ZQ, Wang Z, Chai TY (2008) BjDHNs confer heavy-metal tolerance in plants. Mol. Biotechnol., 38, 91-98 Zhang Y, Li J, Yu F, Cong L, Wang L, Burkard G, Chai T (2006) Cloning and expression analysis of SKn-type dehydrin gene from bean in response to heavy metals. Mol. Biotechnol., 32, 205-218

Phosphorus Starvation Changes the Metabolic Flow in Rice Takuro SHINANO1*, Akira SAITO2, Jun WASAKI3, Mitsuru OSAKI2 1

NARO Hokkaido Agricultural Research Center, Sapporo 062-8555, JAPAN, Hokkaido University, Graduate School of Agriculture, Sapporo 060-8589, JAPAN, 3 Hiroshima University, Graduate School of Biosphere Science, Higashi-Hiroshima 739-8521, JAPAN *Corresponding author: [email protected] 2

Abstract Phosphorus (P) is one of the three major fertilizers whereas P resource depletion and pollution by phosphate (Pi) fertilization become huge issues. Therefore effective ways of using Pi are needed. Change of metabolism in rice was observed by using transcriptomic analysis under not only low P conditoin but also at P replenishment treatment. To obtain further investigation about P tolerance mechanism of the rice plant, transcriptomic and proteomic analyses were conducted simultaneously. For transcriptomic analysis, about 22,000 mRNA were analyzed by oligo DNA microarray. For proteomic analysis, residues of SDS-phenol method to extract mRNA were applied to protein extraction. These proteins were separated by 2D-PAGE, and 60 spots were identified by peptide mass finger printing. As a result, metabolic change of glycolysis is commonly upregulated at mRNA and protein level in low P treatment root. But coefficients of correlation between mRNA and protein expression were very low. Voltage dependent anion selective channel (VDAC) protein was increased over 3-fold under P starvation. This could mean a part of P tolerance system involved in organic acid secretion. However, mRNA coding VDAC was not changed. Therefore, protein level analysis to low-P tolerance is supposed to be needed.

Introduction It is considered that plant has developed two major strategies to overcome low phosphorus condition of the soil. As inorganic phosphate (Pi) is very active and binds to iron, calcium, aluminum, and organic compounds, then makes scarcely soluble compounds in the soil. Which makes the plant more difficult to uptake phosphorus nutrition form the root. One strategy is secreting several compounds is known, such as organic acids (Kraffzyk et al., 1984). It is well known that citrate and malate are the primary components to solubilize inorganic P in the soil (Jones, 1998). though root morphology change is also important (He et al., 2003), t he other important strategy is internal P recycling mechanism. Nanamori et al. (2007) demonstrated that several enzyme activities such as acid phosphatase and ribonuclease increased when the plant suffered with low P condition, and it is suggested that these enzymes may contribute higher rate of cellular P compounds recycling (may be contributing higher rate of retranslocation from older organs to growing organs). On the other hand, many researches have used microarray to investigate the physiological change under P deficiency, and these trials reveal that carbon metabolism is tightly linked with P status in the plant such as facilitating carbon flow in the chloroplast (Shinano et al., 2005), more general carbon flow to support glycolysis (Wasaki et al., 2003, 2006). Though comprehensive analysis of mRNA expression is very powerful and sophisticated way to analyze plant response to the stress, it should be mentioned that mRNA expression is not the only mechanism to change the physiological status of plant. It is also important post-translational modification and expression of mRNA to proteins (Plaxton and Tran, 2011), thus as the actual player for the metabolism is enzymes in the cell, it should be mentioned about protein also. Comparative proteome analysis is also carried out to investigate plant response to P deficiency in rice (Fukuda et al., 2007; Torrabi et al., 2009). From the proteomic analysis also support the major change in the flow of carbon metabolism. In this study, we performed simultaneous transcriptome and proteome analysis on one sample to obtain the data of mRNA expression and protein expression together.

