Unique and overlapping expression patterns among members of photosynthesis-associated nuclear gene families in Arabidopsis

Light provides crucial positional information in plant development, and the morphogenetic processes that are orchestrated by light signals are triggered by changes of gene expression in response to variations in light parameters. Control of expression of members of the RbcS and Lhc families of photosynthesis-associated nuclear genes by light cues is a paradigm for light-regulated gene transcription, but high-resolution expression profiles for these gene families are lacking. In this study, we have investigated expression patterns of members of the RbcS and Lhc gene families in Arabidopsis (Arabidopsis thaliana) at the cellular level during undisturbed development and upon controlled interference of the light environment. Members of the RbcS and Lhc gene families are expressed in specialized territories, including root tip, leaf adaxial, abaxial, and epidermal domains, and with distinct chronologies, identifying successive stages of leaf mesophyll ontogeny. Defined spatial and temporal overlap of gene expression fields suggest that the light-harvesting and photosynthetic apparatus may have a different polypeptide composition in different cells and that such composition could change over time even within the same cell.

Functional proteomics of Arabidopsis thaliana guard cells uncovers new stomatal signaling pathways

We isolated a total of 3 x 10(8) guard cell protoplasts from 22,000 Arabidopsis thaliana plants and identified 1734 unique proteins using three complementary proteomic methods: protein spot identification from broad and narrow pH range two-dimensional (2D) gels, and 2D liquid chromatography-matrix assisted laser desorption/ionization multidimensional protein identification technology. This extensive single-cell-type proteome includes 336 proteins not previously represented in transcriptome analyses of guard cells and 52 proteins classified as signaling proteins by Gene Ontology analysis, of which only two have been previously assessed in the context of guard cell function. THIOGLUCOSIDE GLUCOHYDROLASE1 (TGG1), a myrosinase that catalyzes the production of toxic isothiocyanates from glucosinolates, showed striking abundance in the guard cell proteome. tgg1 mutants were hyposensitive to abscisic acid (ABA) inhibition of guard cell inward K(+) channels and stomatal opening, revealing that the glucosinolate-myrosinase system, previously identified as a defense against biotic invaders, is required for key ABA responses of guard cells. Our results also suggest a mechanism whereby exposure to abiotic stresses may enhance plant defense against subsequent biotic stressors and exemplify how enhanced knowledge of the signaling networks of a specific cell type can be gained by proteomics approaches.

Web-based Arabidopsis functional and structural genomics resources

As plant research moves to a "post-genomic" era, many diverse internet resources become available to the international research community. Arabidopsis thaliana, because of its small size, rapid life cycle and simple genome, has been a model system for decades, with much research funding and many projects devoted to creation of functional and structural genomics resources. Different types of data, including genome, transcriptome, proteome, phenome, metabolome and ionome are stored in these resources. In this chapter, a variety of genomics resources are introduced, with simple descriptions of how some can be accessed by laboratory researchers via the internet.

Analysis of the pumpkin phloem proteome provides insights into angiosperm sieve tube function

Increasing evidence suggests that proteins present in the angiosperm sieve tube system play an important role in the long distance signaling system of plants. To identify the nature of these putatively non-cell-autonomous proteins, we adopted a large scale proteomics approach to analyze pumpkin phloem exudates. Phloem proteins were fractionated by fast protein liquid chromatography using both anion and cation exchange columns and then either in-solution or in-gel digested following further separation by SDS-PAGE. A total of 345 LC-MS/MS data sets were analyzed using a combination of Mascot and X!Tandem against the NCBI non-redundant green plant database and an extensive Cucurbit maxima expressed sequence tag database. In this analysis, 1,209 different consensi were obtained of which 1,121 could be annotated from GenBank and BLAST search analyses against three plant species, Arabidopsis thaliana, rice (Oryza sativa), and poplar (Populus trichocarpa). Gene ontology (GO) enrichment analyses identified sets of phloem proteins that function in RNA binding, mRNA translation, ubiquitin-mediated proteolysis, and macromolecular and vesicle trafficking. Our findings indicate that protein synthesis and turnover, processes that were thought to be absent in enucleate sieve elements, likely occur within the angiosperm phloem translocation stream. In addition, our GO analysis identified a set of phloem proteins that are associated with the GO term "embryonic development ending in seed dormancy"; this finding raises the intriguing question as to whether the phloem may exert some level of control over seed development. The universal significance of the phloem proteome was highlighted by conservation of the phloem proteome in species as diverse as monocots (rice), eudicots (Arabidopsis and pumpkin), and trees (poplar). These results are discussed from the perspective of the role played by the phloem proteome as an integral component of the whole plant communication system.

