Insulin Directly Regulates the Circadian Clock in Adipose Tissue.

Adipose tissue (AT) is a key metabolic organ which functions are rhythmically regulated by an endogenous circadian clock. Feeding is a "zeitgeber" aligning the clock in AT with the external time, but mechanisms of this regulation remain largely unclear. We tested the hypothesis that postprandial changes of the hormone insulin directly entrain circadian clocks in AT and investigated a transcriptional-dependent mechanism of this regulation. We analyzed gene expression in subcutaneous AT (SAT) of obese subjects collected before and after the hyperinsulinemic-euglycemic clamp or control saline infusion (SC). The expressions of core clock genes PER2, PER3, and NR1D1 in SAT were differentially changed upon insulin and saline infusion, suggesting insulin-dependent clock regulation. In human stem cell-derived adipocytes, mouse 3T3-L1 cells, and AT explants from mPer2Luc knockin mice, insulin induced a transient increase of the Per2 mRNA and protein expression, leading to the phase shift of circadian oscillations, with similar effects for Per1 Insulin effects were dependent on the region between -64 and -43 in the Per2 promoter but not on CRE and E-box elements. Our results demonstrate that insulin directly regulates circadian clocks in AT and isolated adipocytes, thus representing a primary mechanism of feeding-induced AT clock entrainment.

Glyoxylate, a new marker metabolite of type 2 diabetes.

Type 2 diabetes (T2D) is characterized by a variety of metabolic impairments that are closely linked to nonenzymatic glycation reactions of proteins and peptides resulting in advanced glycation end-products (AGEs). Reactive aldehydes derived from sugars play an important role in the generation of AGEs. Using metabolite profiling to characterize human plasma from diabetic versus nondiabetic subjects we observed in a recent study that the reactive aldehyde glyoxylate was increased before high levels of plasma glucose, typical for a diabetic condition, could be measured. Following this observation, we explored the relevance of increased glyoxylate in diabetic subjects and in diabetic C57BLKS/J-Lepr (db/db (-/-)) mice in the pathophysiology of diabetes. A retrospective study using samples of long-term blood donors revealed that glyoxylate levels unlike glucose levels became significantly elevated up to 3 years prior to diabetes diagnosis (difference to control P = 0.034). Elevated glyoxylate levels impact on newly identified mechanisms linking hyperglycemia and AGE production with diabetes-associated complications such as diabetic nephropathy. Glyoxylate in its metabolic network may serve as an early marker in diabetes diagnosis with predictive qualities for associated complications and as potential to guide the development of new antidiabetic therapies.

Insulin up-regulates natriuretic peptide clearance receptor expression in the subcutaneous fat depot in obese subjects: a missing link between CVD risk and obesity?

CONTEXT: Natriuretic peptides (NP) regulate cardiovascular homeostasis and have multiple metabolic properties. Decreased levels of NP or "natriuretic handicap" are signs of insulin resistance such as central obesity. Increased expression of NP clearance receptor (NPRC) in sc adipose tissue (SAT) was observed in insulin-resistant subjects. OBJECTIVE: We hypothesized that insulin acutely regulates NP receptor expression in adipose tissue. DESIGN AND PARTICIPANTS: NPRA, NPRB, and NPRC mRNA expression was measured in paired samples of visceral adipose tissue (VAT) and SAT from 157 subjects (108 with type 2 diabetes). The effect of insulin on NPR gene expression in SAT was studied in euglycemic-hyperinsulinemic and hyperglycemic-hyperinsulinemic clamp experiments. Additionally, the effect of insulin and glucose on NPR expression in the culture of primary human monocytes and macrophages was tested. RESULTS: NPRA and NPRC gene expression was higher in VAT compared with SAT (P < 0.01), but only NPRC gene expression strongly correlated with fasting insulin levels (r = 0.65, P = 0.04 × 10(-3); and r = 0.54, P = 0.002, for VAT and SAT, respectively). NPRB expression was lower in VAT than in SAT in subjects with type 2 diabetes and was lower compared with nondiabetic subjects. NPRC gene expression was up-regulated in SAT during both euglycemic- and hyperglycemic-hyperinsulinemic clamps (P = 0.038 and P = 0.048, respectively), and was increased in high glucose and insulin treatment in monocytes (70.2%; P = 0.01), but not in mature macrophages. CONCLUSION: Insulin increased expression of NPRC in SAT independently of circulating glucose concentrations. Thus, insulin might suppress circulating NP via up-regulation of NPRC expression in obesity, providing a novel link between hyperinsulinemia and obesity.