Materials and Methods Sample preparation Seeds of rice (Oryza sativa L. cv. Michikogane) were sterilized with 5 % NaClO for 5 min then washed thoroughly with sterile tap water. Sterilized seeds were transferred to a 1 mM CaCl 2 solution then germination was performed under a constant condition (30˚C, 24 h dark) in a growth chamber (LPH-200-RDSMP, NK System, Osaka, Japan) with aeration. After 48 hours, each seed was transplanted to a floating with 1 mM CaCl 2 under a constant condition (30˚C, 24 h light, 130 µmol photons m-2 s-1 at leaf level) for 7 days. Then the plant was transplanted to a nutrient solution with or without P. The concentration of each element is as follows: NH 4 NO 3 0.83mM, NaH 2 PO 4 2H 2 O 32.36 µM (only under + P treatment), K 2 SO 4 0.19 mM, KCl 0.38 mM, CaCl 2 2H 2 O 0.75 mM, MgSO 4 7H 2 O 0.82 mM, Fe(III) EDTA 35.85 µM, MnSO 4 5H 2 O 9.11 µM, H 3 BO 3 46.30 µM, ZnSO 4 7H 2 O 3.06 µM, CuSO 4 5H 2 O 0.16 µM, (NH 4 ) 6 Mo 7 O 24 4H 2 O 7.40 nM, and the pH was adjusted to 5.2. Thirty plants were grown in a 4 liter vat and the nutrient solution was renewed every day. After 8 days of the cultivation, a part of the sample with or

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without P treatment was sampled and the remained plants were continued to grow for another one day. Half of –P treated plant was transferred to +P treatment for one day, and we call this treatment as P resupply treatment. Harvested plants were separated into shoots and roots. Half of the samples was immediately frozen by dipping in a liquid nitrogen for RNA and protein extraction. Before the extraction of protein, RNA was extracted from the sample by SDS-phenol method (Palmiter, 1974). To obtain mRNA, frozen sample (ca. 1 g) was homogenized in a mortar then extracted by an 0.5 ml of extraction buffer (200 mM Tris-HCl pH 9.0, 100 mM NaCl, 10 mM EDTA, 0.5 % SDS, 14 mM β-mercaptoethanol), then added 0.5 mL of TE (10 mM Tris-HCl pH 8.0, 0.1 mM EDTA) saturated phenol. The mRNA was obtained from the aqueous fraction and remained water insoluble fraction was subjected for the protein extraction. One ml of homogenization buffer (0.5M Tris-HCl pH 7.5, 0.7 M sucrose, 50 mM EDTA, 0.12 M KCl, 10 mM thiourea, 2 mM PMSF, and 2% 2-mercaptoethanol) was added to protein fraction and extracted with gentle shaking by a mixer (MILD MIXER OR-24, TAITEC, Japan) for 30 min at room temperature. After the centrifugation with 11,833 x g for 20 min at room temperature, the lower phenol layer and interstratified layer was taken for another clean tube. This process was repeated until the pure phenol layer was obtained, then equal amount of 0.1 M ammonium acetate in methanol was added and stood still at –20˚C over night. The precipitation was obtained after the centrifugation (11,833 x g, 20 min at 4˚C) and 1.5 m L of DTT/acetone solution (0.07% DTT) was added then homogenized on iced water using ultrasonic bath (15 to 45 min), then centrifuged again (11,833 x g, 20 min at 4 ˚C) and the supernatant was discarded. This step of washing the pellet was repeated twice then the pellet was dried under vacuum. The pellet was resolubilized on iced water using ultrasonic bath (about 15 min) in 50 µl of Lysis buffer (7 M urea, 2 M thiourea, 4% CHAPS, and 65 mM DTT). Protein concentration was determined by Bradford method (Bradford, 1976) with bovine serum albumin as a standard. The remaining samples were weighed and placed under 105˚C for 72 h for the determination of phosphorus content. Separation of protein by 2 dimensional gel electrophoresis The method is based on O’Farrell (1975) with modification as follows. Three hundred µg protein was mixed with 1.5 µl BIO LYTE 3/10 (Bio-Rad) then total volume was adjusted to 300 µl with Lysis buffer. This sample was added to 17 cm Focusing tray (Bio-Rad), then IPG ReadyStrip pH 3-10 (Bio-Rad) was attached to the sample. The electrophoresis was done with 1 hr of rapid ramping with 1000 V, 5 hr of normal ramping with 1000 V then 6000 V hour of rapid ramping with 1000V. After electrophoresis, the IPG ReadyStrip was put on Swelling tray (Bio-Rad) then pured equilibration buffer (6 M urea, 2% SDS, 0.375 M Tris-HCl [pH 8.8], 4% glycerol, and 2.5% iodoacetamide) then equilibrated for 15 min. For the second dimension P II ready gel 10 % T (Bio-Rad Laboratories) was used. The equilibrated IPG ReadyStrip was put on the top of the P II ready gel, then low melting point agarose gel (0.5% agarose, 0.25 M Tris-HCl pH 6.8, 0.1% SDS) was used to attach them. The electrophoresis was done by PROTEAN II xi cell (Bio-Rad). BPB solution was added to the running buffer (25 mM Tris, 192 mM glycine, and 0.1% SDS), then the electrophoresis was done at constant voltage of 200 V. After electrophoresis, the gel was stained by staining solution containing 50 ml of CBB solution (1 tablet of PhastGel Blue R, (Amersham Pharmacia Biotech), H 2 O 80 ml and MeOH 120 ml) and 50 ml of 20% AcOH for 1 hr. Then destained by 25% MeOH, 7% AcOH in water. The stained gel was scanned by a scanner (EPSON ES-2200, 300dpi, 16bit, gray), then analyzed the signal intensity by using PDQuest (Bio-Rad). Peptide Mass Fingerprinting Spots on the gel were cut and placed in holes of 98 well PCR plate then treated with 50 mM ammonium bicarbonate in 50% acetonitrile for 10 min at RT. This treatment was repeated 3 times. Subsequently 100% acetonitrile was added and stood for 5 min at RT then dried up. Twenty µl of digestion reagent (Trypsine 23 µl, H 2 O 16 mL, 100 mM ammonium bicarbonate 0.46 mL, acetonitrile 0.46 mL) was added to each gel then the PCR plate was sealed and placed under 30˚C for one night. Then 1 µL of the digested peptide solution from gel was mixed with the same volume of Matrix solution (α-cyano-4-hydroxycinnamic acid 10 mg, acetonitrile 0.5 ml, MeOH 0.4 ml, trifluoroacetic acid 0.05 mL, H 2 O 0.1 mL), then dried up for the analysis by TOF-MS (Voyager DE-STR/15000, Applied Biosystems). For the standard of mass spectrum, AcTH18-39 and Angiotensin I were used. The obtained data were annotated by using MS-Fit (http://prospector.ucsf.edu/mshome4.0.htm) and Mascot (http://www.matrixscience.com/ home.html). Microarray analysis Rice Oligo Microarray (Agilent Technologies) was used and scanned by Agilent G2565BA Microarray Scanner (Agilent Technologies). Data analysis was performed according to the medhod of Wasaki et al. (2003, 2006). Fractionation of phosphorus compound in the plant To confirm alterations of plant phosphorus compounds, rice plant was further cultivated again. Rice seedlings aged 7 to 8 weeks were grown in 3 different P levels (0, 6.4, and 32 µM) containing nutrient solution for 2 weeks. Phosphorus compounds in plants was fractionated into the following six fractions: acid-soluble P, lipid-P, RNA-P, DNA-P, and residual P. Most of the residual-P fraction is considered to consist of protein P. Fractionation was done by modified STS (Schmidt-Thannhauer-Schneider) method with slight modifications to fractionate P compounds in plants (Mino et al., 1983, Watanabe et al., 1999; Yamamura et al., 2004). Phosphorus concentration in each fraction was measured by the molybdate-blue method.

