Inferring causal metabolic signals that regulate the dynamic TORC1-dependent transcriptome.

Cells react to nutritional cues in changing environments via the integrated action of signaling, transcriptional, and metabolic networks. Mechanistic insight into signaling processes is often complicated because ubiquitous feedback loops obscure causal relationships. Consequently, the endogenous inputs of many nutrient signaling pathways remain unknown.

Nitrogen source activates TOR (target of rapamycin) complex 1 via glutamine and independently of Gtr/Rag proteins.

The evolutionary conserved TOR complex 1 (TORC1) activates cell growth in response to nutrients. In yeast, TORC1 responds to the nitrogen source via a poorly understood mechanism. Leucine, and perhaps other amino acids, activates TORC1 via the small GTPases Gtr1 and Gtr2, orthologs of the mammalian Rag GTPases.

Integration of time-resolved transcriptomics data with flux-based methods reveals stress-induced metabolic adaptation in Escherichia coli.

Background: Changes in environmental conditions require temporal effectuation of different metabolic pathways in order to maintain the organisms' viability but also to enable the settling into newly arising conditions. While analyses of robustness in biological systems have resulted in the characterization of reactions that facilitate homeostasis, temporal adaptation-related processes and the role of cellular pathways in the metabolic response to changing conditions remain elusive.

Results: Here we develop a flux-based approach that allows the integration of time-resolved transcriptomics data with genome-scale metabolic networks.

Metabolomic and transcriptomic stress response of Escherichia coli.

Environmental fluctuations lead to a rapid adjustment of the physiology of Escherichia coli, necessitating changes on every level of the underlying cellular and molecular network. Thus far, the majority of global analyses of E. coli stress responses have been limited to just one level, gene expression.

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.

Transcription factor AtDOF4;2 affects phenylpropanoid metabolism in Arabidopsis thaliana.

In a phenotypic screen of plants constitutively overexpressing DOF (DNA-binding-with-one-finger) transcription factors under the control of the Cauliflower mosaic virus 35S promoter, AtDOF4;2 was identified as a gene inducing a bushy plant phenotype and potentially being involved in the regulation of phenylpropanoid metabolism in Arabidopsis. Further molecular and biochemical characterization was performed in parallel using transgenic plants with enhanced and reduced AtDOF4;2 expression. The expression pattern of AtDOF4;2 was determined by quantitative real-time polymerase chain reaction (Q-RTPCR) and through promoter-beta-glucuronidase (GUS) fusions, indicating preferential transcriptional activity in axillary buds of the flower stalk, the hypocotyls periderm and in tapetum cells.