Articulation of three core metabolic processes in Arabidopsis: Fatty acid biosynthesis, leucine catabolism and starch metabolism

<p>Abstract</p> <p>Background</p> <p>Elucidating metabolic network structures and functions in multicellular organisms is an emerging goal of functional genomics. We describe the co-expression network of three core metabolic processes in the genetic model plant <it>Arabidopsis thaliana</it>: fatty acid biosynthesis, starch metabolism and amino acid (leucine) catabolism.</p> <p>Results</p> <p>These co-expression networks form modules populated by genes coding for enzymes that represent the reactions generally considered to define each pathway. However, the modules also incorporate a wider set of genes that encode transporters, cofactor biosynthetic enzymes, precursor-producing enzymes, and regulatory molecules. We tested experimentally the hypothesis that one of the genes tightly co-expressed with starch metabolism module, a putative kinase AtPERK10, will have a role in this process. Indeed, knockout lines of AtPERK10 have an altered starch accumulation. In addition, the co-expression data define a novel hierarchical transcript-level structure associated with catabolism, in which genes performing smaller, more specific tasks appear to be recruited into higher-order modules with a broader catabolic function.</p> <p>Conclusion</p> <p>Each of these core metabolic pathways is structured as a module of co-expressed transcripts that co-accumulate over a wide range of environmental and genetic perturbations and developmental stages, and represent an expanded set of macromolecules associated with the common task of supporting the functionality of each metabolic pathway. As experimentally demonstrated, co-expression analysis can provide a rich approach towards understanding gene function.</p

A systems biology approach toward understanding seed composition in soybean

Background The molecular, biochemical, and genetic mechanisms that regulate the complex metabolic network of soybean seed development determine the ultimate balance of protein, lipid, and carbohydrate stored in the mature seed. Many of the genes and metabolites that participate in seed metabolism are unknown or poorly defined; even more remains to be understood about the regulation of their metabolic networks. A global omics analysis can provide insights into the regulation of seed metabolism, even without a priori assumptions about the structure of these networks. Results With the future goal of predictive biology in mind, we have combined metabolomics, transcriptomics, and metabolic flux technologies to reveal the global developmental and metabolic networks that determine the structure and composition of the mature soybean seed. We have coupled this global approach with interactive bioinformatics and statistical analyses to gain insights into the biochemical programs that determine soybean seed composition. For this purpose, we used Plant/Eukaryotic and Microbial Metabolomics Systems Resource (PMR, http://www.metnetdb.org/pmr webcite, a platform that incorporates metabolomics data to develop hypotheses concerning the organization and regulation of metabolic networks, and MetNet systems biology tools http://www.metnetdb.org webcite for plant omics data, a framework to enable interactive visualization of metabolic and regulatory networks. Conclusions This combination of high-throughput experimental data and bioinformatics analyses has revealed sets of specific genes, genetic perturbations and mechanisms, and metabolic changes that are associated with the developmental variation in soybean seed composition. Researchers can explore these metabolomics and transcriptomics data interactively at PMR

Mechanism-of-Action Determination of GMP Synthase Inhibitors and Target Validation in Candida albicans and Aspergillus fumigatus

SummaryMechanism-of-action (MOA) studies of bioactive compounds are fundamental to drug discovery. However, in vitro studies alone may not recapitulate a compound's MOA in whole cells. Here, we apply a chemogenomics approach in Candida albicans to evaluate compounds affecting purine metabolism. They include the IMP dehydrogenase inhibitors mycophenolic acid and mizoribine and the previously reported GMP synthase inhibitors acivicin and 6-diazo-5-oxo-L-norleucine (DON). We report important aspects of their whole-cell activity, including their primary target, off-target activity, and drug metabolism. Further, we describe ECC1385, an inhibitor of GMP synthase, and provide biochemical and genetic evidence supporting its MOA to be distinct from acivicin or DON. Importantly, GMP synthase activity is conditionally essential in C. albicans and Aspergillus fumigatus and is required for virulence of both pathogens, thus constituting an unexpected antifungal target

Functional Identification of Valerena-1,10-diene Synthase, a Terpene Synthase Catalyzing a Unique Chemical Cascade in the Biosynthesis of Biologically Active Sesquiterpenes in Valeriana officinalis

