Transcriptome integrated metabolic modeling of carbon assimilation underlying storage root development in cassava

Abstract The existing genome-scale metabolic model of carbon metabolism in cassava storage roots, rMeCBM, has proven particularly resourceful in exploring the metabolic basis for the phenotypic differences between high and low-yield cassava cultivars. However, experimental validation of predicted me...

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Autores principales:	Ratchaprapa Kamsen, Saowalak Kalapanulak, Porntip Chiewchankaset, Treenut Saithong
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/48a5a8a570b04e4cb528709f24a10db5
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spelling	oai:doaj.org-article:48a5a8a570b04e4cb528709f24a10db52021-12-02T13:39:34ZTranscriptome integrated metabolic modeling of carbon assimilation underlying storage root development in cassava10.1038/s41598-021-88129-32045-2322https://doaj.org/article/48a5a8a570b04e4cb528709f24a10db52021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-88129-3https://doaj.org/toc/2045-2322Abstract The existing genome-scale metabolic model of carbon metabolism in cassava storage roots, rMeCBM, has proven particularly resourceful in exploring the metabolic basis for the phenotypic differences between high and low-yield cassava cultivars. However, experimental validation of predicted metabolic fluxes by carbon labeling is quite challenging. Here, we incorporated gene expression data of developing storage roots into the basic flux-balance model to minimize infeasible metabolic fluxes, denoted as rMeCBMx, thereby improving the plausibility of the simulation and predictive power. Three different conceptual algorithms, GIMME, E-Flux, and HPCOF were evaluated. The rMeCBMx-HPCOF model outperformed others in predicting carbon fluxes in the metabolism of storage roots and, in particular, was highly consistent with transcriptome of high-yield cultivars. The flux prediction was improved through the oxidative pentose phosphate pathway in cytosol, as has been reported in various studies on root metabolism, but hardly captured by simple FBA models. Moreover, the presence of fluxes through cytosolic glycolysis and alanine biosynthesis pathways were predicted with high consistency with gene expression levels. This study sheds light on the importance of prediction power in the modeling of complex plant metabolism. Integration of multi-omics data would further help mitigate the ill-posed problem of constraint-based modeling, allowing more realistic simulation.Ratchaprapa KamsenSaowalak KalapanulakPorntip ChiewchankasetTreenut SaithongNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ratchaprapa Kamsen Saowalak Kalapanulak Porntip Chiewchankaset Treenut Saithong Transcriptome integrated metabolic modeling of carbon assimilation underlying storage root development in cassava
description	Abstract The existing genome-scale metabolic model of carbon metabolism in cassava storage roots, rMeCBM, has proven particularly resourceful in exploring the metabolic basis for the phenotypic differences between high and low-yield cassava cultivars. However, experimental validation of predicted metabolic fluxes by carbon labeling is quite challenging. Here, we incorporated gene expression data of developing storage roots into the basic flux-balance model to minimize infeasible metabolic fluxes, denoted as rMeCBMx, thereby improving the plausibility of the simulation and predictive power. Three different conceptual algorithms, GIMME, E-Flux, and HPCOF were evaluated. The rMeCBMx-HPCOF model outperformed others in predicting carbon fluxes in the metabolism of storage roots and, in particular, was highly consistent with transcriptome of high-yield cultivars. The flux prediction was improved through the oxidative pentose phosphate pathway in cytosol, as has been reported in various studies on root metabolism, but hardly captured by simple FBA models. Moreover, the presence of fluxes through cytosolic glycolysis and alanine biosynthesis pathways were predicted with high consistency with gene expression levels. This study sheds light on the importance of prediction power in the modeling of complex plant metabolism. Integration of multi-omics data would further help mitigate the ill-posed problem of constraint-based modeling, allowing more realistic simulation.
format	article
author	Ratchaprapa Kamsen Saowalak Kalapanulak Porntip Chiewchankaset Treenut Saithong
author_facet	Ratchaprapa Kamsen Saowalak Kalapanulak Porntip Chiewchankaset Treenut Saithong
author_sort	Ratchaprapa Kamsen
title	Transcriptome integrated metabolic modeling of carbon assimilation underlying storage root development in cassava
title_short	Transcriptome integrated metabolic modeling of carbon assimilation underlying storage root development in cassava
title_full	Transcriptome integrated metabolic modeling of carbon assimilation underlying storage root development in cassava
title_fullStr	Transcriptome integrated metabolic modeling of carbon assimilation underlying storage root development in cassava
title_full_unstemmed	Transcriptome integrated metabolic modeling of carbon assimilation underlying storage root development in cassava
title_sort	transcriptome integrated metabolic modeling of carbon assimilation underlying storage root development in cassava
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/48a5a8a570b04e4cb528709f24a10db5
work_keys_str_mv	AT ratchaprapakamsen transcriptomeintegratedmetabolicmodelingofcarbonassimilationunderlyingstoragerootdevelopmentincassava AT saowalakkalapanulak transcriptomeintegratedmetabolicmodelingofcarbonassimilationunderlyingstoragerootdevelopmentincassava AT porntipchiewchankaset transcriptomeintegratedmetabolicmodelingofcarbonassimilationunderlyingstoragerootdevelopmentincassava AT treenutsaithong transcriptomeintegratedmetabolicmodelingofcarbonassimilationunderlyingstoragerootdevelopmentincassava
_version_	1718392613006999552

Transcriptome integrated metabolic modeling of carbon assimilation underlying storage root development in cassava

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