Metabolomic linkage reveals functional interaction between glucose-dependent insulinotropic polypeptide and ghrelin in humans.

The gastric peptide ghrelin promotes energy storage, appetite, and food intake. Nutrient intake strongly suppresses circulating ghrelin via molecular mechanisms possibly involving insulin and gastrointestinal hormones. On the basis of the growing evidence that glucose-dependent insulinotropic polypeptide (GIP) is involved in the control of fuel metabolism, we hypothesized that GIP and/or insulin, directly or via changes in plasma metabolites, might affect circulating ghrelin. Fourteen obese subjects were infused with GIP (2.0 pmol·kg(-1)·min(-1)) or placebo in the fasting state during either euglycemic hyperinsulinemic (EC) or hyperglycemic hyperinsulinemic clamps (HC). Apart from analysis of plasma ghrelin and insulin levels, GC-TOF/MS analysis was applied to create a hormone-metabolite network for each experiment. The GIP and insulin effects on circulating ghrelin were analyzed within the framework of those networks. In the HC, ghrelin levels decreased in the absence (19.2% vs. baseline, P = 0.028) as well as in the presence of GIP (33.8%, P = 0.018). Ghrelin levels were significantly lower during HC with GIP than with placebo, despite insulin levels not differing significantly. In the GIP network combining data on GIP-infusion, EC+GIP and HC+GIP experiments, ghrelin was integrated into hormone-metabolite networks through a connection to a group of long-chain fatty acids. In contrast, ghrelin was excluded from the network of experiments without GIP. GIP decreased circulating ghrelin and might have affected the ghrelin system via modification of long-chain fatty acid pools. These observations were independent of insulin and offer potential mechanistic underpinnings for the involvement of GIP in systemic control of energy metabolism.

The complexity of gene expression dynamics revealed by permutation entropy.

BACKGROUND: High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical systems theory. The analysis of gene expression data has so far focused primarily on the identification of differentially expressed genes, or on the elucidation of pathway and regulatory relationships. We aim to study gene expression time series data from the viewpoint of complexity. RESULTS: Applying the PE complexity metric to abiotic stress response time series data in Arabidopsis thaliana, genes involved in stress response and signaling were found to be associated with the highest complexity not only under stress, but surprisingly, also under reference, non-stress conditions. Genes with house-keeping functions exhibited lower PE complexity. Compared to reference conditions, the PE of temporal gene expression patterns generally increased upon stress exposure. High-complexity genes were found to have longer upstream intergenic regions and more cis-regulatory motifs in their promoter regions indicative of a more complex regulatory apparatus needed to orchestrate their expression, and to be associated with higher correlation network connectivity degree. Arabidopsis genes also present in other plant species were observed to exhibit decreased PE complexity compared to Arabidopsis specific genes. CONCLUSIONS: We show that Permutation Entropy is a simple yet robust and powerful approach to identify temporal gene expression profiles of varying complexity that is equally applicable to other types of molecular profile data.

A contribution to identification of novel regulators of plant response to sulfur deficiency: characteristics of a tobacco gene UP9C, its protein product and the effects of UP9C silencing.

