Flux modeling for monolignol biosynthesis

Jack P. Wang; Megan L. Matthews; Punith P. Naik; Cranos M. Williams; Joel J. Ducoste; Ronald R. Sederoff; Vincent L. Chiang

doi:10.1016/j.copbio.2018.12.003

Flux modeling for monolignol biosynthesis

Jack P. Wang, Megan L. Matthews, Punith P. Naik, Cranos M. Williams, Joel J. Ducoste, Ronald R. Sederoff, Vincent L. Chiang

Research output: Contribution to journal › Review article › peer-review

Abstract

The pathway of monolignol biosynthesis involves many components interacting in a metabolic grid to regulate the supply and ratios of monolignols for lignification. The complexity of the pathway challenges any intuitive prediction of the output without mathematical modeling. Several models have been presented to quantify the metabolic flux for monolignol biosynthesis and the regulation of lignin content, composition, and structure in plant cell walls. Constraint-based models using data from transgenic plants were formulated to describe steady-state flux distribution in the pathway. Kinetic-based models using enzyme reaction and inhibition constants were developed to predict flux dynamics for monolignol biosynthesis in wood-forming cells. This review summarizes the recent progress in flux modeling and its application to lignin engineering for improved plant development and utilization.

Original language	English (US)
Pages (from-to)	187-192
Number of pages	6
Journal	Current Opinion in Biotechnology
Volume	56
DOIs	https://doi.org/10.1016/j.copbio.2018.12.003
State	Published - Apr 2019
Externally published	Yes

ASJC Scopus subject areas

Biotechnology
Bioengineering
Biomedical Engineering

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10.1016/j.copbio.2018.12.003

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title = "Flux modeling for monolignol biosynthesis",

abstract = "The pathway of monolignol biosynthesis involves many components interacting in a metabolic grid to regulate the supply and ratios of monolignols for lignification. The complexity of the pathway challenges any intuitive prediction of the output without mathematical modeling. Several models have been presented to quantify the metabolic flux for monolignol biosynthesis and the regulation of lignin content, composition, and structure in plant cell walls. Constraint-based models using data from transgenic plants were formulated to describe steady-state flux distribution in the pathway. Kinetic-based models using enzyme reaction and inhibition constants were developed to predict flux dynamics for monolignol biosynthesis in wood-forming cells. This review summarizes the recent progress in flux modeling and its application to lignin engineering for improved plant development and utilization.",

author = "Wang, {Jack P.} and Matthews, {Megan L.} and Naik, {Punith P.} and Williams, {Cranos M.} and Ducoste, {Joel J.} and Sederoff, {Ronald R.} and Chiang, {Vincent L.}",

note = "Funding Information: This article was supported by the National Natural Science Foundation of China (NSFC) Grants 31430093 and 31470672 . We also thank the financial support from the U.S. National Science Foundation , Plant Genome Research Program Grant DBI-0922391 , the NC State University Jordan Family Distinguished Professor Endowment , and the NC State University Forest Biotechnology Industrial Research Consortium, and the 111 Project (B16010) of the Ministry of Education of China . Publisher Copyright: {\textcopyright} 2018 Elsevier Ltd Copyright: Copyright 2019 Elsevier B.V., All rights reserved.",

year = "2019",

month = apr,

doi = "10.1016/j.copbio.2018.12.003",

language = "English (US)",

volume = "56",

pages = "187--192",

journal = "Current Opinion in Biotechnology",

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AU - Wang, Jack P.

AU - Matthews, Megan L.

AU - Naik, Punith P.

AU - Williams, Cranos M.

AU - Ducoste, Joel J.

AU - Sederoff, Ronald R.

AU - Chiang, Vincent L.

N1 - Funding Information: This article was supported by the National Natural Science Foundation of China (NSFC) Grants 31430093 and 31470672 . We also thank the financial support from the U.S. National Science Foundation , Plant Genome Research Program Grant DBI-0922391 , the NC State University Jordan Family Distinguished Professor Endowment , and the NC State University Forest Biotechnology Industrial Research Consortium, and the 111 Project (B16010) of the Ministry of Education of China . Publisher Copyright: © 2018 Elsevier Ltd Copyright: Copyright 2019 Elsevier B.V., All rights reserved.

PY - 2019/4

Y1 - 2019/4

N2 - The pathway of monolignol biosynthesis involves many components interacting in a metabolic grid to regulate the supply and ratios of monolignols for lignification. The complexity of the pathway challenges any intuitive prediction of the output without mathematical modeling. Several models have been presented to quantify the metabolic flux for monolignol biosynthesis and the regulation of lignin content, composition, and structure in plant cell walls. Constraint-based models using data from transgenic plants were formulated to describe steady-state flux distribution in the pathway. Kinetic-based models using enzyme reaction and inhibition constants were developed to predict flux dynamics for monolignol biosynthesis in wood-forming cells. This review summarizes the recent progress in flux modeling and its application to lignin engineering for improved plant development and utilization.

AB - The pathway of monolignol biosynthesis involves many components interacting in a metabolic grid to regulate the supply and ratios of monolignols for lignification. The complexity of the pathway challenges any intuitive prediction of the output without mathematical modeling. Several models have been presented to quantify the metabolic flux for monolignol biosynthesis and the regulation of lignin content, composition, and structure in plant cell walls. Constraint-based models using data from transgenic plants were formulated to describe steady-state flux distribution in the pathway. Kinetic-based models using enzyme reaction and inhibition constants were developed to predict flux dynamics for monolignol biosynthesis in wood-forming cells. This review summarizes the recent progress in flux modeling and its application to lignin engineering for improved plant development and utilization.

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Flux modeling for monolignol biosynthesis

Abstract

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