Significance test for the coefficients of variation (CVs) for different groups of <i>metabolites</i>, or <i>products</i>, or <i>substrates</i> across the considered environmental conditions.

<p>Given are <i>Wilcoxon</i>-test -values from testing for significantly lower CVs for <b><i>metabolites</i></b> or <b><i>products</i></b> or <b><i>substrates</i></b> in the given six comparisons, respectively. A denotes that the sample size was too small for a statistic test (0 or 1 product in the respective group). The table entries in bold mark the significant comparisons at level 0.05.</p

Histogram of temporal coefficient of variation for metabolites.

<p>Distribution of CVs over all measured metabolites (green) and all metabolites identified as substrates in a differentially behaving functions for the respective conditions (red). The plot summarizes the distributions over all eight considered conditions.</p

Variability of Metabolite Levels Is Linked to Differential Metabolic Pathways in Arabidopsis's Responses to Abiotic Stresses

<div><p>Constraint-based approaches have been used for integrating data in large-scale metabolic networks to obtain insights into metabolism of various organisms. Due to the underlying steady-state assumption, these approaches are usually not suited for making predictions about metabolite levels. Here, we ask whether we can make inferences about the variability of metabolite levels from a constraint-based analysis based on the integration of transcriptomics data. To this end, we analyze time-resolved transcriptomics and metabolomics data from <i>Arabidopsis thaliana</i> under a set of eight different light and temperature conditions. In a previous study, the gene expression data have already been integrated in a genome-scale metabolic network to predict pathways, termed modulators and sustainers, which are differentially regulated with respect to a biochemically meaningful data-driven null model. Here, we present a follow-up analysis which bridges the gap between flux- and metabolite-centric methods. One of our main findings demonstrates that under certain environmental conditions, the levels of metabolites acting as substrates in modulators or sustainers show significantly lower temporal variations with respect to the remaining measured metabolites. This observation is discussed within the context of a systems-view of plasticity and robustness of metabolite contents and pathway fluxes. Our study paves the way for investigating the existence of similar principles in other species for which both genome-scale networks and high-throughput metabolomics data of high quality are becoming increasingly available.</p></div

Schematic representation of the analysis framework.

<p>Transcriptomics and metabolomics data capturing <i>Arabidopsis thaliana</i>'s temporal response to eight different environmental conditions (combinations of different light and/or temperature regimes) are collected for a time-series of 24 hours. The transcriptomic data are used to constrain flux boundaries of the respective reactions in a large-scale network by assuming a correlation between the transcript abundance and the upper flux boundary through the respective enzyme-catalyzed reaction. Based on a model with randomized flux boundaries (null model), pathways are classified as differential for a given condition if they exhibit an absolute 2. Differentially up-regulated (down-regulated) pathways are termed sustainers (modulators) of the metabolic state, respectively. Independently from this categorization, the temporal variation of the metabolite profiles was determined. Under certain conditions, substrates in the differential pathways exhibit a significantly lower temporal variation with respect to other groups of metabolites.</p

Time-series of the metabolites acting as substrates in differential metabolic functions.

<p>Profiles of the relative metabolite content of those measured metabolites that act as substrates in a pathway classified as differential with respect to the null model under the respective condition. The horizontal line indicates time point 60-organization and transition into a new metabolic state.</p

Representation of a metabolic function and its metabolites.

<p>Shown is a metabolic pathway with four reactions, represented by the arrows. The dots represent the metabolites, which are categorized as substrates , intermediates and products with the subgroup of initial substrates and final products .</p

evolutionary metabolomics data

Content of 51 polar and non-polar primary metabolites from 37 genotypes of Triticum turgidum L. including wild emmer, emmer and durum whea