Extensive changes in plant transcriptome and metabolome have been observed by numerous research groups after transferring plants from optimal conditions to sulfur (S) deficiency. Despite intensive studies and recent important achievements, like identification of SLIM1/EIL3 as a major transcriptional regulator of the response to S-deficiency, many questions concerning other elements of the regulatory network remain unanswered. Investigations of genes with expression regulated by S-deficiency stress encoding proteins of unknown function might help to clarify these problems. This study is focused on the UP9C gene and the UP9-like family in tobacco. Homologs of these genes exist in other plant species, including a family of four genes of unknown function in Arabidopsis thaliana (LSU1-4), of which two were reported as strongly induced by S-deficit and to a lesser extent by salt stress and nitrate limitation. Conservation of the predicted structural features, such as coiled coil region or nuclear localization signal, suggests that these proteins might have important functions possibly mediated by interactions with other proteins. Analysis of transgenic tobacco plants with silenced expression of UP9-like genes strongly argues for their significant role in regulation of plant response to S-deficit. Although our study shows that the UP9-like proteins are important components of such response and they might be also required during other stresses, their molecular functions remain a mystery.

Stability of metabolic correlations under changing environmental conditions in Escherichia coli--a systems approach.

BACKGROUND: Biological systems adapt to changing environments by reorganizing their cellular and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underlying metabolic network. METHODOLOGY/PRINCIPAL FINDINGS: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic condition-dependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple observations about the changes of metabolic concentrations. The approach was tested with Escherichia coli as a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diauxie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical pathways, and (3) independently of the response scale, based on their importance in the reorganization of the correlation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response. CONCLUSIONS/SIGNIFICANCE: Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-based approach does not rely on major changes in concentration to identify metabolites important for stress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches.

The influence of genetic variations in HHEX gene on insulin metabolism in the German MESYBEPO cohort.

BACKGROUND: In the present study, we aimed to validate the type 2 diabetes (T2DM) susceptibility alleles identified in the first genome-wide association study in the hematopoietically expressed homeobox protein (HHEX) gene region (rs1111875 and rs7923837). Furthermore, we investigated quantitative metabolic risk phenotypes of these two variants for association with three key components of the insulin metabolism: insulin secretion, insulin sensitivity and insulin degradation. METHODS: Two HHEX polymorphisms were genotyped in 1026 subjects from the German MESYBEPO cohort. Complete OGTT data were available for a subset of 420 with normal glucose tolerance (NGT), 282 with impaired glucose tolerance/impaired fasting glucose (IGT/IFG) and 146 diabetic subjects. RESULTS: We validated association of both HHEX polymorphisms with T2DM. In the non-diabetic subcohort including NGT and IFG/IGT subjects, the risk alleles of rs7923837 and rs1111875 were significantly associated with decreased first and second phases of insulin secretion and lower insulinogenic index after oral glucose loading. In healthy, normal glucose-tolerant subjects, the same association of HHEX SNP rs1111875 with OGTT-derived phases of insulin secretion were detectable, however, rs7923837 was only weakly associated with reduced insulinogenic index. For both polymorphisms, no significant correlations with insulin sensitivity were obtained. Reduced insulin clearance was also observed in heterozygous carriers of rs1111875. CONCLUSIONS: We validated the association of polymorphisms of the HHEX gene with T2DM in the MESYBEPO cohort. Importantly, variations within the HHEX gene conferred the impaired insulin secretion and changes of insulin degradation but no alteration in insulin sensitivity in carriers of risk alleles.

Reconfiguration of the achene and receptacle metabolic networks during strawberry fruit development.

The anatomy of strawberry (Fragaria x ananassa) fruit, in which the achene is found on the outer part of the fruit, makes it an excellent species for studying the regulation of fruit development. It can provide a model for the cross talk between primary and secondary metabolism, whose role is of pivotal importance in the process. By combining gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry with the aim of addressing the metabolic regulation underlying fruit seed development, we simultaneously analyzed the composition of primary and secondary metabolites, separately, in achene and receptacle during fruit ripening of strawberry cultivar Herut. The results from these analyses suggest that changes in primary and secondary metabolism reflect organ and developmental specificities. For instance, the receptacle was characterized by increases in sugars and their direct derivatives, while the achene was characterized by a major decrease in the levels of carbon- and nitrogen-rich compounds, with the exception of storage-related metabolites (e.g. raffinose). Furthermore, the receptacle, and to a lesser extent the achene, exhibited dynamic fluctuations in the levels and nature of secondary metabolites across the ripening process. In the receptacle, proanthocyanidins and flavonol derivatives characterized mainly early developmental stages, while anthocyanins were abundant in the mature red stage; in the achene, ellagitannin and flavonoids were abundant during early and late development, respectively. Correlation-based network analysis suggested that metabolism is substantially coordinated during early development in either organ. Nonetheless, a higher degree of connectivity within and between metabolic pathways was measured in the achenes. The data are discussed within the context of current models both of the interaction of primary and secondary metabolism and of the metabolic interaction between the different plant organs.

