Manipulating PEPC levels in plants

Jeanneau, M.; Vidal, Jean; Gousset-Dupont, Aurélie; Lebouteiller, Bénédicte; Hodges, Michael; Gerentes, Denise; Peréz, Pascual

doi:10.1093/jxb/erf061

Cited by 65 publications

(41 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consistent with this view, a large number of phosphoproteins involved in metabolism and energy have been reported to be expressed in a dynamic manner during seed filling in rapeseed . Moreover, some of these key enzymes have already been implicated in the regulation of Suc assimilation or glycolysis, including Suc synthase (for review, see Hill, 2004), PK (Andre et al, 2007), and PEPC (for review, see Jeanneau et al, 2002).…”

Section: Mapping Of Soybean and Rapeseed Metabolic Proteins On Suc Asmentioning

confidence: 99%

“…Previous studies on oil synthesis in plant seeds have proposed two major routes for carbon flow to de novo fatty acid synthesis (for review, see Jeanneau et al, 2002;Schwender et al, 2004b;Plaxton and Podesta, 2006). The first, and likely ubiquitous, route involves cytosolic glycolysis to PEP followed by PEP import to plastids and production of acetyl-CoA by the sequential action of plastid PK and PDC.…”

Section: Mapping Of Soybean and Rapeseed Metabolic Proteins On Suc Asmentioning

confidence: 99%

See 1 more Smart Citation

In-Depth Investigation of the Soybean Seed-Filling Proteome and Comparison with a Parallel Study of Rapeseed

Agrawal

Hajdúch²,

Graham³

et al. 2008

Plant Physiology

112

123

View full text Add to dashboard Cite

To better understand the metabolic processes of seed filling in soybean (Glycine max), two complementary proteomic approaches, two-dimensional gel electrophoresis (2-DGE) and semicontinuous multidimensional protein identification technology (Sec-MudPIT) coupled with liquid chromatography-mass spectrometry, were employed to analyze whole seed proteins at five developmental stages. 2-DGE and Sec-MudPIT analyses collectively identified 478 nonredundant proteins with only 70 proteins common to both datasets. 2-DGE data revealed that 38% of identified proteins were represented by multiple 2-DGE species. Identified proteins belonged to 13 (2-DGE) and 15 (Sec-MudPIT) functional classes. Proteins involved in metabolism, protein destination and storage, and energy were highly represented, collectively accounting for 61.1% (2-DGE) and 42.2% (Sec-MudPIT) of total identified proteins. Membrane proteins, based upon transmembrane predictions, were 3-fold more prominent in Sec-MudPIT than 2-DGE. Data were integrated into an existing soybean proteome database (www.oilseedproteomics.missouri.edu). The integrated quantitative soybean database was compared to a parallel study of rapeseed (Brassica napus) to further understand the regulation of intermediary metabolism in protein-rich versus oil-rich seeds. Comparative analyses revealed (1) up to 3-fold higher expression of fatty acid biosynthetic proteins during seed filling in rapeseed compared to soybean; and (2) approximately a 48% higher number of protein species and a net 80% higher protein abundance for carbon assimilatory and glycolytic pathways leading to fatty acid synthesis in rapeseed versus soybean. Increased expression of glycolytic and fatty acid biosynthetic proteins in rapeseed compared to soybean suggests that a possible mechanistic basis for higher oil in rapeseed involves the concerted commitment of hexoses to glycolysis and eventual de novo fatty acid synthesis pathways.Plant seeds accumulate proteins, oils, and carbohydrates because these nitrogen and carbon reserves are necessary for early seed germination and seedling growth (for review, see Weber et al., 2005). These reserve components are synthesized during an extended phase of seed development, loosely termed seed filling. Seed filling is the period when rapid metabolic and morphological (size, weight, and color) changes occur, encompassing cellular processes that include cell expansion and the early stage of desiccation (Rubel et al., 1972;Mienke et al., 1981;Agrawal and Thelen, 2006). Seed filling is also the period that largely determines the relative levels of storage reserves in seeds. The relative proportion of storage components in seeds varies dramatically among different plant species. For example, soybean (Glycine max) seed contains approximately 40% protein and 20% oil (Hill and Breidenbach, 1974;Ohlrogge and Kuo, 1984). In contrast, seed of oilseed rape (Brassica napus; also called rapeseed or canola) contains approximately 15% protein and 40% oil (Norton and Harris, 1975). To gain insight into...

show abstract

Section: Mapping Of Soybean and Rapeseed Metabolic Proteins On Suc Asmentioning

confidence: 99%

Section: Mapping Of Soybean and Rapeseed Metabolic Proteins On Suc Asmentioning

confidence: 99%

In-Depth Investigation of the Soybean Seed-Filling Proteome and Comparison with a Parallel Study of Rapeseed

