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ARS Home » Northeast Area » Ithaca, New York » Robert W. Holley Center for Agriculture & Health » Plant, Soil and Nutrition Research » Research » Publications at this Location » Publication #333378

Research Project: Development and Application of Genetic, Genomic, and Bioinformatic Resources in Maize

Location: Plant, Soil and Nutrition Research

Title: Correlation-based network analysis of metabolite and enzyme profiles reveals a role of citrate biosynthesis in modulating N and C metabolism in zea mays

Author
item TOUBIANA, DAVID - Ben Gurion University Of Negev
item XUE, WENTAO - Ben Gurion University Of Negev
item ZHANG, NENGYI - Cornell University - New York
item KREMLING, KARL - Cornell University - New York
item GUR, AMIT - Cornell University - New York
item PILOSOF, SHAI - Ben Gurion University Of Negev
item GIBON, YVES - Max Planck Institute Of Molecular Plant Physiology
item SITT, MARK - Max Planck Institute Of Molecular Plant Physiology
item Buckler, Edward - Ed
item FERNIE, ALISDAIR - Max Planck Institute Of Molecular Plant Physiology
item FAIT, AARON - Ben Gurion University Of Negev

Submitted to: Frontiers in Plant Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/28/2016
Publication Date: 7/12/2016
Citation: Toubiana, D., Xue, W., Zhang, N., Kremling, K., Gur, A., Pilosof, S., Gibon, Y., Sitt, M., Buckler IV, E.S., Fernie, A., Fait, A. 2016. Correlation-based network analysis of metabolite and enzyme profiles reveals a role of citrate biosynthesis in modulating N and C metabolism in zea mays. Frontiers in Plant Science. 7:1022.

Interpretive Summary: Accumulation and use of carbon and nitrogen govern growth rate and yield of all plants. Using chromatography and mass spectrometry, Toubiana et al measured 43 carbon and nitrogen based metabolites and 13 enzymes that control their accumulation in corn. By correlating individual metabolite measurements against one another, Toubiana et al were able to determine 3 distinct modules of metabolites that act in concert in a growing corn plant. This is important because correlation network analyses allowed the authors to determine how the metabolite measurements are related even if the environment perturbed the measurements during the study. This kind of perturbation prevents accurate genetic mapping, which the authors unsuccessfully attempted at the beginning of the study.

Technical Abstract: To investigate the natural variability of leaf metabolism and enzymatic activity in a maize inbred population, statistical and network analyses were employed on metabolite and enzyme profiles. The test of coefficient of variation showed that sugars and amino acids displayed opposite trends in their variance within the population, consistently with their related enzymes. The overall higher CV values for metabolites as compared to the tested enzymes are indicative for their greater phenotypic plasticity. H2 tests revealed galactinol (1) and asparagine (0.91) as the highest scorers among metabolites and nitrate reductase (0.73), NAD-glutamate dehydrogenase (0.52), and phosphoglucomutase (0.51) among enzymes. The overall low H2 scores for metabolites and enzymes are suggestive for a great environmental impact or gene-environment interaction. Correlation-based network generation followed by community detection analysis, partitioned the network into three main communities and one dyad, (i) reflecting the different levels of phenotypic plasticity of the two molecular classes as observed for the CV values and (ii) highlighting the concerted changes between classes of chemically related metabolites. Community 1 is composed mainly of enzymes and specialized metabolites, community 2' is enriched in N-containing compounds and phosphorylated-intermediates. The third community contains mainly organic acids and sugars. Cross-community linkages are supported by aspartate, by the photorespiration amino acids glycine and serine, by the metabolically related GABA and putrescine, and by citrate. The latter displayed the strongest node-betweenness value (185.25) of all nodes highlighting its fundamental structural role in the connectivity of the network by linking between different communities and to the also strongly connected enzyme aldolase.