Rice Proteome Research Articles

Systematic Annotation and Bioinformatics Analyses of Large-Scale Oryza sativa Proteome

Much has been now recognized on the rice (Oryza sativa L.) proteomics by using the powerful experimental tool two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). 2D-PAGE can be utilized for monitoring global changes of quantitative protein expression in specific tissues under various conditions. However, systematic annotations of the protein spots generated by 2D-PAGE are still limited for rice. In this study, a new approach for Oryza sativa proteome annotation based on the 2D-gel maps was developed. Based on the publicly available 2D-PAGE data of rice, 11,201 gel spots were annotated accounting for 87.2% of the total spots on the gel maps. Gel spot alignments were performed for the annotated gel maps belonging to 23 rice tissues or organelles. In summary, 253 alignments between 23 tissues or organelles were performed, and 26,207 co-expressed proteins were identified using our analytical strategy. Large-scale bi-cluster analysis of 23 tissues/organelles proteomes of rice was carried out to detect novel functional proteins. Function and pathway analysis identified a number of common gene products with great potential in regulating specific physiological and biochemical events within various rice tissues/organelles. It also suggested that the tissue- or organelle-specific proteins might be responsible for the functional divergence of these tissues or organelles. Taken together, this study provides us new strategies and informative resources for rice proteome research based on 2D-PAGE data.

Proteomics of ionic stresses in rice: An overview

Abstract Ions deficiency or excess remains one of the critical ground level environmental problems, affecting crop productivity. In this overview, we will discuss an increased application of proteomics technology in addressing this issue using rice ( Oryza sativa L.) as a model crop plant. Proteomics analyses have revealed that rice proteome unde-rgoes changes in the proteins composition and expression in response to several ionic stresses, including mineral nutrients (aluminum, nitrogen, and phosphorous) and heavy metals (arsenic, cadmium, and copper). Developed inventory of responsive proteins and their correlation with changes in physiological symptoms and parameters are a major step forward in: (i) better understanding the underlying mechan-isms of ionic stresses-triggered responses in rice; (ii) comparative proteomics studies; and (iii) designing a novel strategy to improve crop plants. Keywords Ionic stress, rice, proteomics Introduction Rice ( Oryza sativa L.) is a major edible crop contrib-uting directly to growth and development of the human civilization in Asia by providing a source of nourishment in an easily utilizable form, namely the seed. However, its growth and grain (or seed) yield are dramatically affected by adverse environmental stresses (Agrawal et al. 2006, 2009; Agrawal and Rakwal 2006, 2008b, 2011). Heavy metals and excessive use of fertilizers are one of the growing environmental problems. Heavy metals are alone responsible for soil pollution of about 235 million hectares (Giordani et al. 2005). To study the effects of such pollutants is a major area of research in plant biology. Proteomics technology has increasingly been utilized to understand the impact of environmental stresses on changes in the rice proteome, resulting in development of an inventory of responsive proteins (see a series of reviews, Agrawal et al. 2006, 2009; Agrawal and Rakwal 2003, 2006, 2008b, 2011). Such inventory has helped in constructing a working model and biology-driven hy-pothesis to overcome the environmental problems, including the ionic stresses. Ionic stress can be considered as an environmental problem that is by and large man-made. Therefore, it is ironic that we are now working hard to understand the effects of these stresses. In this regard, omics technologies including proteomics play a major role. Identified proteins are being used as potential biomarkers in dissecting the signaling and metabolic pathways responsive to ionic stresses and in crop breeding programs (see, Agrawal and Rakwal 2008a).To date, there are nine proteomics-level studies, dealing with ionic stresses-triggered responses in rice. Those studies include aluminum (Al; Yang et al. 2007), nitrogen (N; Kim et al. 2009; Kim et al. unpublished results), phosphorous (P; Torabi et al. 2009), arsenic (As; Ahsan et al. 2008), cadmium (Cd; Aina et al. 2007; Lee et al.