Agrawal

Hajdúch²,

Graham³

et al. 2008

Plant Physiology

112

123

View full text Add to dashboard Cite

show abstract

“…The sources of information for the primary metabolic and biosynthetic pathways in the model were the recent literature on soybean embryo or higher plant biochemistry (Breitkreuz and Shelp, 1995;Chollet et al, 1996;Lam et al, 1996;Casati et al, 1999;Hermann and Weaver, 1999;Singh, 1999;Drincovich et al, 2001;Jeanneau et al, 2002), plant biochemistry texts (Dey and Harborne, 1997;Lea and Leegood, 1999), and the online catalog Soybase (2004). These sources also provided information on the precursors of the sink metabolites.…”

Section: Metabolic Network Modelmentioning

confidence: 99%

Quantification of Compartmented Metabolic Fluxes in Developing Soybean Embryos by Employing Biosynthetically Directed Fractional 13C Labeling, Two-Dimensional [13C, 1H] Nuclear Magnetic Resonance, and Comprehensive Isotopomer Balancing

et al. 2004

View full text Add to dashboard Cite

Metabolic flux quantification in plants is instrumental in the detailed understanding of metabolism but is difficult to perform on a systemic level. Toward this aim, we report the development and application of a computer-aided metabolic flux analysis tool that enables the concurrent evaluation of fluxes in several primary metabolic pathways. Labeling experiments were performed by feeding a mixture of U-13 C Suc, naturally abundant Suc, and Gln to developing soybean (Glycine max) embryos. Two-dimensional [ 13 C, 1 H] NMR spectra of seed storage protein and starch hydrolysates were acquired and yielded a labeling data set consisting of 155 13 C isotopomer abundances. We developed a computer program to automatically calculate fluxes from this data. This program accepts a user-defined metabolic network model and incorporates recent mathematical advances toward accurate and efficient flux evaluation. Fluxes were calculated and statistical analysis was performed to obtain SDs. A high flux was found through the oxidative pentose phosphate pathway (19.99 6 4.39 mmol d 21 cotyledon 21 , or 104.2 carbon mol 6 23.0 carbon mol per 100 carbon mol of Suc uptake). Separate transketolase and transaldolase fluxes could be distinguished in the plastid and the cytosol, and those in the plastid were found to be at least 6-fold higher. The backflux from triose to hexose phosphate was also found to be substantial in the plastid (21.72 6 5.00 mmol d 21 cotyledon 21, or 113.2 carbon mol 626.0 carbon mol per 100 carbon mol of Suc uptake). Forward and backward directions of anaplerotic fluxes could be distinguished. The glyoxylate shunt flux was found to be negligible. Such a generic flux analysis tool can serve as a quantitative tool for metabolic studies and phenotype comparisons and can be extended to other plant systems.

show abstract

“…Transgenic tobacco over-expressing fructose-1,6-bisphosphatase and sedoheptulose-1,7-bisphosphatase showed increased dry weight (Lefebvre et al, 2005;Tamoi et al, 2006). Similarly, transgenic maize over-expressing sorghum phosphoenolpyruvate carboxylase (PEPC) showed improved carbon dioxide fixation rate and increased fresh and dry weight under drought conditions (Jeanneau, et al, 2002). Change in plant architecture to enhance photosynthetic capacity has also recently shown to be effective in improving biomass and grain yield in rice (Sakamoto et al, 2006).…”

Section: Biomass Yieldmentioning

confidence: 99%

Genetically Engineered Crops for Biofuel Production: Regulatory Perspectives

Lee

Chen

Nair

2008

Biotechnology and Genetic Engineering Reviews

View full text Add to dashboard Cite

There are numerous challenges in realizing the potential of biofuels that many policy makers have envisioned. The technical challenges in making the production of biofuels economical and on a scale to replace a significant fraction of transportation fuel have been well described, along with the potential environmental concerns. The use of biotechnology can potentially address many of these technical challenges and environmental concerns, but brings significant regulatory hurdles that have not been discussed extensively in the scientific community. This review will give an overview of the approaches being developed to produce transgenic biofuel feedstocks, particularly cellulosic ethanol, and the regulatory process in the United States that oversees the development and commercialization of new transgenic plants. We hope to illustrate that the level of regulation for transgenic organisms is not proportional to their potential risk to human health or the environment, and that revisions to the regulatory system in the U.S. currently under consideration are necessary to streamline the process.

show abstract

Manipulating PEPC levels in plants

Cited by 65 publications

References 45 publications

In-Depth Investigation of the Soybean Seed-Filling Proteome and Comparison with a Parallel Study of Rapeseed

In-Depth Investigation of the Soybean Seed-Filling Proteome and Comparison with a Parallel Study of Rapeseed

Quantification of Compartmented Metabolic Fluxes in Developing Soybean Embryos by Employing Biosynthetically Directed Fractional 13C Labeling, Two-Dimensional [13C, 1H] Nuclear Magnetic Resonance, and Comprehensive Isotopomer Balancing

Genetically Engineered Crops for Biofuel Production: Regulatory Perspectives

Contact Info

Product

Resources

About