Fructokinase is required for carbon partitioning to cellulose in aspen wood.

Sucrose is the main transported form of carbon in several plant species, including Populus species. Sucrose metabolism in developing wood has therefore a central role in carbon partitioning to stem biomass. Half of the sucrose-derived carbon is in the form of fructose, but metabolism of fructose has received little attention as a factor in carbon partitioning to walls of wood cells. We show that RNAi-mediated reduction of FRK2 activity in developing wood of hybrid aspen (Populus tremula × tremuloides) led to the accumulation of soluble neutral sugars and a decrease in hexose phosphates and UDP-glucose, indicating that carbon flux to cell-wall polysaccharide precursors is decreased. Reduced FRK2 activity also led to thinner fiber cell walls with a reduction in the proportion of cellulose. No pleiotropic effects on stem height or diameter were observed. The results establish a central role for FRK2 activity in carbon flux to wood cellulose.

Identification of enzyme activity quantitative trait loci in a Solanum lycopersicum x Solanum pennellii introgression line population.

Activities of 28 enzymes from central carbon metabolism were measured in pericarp tissue of ripe tomato fruits from field trials with an introgression line (IL) population generated by introgressing segments of the genome of the wild relative Solanum pennellii (LA0716) into the modern tomato cultivar Solanum lycopersicum M82. Enzyme activities were determined using a robotized platform in optimized conditions, where the activities largely reflect the level of the corresponding proteins. Two experiments were analyzed from years with markedly different climate conditions. A total of 27 quantitative trait loci were shared in both experiments. Most resulted in increased enzyme activity when a portion of the S. lycopersicum genome was substituted with the corresponding portion of the genome of S. pennellii. This reflects the change in activity between the two parental genotypes. The mode of inheritance was studied in a heterozygote IL population. A similar proportion of quantitative trait loci (approximately 30%) showed additive, recessive, and dominant modes of inheritance, with only 5% showing overdominance. Comparison with the location of putative genes for the corresponding proteins indicates a large role of trans-regulatory mechanisms. These results point to the genetic control of individual enzyme activities being under the control of a complex program that is dominated by a network of trans-acting genes.

A topological map of the compartmentalized Arabidopsis thaliana leaf metabolome.

BACKGROUND: The extensive subcellular compartmentalization of metabolites and metabolism in eukaryotic cells is widely acknowledged and represents a key factor of metabolic activity and functionality. In striking contrast, the knowledge of actual compartmental distribution of metabolites from experimental studies is surprisingly low. However, a precise knowledge of, possibly all, metabolites and their subcellular distributions remains a key prerequisite for the understanding of any cellular function. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe results for the subcellular distribution of 1,117 polar and 2,804 lipophilic mass spectrometric features associated to known and unknown compounds from leaves of the model plant Arabidopsis thaliana. Using an optimized non-aqueous fractionation protocol in conjunction with GC/MS- and LC/MS-based metabolite profiling, 81.5% of the metabolic data could be associated to one of three subcellular compartments: the cytosol (including the mitochondria), vacuole, or plastids. Statistical analysis using a marker-'free' approach revealed that 18.5% of these metabolites show intermediate distributions, which can either be explained by transport processes or by additional subcellular compartments. CONCLUSION/SIGNIFICANCE: Next to a functional and conceptual workflow for the efficient, highly resolved metabolite analysis of the fractionated Arabidopsis thaliana leaf metabolome, a detailed survey of the subcellular distribution of several compounds, in the graphical format of a topological map, is provided. This complex data set therefore does not only contain a rich repository of metabolic information, but due to thorough validation and testing by statistical methods, represents an initial step in the analysis of metabolite dynamics and fluxes within and between subcellular compartments.

Sample amount alternatives for data adjustment in comparative cyanobacterial metabolomics.