Biotic Stress-Responsive Rice Proteome: An Overview

Biotic stresses affect the plant growth, seed quality, and crop yield. The monocot model rice crop plant is no exception and is affected by a variety of biotic stress factors. High-throughput proteomics approaches are being applied in rice for the past several years to exploit better understanding the biotic stresses-responsive regulatory mechanisms. A large number of proteins responsive to biotic stresses, including pathogens and herbivores, have been cataloged. Cataloged proteins mainly belong to functional categories into metabolism, energy, defense mechanisms, and signaling. To date, majority of these proteins have not been functionally characterized yet, except the pathogen-related 10 protein, PBZ1. This review will briefly summarize and discuss: (1) the proteomics-based investigation of biotic stress-responsive proteins in rice and (2) increasing importance of proteomics approach in defense biology and engineering the next-generation rice/crop plants.

OryzaPG-DB: Rice Proteome Database based on Shotgun Proteogenomics

BackgroundProteogenomics aims to utilize experimental proteome information for refinement of genome annotation. Since mass spectrometry-based shotgun proteomics approaches provide large-scale peptide sequencing data with high throughput, a data repository for shotgun proteogenomics would represent a valuable source of gene expression evidence at the translational level for genome re-annotation.DescriptionHere, we present OryzaPG-DB, a rice proteome database based on shotgun proteogenomics, which incorporates the genomic features of experimental shotgun proteomics data. This version of the database was created from the results of 27 nanoLC-MS/MS runs on a hybrid ion trap-orbitrap mass spectrometer, which offers high accuracy for analyzing tryptic digests from undifferentiated cultured rice cells. Peptides were identified by searching the product ion spectra against the protein, cDNA, transcript and genome databases from Michigan State University, and were mapped to the rice genome. Approximately 3200 genes were covered by these peptides and 40 of them contained novel genomic features. Users can search, download or navigate the database per chromosome, gene, protein, cDNA or transcript and download the updated annotations in standard GFF3 format, with visualization in PNG format. In addition, the database scheme of OryzaPG was designed to be generic and can be reused to host similar proteogenomic information for other species. OryzaPG is the first proteogenomics-based database of the rice proteome, providing peptide-based expression profiles, together with the corresponding genomic origin, including the annotation of novelty for each peptide.ConclusionsThe OryzaPG database was constructed and is freely available at http://oryzapg.iab.keio.ac.jp/.

Rice proteomics: A move toward expanded proteome coverage to comparative and functional proteomics uncovers the mysteries of rice and plant biology

Growing rice is an important socio-economic activity. Rice proteomics has achieved a tremendous progress in establishing techniques to proteomes of almost all tissues, organs, and organelles during the past one decade (year 2000-2010). We have compiled these progresses time to time over this period. The present compilation discusses proteomics research in rice published between 1st April 2008 and 30th July 2010. Progress continues mainly towards protein cataloging deep into the proteome with high-confident protein assignment and some functional significance than ever before by (i) identifying previously unreported/low-abundance proteins, (ii) quantifying relative/absolute values of proteins, (iii) assigning protein responses to biotic/abiotic stresses, (iv) protein localization into organelles, (v) validating previous proteomes and eliminating false-positive proteins, and (vi) discovering potential biomarkers for tissues, organs, organelles, and for screening transgenic plants and food-safety evaluation. The notable achievements in global mapping of phosphorylation sites and identifying several novel secreted proteins into the extracellular space are worth appreciating. Our ever-increasing knowledge on the rice proteomics is beginning to impact the biology of not only rice, but also crops and plants. These major achievements will be discussed in this review keeping in mind newcomers, young, and established scientists in proteomics and plants.

