muraro1

The SBML for this model was obtained from the BioModels database (BioModels ID: BIOMD0000000416) Biomodels notes: Figure 7 of the reference publication has been reproduced here. The parameter values of alphaARRB and alphaCk has to set to the values mentioned in the curation figure, to get the appropriate plots. The model was simulated using Copasi v4.7 (Build 34). JWS Online curation: This model was curated by reproducing the figures as described in the BioModels Notes. No additional changes were made.

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The influence of cytokinin-auxin cross-regulation on cell-fate determination in Arabidopsis thaliana root development.

  • Daniele Muraro
  • Helen Byrne
  • John King
  • Ute Voss
  • Joseph Kieber
  • Malcolm Bennett
J. Theor. Biol. 2011; 283 (1): 152-167
Abstract
Root growth and development in Arabidopsis thaliana are sustained by a specialised zone termed the meristem, which contains a population of dividing and differentiating cells that are functionally analogous to a stem cell niche in animals. The hormones auxin and cytokinin control meristem size antagonistically. Local accumulation of auxin promotes cell division and the initiation of a lateral root primordium. By contrast, high cytokinin concentrations disrupt the regular pattern of divisions that characterises lateral root development, and promote differentiation. The way in which the hormones interact is controlled by a genetic regulatory network. In this paper, we propose a deterministic mathematical model to describe this network and present model simulations that reproduce the experimentally observed effects of cytokinin on the expression of auxin regulated genes. We show how auxin response genes and auxin efflux transporters may be affected by the presence of cytokinin. We also analyse and compare the responses of the hormones auxin and cytokinin to changes in their supply with the responses obtained by genetic mutations of SHY2, which encodes a protein that plays a key role in balancing cytokinin and auxin regulation of meristem size. We show that although shy2 mutations can qualitatively reproduce the effect of varying auxin and cytokinin supply on their response genes, some elements of the network respond differently to changes in hormonal supply and to genetic mutations, implying a different, general response of the network. We conclude that an analysis based on the ratio between these two hormones may be misleading and that a mathematical model can serve as a useful tool for stimulate further experimental work by predicting the response of the network to changes in hormone levels and to other genetic mutations.

Unit definitions have no effect on the numerical analysis of the model. It remains the responsibility of the modeler to ensure the internal numerical consistency of the model. If units are provided, however, the consistency of the model units will be checked.

Name Definition
Id Name Spatial dimensions Size
cell 3.0 1.0
Id Name Initial quantity Compartment Fixed
AHKph 1.0 cell
ARF 0.0 cell
ARF2 0.0 cell
ARFIAA 0.0 cell
ARRAm 0.0 cell
ARRAp 0.0 cell
ARRAph 0.0 cell
ARRBp 0.0 cell
ARRBph 0.0 cell
ARm 0.0 cell
ARp 0.0 cell
Aux 1.0 cell
AuxTIAA 0.0 cell
AuxTIR1 0.0 cell
CRm 0.0 cell
CRp 0.0 cell
Ck 1.0 cell
CkAHK 0.0 cell
CkAHKph 0.0 cell
F1 0.0 cell
F2 0.0 cell
F3 0.0 cell
F4 0.0 cell
F5a 0.0 cell
F5b 0.0 cell
F6 0.0 cell
IAAm 0.0 cell
IAAp 0.0 cell
IAAs 0.0 cell
PINm 0.0 cell
PINp 0.0 cell
TIR1 0.0 cell

Initial assignments are expressions that are evaluated at time=0. It is not recommended to create initial assignments for all model entities. Restrict the use of initial assignments to cases where a value is expressed in terms of values or sizes of other model entities. Note that it is not permitted to have both an initial assignment and an assignment rule for a single model entity.

Definition
Id Name Objective coefficient Reaction Equation and Kinetic Law Flux bounds
r1 ∅ > IAAm

phiIAAp * (lambda1 * F1 + F2 + lambda3 * F3) - IAAm
r10 ∅ > PINp

1 / eps * (deltaPINp * PINm - PINp)
r11 ∅ > ARm

phiARp * (lambda1 * F5a + F5b) - ARm
r12 ∅ > ARp

1 / eps * (deltaARp * ARm - ARp)
r13 ∅ > CRm

phiCRp * F4 - CRm
r14 ∅ > CRp

1 / eps * (deltaCRp * CRm - CRp)
r15 ∅ > AHKph

1 / eps * (rd * CkAHKph - ra * AHKph * Ck)
r16 ∅ > Ck

muCk * (alphaCk - Ck) - etaCkPh / eps * (ra * AHKph * Ck - rd * CkAHKph)
r17 ∅ > ARRBph

