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Published on: October 29, 2016
The motility-matrix production switch in Bacillus subtilis-a modeling perspective
Simon Dannenberg1, Jonas Penning1, Alexander Simm1
1University of Göttingen, Institute for the Dynamics of Complex Systems , Göttingen, Germany.
Bacillus subtilis switches between motility and matrix production via a SinR-SlrR bistable switch. Intrinsic noise is insufficient; upstream Spo0A phosphorelay noise triggers this crucial transition for biofilm formation.
Area of Science:
- Microbiology
- Systems Biology
- Biophysics
Background:
- Phenotype switching in Bacillus subtilis, particularly the transition from motility to matrix production, is a critical step in biofilm formation and multicellular behavior.
- This switch is governed by a bistable regulatory system involving SinR, SlrR, and SinI.
Purpose of the Study:
- To model the SinR-SlrR bistable switch and its regulation by SinI in Bacillus subtilis.
- To differentiate between intrinsic and extrinsic sources of stochasticity influencing the motility-matrix production switch.
- To identify the primary trigger for spontaneous switching behavior.
Main Methods:
- Development of a step-by-step quantitative model to simulate the dynamics of the SinR-SlrR switch.
- Analysis of stochastic fluctuations in SinI synthesis and upstream signaling pathways.
- Distinguishing the contribution of intrinsic cellular noise versus external signaling noise.
Main Results:
- Simulations demonstrated that intrinsic fluctuations in SinI synthesis alone cannot induce spontaneous switching.
- The study identified upstream noise originating from the Spo0A phosphorelay as the likely trigger for the switch.
- The model successfully described the regulatory dynamics and switching behavior.
Conclusions:
- The motility-matrix production switch in Bacillus subtilis is primarily driven by external noise from the Spo0A phosphorelay, not solely by internal stochasticity.
- Understanding these regulatory dynamics is key to comprehending biofilm development and multicellularity in bacteria.
- Quantitative modeling provides valuable insights into complex biological switching mechanisms.
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