Modeling of gene regulatory networks controlling cell-fate decisions in Bacillus subtilis
To adapt to various environments, bacterial cells can activate distinct gene-expression programs and differentiate into mutually exclusive cell types. This process is called cell-fate decision. Bacillus subtilis is a well-studied model system for investigating bacterial cell-fate decisions. In Bacillus subtilis, a master regulator, Spo0A, controls several cell-differentiation pathways. Spo0A is activated by phosphorylation via a phosphorelay – a cascade of phosphotransfer reactions commencing with autophosphorylation of histidine kinases KinA, KinB, KinC, KinD, and KinE. Upon moderate starvation, phosphorylated Spo0A (Spo0A~P) activates biofilm formation by indirectly inducing matrix production in a subpopulation of cells via a SinI-SinR-SlrR regulatory network. When the nutrient is further depleted, Spo0A~P activates sporulation by directly and indirectly regulating sporulation gene expression. In this work, using mathematical modeling, we provide system-level understandings of the mechanisms controlling cell-fate decisions in Bacillus subtilis. It is unclear how different kinases regulate distinct cell fates via the same master regulator. To understand the roles of different kinases in the regulation of cell-fate decisions in B. subtilis, we built a mathematical model of the phosphorelay network. With this model, we revealed that KinC, one of the sensor kinases that activate Spo0A, has distinct effects on Spo0A at different growth stages: under fast growth, KinC acts as a phosphate source and activates Spo0A; whereas under slow growth, KinC becomes a phosphate sink and contributes to decreasing Spo0A activity. Moreover, we showed that considering the single-cell level heterogeneity is essential to understand the role of KinC in the regulation of cell-fate decisions. Next, to understand the single-cell heterogeneity of different cell fates, we built a model of the SinI-SinR-SlrR regulatory network. With this model we showed that the fluctuations in the cellular growth rate and the intrinsic noise in the SinI-SinR-SlrR regulatory network can explain the single-cell heterogeneity of biofilm matrix production; moreover, we showed that the cellular growth rate affects matrix production in a feed-forward manner. Our model successfully predicts the dynamics of biofilm matrix production under genetic perturbations and explains why matrix production and sporulation are mutually exclusive on single-cell level.
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