Results and Discussion

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After total RNA extraction from the sample based on SDS-Phenol method, the protein fraction, which is normally discarded, was further used to extract protein. The scheme of the extraction procedure is shown in Figure 1. By using this technique, we consider that it is possible to compare mRNA and protein expression directly. In the case of proteome analysis we have applied 80 spots for the identification and 60 spots were annotated as rice protein. Obtained mRNA and protein data were subsequently subjected to KaPPA View (Tokimatsu et al., 2005). By using these 60 proteins and coding gene’s data were plotted in Fig. 2. Even though the RNA and protein sample were obtained from one sample in the continuous preparation method, the expression pattern was not consistent. Correlation between mRNA expression and protein level is thus suggested to be low, which has been mentioned by Anderson and Seihamer (1997) and Gygi et al. (1999). Though there was a difference between mRNA and protein expression (Table 1), carbon flow through glycolysis seems to be consistent regardless of mRNA or protein expression. The improved glycolytic metabolic flow was observed frequently by using microarray (Wasaki et al., 2003, 2006; Li et al., 2010). It is suggested that maintaining major metabolic flow is essential to survive stressed condition. The increase of voltage-dependent anion-selective channel protein (VDAC) is only observed in protein level, while those of sulfolipid related genes expression was observed only in mRNA level.

Fig. 1. Simultaneous extraction of mRNA and protein from one sample. The method is based on SDS-Phenol method, and the protein fraction after mRNA extraction was used for the protein extraction.

