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Title: Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis

Abstract

The use of large-scale or genome-scale metabolic reconstructions for modeling and simulation of plant metabolism and integration of those models with large-scale omics and experimental flux data is becoming increasingly important in plant metabolic research. Here we report an updated version of bna572, a bottom-up reconstruction of oilseed rape (Brassica napus L.; Brassicaceae) developing seeds with emphasis on representation of biomass-component biosynthesis. New features include additional seed-relevant pathways for isoprenoid, sterol, phenylpropanoid, flavonoid, and choline biosynthesis. Being now based on standardized data formats and procedures for model reconstruction, bna572+ is available as a COBRA-compliant Systems Biology Markup Language (SBML) model and conforms to the Minimum Information Requested in the Annotation of Biochemical Models (MIRIAM) standards for annotation of external data resources. Bna572+ contains 966 genes, 671 reactions, and 666 metabolites distributed among 11 subcellular compartments. It is referenced to the Arabidopsis thaliana genome, with gene-protein-reaction (GPR) associations resolving subcellular localization. Detailed mass and charge balancing and confidence scoring were applied to all reactions. Using B. napus seed specific transcriptome data, expression was verified for 78% of bna572+ genes and 97% of reactions. Alongside bna572+ we also present a revised carbon centric model for 13C-Metabolic Flux Analysis (13C-MFA) with all itsmore » reactions being referenced to bna572+ based on linear projections. By integration of flux ratio constraints obtained from 13C-MFA and by elimination of infinite flux bounds around thermodynamically infeasible loops based on COBRA loopless methods, we demonstrate improvements in predictive power of Flux Variability Analysis (FVA). In conclusion, using this combined approach we characterize the difference in metabolic flux of developing seeds of two B. napus genotypes contrasting in starch and oil content.« less

Authors:
 [1];  [1];  [2];  [1];  [2];  [1]
  1. Brookhaven National Lab. (BNL), Upton, NY (United States). Biological, Environmental & Climate Sciences Dept.
  2. Leibniz Inst. for Plant Genetics and Culture Plant Research (IPK), Gatersleben (Germany)
Publication Date:
Research Org.:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1178233
Report Number(s):
BNL-106138-2015-JA
Journal ID: ISSN 1664-462X; R&D Project: BO-133; KC0304000
Grant/Contract Number:  
SC00112704; AC0298CH10886
Resource Type:
Accepted Manuscript
Journal Name:
Frontiers in Plant Science
Additional Journal Information:
Journal Volume: 5; Journal ID: ISSN 1664-462X
Publisher:
Frontiers Research Foundation
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; loopless flux balance analysis; 13C-metabolic flux analysis; central metabolism; carbon partitioning; constraint-based reconstruction and analysis

Citation Formats

Hay, Jordan O., Shi, Hai, Heinzel, Nicolas, Hebbelmann, Inga, Rolletschek, Hardy, and Schwender, Jorg. Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis. United States: N. p., 2014. Web. doi:10.3389/fpls.2014.00724.
Hay, Jordan O., Shi, Hai, Heinzel, Nicolas, Hebbelmann, Inga, Rolletschek, Hardy, & Schwender, Jorg. Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis. United States. https://doi.org/10.3389/fpls.2014.00724
Hay, Jordan O., Shi, Hai, Heinzel, Nicolas, Hebbelmann, Inga, Rolletschek, Hardy, and Schwender, Jorg. Fri . "Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis". United States. https://doi.org/10.3389/fpls.2014.00724. https://www.osti.gov/servlets/purl/1178233.
@article{osti_1178233,
title = {Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis},
author = {Hay, Jordan O. and Shi, Hai and Heinzel, Nicolas and Hebbelmann, Inga and Rolletschek, Hardy and Schwender, Jorg},
abstractNote = {The use of large-scale or genome-scale metabolic reconstructions for modeling and simulation of plant metabolism and integration of those models with large-scale omics and experimental flux data is becoming increasingly important in plant metabolic research. Here we report an updated version of bna572, a bottom-up reconstruction of oilseed rape (Brassica napus L.; Brassicaceae) developing seeds with emphasis on representation of biomass-component biosynthesis. New features include additional seed-relevant pathways for isoprenoid, sterol, phenylpropanoid, flavonoid, and choline biosynthesis. Being now based on standardized data formats and procedures for model reconstruction, bna572+ is available as a COBRA-compliant Systems Biology Markup Language (SBML) model and conforms to the Minimum Information Requested in the Annotation of Biochemical Models (MIRIAM) standards for annotation of external data resources. Bna572+ contains 966 genes, 671 reactions, and 666 metabolites distributed among 11 subcellular compartments. It is referenced to the Arabidopsis thaliana genome, with gene-protein-reaction (GPR) associations resolving subcellular localization. Detailed mass and charge balancing and confidence scoring were applied to all reactions. Using B. napus seed specific transcriptome data, expression was verified for 78% of bna572+ genes and 97% of reactions. Alongside bna572+ we also present a revised carbon centric model for 13C-Metabolic Flux Analysis (13C-MFA) with all its reactions being referenced to bna572+ based on linear projections. By integration of flux ratio constraints obtained from 13C-MFA and by elimination of infinite flux bounds around thermodynamically infeasible loops based on COBRA loopless methods, we demonstrate improvements in predictive power of Flux Variability Analysis (FVA). In conclusion, using this combined approach we characterize the difference in metabolic flux of developing seeds of two B. napus genotypes contrasting in starch and oil content.},
doi = {10.3389/fpls.2014.00724},
journal = {Frontiers in Plant Science},
number = ,
volume = 5,
place = {United States},
year = {Fri Dec 19 00:00:00 EST 2014},
month = {Fri Dec 19 00:00:00 EST 2014}
}

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Works referencing / citing this record:

Fluxomics links cellular functional analyses to whole-plant phenotyping
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