Sakarindr Bhumiratana

Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model

BackgroundStarch serves as a temporal storage of carbohydrates in plant leaves during day/night cycles. To study transcriptional regulatory modules of this dynamic metabolic process, we conducted gene regulation network analysis based on small-sample inference of graphical Gaussian model (GGM).ResultsTime-series significant analysis was applied for Arabidopsis leaf transcriptome data to obtain a set of genes that are highly regulated under a diurnal cycle. A total of 1,480 diurnally regulated genes included 21 starch metabolic enzymes, 6 clock-associated genes, and 106 transcription factors (TF). A starch-clock-TF gene regulation network comprising 117 nodes and 266 edges was constructed by GGM from these 133 significant genes that are potentially related to the diurnal control of starch metabolism. From this network, we found that β-amylase 3 (b-amy3: At4g17090), which participates in starch degradation in chloroplast, is the most frequently connected gene (a hub gene). The robustness of gene-to-gene regulatory network was further analyzed by TF binding site prediction and by evaluating global co-expression of TFs and target starch metabolic enzymes. As a result, two TFs, indeterminate domain 5 (AtIDD5: At2g02070) and constans-like (COL: At2g21320), were identified as positive regulators of starch synthase 4 (SS4: At4g18240). The inference model of AtIDD5-dependent positive regulation of SS4 gene expression was experimentally supported by decreased SS4 mRNA accumulation in Atidd5 mutant plants during the light period of both short and long day conditions. COL was also shown to positively control SS4 mRNA accumulation. Furthermore, the knockout of AtIDD5 and COL led to deformation of chloroplast and its contained starch granules. This deformity also affected the number of starch granules per chloroplast, which increased significantly in both knockout mutant lines.ConclusionsIn this study, we utilized a systematic approach of microarray analysis to discover the transcriptional regulatory network of starch metabolism in Arabidopsis leaves. With this inference method, the starch regulatory network of Arabidopsis was found to be strongly associated with clock genes and TFs, of which AtIDD5 and COL were evidenced to control SS4 gene expression and starch granule formation in chloroplasts.

Metabolic flux distribution for γ-linolenic acid synthetic pathways inSpirulina platensis

Spirulina produces γ-linolenic acid (GLA), an important pharmaceutical substance, in a relatively low level compared with fungi and plants, prompting more research to improve its GLA yield. In this study, metabolic flux analysis was applied to determine the cellular metabolic flux distributions in the GLA synthetic pathways of twoSpirulina strains, wild type BP and a high-GLA producing mutant Z19/2. Simplified pathways involving the GLA synthesis ofS. platensis formulated comprise of photosynthesis, gluconeogenesis, the pentose phosphate pathway, the anaplerotic pathway, the tricarboxylic cycle, the GLA synthesis pathway, and the biomass synthesis pathway. A stoichiometric model reflecting these pathways contains 17 intermediates and 22 reactions. Three fluxes—the bicarbonate (C-source) uptake rate, the specific growth rate, and the GLA synthesis rate—were measured and the remaining fluxes were calculated using linear optimization. The calculation showed that the flux through the reaction converting acetyl-CoA into malonyl-CoA in the mutant strain was nearly three times higher than that in the wild-type strain. This finding implies that this reaction is rate controlling. This suggestion was supported by experiments, in which the stimulating factors for this reaction (NADPH and MgCl2) were added into the culture medium, resulting in an increased GLA-synthesis rate in the wild type strain.

The role of moisture movement and crust thermal property on heat and mass process during deep-fat frying

The role of moisture movement and crust thermal property on heat and mass (moisture) transfer during deep-fat frying was studied. Direct effect (as convection heat transfer) and indirect effect (as contribution to food property changes) were examined. The heat transfer model was formulated using the enthalpy approach and moving boundary concept, while the moisture transfer was expressed by Ficks law of diffusion assuming a constant diffusivity. The calculation procedure, which was controlled by the surface temperature of the sample being fried, was divided into two steps namely the initial heating period and the surface boiling period

Enzyme Relational Network Reveals Target Enzymes within Metabolic Submodules

Identification of enzyme targets for metabolic engineering requires a global view of the functional relationship among enzymes within metabolic network. In this paper, we propose a method to construct an enzyme relational network based on the significant effect of the rate change of one reaction on the rate of another reaction. We illustrate the method by using a kinetic model to formulate the enzyme relational network of the sucrose-to-starch conversion process. The network obtained shows two separate submodules, one of which possesses the enzymes located in cytosol; the other, in amyloplast. The network reveals that ADP-glucose pyrophosphorylase and inorganic pyrophosphatase are potential target enzymes for metabolic engineering to improve starch yield.

The Future of Biotechnology for the Improvement of Nutrition and Health: Realizing the Potential for Asia

Food and Nutrition Bulletin, vol. 26, no. 4 (supplement)