Optimization Process and Method of 2-D Electrophoresis for Rice Proteomics

Optimization Process and Method of 2-D Electrophoresis for Rice Proteomics

Expression Profiling of Rice Chloroplast Proteins During Growth and Development*

In plants, chloroplast is the key organelle for the photosynthesis, the knowledge about biological processes in chloroplast has been accumulated. However, limited information exists on the expression of chloroplast proteins. To investigate the expression profiling of rice chloroplast proteins in different growth and developmental stages and provide a pilot experiment for rice antibody-based proteomics. To address this questions, ten rice chloroplast genes were chosen and antibodies were generated using proteins expressed in E. coli or epitope peptides synthesized in vitro as immunogen, protein expression profiling were investigated by Western blotting for root, stem, leaf and panicles at five developmental stages. The results indicated that all chloroplast proteins tested were expressed in leaf, but not detectable in root. The photosynthesis primary reaction protein CAB1 and CAB2, the electron transport protein OEE1, and the ROS scavenging-related proteins 2-CysP and Trx were expressed in stem, but four carbon fixation proteins RCA, GAPDH, FBPA and SBPase, which involved in Calvin cycle, were not detected in stem. In panicle, the chloroplast proteins showed different expression patterns, CAB2 and 2-CysP were expressed at all stages during panicle growth and development, CAB1 and OEE1 were expressed at late stage, and the four proteins involved in Calvin cycle were expressed only in the middle stage. Interestingly, four proteins in Calvin cycle showed the same expression patterns, supporting their cohesive relationship. In addition, the data revealed possible clues of post-translational modification, dimer and different forms of transcripts. Comparison analysis between the profiling of gene transcription and translation revealed parallel phenomena; however, they are quite different at least in some instances. Taking together, this experiment revealed the expression patterns of rice chloroplast proteins in a direct and relative quantitative way, provided helpful information for better understanding their function and also provided a preliminary proof for the concept of a rice antibody-based proteomics strategy.

Identification of Extracellular Matrix Proteins of Rice (Oryza sativa L.) Involved in Dehydration-Responsive Network: A Proteomic Approach

Water-deficit or dehydration impairs almost all physiological processes and greatly influences the geographical distribution of many crop species. It has been postulated that higher plants rely mostly on induction mechanisms to maintain cellular integrity during stress conditions. Plant cell wall or extracellular matrix (ECM) forms an important conduit for signal transduction between the apoplast and symplast and acts as front-line defense, thereby playing a key role in cell fate decision under various stress conditions. To better understand the molecular mechanism of dehydration response in plants, four-week-old rice seedlings were subjected to progressive dehydration by withdrawing water and the changes in the ECM proteome were examined using two-dimensional gel electrophoresis. Dehydration-responsive temporal changes revealed 192 proteins that change their intensities by more than 2.5-fold, at one or more time points during dehydration. The proteomic analysis led to the identification of about 100 differentially regulated proteins presumably involved in a variety of functions, including carbohydrate metabolism, cell defense and rescue, cell wall modification, cell signaling and molecular chaperones, among others. The differential rice proteome was compared with the dehydration-responsive proteome data of chickpea and maize. The results revealed an evolutionary divergence in the dehydration response as well as organ specificity, with few conserved proteins. The differential expression of the candidate proteins, in conjunction with previously reported results, may provide new insight into the underlying mechanisms of the dehydration response in plants. This may also facilitate the targeted alteration of metabolic routes in the cell wall for agricultural and industrial exploitation.

Evaluation of Protein Phosphorylation Site Predictors

A series of elegant phosphorylation site prediction methods have been developed, which are playing an increasingly important role in accelerating the experimental characterization of phosphorylation sites in phosphoproteins. In this study, we selected six recently published methods (DISPHOS, NetPhosK, PPSP, KinasePhos, Scansite and PredPhospho) to evaluate their performance. First, we compiled three testing datasets containing experimentally verified phosphorylation sites for mammalian, Arabidopsis and rice proteins. Then, we present the prediction performance of the tested methods on these three independent datasets. Rather than quantitatively ranking the performance of these methods, we focused on providing an understanding of the overall performance of the predictors. Based on this evaluation, we found the following results: i) current phosphorylation site predictors are not effective for practical use and there is substantial need to improve phosphorylation site prediction; ii) current predictors perform poorly when used to predict phosphorylation sites in plant phosphoproteins, suggesting that a rice-specific predictor will be required to obtain confident computational annotation of phosphorylation sites in rice proteomics research; and iii) the tested predictors are complementary to some extent, implying that establishment of a meta-server might be a promising approach to developing an improved prediction system.