Metabolomics integrated with transcriptomics: assessing systems response to sulfur-deficiency stress.

Sulfur-containing amino acids, cysteine and methionine synthesized in plants are essential for human and animal nutrition. That is why understanding of how inorganic sulfur is taken up by plants and built into the organic molecules in the process of sulfur assimilation is important. As complex biological systems, plants subsist as integrated molecular, organelle, cell, tissue and organ entities, being in permanent synergistic coordination. The process of sulfur uptake and assimilation is an integral part of this dense network of influences, its reconstruction may help in manipulating the bioproduction of organic sulfur-containing compounds. New high-throughput technologies allow the systems' view on the coordination of complex processes in living organisms. Among them, transcriptomics and metabolomics studies were applied to Arabidopsis plants subjected to sulfur-deficiency stress. From the integrated analysis of the obtained data, the mosaic picture of distinct sulfur stress response events and processes are starting to be assembled into the whole systems' network of sulfur assimilation. At the time trajectory of sulfur stress response, two system states can be distinguished. The first state of short-term responses is characterized by the development of enhanced lateral roots exploring the space in search for the lacking nutrient. When this physiological reaction cannot be accomplished by bringing the system back to the initial state of sulfur sufficiency, a new program is toggled aiming at saving the organismal resources for vital seed production. Here, we describe the biological reasoning in these two system states and the process of state transition between them.

Gene expression profiling of the different stages of Arabidopsis thaliana trichome development on the single cell level.

Leaf hairs (trichomes) of Arabidopsis thaliana are a model system for studying cell development, differentiation and cell cycle regulation. To exploit this model system with ultimate spatial resolution we applied single cell sampling, thus avoiding the averaging effect induced by complex tissue mixtures. In particular, we analysed gene expression profiles of two selected stages of the developing trichome: trichome initial cells and mature trichomes, as well as pavement cells. Ten single cells per sample were collected by glass microcapillaries and used for the generation of radioactive probes for subsequent hybridization to nylon filters representing approximately 8000 genes of A. thaliana. Functional categorization of genes transcribed in trichome initials, mature trichomes and pavement cells demonstrated involvement of these surface cells in the stress response. In silico promoter analysis of genes preferentially expressed in trichome initials revealed enrichment in MYB-binding sites and presence of elements involved in hormonal, metal, sulphur response and cell cycle regulation. Three candidate genes preferentially expressed in trichome initials were selected for further analysis: At3g16980 (putative RNA polymerase II), At5g15230 (GASA4) and At4g27260 (GH3.5, WES1). Promoter:GUS studies confirmed expression of the putative RNA polymerase II and the gibberellin responsive GASA4 in trichome initials and partially in mature trichomes. Functional implication of the three selected candidates in trichome development and hence in cell cycle regulation in A. thaliana is discussed. We suggest that these genes are involved in differentiation and initiation of endocycling during trichome development.

On the processing of metabolic information through metabolite-gene communication networks: an approach for modelling causality.

