TY - JOUR
T1 - Total optimization potential (TOP) approach based constrained design of isoprene and cis-abienol production in A. thaliana
AU - Neiburga, Katrina D.
AU - Muiznieks, Reinis
AU - Zake, Darta M.
AU - Pentjuss, Agris
AU - Komasilovs, Vitalijs
AU - Rohwer, Johann
AU - Tissier, Alain
AU - Stalidzans, Egils
N1 - Funding Information:
This research is partly funded by ERASynBio project ‘Control of engineered metabolism by flowering and temperature triggered plant regulatory networks’ (SMARTPLANTS) and University of Latvia project “Climate change and its impacts on sustainability of natural resources” (Nr. Y5-AZ20-ZF-N-270 ).
Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2023/1
Y1 - 2023/1
N2 - Mathematical modelling is an important approach in metabolic engineering projects to support the design and adaptation of organisms for the needs of biotechnology. Assuming sufficient quality of the model, mechanistic mathematical descriptions of the processes enable the prediction of the systemic impact of metabolic pathway engineering on the organism's metabolism. In this paper, modelling is used to design the necessary changes in Arabidopsis thaliana metabolism for the production of cis-abienol and isoprene. We developed a kinetic model of the A. thaliana 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway, including the production of plastoquinone, chlorophyll side chains and carotenoids. For the purpose of optimisation, it was extended with additional reactions leading to the production of cis-abienol (using geranylgeranyl diphosphate as precursor) and isoprene (using dimethylallyl pyrophosphate as precursor).A total optimisation potential (TOP) based search of reasonable enzyme concentration adjustments yielded sets of parameter combinations, from which those were selected that gave the largest increase in the product flux compared to parameter sets with a smaller number of parameters. Three designs (sets of required concentration changes of particular enzymes) are suggested for each product, based on optimisation of the 2048 possible combinations of adjustable parameters (enzyme concentrations). The resulting optimization of the model forecasts a cis-abienol production of 0.021 nmol.s
−1.ml
−1 and an isoprene production of 0.048 nmol.s
−1.ml
−1 in plastids of A. thaliana.
AB - Mathematical modelling is an important approach in metabolic engineering projects to support the design and adaptation of organisms for the needs of biotechnology. Assuming sufficient quality of the model, mechanistic mathematical descriptions of the processes enable the prediction of the systemic impact of metabolic pathway engineering on the organism's metabolism. In this paper, modelling is used to design the necessary changes in Arabidopsis thaliana metabolism for the production of cis-abienol and isoprene. We developed a kinetic model of the A. thaliana 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway, including the production of plastoquinone, chlorophyll side chains and carotenoids. For the purpose of optimisation, it was extended with additional reactions leading to the production of cis-abienol (using geranylgeranyl diphosphate as precursor) and isoprene (using dimethylallyl pyrophosphate as precursor).A total optimisation potential (TOP) based search of reasonable enzyme concentration adjustments yielded sets of parameter combinations, from which those were selected that gave the largest increase in the product flux compared to parameter sets with a smaller number of parameters. Three designs (sets of required concentration changes of particular enzymes) are suggested for each product, based on optimisation of the 2048 possible combinations of adjustable parameters (enzyme concentrations). The resulting optimization of the model forecasts a cis-abienol production of 0.021 nmol.s
−1.ml
−1 and an isoprene production of 0.048 nmol.s
−1.ml
−1 in plastids of A. thaliana.
KW - Kinetic model
KW - MEP pathway
KW - Metabolic engineering
KW - Optimisation
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UR - https://www.mendeley.com/catalogue/d1c105f2-7587-3eed-85f5-788055dc8ef5/
U2 - 10.1016/j.bej.2022.108723
DO - 10.1016/j.bej.2022.108723
M3 - Article
SN - 1369-703X
VL - 190
JO - Biochemical Engineering Journal
JF - Biochemical Engineering Journal
M1 - 108723
ER -