Valerian is an herbal preparation from the roots of Valeriana officinalis used as an anxiolytic and sedative and in the treatment of insomnia. The biological activities of valerian are attributed to valerenic acid and its putative biosynthetic precursor valerenadiene, sesquiterpenes, found in V. officinalis roots. These sesquiterpenes retain an isobutenyl side chain whose origin has been long recognized as enigmatic because a chemical rationalization for their biosynthesis has not been obvious. Using recently developed metabolomic and transcriptomic resources, we identified seven V. officinalis terpene synthase genes (VoTPSs), two that were functionally characterized as monoterpene synthases and three that preferred farnesyl diphosphate, the substrate for sesquiterpene synthases. The reaction products for two of the sesquiterpene synthases exhibiting root-specific expression were characterized by a combination of GC-MS and NMR in comparison to the terpenes accumulating in planta. VoTPS7 encodes for a synthase that biosynthesizes predominately germacrene C, whereas VoTPS1 catalyzes the conversion of farnesyl diphosphate to valerena-1,10-diene. Using a yeast expression system, specific labeled [13C]acetate, and NMR, we investigated the catalytic mechanism for VoTPS1 and provide evidence for the involvement of a caryophyllenyl carbocation, a cyclobutyl intermediate, in the biosynthesis of valerena-1,10-diene. We suggest a similar mechanism for the biosynthesis of several other biologically related isobutenyl-containing sesquiterpenes

Comprehensive analysis of correlation coefficients estimated from pooling heterogeneous microarray data

Background The synthesis of information across microarray studies has been performed by combining statistical results of individual studies (as in a mosaic), or by combining data from multiple studies into a large pool to be analyzed as a single data set (as in a melting pot of data). Specific issues relating to data heterogeneity across microarray studies, such as differences within and between labs or differences among experimental conditions, could lead to equivocal results in a melting pot approach. Results We applied statistical theory to determine the specific effect of different means and heteroskedasticity across 19 groups of microarray data on the sign and magnitude of gene-to-gene Pearson correlation coefficients obtained from the pool of 19 groups. We quantified the biases of the pooled coefficients and compared them to the biases of correlations estimated by an effect-size model. Mean differences across the 19 groups were the main factor determining the magnitude and sign of the pooled coefficients, which showed largest values of bias as they approached ±1. Only heteroskedasticity across the pool of 19 groups resulted in less efficient estimations of correlations than did a classical meta-analysis approach of combining correlation coefficients. These results were corroborated by simulation studies involving either mean differences or heteroskedasticity across a pool of N \u3e 2 groups. Conclusions The combination of statistical results is best suited for synthesizing the correlation between expression profiles of a gene pair across several microarray studies

Chromosome Duplication in <i>Saccharomyces cerevisiae</i>

The accurate and complete replication of genomic DNA is essential for all life. In eukaryotic cells, the assembly of the multi-enzyme replisomes that perform replication is divided into stages that occur at distinct phases of the cell cycle. Replicative DNA helicases are loaded around origins of DNA replication exclusively during G 1 phase. The loaded helicases are then activated during S phase and associate with the replicative DNA polymerases and other accessory proteins. The function of the resulting replisomes is monitored by checkpoint proteins that protect arrested replisomes and inhibit new initiation when replication is inhibited. The replisome also coordinates nucleosome disassembly, assembly, and the establishment of sister chromatid cohesion. Finally, when two replisomes converge they are disassembled. Studies in Saccharomyces cerevisiae have led the way in our understanding of these processes. Here, we review our increasingly molecular understanding of these events and their regulation. Keywords: DNA replication; cell cycle; chromatin; chromosome duplication; genome stability; YeastBookNational Institutes of Health (U.S.) (Grant GM-052339

Articulation of three core metabolic processes in Arabidopsis: Fatty acid biosynthesis, leucine catabolism and starch metabolism

Background: Elucidating metabolic network structures and functions in multicellular organisms is an emerging goal of functional genomics. We describe the co-expression network of three core metabolic processes in the genetic model plant Arabidopsis thaliana: fatty acid biosynthesis, starch metabolism and amino acid (leucine) catabolism. Results: These co-expression networks form modules populated by genes coding for enzymes that represent the reactions generally considered to define each pathway. However, the modules also incorporate a wider set of genes that encode transporters, cofactor biosynthetic enzymes, precursor-producing enzymes, and regulatory molecules. We tested experimentally the hypothesis that one of the genes tightly co-expressed with starch metabolism module, a putative kinase AtPERK10, will have a role in this process. Indeed, knockout lines of AtPERK10 have an altered starch accumulation. In addition, the co-expression data define a novel hierarchical transcript-level structure associated with catabolism, in which genes performing smaller, more specific tasks appear to be recruited into higher-order modules with a broader catabolic function. Conclusion: Each of these core metabolic pathways is structured as a module of co-expressed transcripts that co-accumulate over a wide range of environmental and genetic perturbations and developmental stages, and represent an expanded set of macromolecules associated with the common task of supporting the functionality of each metabolic pathway. As experimentally demonstrated, co-expression analysis can provide a rich approach towards understanding gene function.This is an article from BMC Plant Biology 8 (2008): 1, doi:10.1186/1471-2229-8-76. Posted with permission.</p