Fig. 2. Scatter plot of protein versus mRNA expression ratios to 9day+P. a) ratios of 9 day-P (replication 1), b) ratios of 9 day-P (replication 2), c) ratios of P rep. (replication 1), and d) ratios of P rep. (replication 2). Table 1. mRNA and protein expression change by the phosphorus treatments. Glycolysis TCA cycle Glumine synthesis Voltage-dependent anion-selective channel protein (VDAC) Glycolipid and sulfolipid pathway

-P treatment UP DOWN DOWN Not changed UP

UP? Not changed UP? UP

ND

P replenishment DOWN DOWN

Not changed UP?

DOWN Not changed

DOWN UP

UP

ND

UP and DOWN were evaluated based on the sample which has been continuously phosphorus supplied treatment. ND indicates that the protein was not detected in this study.


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To confirm whether any change was actually occurred in the lipid composition, we have roughly fractionated phosphorus compound based on their solubility (Fig. 3). It is indicated that Lipid-P fraction (phospholipid) was selectively decreased under the P deficient condition. Which indicate P deficiency may change the lipid composition from phosphorus-containing lipid to glyco- and/or sulfolipid. Based on the mRNA expression analysis by the oligoDNA microarray those genes involving the synthesis of glycolipid from UDP-galactose and sulfolipid from UDP-sulfoquinovose and also pathway from glyceraldehyde 3-phosphate also increased (data not shown).

Fig. 3. Distribution of P compounds in the rice under three levels of P supply. Rice seedlings aged 7 to 8 weeks were grown in P-deficit nutrient solution for 2 weeks. Phosphorus in plants was fractionated into the following six fractions: acid-soluble P, lipid-P, RNA-P, DNA-P, and residual P. Most of the residual-P fraction is considered to consist of protein P.

Conclusion Under P limiting condition, rice plant seems to develop not only single adaptive way but many metabolic flows may change in accordance with its physiological status. From this analysis, it is considered that lipid metabolism is also an important metabolic adaptation to low P condition of the plant. And it is indicated that combining different omics approaches will help to investigate the plant physiological status more precisely.

Acknowledgements Microarray analysis was supported by National Institute of Agrobiological Sciences, Japan. References Anderson L, Seihamer J (1997) A comparison of selected mRNA and protein abundances in human liver Electrophoresis 18, 533-537 Bhattacharyya, P., Datta SC, Dureja P (2003) Interrelationship of pH, organic acids, and phosphorus concentration in soil solution of rhizosphere and non-rhizosphere of wheat and rice crops. Commun. Soil Sci. Plant Anal., 34, 231245 Fukuda T, Saito A, Wasaki J, Shinano T, Osaki M (2007) Metabolic alterations proposed by proteome in rice roots grown under low P and high Al concentration under low pH. Plant Sci., 172, 1157-1165 Gygi S, Rochon Y, Franza BR, Aebersold R (1999) Correlation between protein and mRNA abundance in yeast. Mol. Cell. Biol., 19, 1720-1730 He Y, Liao H, Yan X (2003) Localized supply of phosphorus induces root morphological and architectural changes of rice in split and stratified soil cultures. Plant Soil, 248, 247-256 Jones DL. (1998) Organic acids in the rhizosphere: A critical review, University of Wales, Gwynedd. Kraffczyk I, Torlldenier G, Beringer H (1984) Soluble root exudates of maize: Influence of potassium supply and rhizosphere microorganisms. Soil Biol. Biochem., 16, 315-322 Li L, Qiu X, Li X, Wang S, Zhang Q, Lian X (2010) Transcriptomic analysis determined rice responses to low phosphorus stress. Chinese Sci. Bull., 55, 251-258. Mino T, Matsuo T, Kawakami T (1983) Studies on phosphorus composition and phosphorus metabolism in activated sludge, 1. J. Japanese Sewage Works Association, 20, 28-36 Nanamori M, Shinano T, Wasaki J, Yamamura T, Rao IM, Osaki M (2004) Low phosphorus tolerance mechanisms: phosphorus recycling and photosynthate partitioning in the tropical forage grass, Brachiaria Hybrid cultivar Mulato compared with rice. Plant Cell Physiol., 45, 460-468 O’Farrell PH (1975) High resolution two-dimensional electrophoresis of proteins. J. Biol. Chem., 250, 4007-4021 Palmiter RD (1974) Magnesium precipitation of ribonucleoprotein complexes: Expedient techniques for the isolation of undegraded polysomes and messenger ribonucleic acid. Biochemistry, 13, 3606-3615 Plaxton WC, Tran HT (2011) Metabolic adaptations of phosphate-starved plants. Plant Physiol., 156, 1006-1015

