ratushny5

___r1

∅ > P1

___r2

P1 > ∅

___r3

∅ > Target

___r4

Target > ∅

Global parameters
___r2
___r4

Assignment rules

dsp1p2kd = Kd / 2.0 * (1.0 + (dsp1ksp + P2) / Kd - pow(pow(1.0 + (dsp1ksp + P2) / Kd, 2.0) - 4.0 * dsp1ksp * P2 / pow(Kd, 2.0), 0.5))

dsp1ksp = Ksp / 2.0 * (1.0 + (s + P1 * univ) / Ksp - pow(pow(1.0 + (s + P1 * univ) / Ksp, 2.0) - 4.0 * s * P1 * univ / pow(Ksp, 2.0), 0.5))

Function definitions

Note that constraints are not enforced in simulations. It remains the responsibility of the user to verify that simulation results satisfy these constraints.


Species:

Reactions:


Middle-click: pin/unpin nodes
Shift-click: pool/unpool species
Right-click: context menu

Apply alternate model layout to overlapping elements in current model:

log scales

y-axis min/max

x-axis min/max

Asymmetric positive feedback loops reliably control biological responses.

  • Alexander V Ratushny
  • Ramsey A Saleem
  • Katherine Sitko
  • Stephen A Ramsey
  • John D Aitchison
Mol. Syst. Biol. 2012; 8 : 577
Abstract
Positive feedback is a common mechanism enabling biological systems to respond to stimuli in a switch-like manner. Such systems are often characterized by the requisite formation of a heterodimer where only one of the pair is subject to feedback. This ASymmetric Self-UpREgulation (ASSURE) motif is central to many biological systems, including cholesterol homeostasis (LXRα/RXRα), adipocyte differentiation (PPARγ/RXRα), development and differentiation (RAR/RXR), myogenesis (MyoD/E12) and cellular antiviral defense (IRF3/IRF7). To understand why this motif is so prevalent, we examined its properties in an evolutionarily conserved transcriptional regulatory network in yeast (Oaf1p/Pip2p). We demonstrate that the asymmetry in positive feedback confers a competitive advantage and allows the system to robustly increase its responsiveness while precisely tuning the response to a consistent level in the presence of varying stimuli. This study reveals evolutionary advantages for the ASSURE motif, and mechanisms for control, that are relevant to pharmacologic intervention and synthetic biology applications.
The SBML for this model was obtained from the BioModels database (BioModels ID: BIOMD0000000421) Biomodels notes: The plot corresponding to "ASSURE11" in Figure 2f of the reference publication has been reproduced here. The data for the plot was obtained by simulating the model using Copasi v4.8 (Build 35) and plotted using gnuplot. JWS Online curation: This model was curated by reproducing the figures as described in the BioModels Notes. No additional changes were made.