Metabolomics data reveal a crucial role of cytosolic glutamine synthetase 1;1 in coordinating metabolic balance in rice

Abstract

SUMMARYRice plants grown in paddy fields preferentially use ammonium as a source of inorganic nitrogen. Glutamine synthetase (GS) catalyses the conversion of ammonium to glutamine. Of the three genes encoding cytosolic GS in rice, OsGS1;1 is critical for normal growth and grain filling. However, the basis of its physiological function that may alter the rate of nitrogen assimilation and carbon metabolism within the context of metabolic networks remains unclear. To address this issue, we carried out quantitative comparative analyses between the metabolite profiles of a rice mutant lacking OsGS1;1 and its background wild type (WT). The mutant plants exhibited severe retardation of shoot growth in the presence of ammonium compared with the WT. Overaccumulation of free ammonium in the leaf sheath and roots of the mutant indicated the importance of OsGS1;1 for ammonium assimilation in both organs. The metabolite profiles of the mutant line revealed: (i) an imbalance in levels of sugars, amino acids and metabolites in the tricarboxylic acid cycle, and (ii) overaccumulation of secondary metabolites, particularly in the roots under a continuous supply of ammonium. Metabolite-to-metabolite correlation analysis revealed the presence of mutant-specific networks between tryptamine and other primary metabolites in the roots. These results demonstrated a crucial function of OsGS1;1 in coordinating the global metabolic network in rice plants grown using ammonium as the nitrogen source.

Transcriptomic and Metabolic Changes Associated with Photorespiratory Ammonium Accumulation in the Model Legume Lotus japonicus

“…Interestingly, rice (Oryza sativa) mutants lacking a cytosolic GS 1 isoform showed a decrease in tricarboxylic acid cycle intermediates in the leaves, as well as a decrease of the Asp family amino acids when compared with the wild type (Kusano et al, 2011). While differences between the metabolite profiles of cytosolic and plastidic GS mutants are to be expected, both the data from Kusano et al (2011) and from this study point out the central role of GS in coordinating carbon and nitrogen metabolism in plants.…”

“…Supporting this hypothesis, the accumulation of branched-chain amino acids together with the accumulation of Krebs cycle intermediates in Arabidopsis indicates that alternative pathways of respiration based on protein and fatty acid degradation are induced (Timm et al, 2012). Interestingly, rice (Oryza sativa) mutants lacking a cytosolic GS 1 isoform showed a decrease in tricarboxylic acid cycle intermediates in the leaves, as well as a decrease of the Asp family amino acids when compared with the wild type (Kusano et al, 2011). While differences between the metabolite profiles of cytosolic and plastidic GS mutants are to be expected, both the data from Kusano et al (2011) and from this study point out the central role of GS in coordinating carbon and nitrogen metabolism in plants.…”

Superexpressão do transportador OsNPF4.11 (OsNRT1.2) afeta teor de nitrato, parâmetros radiculares e crescimento de arroz

“…Tendo em vista que a enzima Nitrato Redutase (NR) é citosólica, a redução do nitrato é principalmente realizada no citoplasma, desta forma o NO 3 -acumulado no vacúolo precisa ser remobilizado para o citoplasma para ser então assimilado e reduzido, assim a EUN em plantas está intimamente relacionada com a capacidade de reutilização do NO 3 -do vacúolo (Zhang et al, 2012). Por meio do estudo de plantas transgênicas, já foi demonstrado que uma redução na assimilação do N acarretou em uma redução na biomassa em plantas de arroz (Kusano et al, 2011) e que um aumento na assimilação acarretou em um aumento na biomassa das plantas, assim como um aumento na massa seca de raiz e de parte aérea em plantas de trigo e tabaco (Migge et al, 2000;Fuentes et al, 2001;Habash et al, 2001).…”

Exploring Tomato Gene Functions Based on Coexpression Modules Using Graph Clustering and Differential Coexpression Approaches

“…For example, this feature has been used to identify disease-specific networks (de la Fuente, 2010). Differential metabolomic correlations were utilized in some metabolomics studies (Weckwerth et al, 2004;Morgenthal et al, 2006;Fukushima et al, 2011;Kusano et al, 2011). While the differential expression of genes and gene coexpression in plants have been addressed in earlier microarray studies, their differential coexpression has not been addressed.…”