Adams2019 - The regulatory role of shikimate in plant phenylalanine metabolism

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This is a mathematical model of phenylalanine metabolism in plants as influenced by shikimate, with specific evidence of how shikimate dynamics influence phenylalanine metabolism as a function of phenylalanine availability.
Related Publication
  • The regulatory role of shikimate in plant phenylalanine metabolism.
  • Adams ZP, Ehlting J, Edwards R
  • Journal of theoretical biology , 2/ 2019 , Volume 462 , pages: 158-170 , PubMed ID: 30412698
  • Max Planck Institute for Mathematics in the Sciences, Inselstra├če 22, 04103 Leipzig, Germany. Electronic address:
  • In higher plants, the amino acid phenylalanine is a substrate of both primary and secondary metabolic pathways. The primary pathway that consumes phenylalanine, protein biosynthesis, is essential for the viability of all cells. Meanwhile, the secondary pathways are not necessary for the survival of individual cells, but benefit of the plant as a whole. Here we focus on the monolignol pathway, a secondary metabolic pathway in the cytosol that rapidly consumes phenylalanine to produce the precursors of lignin during wood formation. In planta┬ámonolignol biosynthesis involves a series of seemingly redundant steps wherein shikimate, a precursor of phenylalanine synthesized in the plastid, is transiently ligated to the main substrate of the pathway. However, shikimate is not catalytically involved in the reactions of the monolignol pathway, and is only needed for pathway enzymes to recognize their main substrates. After some steps the shikimate moiety is removed unaltered, and the main substrate continues along the pathway. It has been suggested that this portion of the monolignol pathway fulfills a regulatory role in the following way. Low phenylalanine concentrations (viz. availability) correlate with low shikimate concentrations. When shikimate concentratios are low, flux into the monolignol pathway will be limited by means of the steps requiring shikimate. Thus, when the concentration of phenylalanine is low it will be reserved for protein biosynthesis. Here we employ a theoretical approach to test this hypothesis. Simplified versions of plant phenylalanine metabolism are modelled as systems of ordinary differential equations. Our analysis shows that the seemingly redundant steps can be sufficient for the prioritization of protein biosynthesis over the monolignol pathway when the availability of phenylalanine is low, depending on system parameters. Thus, the phenylalanine precursor shikimate may signal low phenylalanine availability to secondary pathways. Because our models have been abstracted from plant phenylalanine metabolism, this mechanism of metabolic signalling, which we call the Precursor Shutoff Valve (PSV), may also be present in other biochemical networks comprised of two pathways that share a common substrate.
Submitter of the first revision: Johannes Meyer
Submitter of this revision: Johannes Meyer
Modellers: Johannes Meyer

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hasProperty (1 statement)
Mathematical Modelling Ontology Ordinary differential equation model

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Adams2019.xml SBML L2V4 Representation of Adams2019 - The regulatory role of shikimate in plant phenylalanine metabolism 37.70 KB Preview | Download

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Adams2019.cps COPASI file of Adams2019 - The regulatory role of shikimate in plant phenylalanine metabolism 69.66 KB Preview | Download
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  • Model originally submitted by : Johannes Meyer
  • Submitted: Nov 10, 2019 8:58:13 PM
  • Last Modified: Nov 10, 2019 8:58:13 PM
  • Version: 4 public model Download this version
    • Submitted on: Nov 10, 2019 8:58:13 PM
    • Submitted by: Johannes Meyer
    • With comment: Automatically added model identifier BIOMD0000000847
: Variable used inside SBML models

Species Initial Concentration/Amount
X 3

shikimate ; cytosol
0.0 item
X 2

0.0 item
X 4

0.0 item
X 1

shikimate ; GO:0009536
0.0 item
Reactions Rate Parameters
X_4 => X_3 compartment*a_4*X_4/(K_4+X_4) K_4 = 1.0; a_4 = 75.0
X_2 + X_3 => X_4 compartment*a_3*X_2*X_3/((K_3_2+X_2)*(K_3_3+X_3)) K_3_2 = 1.0; K_3_3 = 0.1; a_3 = 75.0
X_1 => X_3 compartment*(a_2_plus*X_1/(K_2_plus*(1+b2f*X_3)+X_1)-a_2_minus*X_3/(K_2_minus*(1+b2r*X_1)+X_3)) a_2_minus = 1.5; K_2_minus = 100.0; a_2_plus = 2.0; b2r = 0.0; K_2_plus = 100.0; b2f = 0.0
X_1 => X_2 compartment*a_1*X_1/(K_1*(1+b*X_2)+X_1) a_1 = 100.0; b = 1.0; K_1 = 0.1
=> X_1 compartment*a_0 a_0 = 25.0
Curator's comment:
(added: 10 Nov 2019, 20:58:06, updated: 10 Nov 2019, 20:58:06)
Reproduced plot of Figure 4(d) in the original publication. Model simulated and plot produced using COPASI 4.24 (Build 197).