Rice proteomics: Ending phase I and the beginning of phase II

Rice is a critically important food crop plant on our planet. It is also an excellent model plant for cereal crops, and now in position to serve as a reference plant for biofuel production. Proteomics study of rice therefore is crucial to better understand "rice" as a whole. Rice proteomics has moved well beyond the initial proteome analysis in the early to late 1990s. Since the year 2000, numerous proteomic studies have been performed in rice during growth and development and against a wide variety of environmental factors. These proteomic investigations have established the high-resolution 2-D reference gels of rice tissues, organs, and organelle under normal and adverse (stressed) conditions by optimizing suitable, reproducible systems for gel, and MS-based proteomic techniques, which "rejuvenated" the rice proteome field. This constituted the "phase I" in rice proteomics, and resulted in rice being labeled as the "cornerstone" of cereal food crop proteomes. Now, we are in position to state that rice proteomics today marks the "beginning of phase II". This is due to the fact that rice researchers are capable of digging deeper into the rice proteome, mapping PTMs (in particular reversible protein phosphorylation), performing inter- and intra-species comparisons, integrating proteomics data with other "omic" technologies-generated data, and probing the functional aspect of individual proteins. These advancements and their impact on the future of rice proteomics are the focus of this review.

Research on the Rice Proteome: The Contribution of Proteomics Technology in the Creation of Abiotic Stress-Tolerant Plants

AbstractProteomics techniques have identified a vast number of proteins that participate in the growth of plants or their adaptation to environmental stresses. Functional analysis of those proteins will contribute to the development of high-yielding crops through artificial manipulation of the basic life phenomena of plants or through the assessment of their stress tolerance. The conditions in almost all farmlands are suboptimal for plant growth, resulting in a calculation that causes the loss to three quarters of the potential yield of crops. Breeding of stress-tolerant cultivars has been hampered by the paucity of information on molecular events underlying stress tolerance. A comparative analysis of the response of plants to stress at the protein level, together with physiological measurements, will assist in identifying the genes and pathways that are crucial for stress tolerance. This review examines analyses of the rice proteome under abiotic stress and the potential contribution of proteomics technology in the creation of abiotic stress-tolerant plants.

Predicting the Interactome of Xanthomonas oryzae pathovar oryzae for target selection and DB service

BackgroundProtein-protein interactions (PPIs) play key roles in various cellular functions. In addition, some critical inter-species interactions such as host-pathogen interactions and pathogenicity occur through PPIs. Phytopathogenic bacteria infect hosts through attachment to host tissue, enzyme secretion, exopolysaccharides production, toxins release, iron acquisition, and effector proteins secretion. Many such mechanisms involve some kind of protein-protein interaction in hosts. Our first aim was to predict the whole protein interaction pairs (interactome) of Xanthomonas oryzae pathovar oryzae (Xoo) that is an important pathogenic bacterium that causes bacterial blight (BB) in rice. We developed a detection protocol to find possibly interacting proteins in its host using whole genome PPI prediction algorithms. The second aim was to build a DB server and a bioinformatic procedure for finding target proteins in Xoo for developing pesticides that block host-pathogen protein interactions within critical biochemical pathways.DescriptionA PPI network in Xoo proteome was predicted by bioinformatics algorithms: PSIMAP, PEIMAP, and iPfam. We present the resultant species specific interaction network and host-pathogen interaction, XooNET. It is a comprehensive predicted initial PPI data for Xoo. XooNET can be used by experimentalists to pick up protein targets for blocking pathological interactions. XooNET uses most of the major types of PPI algorithms. They are: 1) Protein Structural Interactome MAP (PSIMAP), a method using structural domain of SCOP, 2) Protein Experimental Interactome MAP (PEIMAP), a common method using public resources of experimental protein interaction information such as HPRD, BIND, DIP, MINT, IntAct, and BioGrid, and 3) Domain-domain interactions, a method using Pfam domains such as iPfam. Additionally, XooNET provides information on network properties of the Xoo interactome.ConclusionXooNET is an open and free public database server for protein interaction information for Xoo. It contains 4,538 proteins and 26,932 possible interactions consisting of 18,503 (PSIMAP), 3,118 (PEIMAP), and 8,938 (iPfam) pairs. In addition, XooNET provides 3,407 possible interaction pairs between two sets of proteins; 141 Xoo proteins that are predicted as membrane proteins and rice proteomes. The resultant interacting partners of a query protein can be easily retrieved by users as well as the interaction networks in graphical web interfaces. XooNET is freely available from .

