Impact of the Carbon and Nitrogen Supply on Relationships and Connectivity between Metabolism and Biomass in a Broad Panel of Arabidopsis Accessions    

Abstract

Natural genetic diversity provides a powerful tool to study the complex interrelationship between metabolism and growth. Profiling of metabolic traits combined with network-based and statistical analyses allow the comparison of conditions and identification of sets of traits that predict biomass. However, it often remains unclear why a particular set of metabolites is linked with biomass and to what extent the predictive model is applicable beyond a particular growth condition. A panel of 97 genetically diverse Arabidopsis (Arabidopsis thaliana) accessions was grown in near-optimal carbon and nitrogen supply, restricted carbon supply, and restricted nitrogen supply and analyzed for biomass and 54 metabolic traits. Correlation-based metabolic networks were generated from the genotype-dependent variation in each condition to reveal sets of metabolites that show coordinated changes across accessions. The networks were largely specific for a single growth condition. Partial least squares regression from metabolic traits allowed prediction of biomass within and, slightly more weakly, across conditions (cross-validated Pearson correlations in the range of 0.27-0.58 and 0.21-0.51 and P values in the range of ,0.001-,0.13 and ,0.001-,0.023, respectively). Metabolic traits that correlate with growth or have a high weighting in the partial least squares regression were mainly condition specific and often related to the resource that restricts growth under that condition. Linear mixed-model analysis using the combined metabolic traits from all growth conditions as an input indicated that inclusion of random effects for the conditions improves predictions of biomass. Thus, robust prediction of biomass across a range of conditions requires condition-specific measurement of metabolic traits to take account of environment-dependent changes of the underlying networks.

Bottom-up Metabolic Reconstruction of Arabidopsis and Its Application to Determining the Metabolic Costs of Enzyme Production

“…As the biomass reaction does not comprise NO 3 2 , only the increase in the organic nitrogen can be examined. Moreover, it has been experimentally shown that the reduced overall nitrogen availability can almost be compensated by an elevated NO 3 2 assimilation (Sulpice et al, 2013). In support of this claim, the gene expression of the low-affinity NO 3 2 transport system is shown to be induced under low NO 3 2 concentrations (Wang et al, 2000).…”

“…In accordance with the authors, we stress that this differs from earlier nitrogen deficiency experiments, where strong nitrogen limitations were obtained. In contrast, the carbon limitation is experimentally realized via short-day conditions (8-hlight/16-h-dark cycle; Gibon et al, 2004Gibon et al, , 2009Stitt et al, 2007;Sulpice et al, 2013), which affect the starch accumulation during the day and result in a restriction of carbon availability at night Sulpice et al, 2013).…”

Genome-Wide Association Mapping Reveals That Specific and Pleiotropic Regulatory Mechanisms Fine-Tune Central Metabolism and Growth in Arabidopsis

“…Plant metabolism is subject to ageor plant-size-dependent effects (Geronimo and Beevers, 1964;Meyer et al, 2007) and is modified in response to environmental changes such as photoperiod (Graf et al, 2010;Sulpice et al, 2014;Yang et al, 2016). These factors modified the metabolic network, as shown by the differing correlation networks in the two experiments (Figure 1; see also Sulpice et al, 2013) and a weakening of correlations in the cross-experiment comparison. Furthermore, the activities of some enzymes, such as FK, GK, G6PDH, FBP, fumarase, and SPS, showed high plasticity.…”

“…As mentioned above, network structure is altered by relatively small changes in growth conditions (Figure 1; see also Sulpice et al, 2013), indicating that connectivity is partly due to the coordinated regulation of metabolism by metabolic, environmental, or developmental cues. To determine if genetic regulation also contributes to the connectivity in central metabolism, we searched for pleiotropic loci at which several metabolic QTL colocalize.…”

“…Multivariate analysis of metabolite profiles across panels of genotypes provides predictions of biomass (Meyer et al, 2007;Riedelsheimer et al, 2012) and has delivered first insights into which features promote rapid growth. For example, a negative correlation between starch turnover and biomass formation indicates that fast-growing Arabidopsis accessions use their carbohydrates more efficiently than slowergrowing lines (Cross et al, 2006;Sulpice et al, 2009Sulpice et al, , 2013. This was recently shown to be partly due to fast-growing accessions having a lower rate of protein turnover (Ishihara et al, 2017).…”