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Shinano T, Nanamori M, Dohi M, Wasaki J, Osaki M (2005) Evaluation of phosphorus starvation inducible bypasses to increase the effieciency of phosphorus utilization in rice. Plant Soil, 269, 81-87 Tokimatsu T, Sakurai N, Suzuki H, Ohta H, Nishitani K, Koyama T, Umezawa T, Misawa N, Saito K, Shibata D (2005) KaPPA-View. A web-based analysis tool for integration of transcript and metabolite data on plant metabolic pathway maps. Plant Physiol., 138, 1289-1300 Torabi S, Wissuwa M, Heiden M, Naghavi M-R, Gilany K, Hajirezaei M-R, Omidi M, Yazdi-Samadi B, Ismali AM, Salekdeh GH (2009) A comparative proteome approach to decipher the mechanism of rice adaptation to phosphorous deficiency. Proteomics, 9, 159-170 Wasaki J, Shinano T, Onishi K, Yonetani R, Yazaki J, Fujii F, Shimbo K, Ishikawa M, Shimatani Z, Nagata Y, Hashimoto A, Ohta T, Sato Y, Miyamoto C, Honda S, Kojima K, Sasaki T, Kishimoto N, Kikuchi S, Osaki M (2006) Transcriptomic analysis indicates putative metabolic changes caused by manipulation of phosphorus availability in rice leaves J. Exp. Bot., 57, 2049-2059 Wasaki J, Yonetani R, Kuroda S, Shinano T, Yazaki J, Fujii E, Shimbo K, Yamamoto K, Sakata K, Sasaki T, Kishimoto N, Kikuchi S, Yamagishi M, Osaki M (2003) Transcriptomic analysis of metabolic changes by phosphorus stress in rice plant roots. Plant Cell Environ., 26, 1515-1523 Watanabe Y, Prasityousil J, Kameda S (1999) Hybrid municipal wastewater treatment system for phosphorus recovery. Proc. International Symposium on Bio-Recycling/Composting in Sapporo, V4-1-V-4-13, International Symposium of Bio-recycling/Composting Organizing Committee, Sapporo. Yamamura T, Dateki H, Wasaki J, Shinano T, Osaki M (2004) Possibility of rhizosphere regulation using acid phosphatase and organic acid for recycling phosphorus in sewage sludge. Soil Sci. Plant Nutr., 50, 77-83

Specifically Extracted Beta-1,3-glucanase from Elongation Zone of Soybean Root Apoplast and Its Possible Involvement in Aluminum Toxicity Eri SOGA, Hiroaki IWAI, Shinobu SATOH, Jun FURUKAWA * University of Tsukuba, Tsukuba 305-8571, JAPAN *Corresponding author: [email protected]

Abstract On the acid soils, which comprise 30–40% of the world's arable soils, crop yields are reduced because Al is solubilized to its ionic form. Plants show severe toxicity there. Especially inhibition of root elongation is the most critical matter and is considered as a result of direct interaction between Al3+ ion and cell wall components including protein. To identify the protein affected by Al3+ ion, we focused on the protein weakly bound to cell wall and specifically extracted from the apoplast of root elongation zone. At first, extracted proteins by 20 mM MgCl 2 from the apoplast of elongation zone was compared with those of adjacent non-elongation zone with SDS-PAGE. The protein profile indicated that the band of 27 kDa protein was observed only at the elongation zone. To identify this elongation-zone-specific protein, mass spectrometry analysis was performed with MALDI-TOF MS. The result of PMF identification indicated that the protein was supposed to be one of the beta-1,3-glucanases. For verifying this identification, immunoblotting with tobacco beta-1,3-glucanase antibody was carried out, and the bands indicating 33 and 27 kDa were detected. These results indicate that the beta-1,3-glucanase is abundant in the apoplast of root elongation zone and it interacts weakly with other cell wall components. The relationship between beta-1,3glucanases and Al toxicity was investigated with 2-DE and immunoblotting. The result showed isoelectric point of 33 kDa beta-1,3-glucanase were shifted in Al-treated root, suggesting beta-1,3-glucanases located at the apoplast might be affected in its function by Al and involved in Al toxicity.