Rejuvenating rice proteomics: Facts, challenges, and visions

Proteomics is progressing at an unprecedented pace, as can be exemplified by the progress in model organisms such as yeast, bacteria, and mammals. Proteomics research in plants, however, has not progressed at the same pace. Unscrambling of the genome sequences of the dicotyledoneous Arabidopsis thaliana (L.) and monocotyledoneous rice (Oryza sativa L.) plant species, respectively, has made them accessible reference organisms to study plant proteomics. Study of these two reference plants is expected to unravel the mystery of plant biology. Rice, a critically important food crop on the earth, has been termed a "cornerstone" and the "Rosetta stone" for functional genomics of cereal crops. Here, we look at the progress in unraveling rice proteomes and present the facts, challenges, and vision. The text is divided into two major parts: the first part presents the facts and the second part discusses the challenges and vision. The facts include the technology and its use in developing proteomes, which have been critically and constructively reviewed. The challenges and vision deal with the establishment of technologies to exhaustively investigate the protein components of a proteome, to generate high-resolution gel-based reference maps, and to give rice proteomics a functional dimension by studying PTMs and isolation of multiprotein complexes. Finally, we direct a vision on rice proteomics. This is our third review in series on rice proteomics, which aims to stimulate an objective discussion among rice researchers and to understand the necessity and impact of unraveling rice proteomes to their full potential.

Expanding the Subproteome of the Inner Mitochondria Using Protein Separation Technologies

Currently no single proteomics technology has sufficient analytical power to allow for the detection of an entire proteome of an organelle, cell, or tissue. One approach that can be used to expand proteome coverage is the use of multiple separation technologies especially if there is minimal overlap in the proteins observed by the different methods. Using the inner mitochondrial membrane subproteome as a model proteome, we compared for the first time the ability of three protein separation methods (two-dimensional liquid chromatography using the ProteomeLab PF 2D Protein Fractionation System from Beckman Coulter, one-dimensional reversed phase high performance liquid chromatography, and two-dimensional gel electrophoresis) to determine the relative overlap in protein separation for these technologies. Data from these different methods indicated that a strikingly low number of proteins overlapped with less than 24% of proteins common between any two technologies and only 7% common among all three methods. Utilizing the three technologies allowed the creation of a composite database totaling 348 non-redundant proteins. 82% of these proteins had not been observed previously in proteomics studies of this subproteome, whereas 44% had not been identified in proteomics studies of intact mitochondria. Each protein separation method was found to successfully resolve a unique subset of proteins with the liquid chromatography methods being more suited for the analysis of transmembrane domain proteins and novel protein discovery. We also demonstrated that both the one- and two-dimensional LC allowed for the separation of the alpha-subunit of F1F0 ATP synthase that differed due to a change in pI or hydrophobicity.

Update and challenges on proteomics in rice

Rice is not only an important agricultural resource but also a model plant for biological research. Our previous review highlighted different aspects of the construction of rice proteome database, cataloguing rice proteins of different tissues and organelle, differential proteomics using 2-DE and functional characterization of some of the proteins identified (Komatsu, S., Tanaka, N., Proteomics 2005, 5, 938-949). In this review, the powerfulness and weaknesses of proteomic technologies as a whole and limitations of the currently used techniques in rice proteomics are discussed. The information obtained from these techniques regarding proteins modification, protein-protein interaction and the development of new methods for differential proteomics will aid in deciphering more precisely the functions of known and/or unknown proteins in rice.

Proteome analysis of rice uppermost internodes at the milky stage

Uppermost internodes, which connect the part between the ear and lower stem, form an important pathway transporting mineral nutrition from roots and photosynthates from leaves (especially the flag leaf) to the ear. The milky stage is the first stage of seed ripening. The uppermost internodes of rice at the milky stage are critical for seed quality and yield. Total soluble proteins of the uppermost internodes of rice (Oryza sativa L. ssp. indica) at the milky stage were analyzed using proteomic methods. Using 2-DE, 762 reproducible protein spots were detected. Among them, 132 abundant proteins were analyzed using MALDI-TOF-MS. Searching in the National Center for Biotechnology Information database, we could identify 98 proteins, which represent 80 gene products. These proteins belong to 11 functional groups with energy production-associated proteins in the first place. The large accumulation of proteins involved in metabolism, signaling, and stress resistance indicated that the uppermost internodes of rice have a high physiological and stress-resistant activity. In addition, our results will also enrich the database of the rice proteome.

