A multi-tissue genome-scale metabolic modelling framework for the analysis of whole plant systems
Genome scale metabolic modelling has traditionally been used to explore metabolism of individual cells or tissues. In higher organisms, the metabolism of individual tissues and organs is coordinated for the overall growth and well-being of the organism. Understanding the dependencies and rationale f...
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doaj-cf6d296b158f41d099a2f0db5a52be2e2020-11-24T21:20:10ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2015-01-01610.3389/fpls.2015.00004111599A multi-tissue genome-scale metabolic modelling framework for the analysis of whole plant systemsCristiana eGomes De Oliveira Dal'molin0Lake-Ee eQuek1Pedro Andres Saa2Lars Keld Nielsen3The University of QueenslandThe University of QueenslandThe University of QueenslandThe University of QueenslandGenome scale metabolic modelling has traditionally been used to explore metabolism of individual cells or tissues. In higher organisms, the metabolism of individual tissues and organs is coordinated for the overall growth and well-being of the organism. Understanding the dependencies and rationale for multicellular metabolism is far from trivial. Here, we have advanced the use of AraGEM (a genome-scale reconstruction of Arabidopsis metabolism) in a multi-tissue context to understand how plants grow utilizing their leaf, stem and root systems across the day-night (diurnal) cycle. Six tissue compartments were created, each with their own distinct set of metabolic capabilities, and hence a reliance on other compartments for support. We used the multi-tissue framework to explore differences in the ‘division-of-labour’ between the sources and sink tissues in response to: (a) the energy demand for the translocation of C and N species in between tissues; and (b) the use of two distinct nitrogen sources (NO3- or NH4+). The ‘division-of-labour’ between compartments was investigated using a minimum energy (photon) objective function. Random sampling of the solution space was used to explore the flux distributions under different scenarios as well as to identify highly coupled reaction sets in different tissues and organelles. Efficient identification of these sets was achieved by casting this problem as a maximum clique enumeration problem. The framework also enabled assessing the impact of energetic constraints in resource (redox and ATP) allocation between leaf, stem and root tissues required for efficient carbon and nitrogen assimilation, including the diurnal cycle constraint forcing the plant to set aside resources during the day and defer metabolic processes that are more efficiently performed at night. This study is a first step towards autonomous modelling of whole plant metabolism.http://journal.frontiersin.org/Journal/10.3389/fpls.2015.00004/fullmodellingPlant metabolismmulti-tissuegenome-scaleAraGEM |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Cristiana eGomes De Oliveira Dal'molin Lake-Ee eQuek Pedro Andres Saa Lars Keld Nielsen |
spellingShingle |
Cristiana eGomes De Oliveira Dal'molin Lake-Ee eQuek Pedro Andres Saa Lars Keld Nielsen A multi-tissue genome-scale metabolic modelling framework for the analysis of whole plant systems Frontiers in Plant Science modelling Plant metabolism multi-tissue genome-scale AraGEM |
author_facet |
Cristiana eGomes De Oliveira Dal'molin Lake-Ee eQuek Pedro Andres Saa Lars Keld Nielsen |
author_sort |
Cristiana eGomes De Oliveira Dal'molin |
title |
A multi-tissue genome-scale metabolic modelling framework for the analysis of whole plant systems |
title_short |
A multi-tissue genome-scale metabolic modelling framework for the analysis of whole plant systems |
title_full |
A multi-tissue genome-scale metabolic modelling framework for the analysis of whole plant systems |
title_fullStr |
A multi-tissue genome-scale metabolic modelling framework for the analysis of whole plant systems |
title_full_unstemmed |
A multi-tissue genome-scale metabolic modelling framework for the analysis of whole plant systems |
title_sort |
multi-tissue genome-scale metabolic modelling framework for the analysis of whole plant systems |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Plant Science |
issn |
1664-462X |
publishDate |
2015-01-01 |
description |
Genome scale metabolic modelling has traditionally been used to explore metabolism of individual cells or tissues. In higher organisms, the metabolism of individual tissues and organs is coordinated for the overall growth and well-being of the organism. Understanding the dependencies and rationale for multicellular metabolism is far from trivial. Here, we have advanced the use of AraGEM (a genome-scale reconstruction of Arabidopsis metabolism) in a multi-tissue context to understand how plants grow utilizing their leaf, stem and root systems across the day-night (diurnal) cycle. Six tissue compartments were created, each with their own distinct set of metabolic capabilities, and hence a reliance on other compartments for support. We used the multi-tissue framework to explore differences in the ‘division-of-labour’ between the sources and sink tissues in response to: (a) the energy demand for the translocation of C and N species in between tissues; and (b) the use of two distinct nitrogen sources (NO3- or NH4+). The ‘division-of-labour’ between compartments was investigated using a minimum energy (photon) objective function. Random sampling of the solution space was used to explore the flux distributions under different scenarios as well as to identify highly coupled reaction sets in different tissues and organelles. Efficient identification of these sets was achieved by casting this problem as a maximum clique enumeration problem. The framework also enabled assessing the impact of energetic constraints in resource (redox and ATP) allocation between leaf, stem and root tissues required for efficient carbon and nitrogen assimilation, including the diurnal cycle constraint forcing the plant to set aside resources during the day and defer metabolic processes that are more efficiently performed at night. This study is a first step towards autonomous modelling of whole plant metabolism. |
topic |
modelling Plant metabolism multi-tissue genome-scale AraGEM |
url |
http://journal.frontiersin.org/Journal/10.3389/fpls.2015.00004/full |
work_keys_str_mv |
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