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Correlation-based network analysis of metabolite and enzyme profiles reveals a role of citrate biosynthesis in modulating N and C metabolism in zea mays
Year:
2016
Source of publication :
Frontiers in Plant Science
Authors :
Gur, Amit
;
.
Volume :
7
Co-Authors:
Toubiana, D., Institute of Dryland Biotechnology and Agriculture, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel
Xue, W., Institute of Dryland Biotechnology and Agriculture, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel, College of Life Sciences, Guizhou University, Guiyang, Guizhou, China
Zhang, N., Institute for Genomic Diversity, Cornell University, Ithaca, NY, United States
Kremling, K., Institute for Genomic Diversity, Cornell University, Ithaca, NY, United States
Gur, A., Institute for Genomic Diversity, Cornell University, Ithaca, NY, United States, Department of Vegetable Crops and Plant Genetics, Israeli Agricultural Research Organization, Newe Yaâr Research Center, Ramat, Yshay, Israel
Pilosof, S., Mitrani Department of Desert Ecology, Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel, Department of Ecology and Evolution, University of Chicago, Chicago, IL, United States
Gibon, Y., Max Planck Institute of Molecular Plant Physiology, Golm, Germany, Institut National de la Recherche Agronomique, UMR 1332 Biologie du Fruit et Pathologie, Université de Bordeaux, Bordeaux Cedex, France
Stitt, M., Max Planck Institute of Molecular Plant Physiology, Golm, Germany
Buckler, E.S., Institute for Genomic Diversity, Cornell University, Ithaca, NY, United States
Fernie, A.R., Max Planck Institute of Molecular Plant Physiology, Golm, Germany
Fait, A., Institute of Dryland Biotechnology and Agriculture, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel
Facilitators :
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Total pages:
1
)
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. © 2016 Toubiana, Xue, Zhang, Kremling, Gur, Pilosof, Gibon, Stitt, Buckler, Fernie and Fait.
Note:
Related Files :
Correlation-based network analysis
Enzymatic processes
Metabolic Networks and Pathways
metabolism
TCA cycle
Zea mays
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More details
DOI :
10.3389/fpls.2016.01022
Article number:
1022
Affiliations:
Database:
Scopus
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
30101
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:52
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Scientific Publication
Correlation-based network analysis of metabolite and enzyme profiles reveals a role of citrate biosynthesis in modulating N and C metabolism in zea mays
7
Toubiana, D., Institute of Dryland Biotechnology and Agriculture, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel
Xue, W., Institute of Dryland Biotechnology and Agriculture, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel, College of Life Sciences, Guizhou University, Guiyang, Guizhou, China
Zhang, N., Institute for Genomic Diversity, Cornell University, Ithaca, NY, United States
Kremling, K., Institute for Genomic Diversity, Cornell University, Ithaca, NY, United States
Gur, A., Institute for Genomic Diversity, Cornell University, Ithaca, NY, United States, Department of Vegetable Crops and Plant Genetics, Israeli Agricultural Research Organization, Newe Yaâr Research Center, Ramat, Yshay, Israel
Pilosof, S., Mitrani Department of Desert Ecology, Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel, Department of Ecology and Evolution, University of Chicago, Chicago, IL, United States
Gibon, Y., Max Planck Institute of Molecular Plant Physiology, Golm, Germany, Institut National de la Recherche Agronomique, UMR 1332 Biologie du Fruit et Pathologie, Université de Bordeaux, Bordeaux Cedex, France
Stitt, M., Max Planck Institute of Molecular Plant Physiology, Golm, Germany
Buckler, E.S., Institute for Genomic Diversity, Cornell University, Ithaca, NY, United States
Fernie, A.R., Max Planck Institute of Molecular Plant Physiology, Golm, Germany
Fait, A., Institute of Dryland Biotechnology and Agriculture, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel
Correlation-based network analysis of metabolite and enzyme profiles reveals a role of citrate biosynthesis in modulating N and C metabolism in zea mays
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. © 2016 Toubiana, Xue, Zhang, Kremling, Gur, Pilosof, Gibon, Stitt, Buckler, Fernie and Fait.
Scientific Publication
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