1 / eps * (ua * CkAHKph * ARRBp - ud * CkAHK * ARRBph)
r18 ∅ > ARRAph

1 / eps * (sa * CkAHKph * ARRAp - sd * CkAHK * ARRAph)
r19 ∅ > ARRAm

phiARRAp * F6 - ARRAm
r2 ∅ > IAAp

1 / eps * (deltaIAAp * IAAm - la * IAAp * AuxTIR1 + ld * AuxTIAA) + etaARFIAA * (pd * ARFIAA - pa * IAAp * ARF)
r20 ∅ > ARRAp

1 / eps * (deltaARRAp * ARRAm - ARRAp + etaAHKph * (sd * CkAHK * ARRAph - sa * CkAHKph * ARRAp))
r3 ∅ > AuxTIR1

1 / eps * (ka * Aux * TIR1 - kd * AuxTIR1 + (ld + 1) * AuxTIAA - la * AuxTIR1 * IAAp)
r4 ∅ > AuxTIAA

1 / eps * (la * IAAp * AuxTIR1 - (ld + 1) * AuxTIAA)
r5 ∅ > IAAs

1 / eps * (AuxTIAA - muIAAs * IAAs)
r6 ∅ > ARFIAA

pa * ARF * IAAp - pd * ARFIAA
r7 ∅ > ARF2

qa * pow(ARF, 2) - qd * ARF2
r8 ∅ > Aux

muAux * (alphaAux - Aux) - 1 / eps * etaAuxTIR1 * (ka * Aux * TIR1 - kd * AuxTIR1)
r9 ∅ > PINm

phiPINp * (lambda1 * F5a + F5b) - PINm

Global parameters

Id Value
alphaAHK 1.0
alphaARF 1.0
alphaARRB 2.0
alphaAux 1.0
alphaCk 1.0
alphaPH 1.0
alphaTIR1 1.0
deltaARRAp 1.0
deltaARp 1.0
deltaCRp 1.0
deltaIAAp 1.0
deltaPINp 1.0
eps 0.01
etaAHKph 1.0
etaARFIAA 1.0
etaAuxTIR1 10.0
etaCkPh 1.0
ka 100.0
kd 1.0
la 0.5
lambda1 0.1
lambda3 0.02
ld 0.1
muAux 0.1
muCk 0.1
muIAAs 1.0
pa 10.0
pd 10.0
phiARRAp 100.0
phiARp 2.0
phiCRp 2.0
phiIAAp 100.0
phiPINp 100.0
psiARF 0.1
psiARFIAA 0.1
qa 1.0
qd 1.0
ra 1.0
rd 1.0
sa 1.0
sd 1.0
thARFIAA 0.1
thARRAph 0.1
thARRBph 0.1
thetaARF 0.1
thetaARF2 0.01
thetaARp 0.1
thetaIAAp 0.1
ua 1.0
ud 1.0

Local parameters

Id Value Reaction

Assignment rules

Definition
CkAHK = alphaAHK - etaAHKph * (AHKph + CkAHKph)
CkAHKph = alphaPH - AHKph - ARRAph - ARRBph
ARRBp = alphaARRB - etaAHKph * ARRBph
ARF = alphaARF - 2.0 * ARF2 - ARFIAA
TIR1 = alphaTIR1 - AuxTIR1 - AuxTIAA
F6 = ARp / thetaARp / (1.0 + ARp / thetaARp)
F5b = (ARF2 / thetaARF2 + pow(ARF, 2.0) / psiARF) / (1.0 + ARF / thetaARF + ARF2 / thetaARF2 + ARFIAA / thARFIAA + ARF * IAAp / psiARFIAA + pow(ARF, 2.0) / psiARF)
F5a = ARF / thetaARF / (1.0 + ARF / thetaARF + ARF2 / thetaARF2 + ARFIAA / thARFIAA + ARF * IAAp / psiARFIAA + pow(ARF, 2.0) / psiARF)
F4 = ARRBph / thARRBph / (1.0 + ARRAph / thARRAph + ARRBph / thARRBph)
F3 = ARRBph / thARRBph / (1.0 + ARF / thetaARF + ARF2 / thetaARF2 + ARFIAA / thARFIAA + ARF * IAAp / psiARFIAA + pow(ARF, 2.0) / psiARF + ARRBph / thARRBph)
F2 = (ARF2 / thetaARF2 + pow(ARF, 2.0) / psiARF) / (1.0 + ARF / thetaARF + ARF2 / thetaARF2 + ARFIAA / thARFIAA + ARF * IAAp / psiARFIAA + pow(ARF, 2.0) / psiARF + ARRBph / thARRBph)
F1 = ARF / thetaARF / (1.0 + ARF / thetaARF + ARF2 / thetaARF2 + ARFIAA / thARFIAA + ARF * IAAp / psiARFIAA + pow(ARF, 2.0) / psiARF + ARRBph / thARRBph)

Rate rules

Definition

Algebraic rules

Definition
Trigger Assignments