Here we describe an integrative protocol for metabolite extraction and the measurement of three cellular constituents, chlorophyll a, total protein, and glycogen from the same small volume of cyanobacterial cultures that can be used as alternative sample amount parameters for data adjustment in comparative metabolome studies. We conducted recovery experiments to assess the robustness and reproducibility of the measurements obtained for the cellular constituents. Also, we have chosen three profile-intrinsic parameters derived from gas chromatography-mass spectrometry (GC/MS) data in order to test their utility for spectral data adjustment. To demonstrate the relevance of these six parameters, we analyzed three cyanobacteria with greatly different morphologies, comprising a unicellular, a filamentous, and a filamentous biofilm-forming strain. Comparative analysis of GC/MS data from cultures grown under standardized conditions indicated that adjustment of the corresponding metabolite profiles by any of the measured cellular constituents or chosen intrinsic parameters led to similar results with respect to sample cohesion and strain separation. Twenty-one metabolites significantly enriched for the carbohydrate and amine superclasses are mainly responsible for strain separation, with a majority of the remaining metabolites contributing to sample group cohesion. Therefore, we conclude that any of the parameters tested in this study can be used for spectral data adjustment of cyanobacterial strains grown under controlled conditions. However, their use for the differentiation between different stresses or physiological states within a strain remains to be shown. Interestingly, both the adjustment approaches and statistical tests applied effected the detection of metabolic differences and their patterns among the analyzed strains.

Malate plays a crucial role in starch metabolism, ripening, and soluble solid content of tomato fruit and affects postharvest softening.

Despite the fact that the organic acid content of a fruit is regarded as one of its most commercially important quality traits when assessed by the consumer, relatively little is known concerning the physiological importance of organic acid metabolism for the fruit itself. Here, we evaluate the effect of modifying malate metabolism in a fruit-specific manner, by reduction of the activities of either mitochondrial malate dehydrogenase or fumarase, via targeted antisense approaches in tomato (Solanum lycopersicum). While these genetic perturbations had relatively little effect on the total fruit yield, they had dramatic consequences for fruit metabolism, as well as unanticipated changes in postharvest shelf life and susceptibility to bacterial infection. Detailed characterization suggested that the rate of ripening was essentially unaltered but that lines containing higher malate were characterized by lower levels of transitory starch and a lower soluble sugars content at harvest, whereas those with lower malate contained higher levels of these carbohydrates. Analysis of the activation state of ADP-glucose pyrophosphorylase revealed that it correlated with the accumulation of transitory starch. Taken together with the altered activation state of the plastidial malate dehydrogenase and the modified pigment biosynthesis of the transgenic lines, these results suggest that the phenotypes are due to an altered cellular redox status. The combined data reveal the importance of malate metabolism in tomato fruit metabolism and development and confirm the importance of transitory starch in the determination of agronomic yield in this species.

Network analysis of enzyme activities and metabolite levels and their relationship to biomass in a large panel of Arabidopsis accessions.

Natural genetic diversity provides a powerful resource to investigate how networks respond to multiple simultaneous changes. In this work, we profile maximum catalytic activities of 37 enzymes from central metabolism and generate a matrix to investigate species-wide connectivity between metabolites, enzymes, and biomass. Most enzyme activities change in a highly coordinated manner, especially those in the Calvin-Benson cycle. Metabolites show coordinated changes in defined sectors of metabolism. Little connectivity was observed between maximum enzyme activities and metabolites, even after applying multivariate analysis methods. Measurements of posttranscriptional regulation will be required to relate these two functional levels. Individual enzyme activities correlate only weakly with biomass. However, when they are used to estimate protein abundances, and the latter are summed and expressed as a fraction of total protein, a significant positive correlation to biomass is observed. The correlation is additive to that obtained between starch and biomass. Thus, biomass is predicted by two independent integrative metabolic biomarkers: preferential investment in photosynthetic machinery and optimization of carbon use.

Enzyme activity profiles during fruit development in tomato cultivars and Solanum pennellii.

Enzymes interact to generate metabolic networks. The activities of more than 22 enzymes from central metabolism were profiled during the development of fruit of the modern tomato cultivar Solanum lycopersicum 'M82' and its wild relative Solanum pennellii (LA0716). In S. pennellii, the mature fruit remains green and contains lower sugar and higher organic acid levels. These genotypes are the parents of a widely used near introgression line population. Enzymes were also profiled in a second cultivar, S. lycopersicum 'Moneymaker', for which data sets for the developmental changes of metabolites and transcripts are available. Whereas most enzyme activities declined during fruit development in the modern S. lycopersicum cultivars, they remained high or even increased in S. pennellii, especially enzymes required for organic acid synthesis. The enzyme profiles were sufficiently characteristic to allow stages of development and cultivars and the wild species to be distinguished by principal component analysis and clustering. Many enzymes showed coordinated changes during fruit development of a given genotype. Comparison of the correlation matrices revealed a large overlap between the two modern cultivars and considerable overlap with S. pennellii, indicating that despite the very different development responses, some basic modules are retained. Comparison of enzyme activity, metabolite profiles, and transcript profiles in S. lycopersicum 'Moneymaker' revealed remarkably little connectivity between the developmental changes of transcripts and enzymes and even less between enzymes and metabolites. We discuss the concept that the metabolite profile is an emergent property that is generated by complex network interactions.