Gene-metabolite correlation networks of three independent biological systems were interrogated using an approach to define, and subsequently model, causality. The major goal of this work was to analyse how information from those metabolites, that displayed a rapid response to perturbation of the biological system, is processed through the response network to provide signal-specific adaptation of metabolism. For this purpose, comparison of network topologies was carried out on three different groups of system elements: transcription factors, other genes and metabolites, with special emphasis placed on those features which are possible sites of metabolic regulation or response propagation. The degree of connectivity in all three analysed gene-metabolite networks followed power-law and exponential functions, whilst a comparison of connectivities of the various cellular entities suggested, that metabolites are less involved in the regulation of the sulfur stress response than in the ripening of tomatoes (in which metabolites seem to have an even greater regulatory role than transcription factors). These findings reflect different degree of metabolic regulation for distinct biological processes. Implementing causality into the network allowed classification of metabolite-gene associations into those with causal directionality from gene to metabolite and from metabolite to gene. Several metabolites were positioned relatively early in the causal hierarchy and possessed many connections to the downstream elements. Such metabolites were considered to have higher regulatory potential. For the biological example of hypo-sulfur stress response in Arabidopsis, the highest regulatory potential scores were established for fructose and sucrose, isoleucine, methionine and sinapic acid. Further developments in profiling techniques will allow greater cross-systems comparisons, necessary for reliability and universality checks of inferred regulatory capacities of the particular metabolites.

Network visualization and network analysis.

Network analysis of living systems is an essential component of contemporary systems biology. It is targeted at assemblance of mutual dependences between interacting systems elements into an integrated view of whole-system functioning. In the following chapter we describe the existing classification of what is referred to as biological networks and show how complex interdependencies in biological systems can be represented in a simpler form of network graphs. Further structural analysis of the assembled biological network allows getting knowledge on the functioning of the entire biological system. Such aspects of network structure as connectivity of network elements and connectivity degree distribution, degree of node centralities, clustering coefficient, network diameter and average path length are touched. Networks are analyzed as static entities, or the dynamical behavior of underlying biological systems may be considered. The description of mathematical and computational approaches for determining the dynamics of regulatory networks is provided. Causality as another characteristic feature of a dynamically functioning biosystem can be also accessed in the reconstruction of biological networks; we give the examples of how this integration is accomplished. Further questions about network dynamics and evolution can be approached by means of network comparison. Network analysis gives rise to new global hypotheses on systems functionality and reductionist findings of novel molecular interactions, based on the reliability of network reconstructions, which has to be tested in the subsequent experiments. We provide a collection of useful links to be used for the analysis of biological networks.

Integrated analysis of metabolite and transcript levels reveals the metabolic shifts that underlie tomato fruit development and highlight regulatory aspects of metabolic network behavior.

Tomato (Solanum lycopersicum) is a well-studied model of fleshy fruit development and ripening. Tomato fruit development is well understood from a hormonal-regulatory perspective, and developmental changes in pigment and cell wall metabolism are also well characterized. However, more general aspects of metabolic change during fruit development have not been studied despite the importance of metabolism in the context of final composition of the ripe fruit. In this study, we quantified the abundance of a broad range of metabolites by gas chromatography-mass spectrometry, analyzed a number of the principal metabolic fluxes, and in parallel analyzed transcriptomic changes during tomato fruit development. Metabolic profiling revealed pronounced shifts in the abundance of metabolites of both primary and secondary metabolism during development. The metabolite changes were reflected in the flux analysis that revealed a general decrease in metabolic activity during ripening. However, there were several distinct patterns of metabolite profile, and statistical analysis demonstrated that metabolites in the same (or closely related) pathways changed in abundance in a coordinated manner, indicating a tight regulation of metabolic activity. The metabolite data alone allowed investigations of likely routes through the metabolic network, and, as an example, we analyze the operational feasibility of different pathways of ascorbate synthesis. When combined with the transcriptomic data, several aspects of the regulation of metabolism during fruit ripening were revealed. First, it was apparent that transcript abundance was less strictly coordinated by functional group than metabolite abundance, suggesting that posttranslational mechanisms dominate metabolic regulation. Nevertheless, there were some correlations between specific transcripts and metabolites, and several novel associations were identified that could provide potential targets for manipulation of fruit compositional traits. Finally, there was a strong relationship between ripening-associated transcripts and specific metabolite groups, such as TCA-cycle organic acids and sugar phosphates, underlining the importance of the respective metabolic pathways during fruit development.

Integrative gene-metabolite network with implemented causality deciphers informational fluxes of sulphur stress response.

