liebal3

The SBML for this model was obtained from the BioModels database (BioModels ID: BIOMD0000000461) Biomodels notes: Figure 3a of the reference publication has been reproduced. Beta-galactosidase (lacz) activity at different values of IPTG (100M, 200M and 1000M) is observed in plot. The SED-ML file for this corresponding simulation can be downloaded (see below). 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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Proteolysis of beta-galactosidase following SigmaB activation in Bacillus subtilis.

  • Ulf W Liebal
  • Praveen K Sappa
  • Thomas Millat
  • Leif Steil
  • Georg Homuth
  • Uwe Völker
  • Olaf Wolkenhauer
Mol Biosyst 2012; 8 (6): 1806-1814
Abstract
In Bacillus subtilis the σ(B) mediated general stress response provides protection against various environmental and energy related stress conditions. To better understand the general stress response, we need to explore the mechanism by which the components interact. Here, we performed experiments in B. subtilis wild type and mutant strains to test and validate a mathematical model of the dynamics of σ(B) activity. In the mutant strain BSA115, σ(B) transcription is inducible by the addition of IPTG and negative control of σ(B) activity by the anti-sigma factor RsbW is absent. In contrast to our expectations of a continuous β-galactosidase activity from a ctc::lacZ fusion, we observed a transient activity in the mutant. To explain this experimental finding, we constructed mathematical models reflecting different hypotheses regarding the regulation of σ(B) and β-galactosidase dynamics. Only the model assuming instability of either ctc::lacZ mRNA or β-galactosidase protein is able to reproduce the experiments in silico. Subsequent Northern blot experiments revealed stable high-level ctc::lacZ mRNA concentrations after the induction of the σ(B) response. Therefore, we conclude that protein instability following σ(B) activation is the most likely explanation for the experimental observations. Our results thus support the idea that B. subtilis increases the cytoplasmic proteolytic degradation to adapt the proteome in face of environmental challenges following activation of the general stress response. The findings also have practical implications for the analysis of stress response dynamics using lacZ reporter gene fusions, a frequently used strategy for the σ(B) response.

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
compartment compartment 3.0 1.0
Id Name Initial quantity Compartment Fixed
IPTG IPTG 100.0 compartment (compartment)
lacz lacz 0.0 compartment (compartment)
sigb sigb 0.0 compartment (compartment)
x x 0.0 compartment (compartment)

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
v1 v1 IPTG = sigb

multiplier * IPTG * kbs - kbd * sigb
v2 v2 sigb = lacz

-(kzd * lacz) + kzs * sigb / (1 + x)
v3 v3 sigb = x

-(kxd * x) + kxs * sigb / (1 + x)

Global parameters

Id Value
kbd 0.044
kbs 100.0
kxd 9.0
kxs 0.76
kzd 0.041
kzs 0.0004
multiplier 1.0

Local parameters

Id Value Reaction

Assignment rules

Definition

Rate rules

Definition

Algebraic rules

Definition
Trigger Assignments