Summary Genes encoding proteins in a common regulatory network are frequently located close to one another on the chromosome to facilitate co-regulation or couple gene expression to growth rate. Contrasting with these observations, here we demonstrate a functional role for the arrangement of Bacillus subtilis sporulation network genes on opposite sides of the chromosome. We show that the arrangement of two sporulation network genes, one located close to the origin, the other close to the terminus leads to a transient gene dosage imbalance during chromosome replication. This imbalance is detected by the sporulation network to produce cell-cycle coordinated pulses of the sporulation master regulator Spo0A~P. This pulsed response allows cells to decide between sporulation and continued vegetative growth during each cell-cycle spent in starvation. The simplicity of this coordination mechanism suggests that it may be widely applicable in a variety of gene regulatory and stress-response settings.

Starving Bacillus subtilis cells execute a gene expression program resulting in the formation of stress-resistant spores. Sporulation master regulator, Spo0A, is activated by a phosphorelay and controls the expression of a multitude of genes, including the forespore-specific sigma factor σ F and the mother cell-specific sigma factor σ E . Identification of the system-level mechanism of the sporulation decision is hindered by a lack of direct control over Spo0A activity. This limitation can be overcome by using a synthetic system in which Spo0A activation is controlled by inducing expression of phosphorelay kinase KinA. This induction results in a switch-like increase in the number of sporulating cells at a threshold of KinA. Using a combination of mathematical modeling and single-cell microscopy, we investigate the origin and physiological significance of this ultrasensitive threshold. The results indicate that the phosphorelay is unable to achieve a sufficiently fast and ultrasensitive response via its positive feedback architecture, suggesting that the sporulation decision is made downstream. In contrast, activation of σ F in the forespore and of σ E in the mother cell compartments occurs via a cascade of coherent feed-forward loops, and thereby can produce fast and ultrasensitive responses as a result of KinA induction. Unlike σ F activation, σ E activation in the mother cell compartment only occurs above the KinA threshold, resulting in completion of sporulation. Thus, ultrasensitive σ E activation explains the KinA threshold for sporulation induction. We therefore infer that under uncertain conditions, cells initiate sporulation but postpone making the sporulation decision to average stochastic fluctuations and to achieve a robust population response.cell fate | development | differentiation | stochasticity | network I n response to nutrient deprivation, Bacillus subtilis cells undergo asymmetrical cell division and then follow a cell differentiation program resulting in formation of metabolically inert spores (1, 2) (Fig. 1A). Sporulation requires the execution of a complex gene expression program involving hundreds of "sporulation" genes (3-6). The availability of a large number of genetic mutants that differ from the WT only in their sporulation response makes B. subtilis an ideal model system to study the relationship between gene expression and cell fate specification during bacterial differentiation (7).Progression of the sporulation program is under the control of a large regulatory network (hereafter called the sporulation network). This network involves the sporulation master regulator Spo0A and five alternative sigma factors (σ H , σ F , σ E , σ K , and σ G ) that are activated in precise temporal order (8). Initiation of the sporulation program is controlled by Spo0A (4, 9). The activity and concentration of this master transcription factor are regulated by phosphorelay through both posttranslational and transcriptional interactions (10). Posttranslationally, phosphoryl groups are transferred fro...

A key property of living cells is their ability to react to stimuli with specific biochemical responses. These responses can be understood through the dynamics of underlying biochemical and genetic networks. Evolutionary design principles have been well studied in networks that display graded responses, with a continuous relationship between input signal and system output. Alternatively, biochemical networks can exhibit bistable responses so that over a range of signals the network possesses two stable steady states. In this review, we discuss several conceptual examples illustrating network designs that can result in a bistable response of the biochemical network. Next, we examine manifestations of these designs in bacterial master-regulatory genetic circuits. In particular, we discuss mechanisms and dynamic consequences of bistability in three circuits: two-component systems, sigma-factor networks, and a multistep phosphorelay. Analyzing these examples allows us to expand our knowledge of evolutionary design principles for networks with bistable responses.

How can changes in growth rate affect the regulatory networks behavior and the outcomes of cellular differentiation? We address this question by focusing on starvation response in sporulating Bacillus subtilis. We show that the activity of sporulation master regulator Spo0A increases with decreasing cellular growth rate. Using a mathematical model of the phosphorelay—the network controlling Spo0A—we predict that this increase in Spo0A activity can be explained by the phosphorelay protein accumulation and lengthening of the period between chromosomal replication events caused by growth slowdown. As a result, only cells growing slower than a certain rate reach threshold Spo0A activity necessary for sporulation. This growth threshold model accurately predicts cell fates and explains the distribution of sporulation deferral times. We confirm our predictions experimentally and show that the concentration rather than activity of phosphorelay proteins is affected by the growth slowdown. We conclude that sensing the growth rates enables cells to indirectly detect starvation without the need for evaluating specific stress signals.