The flavonoid pathway in tomato seedlings: transcript abundance and the modeling of metabolite dynamics.

Flavonoids are secondary metabolites present in all terrestrial plants. The flavonoid pathway has been extensively studied, and many of the involved genes and metabolites have been described in the literature. Despite this extensive knowledge, the functioning of the pathway in vivo is still poorly u...

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Autores principales: Marian Groenenboom, Victoria Gomez-Roldan, Hans Stigter, Laura Astola, Raymond van Daelen, Jules Beekwilder, Arnaud Bovy, Robert Hall, Jaap Molenaar
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spelling oai:doaj.org-article:3b9cc0f5c6a34ad3a8815cc12463671d2021-11-18T09:02:48ZThe flavonoid pathway in tomato seedlings: transcript abundance and the modeling of metabolite dynamics.1932-620310.1371/journal.pone.0068960https://doaj.org/article/3b9cc0f5c6a34ad3a8815cc12463671d2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23922672/?tool=EBIhttps://doaj.org/toc/1932-6203Flavonoids are secondary metabolites present in all terrestrial plants. The flavonoid pathway has been extensively studied, and many of the involved genes and metabolites have been described in the literature. Despite this extensive knowledge, the functioning of the pathway in vivo is still poorly understood. Here, we study the flavonoid pathway using both experiments and mathematical models. We measured flavonoid metabolite dynamics in two tissues, hypocotyls and cotyledons, during tomato seedling development. Interestingly, the same backbone of interactions leads to very different accumulation patterns in the different tissues. Initially, we developed a mathematical model with constant enzyme concentrations that described the metabolic networks separately in both tissues. This model was unable to fit the measured flavonoid dynamics in the hypocotyls, even if we allowed unrealistic parameter values. This suggested us to investigate the effect of transcript abundance on flavonoid accumulation. We found that the expression of candidate flavonoid genes varies considerably with time. Variation in transcript abundance results in enzymatic variation, which could have a large effect on metabolite accumulation. Candidate transcript abundance was included in the mathematical model as representative for enzyme concentration. We fitted the resulting model to the flavonoid dynamics in the cotyledons, and tested it by applying it to the data from hypocotyls. When transcript abundance is included, we are indeed able to explain flavonoid dynamics in both tissues. Importantly, this is possible under the biologically relevant restriction that the enzymatic properties estimated by the model are conserved between the tissues.Marian GroenenboomVictoria Gomez-RoldanHans StigterLaura AstolaRaymond van DaelenJules BeekwilderArnaud BovyRobert HallJaap MolenaarPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 7, p e68960 (2013)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Marian Groenenboom
Victoria Gomez-Roldan
Hans Stigter
Laura Astola
Raymond van Daelen
Jules Beekwilder
Arnaud Bovy
Robert Hall
Jaap Molenaar
The flavonoid pathway in tomato seedlings: transcript abundance and the modeling of metabolite dynamics.
description Flavonoids are secondary metabolites present in all terrestrial plants. The flavonoid pathway has been extensively studied, and many of the involved genes and metabolites have been described in the literature. Despite this extensive knowledge, the functioning of the pathway in vivo is still poorly understood. Here, we study the flavonoid pathway using both experiments and mathematical models. We measured flavonoid metabolite dynamics in two tissues, hypocotyls and cotyledons, during tomato seedling development. Interestingly, the same backbone of interactions leads to very different accumulation patterns in the different tissues. Initially, we developed a mathematical model with constant enzyme concentrations that described the metabolic networks separately in both tissues. This model was unable to fit the measured flavonoid dynamics in the hypocotyls, even if we allowed unrealistic parameter values. This suggested us to investigate the effect of transcript abundance on flavonoid accumulation. We found that the expression of candidate flavonoid genes varies considerably with time. Variation in transcript abundance results in enzymatic variation, which could have a large effect on metabolite accumulation. Candidate transcript abundance was included in the mathematical model as representative for enzyme concentration. We fitted the resulting model to the flavonoid dynamics in the cotyledons, and tested it by applying it to the data from hypocotyls. When transcript abundance is included, we are indeed able to explain flavonoid dynamics in both tissues. Importantly, this is possible under the biologically relevant restriction that the enzymatic properties estimated by the model are conserved between the tissues.
format article
author Marian Groenenboom
Victoria Gomez-Roldan
Hans Stigter
Laura Astola
Raymond van Daelen
Jules Beekwilder
Arnaud Bovy
Robert Hall
Jaap Molenaar
author_facet Marian Groenenboom
Victoria Gomez-Roldan
Hans Stigter
Laura Astola
Raymond van Daelen
Jules Beekwilder
Arnaud Bovy
Robert Hall
Jaap Molenaar
author_sort Marian Groenenboom
title The flavonoid pathway in tomato seedlings: transcript abundance and the modeling of metabolite dynamics.
title_short The flavonoid pathway in tomato seedlings: transcript abundance and the modeling of metabolite dynamics.
title_full The flavonoid pathway in tomato seedlings: transcript abundance and the modeling of metabolite dynamics.
title_fullStr The flavonoid pathway in tomato seedlings: transcript abundance and the modeling of metabolite dynamics.
title_full_unstemmed The flavonoid pathway in tomato seedlings: transcript abundance and the modeling of metabolite dynamics.
title_sort flavonoid pathway in tomato seedlings: transcript abundance and the modeling of metabolite dynamics.
publisher Public Library of Science (PLoS)
publishDate 2013
url https://doaj.org/article/3b9cc0f5c6a34ad3a8815cc12463671d
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