The systematic accumulation of gene expression data, although revolutionary, is insufficient in itself for an understanding of system-level physiology. In the post-genomic era, the next cognitive step is linking genes to biological processes and assembling a mosaic of data into global models of biosystem function. A dynamic network of informational flows in Arabidopsis plants perturbed by sulphur depletion is presented here. With the use of an original protocol, the first biosystem response network was reconstructed from a time series of transcript and metabolite profiles, which, on the one hand, integrates complex metabolic and transcript data and, on the other hand, possesses a causal relationship. Using the informational fluxes within this reconstruction, it was possible to link system perturbation to response endpoints. Robustness and stress tolerance, as consequences of scale-free network topology, and hubs, as potential controllers of homeostasis maintenance, were revealed. Communication paths of propagating system excitement directed to physiological endpoints, such as anthocyanin accumulation and enforced root formation were dissected from the network. An auxin regulatory circuit involved in the control of a hypo-sulphur stress response was uncovered.

Impact of elevated H(2)S on metabolite levels, activity of enzymes and expression of genes involved in cysteine metabolism.

The effects of elevated atmospheric hydrogen sulfide (H(2)S) levels (0.25, 0.5, and 0.75 microl l(-1)) have been investigated in a short-term exposure experiment (3-48 h) on the model plant Arabidopsis thaliana (L.) Heynh. in comparison to untreated control plants. The most pronounced effects of H(2)S fumigation could be observed on the metabolite level: the contents of the thiols cysteine and glutathione were increased up to 20- and fourfold, respectively. A direct positive correlation of the thiol contents with the H(2)S concentrations applied was observed. To elucidate the molecular basis for the increased thiol levels, enzyme activities, messenger RNA and protein steady-state levels of cysteine-synthesizing and degrading pathways have been determined. The enzyme activities of O-acetyl-l-serine(thiol)lyase (OAS-TL) (EC 4.2.99.8) and l-cysteine desulfhydrase (EC 4.4.1.-) proteins were not significantly higher at elevated H(2)S levels in comparison to untreated control plants. 3-Mercaptopyruvate sulfurtransferase (EC 2.8.1.2) activity was slightly higher after the longest H(2)S exposure times. Elevated H(2)S levels of 0.25 and 0.5 microl l(-1) had promoting effects on both mRNA and protein levels of cysteine-synthesizing and degrading enzymes whereas the highest H(2)S concentrations caused lower levels of expression combined with mild symptoms of oxidative stress, as the consequence of its phytotoxicity. The differences in the expression of the three different OAS-TL isoforms (cytoplasmic, plastidic and mitochondrial) by H(2)S were very small. Increasing concentrations of H(2)S and longer exposure times to H(2)S let to a reduction in the pool of O-acetyl-l-serine, the second precursor of cysteine, and N-acetyl-l-serine in the leaves and shoots, indicating a substrate depletion in agreement with the increased thiol levels.

Systems rebalancing of metabolism in response to sulfur deprivation, as revealed by metabolome analysis of Arabidopsis plants.

Sulfur is an essential macro-element in plant and animal nutrition. Plants assimilate inorganic sulfate into two sulfur-containing amino acids, cysteine and methionine. Low supply of sulfate leads to decreased sulfur pools within plant tissues. As sulfur-related metabolites represent an integral part of plant metabolism with multiple interactions, sulfur deficiency stress induces a number of adaptive responses, which must be coordinated. To reveal the coordinating network of adaptations to sulfur deficiency, metabolite profiling of Arabidopsis has been undertaken. Gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry techniques revealed the response patterns of 6,023 peaks of nonredundant ion traces and relative concentration levels of 134 nonredundant compounds of known chemical structure. Here, we provide a catalogue of the detected metabolic changes and reconstruct the coordinating network of their mutual influences. The observed decrease in biomass, as well as in levels of proteins, chlorophylls, and total RNA, gives evidence for a general reduction of metabolic activity under conditions of depleted sulfur supply. This is achieved by a systemic adjustment of metabolism involving the major metabolic pathways. Sulfur/carbon/nitrogen are partitioned by accumulation of metabolites along the pathway O-acetylserine to serine to glycine, and are further channeled together with the nitrogen-rich compound glutamine into allantoin. Mutual influences between sulfur assimilation, nitrogen imbalance, lipid breakdown, purine metabolism, and enhanced photorespiration associated with sulfur-deficiency stress are revealed in this study. These responses may be assembled into a global scheme of metabolic regulation induced by sulfur nutritional stress, which optimizes resources for seed production.

