Dataset Information

Prediction stability in a data-based, mechanistic model of ?F regulation during sporulation in Bacillus subtilis.

ABSTRACT: Mathematical modeling of biological networks can help to integrate a large body of information into a consistent framework, which can then be used to arrive at novel mechanistic insight and predictions. We have previously developed a detailed, mechanistic model for the regulation of ?(F) during sporulation in Bacillus subtilis. The model was based on a wide range of quantitative data, and once fitted to the data, the model made predictions that could be confirmed in experiments. However, the analysis was based on a single optimal parameter set. We wondered whether the predictions of the model would be stable for all optimal parameter sets. To that end we conducted a global parameter screen within the physiological parameter ranges. The screening approach allowed us to identify sensitive and sloppy parameters, and highlighted further required datasets during the optimization. Eventually, all parameter sets that reproduced all available data predicted the physiological situation correctly.

SUBMITTER: Fengos G

PROVIDER: S-EPMC3783014 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Prediction stability in a data-based, mechanistic model of σF regulation during sporulation in Bacillus subtilis.

Fengos Georgios G Iber Dagmar D

Scientific reports 20130925

Mathematical modeling of biological networks can help to integrate a large body of information into a consistent framework, which can then be used to arrive at novel mechanistic insight and predictions. We have previously developed a detailed, mechanistic model for the regulation of σ(F) during sporulation in Bacillus subtilis. The model was based on a wide range of quantitative data, and once fitted to the data, the model made predictions that could be confirmed in experiments. However, the ana ...[more]

PMID: 24067622

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Project description:RNA polymerase sigma factor sigma(F) initiates the prespore-specific program of gene expression during Bacillus subtilis sporulation. sigma(F) governs transcription of spoIIIG, encoding the late prespore-specific regulator sigma(G). However, transcription of spoIIIG is delayed relative to other genes under the control of sigma(F), and after synthesis, sigma(G) is initially kept in an inactive form. Activation of sigma(G) requires the complete engulfment of the prespore by the mother cell and expression of the spoIIIA and spoIIIJ loci. We screened for random mutations in spoIIIG that bypassed the requirement for spoIIIA for the activation of sigma(G). We found a mutation (spoIIIGE156K) that resulted in an amino acid substitution at position 156, which is adjacent to the position of a mutation (E155K) previously shown to prevent interaction of SpoIIAB with sigma(G). Comparative modelling techniques and in vivo studies suggested that the spoIIIGE156K mutation interferes with the interaction of SpoIIAB with sigma(G). The sigma(GE156K) isoform restored sigma(G)-directed gene expression to spoIIIA mutant cells. However, expression of sspE-lacZ in the spoIIIA spoIIIGE156K double mutant was delayed relative to completion of the engulfment process and was not confined to the prespore. Rather, beta-galactosidase accumulated throughout the entire cell at late times in development. This suggests that the activity of sigma(GE156K) is still regulated in the prespore of a spoIIIA mutant, but not by SpoIIAB. In agreement with this suggestion, we also found that expression of spoIIIGE156K from the promoter for the early prespore-specific gene spoIIQ still resulted in sspE-lacZ induction at the normal time during sporulation, coincidently with completion of the engulfment process. In contrast, transcription of spoIIIGE156K, but not of the wild-type spoIIIG gene, from the mother cell-specific spoIID promoter permitted the rapid induction of sspE-lacZ expression. Together, the results suggest that SpoIIAB is either redundant or has no role in the regulation of sigma(G) in the prespore.

Dataset Information

Prediction stability in a data-based, mechanistic model of ?F regulation during sporulation in Bacillus subtilis.

Publications

Prediction stability in a data-based, mechanistic model of σF regulation during sporulation in Bacillus subtilis.

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