Ascorbate peroxidase 1 plays a key role in the response of Arabidopsis thaliana to stress combination

Within their natural habitat plants are subjected to a combination of different abiotic stresses, each with the potential to exacerbate the damage caused by the others. One of the most devastating stress combinations for crop productivity, which frequently occurs in the field, is drought and heat stress. In this study we conducted proteomic and metabolic analysis of Arabidopsis thaliana plants subjected to a combination of drought and heat stress. We identified 45 different proteins that specifically accumulated in Arabidopsis in response to the stress combination. These included enzymes involved in reactive oxygen detoxification, malate metabolism, and the Calvin cycle. The accumulation of malic enzyme during the combined stress corresponded with enhanced malic enzyme activity, a decrease in malic acid, and lower amounts of oxaloacetate, suggesting that malate metabolism plays an important role in the response of Arabidopsis to the stress combination. Cytosolic ascorbate peroxidase 1 (APX1) protein and mRNA accumulated during the stress combination. When exposed to heat stress combined with drought, an APX1-deficient mutant (apx1) accumulated more hydrogen peroxide and was significantly more sensitive to the stress combination than wild type. In contrast, mutants deficient in thylakoid or stromal/mitochondrial APXs were not more sensitive to the stress combination than apx1 or wild type. Our findings suggest that cytosolic APX1 plays a key role in the acclimation of plants to a combination of drought and heat stress.

Metabolic network fluxes in heterotrophic Arabidopsis cells: stability of the flux distribution under different oxygenation conditions

Steady-state labeling experiments with [1-(13)C]Glc were used to measure multiple metabolic fluxes through the pathways of central metabolism in a heterotrophic cell suspension culture of Arabidopsis (Arabidopsis thaliana). The protocol was based on in silico modeling to establish the optimal labeled precursor, validation of the isotopic and metabolic steady state, extensive nuclear magnetic resonance analysis of the redistribution of label into soluble metabolites, starch, and protein, and a comprehensive set of biomass measurements. Following a simple modification of the cell culture procedure, cells were grown at two oxygen concentrations, and flux maps of central metabolism were constructed on the basis of replicated experiments and rigorous statistical analysis. Increased growth rate at the higher O(2) concentration was associated with an increase in fluxes throughout the network, and this was achieved without any significant change in relative fluxes despite differences in the metabolite profile of organic acids, amino acids, and carbohydrates. The balance between biosynthesis and respiration within the tricarboxylic acid cycle was unchanged, with 38% +/- 5% of carbon entering used for biosynthesis under standard O(2) conditions and 33% +/- 2% under elevated O(2). These results add to the emerging picture of the stability of the central metabolic network and its capacity to respond to physiological perturbations with the minimum of rearrangement. The lack of correlation between the change in metabolite profile, which implied significant disruption of the metabolic network following the alteration in the oxygen supply, and the unchanging flux distribution highlights a potential difficulty in the interpretation of metabolomic data.

Towards systems metabolic engineering of microorganisms for amino acid production

Microorganisms capable of efficient production of amino acids have traditionally been developed by random mutation and selection method, which might cause unwanted physiological changes in cellular metabolism. Rational genome-wide metabolic engineering based on systems and synthetic biology tools, which is termed 'systems metabolic engineering', is rising as an alternative to overcome these problems. Recently, several amino acid producers have been successfully developed by systems metabolic engineering, where the metabolic engineering procedures were performed within a systems biology framework, and entire metabolic networks, including complex regulatory circuits, were engineered in an integrated manner. Here we review the current status of systems metabolic engineering successfully applied for developing amino acid producing strains and discuss future prospects.

Genevestigator transcriptome meta-analysis and biomarker search using rice and barley gene expression databases

The wide-spread use of microarray technologies to study plant transcriptomes has led to important discoveries and to an accumulation of profiling data covering a wide range of different tissues, developmental stages, perturbations, and genotypes. Querying a large number of microarray experiments can provide insights that cannot be gained by analyzing single experiments. However, such a meta-analysis poses significant challenges with respect to data comparability and normalization, systematic sample annotation, and analysis tools. Genevestigator addresses these issues using a large curated expression database and a set of specifically developed analysis tools that are accessible over the internet. This combination has already proven to be useful in the area of plant research based on a large set of Arabidopsis data (Grennan, 2006). Here, we present the release of the Genevestigator rice and barley gene expression databases that contain quality-controlled and well annotated microarray experiments using ontologies. The databases currently comprise experiments from pathology, plant nutrition, abiotic stress, hormone treatment, genotype, and spatial or temporal analysis, but are expected to cover a broad variety of research areas as more experimental data become available. The transcriptome meta-analysis of the model species rice and barley is expected to deliver results that can be used for functional genomics and biotechnological applications in cereals.

Quantitative proteomics as a new piece of the systems biology puzzle

The definition of the role of each gene product in its cellular context is of outstanding importance in the post-genomics era. Recent technological innovations have driven research in proteomics from single protein characterization to global approaches, aiming to achieve a comprehensive qualitative and quantitative description of complex molecular mechanisms. In this review, we discuss the methodology of quantitative proteomics as it applies to the analysis of complex biological model systems. A special attention will be given to model systems that are suitable for functional genomic studies, where the potential of quantitative proteomics can be effectively demonstrated.