Towards dissecting nutrient metabolism in plants: a systems biology case study on sulphur metabolism.

A genomics analysis on sulphur metabolism has been conducted at the level of transcriptomics and metabolomics. The analysis of these data after applying bioinformatic tools is to reveal novel findings. The findings are discussed and the knowledge obtained from comparable analyses on sulphur metabolism and other plant nutrient genomic studies is reviewed. The analysis of the response of the transcriptome and metabolome to sulphur deprivation in the growth medium provides a tool set for the analysis of comparable genomics studies of other nutrients. The goal of this 'sulphobolomics' (i.e. sulphur genomics and metabolome analysis) approach, and of other investigations, is to describe in a holistic way the biochemical, molecular, and physiological response of a plant to nutrient starvation, here sulphate, or, more generally, to alterations and imbalances in nutrient availability. Eventually, this analysis will provide a case study for a systems biology approach.

Molecular analysis and control of cysteine biosynthesis: integration of nitrogen and sulphur metabolism.

Since cysteine is the first committed molecule in plant metabolism containing both sulphur and nitrogen, the regulation of its biosynthesis is critically important. Cysteine itself is required for the production of an abundance of key metabolites in diverse pathways. Plants alter their metabolism to compensate for sulphur and nitrogen deficiencies as best as they can, but limitations in either nutrient not only curb a plant's ability to synthesize cysteine, but also restrict protein synthesis. Nutrients such as nitrate and sulphate (and carbon) act as signals; they trigger molecular mechanisms that modify biosynthetic pathways and thereby have a profound impact on metabolite fluxes. Cysteine biosynthesis is modified by regulators acting at the site of uptake and throughout the plant system. Recent data point to the existence of nutrient-specific signal transduction pathways that relay information about external and internal nutrient concentrations, resulting in alterations to cysteine biosynthesis. Progress in this field has led to the cloning of genes that play pivotal roles in nutrient-induced changes in cysteine formation.

Transcriptome analysis of sulfur depletion in Arabidopsis thaliana: interlacing of biosynthetic pathways provides response specificity.

Higher plants assimilate inorganic sulfate into cysteine, which is subsequently converted to methionine, and into a variety of other sulfur-containing organic compounds. To resist sulfur deficiency, plants must demonstrate physiological flexibility: the expression of an extensive set of genes and gene regulators that act in the affected pathways or signalling cascades must be delicately tuned in response to environmental challenges. To elucidate this network of interactions, we have applied an array hybridisation/transcript profiling method to Arabidopsis plants subjected to 6, 10 and 13 days of constitutive and induced sulfur starvation. The temporal expression behaviour of approximately 7200 non-redundant genes was analysed simultaneously. The experiment was designed in a way to identify statistically significant changes of gene expression based on sufficient numbers of repeated hybridisations performed with five uniform pools of plant material. The expression profiles were processed to select differentially expressed genes. Among the 1507 sulfur-responsive clones implicated in this way, 632 genes responded specifically to sulfur deficiency by significant over-expression. The sulfur-responsive genes were grouped according to functional categories or biosynthetic pathways. As expected, genes of the sulfur assimilation pathway were altered in expression. Furthermore, genes involved in flavonoid, auxin, and jasmonate biosynthesis pathways were upregulated in conditions of sulfur deficiency. Based on the correlative analysis of gene expression patterns, we suggest that a complex co-ordination of systematic responses to sulfur depletion is provided via integration of flavonoid, auxin and jasmonate pathway elements. Plait concept for transduction of specificity via the main non-specific signalling stream is proposed.