Plant Proteomics Databases: Their Status in 2005

Proteome analysis linked to genome sequence information is very useful for functional genomics. Since proteins are the major players in most processes of living cells, knowledge of the proteome has great relevance to the study of cells and organisms at the molecular level. The technique of proteome analysis using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) has the power to monitor global changes that occur in the protein complement of tissues and subcellular compartments. As a complement to more focused studies, and to facilitate further advances in functional genomics, several databases based on 2D-PAGE are already available including those for plants. In this review, the rice proteome database and other plant proteome databases are discussed. Organizing and streamlining the access of information into plant proteome databases, especially the rice proteome database, will aid in cloning the genes and predicting the function of unknown proteins. Keywords: Plant, rice, proteome, database, two-dimensional gel electrophoresis, mass spectrometry

Susceptibility to Coolness at the Young Microspore Stage under High Nitrogen Supply in Rice (Oryza Sativa L.). Proteome Analysis of Mature Anthers

In vitro pollen germination experiment using agar plates showed that the growth under high nitrogen conditions enhanced the damage to pollen germination ability caused by the cooling at the young microspore stage. To clarify the physiological factors related to this damage to pollen germination, we performed the comparative proteome analysis of mature anthers and identified proteins that were changed by high nitrogen conditions or high nitrogen plus cooling conditions. Proteins were extracted from mature anther samples and separated by two-dimensional polyacrylamide gel electrophoresis. By comparing anther protein maps of the samples collected from the plants grown under standard nitrogen conditions, high nitrogen conditions and high nitrogen plus cooling conditions, we found 11 protein spots, which varied with the treatment. These protein spots were identified based on the rice proteome database and/or peptide mass fingerprinting (PMF) analysis after digestion with trypsin. Digested samples were analyzed by matrix-assisted laser desorption/ionization-time flight mass spectrometry to produce PMF data. Database searches using these PMF data revealed the identities of 9 proteins. Seven of these proteins were polypeptides involved in cell elongation, stress responses and sugar metabolism. The relation between the fluctuations of these proteins and the decrease in pollen germination are discussed.

Rice Proteome Database: A Step toward Functional Analysis of the Rice Genome

The technique of proteome analysis using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) has the power to monitor global changes that occur in the protein complement of tissues and subcellular compartments. In this study, the proteins of rice were cataloged, a rice proteome database was constructed, and a functional characterization of some of the identified proteins was undertaken. Proteins extracted from various tissues and subcellular compartments in rice were separated by 2D-PAGE and an image analyzer was used to construct a display of the proteins. The Rice Proteome Database contains 23 reference maps based on 2D-PAGE of proteins from various rice tissues and subcellular compartments. These reference maps comprise 13129 identified proteins, and the amino acid sequences of 5092 proteins are entered in the database. Major proteins involved in growth or stress responses were identified using the proteome approach. Some of these proteins, including a beta-tubulin, calreticulin, and ribulose-1,5-bisphosphate carboxylase/oxygenase activase in rice, have unexpected functions. The information obtained from the Rice Proteome Database will aid in cloning the genes for and predicting the function of unknown proteins.

The map-based sequence of the rice genome

Rice, one of the world's most important food plants, has important syntenic relationships with the other cereal species and is a model plant for the grasses. Here we present a map-based, finished quality sequence that covers 95% of the 389 Mb genome, including virtually all of the euchromatin and two complete centromeres. A total of 37,544 non-transposable-element-related protein-coding genes were identified, of which 71% had a putative homologue in Arabidopsis. In a reciprocal analysis, 90% of the Arabidopsis proteins had a putative homologue in the predicted rice proteome. Twenty-nine per cent of the 37,544 predicted genes appear in clustered gene families. The number and classes of transposable elements found in the rice genome are consistent with the expansion of syntenic regions in the maize and sorghum genomes. We find evidence for widespread and recurrent gene transfer from the organelles to the nuclear chromosomes. The map-based sequence has proven useful for the identification of genes underlying agronomic traits. The additional single-nucleotide polymorphisms and simple sequence repeats identified in our study should accelerate improvements in rice production.