Starch as a major integrator in the regulation of plant growth.

Rising demand for food and bioenergy makes it imperative to breed for increased crop yield. Vegetative plant growth could be driven by resource acquisition or developmental programs. Metabolite profiling in 94 Arabidopsis accessions revealed that biomass correlates negatively with many metabolites, especially starch. Starch accumulates in the light and is degraded at night to provide a sustained supply of carbon for growth. Multivariate analysis revealed that starch is an integrator of the overall metabolic response. We hypothesized that this reflects variation in a regulatory network that balances growth with the carbon supply. Transcript profiling in 21 accessions revealed coordinated changes of transcripts of more than 70 carbon-regulated genes and identified 2 genes (myo-inositol-1-phosphate synthase, a Kelch-domain protein) whose transcripts correlate with biomass. The impact of allelic variation at these 2 loci was shown by association mapping, identifying them as candidate lead genes with the potential to increase biomass production.

Integrative analyses of genetic variation in enzyme activities of primary carbohydrate metabolism reveal distinct modes of regulation in Arabidopsis thaliana.

BACKGROUND: Plant primary carbohydrate metabolism is complex and flexible, and is regulated at many levels. Changes of transcript levels do not always lead to changes in enzyme activities, and these do not always affect metabolite levels and fluxes. To analyze interactions between these three levels of function, we have performed parallel genetic analyses of 15 enzyme activities involved in primary carbohydrate metabolism, transcript levels for their encoding structural genes, and a set of relevant metabolites. Quantitative analyses of each trait were performed in the Arabidopsis thaliana Ler x Cvi recombinant inbred line (RIL) population and subjected to correlation and quantitative trait locus (QTL) analysis. RESULTS: Traits affecting primary metabolism were often correlated, possibly due to developmental control affecting multiple genes, enzymes, or metabolites. Moreover, the activity QTLs of several enzymes co-localized with the expression QTLs (eQTLs) of their structural genes, or with metabolite accumulation QTLs of their substrates or products. In addition, many trait-specific QTLs were identified, revealing that there is also specific regulation of individual metabolic traits. Regulation of enzyme activities often occurred through multiple loci, involving both cis- and trans-acting transcriptional or post-transcriptional control of structural genes, as well as independently of the structural genes. CONCLUSION: Future studies of the regulatory processes in primary carbohydrate metabolism will benefit from an integrative genetic analysis of gene transcription, enzyme activity, and metabolite content. The multiparallel QTL analyses of the various interconnected transducers of biological information flow, described here for the first time, can assist in determining the causes and consequences of genetic regulation at different levels of complex biological systems.

On-chip hybridization kinetics for optimization of gene expression experiments.

DNA microarray technology is a powerful tool for getting an overview of gene expression in biological samples. Although the successful use of microarray-based expression analysis was demonstrated in a number of applications, the main problem with this approach is the fact that expression levels deduced from hybridization experiments do not necessarily correlate with RNA concentrations. Moreover oligonucleotide probes corresponding to the same gene can give different hybridization signals. Apart from cross-hybridizations and differential splicing, this could be due to secondary structures of probes or targets. In addition, for low-copy genes, hybridization equilibrium may be reached after hybridization times much longer than the one commonly used (overnight, i.e., 15 h). Thus, hybridization signals could depend on kinetic properties of the probe, which may vary between different oligonucleotide probes immobilized on the same microarray. To validate this hypothesis, on-chip hybridization kinetics and duplex thermostability analysis were performed using oligonucleotide microarrays containing 50-mer probes corresponding to 10 mouse genes. We demonstrate that differences in hybridization kinetics between the probes exist and can influence the interpretation of expression data. In addition, we show that using on-chip hybridization kinetics, quantification of targets is feasible using calibration curves.