Introduction On the acid soils, which comprise 30-40% of the world’s arable soils, crop yields are reduced by the Al toxicity. Al is the most abundant metal in the soil, however, where the soil pH is low, Al is solubilized to its ionic form, Al3+, and severely inhibits plant growth. Especially inhibition of root elongation is the most critical phenomenon and the initial Al binding was observed at the transition zone localized between the part of cell division and cell elongation (Fig. 1). Based on the low radial mobility of Al in the root and the rapid cessation of root elongation after Al application, Al-induced inhibition of root elongation is considered as a result of direct interaction between Al3+ ion and cell wall components (Horst, 1995). In the apoplast, the negative charge of the cell wall is mainly derived from the pectin content and its degree of methylation and was thought to be a major determinant of Al accumulation. Demethylated pectin is bridged by Ca2+ at some part and, when Al3+ was applied, it was expected that Ca2+ was exchanged by Al3+ (Blamey et al., 1997). Although the relationship between the property of Al3+-binding pectin and cell wall loosening was often hypothesized as a candidate mechanism of rapid Al toxicity, the biochemical basis of Al3+ and pectin has not been elucidated. Additionally, proteins in the apoplast are also considered as a primary cite of Al3+ binding. Cell elongation is regulated by some apoplast proteins and the loss of those functions, especially mobility of those proteins in the cell wall, by Al application was suggested to be one of the responsible mechanisms for the Al toxicity (Kataoka et al., 2003). To obtain the candidate proteins affected in its functions by Al, we extracted apoplast proteins from soybean root and the difference between with and without Al treatment was focused. Based on the inhibition of root elongation observed within the several hours after the onset of Al3+ treatment, we compared the apoplast protein profiles after short time Al treatment.

Fig.1 Aluminum (Al3+) induced damage in root tip. (A) Inhibition of root elongation induced by Al3+. (B) Al accumulation in root tip stained by Eriochrome Cyanine R. Roots were stained after 1 day AlCl 3 treatment.

Root Elongation Zone Specific Beta-1,3-Glucanase and Its Possible Involvement in Al Toxicity

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Materials and Methods Two-day old seedlings of soybean [Glycine max (L.) cv. Enrei] were treated with 0.2 mM CaCl 2 (pH 4.5) with or without 20 µM AlCl 3 for 2 h. Their roots were excised at 2-6 mm from the tip as elongation zone and 6-10 mm as non-elongation zone. Excised root segments were treated with 20 mM MgCl 2 to extract apoplast proteins which were weakly bound to cell wall components according to Kataoka et al., 2003. Extracted apoplast proteins were separated by SDS-PAGE and stained with silver. The identification of protein was carried out with MALDI-TOF MS (AB SCIEX, TOF/TOF5800, USA). The trypsin digested peptide fragments were subjected to mass spectrometry and the candidate proteins were identified with peptide mass fingerprinting (PMF) analysis using NCBI non- redundant public protein database. Immunoblotting was performed with tobacco beta-1,3-glucanase antibody (Agrisera, Sweden) and, in the 2D gel electrophoresis, proteins were separated by their pI on 4-9 and subsequently by their molecular weight with SDSPAGE.

Results and Discussion 27 kDa protein specifically extracted from the apoplast of elongation zone SDS-PAGE profiles of proteins extracted from elongation zone and those extracted from non-elongation zone were compared. The protein with 27 kDa was specifically extracted from the elongation zone (Fig. 2). This protein was designated as Soybean Apoplast Protein with 27 kDa (SAP27). Between +Al and –Al treatments, the obvious differences in the protein profiles were not observed both in the elongation and non-elongation zones. Since elongation zone specific protein was possibly involved in the root elongation and its activity might be altered by Al, the protein contained in this band, SAP27, was identified with MALDI-TOF MS.

Fig. 2. Comparison of apoplast proteins between elongation zone and non-elongation zone extracted under –Al and +Al conditions. -Al : 0.2 mM CaCl 2 (pH 4.5), +Al : 0.2 mM CaCl 2 with 20 µM AlCl 3 (pH 4.5). Before the extraction of apoplast proteins, soybean roots were treated for 2 hours under –Al or +Al conditions. Elongation zone was 2-6 mm and adjacent non-elongation zone was 6-10 mm from the root tip. Identification of SAP27 with MALDI-TOF MS analysis MS analyses of SAP27 using the PMF method identified SAP27 as beta-1,3-glucanases (Table 1). In our identification method, other proteins were not identified as significant candidates (p