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. 2006 Jul;61(1):165-84.
doi: 10.1111/j.1365-2958.2006.05212.x.

Signalling network with a bistable hysteretic switch controls developmental activation of the sigma transcription factor in Bacillus subtilis

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Signalling network with a bistable hysteretic switch controls developmental activation of the sigma transcription factor in Bacillus subtilis

Oleg A Igoshin et al. Mol Microbiol. 2006 Jul.
Free article

Abstract

The sporulation process of the bacterium Bacillus subtilis unfolds by means of separate but co-ordinated programmes of gene expression within two unequal cell compartments, the mother cell and the smaller forespore. sigmaF is the first compartment-specific transcription factor activated during this process, and it is controlled at the post-translational level by a partner-switching mechanism that restricts sigmaF activity to the forespore. The crux of this mechanism lies in the ability of the anti-sigma factor SpoIIAB (AB) to form alternative complexes either with sigmaF, holding it in an inactive form, or with the anti-anti-sigma factor SpoIIAA (AA) and a nucleotide, either ATP or ADP. In the complex with AB and ATP, AA is phosphorylated on a serine residue and released, making AB available to capture sigmaF in an inactive complex. Subsequent activation of sigmaF requires the intervention of the SpoIIE serine phosphatase to dephosphorylate AA, which can then attack the AB-sigmaF complex to induce the release of sigmaF. By incorporating biochemical, biophysical and genetic data from the literature we have constructed an integrative mathematical model of this partner-switching network. The model predicts that the self-enhancing formation of a long-lived complex of AA, AB and ADP transforms the network into an essentially irreversible hysteretic switch, thereby explaining the sharp, robust and irreversible activation of sigmaF in the forespore compartment. The model also clarifies the contributions of the partly redundant mechanisms that ensure correct spatial and temporal activation of sigmaF, reproduces the behaviour of various mutants and makes strong, testable predictions.

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