Genetically identical cells have the capacity to stochastically differentiate into various phenotypes each with it own with unique attributes. This hedge survival strategy allows the population to continuously deploy specialized cells in response to and in anticipation of, possible drastic changes in conditions1,2,3,4,5,6,7,8,9,10,11. The stochastic phenotype differentiations (or stochastic fate determinations) involve cell-cell communication and coordination and provide each cell with the flexibility and freedom to select its own phenotype according to the specific conditions it encounters but in harmony with the other cells. A variety of different phenotypes interact and contribute for the well-being of the colony by performing different tasks12,13.

The phenotypical diversity arising from isogenic populations leads to the question, how random these individual decisions are. On one hand, neighbors exposed to the same environment need to make different decisions about their fates, in order to achieve diversity at the local level. On the other hand, the individual cell decisions must be collectivley regulated and coordinated carefully to garantee the optimal distribution of phenotypes for the colony as a whole. That means that even though there is need for randomness in the decision process to break symmetry, the probabilities of the possible outcomes must be carefully regulated by sensorial inputs and cell-cell communication.

The challenge is to reveal the principles governing how individual cells sense their environment and communicate with their neighbors before their own fate determination. And how, at the same time, these same individuals leave the final decision to chance in order to avoid the choice of the same phenotype by the whole population? To do so, the decision circuits must have a special capacity (yet not understood) for noise managment, allowing the bacteria to detemine fate by “playing dice with controled odds”1. Cellular capacity to manage the odds should entail both means to program and regulate the noise level and means to program the effect of the noise on the gene circuit performance5,6,7,8,9,10,14. Several studies have shown that circuit architecture (the connectivity map between the circuit genes) can encode distinct noise behaviors critical to the function implemented by the circuit4,5,6,15,16,17.

A prototypic example of how genetic networks harness noise for performance of cellular differentiation is the fate determination between sporulation and competence in Bacillus subtilis. Many bacteria strains, in response to severe starvation, can form endospores – dormant cells that are remarkably resistant to many hazards like heat, radiation and toxic chemicals. The process of sporulation is accompanied eventually by termination of metabolic activity in one daughter cell (the spore) and death by lysis of the other (the ‘mother cell’). Sporulation is not initiated automatically upon nutrient limitation, but instead it is a last resort. Initially, a variety of other tactics to survive the stress can be employed. Up to eight different phenotypes have been identified in Bacillus subtilis when facing starvation, including differentiation into higher flagellated motile phenotype seeking new food niches, differentiation into phenotypes mastering in the secretion of hydrolytic enzymes to scavenge extracellular proteins and polysaccharides and differentiation into cannibal phenotype feeding on its peers12,13. When other tactics fail in lifting the stress, sporulation is the cell fate chosen by a majority of the cells. The material released by lysis of the sporulating cells is not wasted but can be taken up by a minority of competent cells. On the path towards sporulation, the individual cells can switch (escape) into competence and become able to uptake the genetic material from lysed cells which can be used as a food sources, for DNA repair and occasionally even as new genetic information to enable resisting the encountered stress. The competent cells can switch back (after about a day) into vegetative growth and proceed towards sporulation18.

The network performing the decision between sporulation competence is a complex one, involving several modules and inputs. Many different stress signals are integrated into a phosphorelay leading to the phosphorylation of the sporulation master regulator Spo0A which have been show to act as a timer with adaptable clock rate - the production rate of Spo0A* (phosphorylated Spo0A)19,20. The process terminate upon comitment to sporulation when Spo0A* exceeeds a thereshold level. In order to regulate this process, pheromones are sent and received by the cell to indicate not only the local population density, but also information on stress levels sensed by the neighbors, which indicate their propensities of entering competence or sporulation21. The transition into competence requires noise in the expression of its master regulator ComK. A positive feedback loop on ComK is activated when fluctuations lead its concentration to cross a certain threshold. By interfering with the active degradation of ComK by MecA, a peptide ComS linked to the quorum sensing response sets the threshold for self-activation of ComK.

The stand-alone operations of the two modules – the sporulation timer and the competence switch - are well understood. The next challenge requires understanding of the interplay between the operations of the two modules, which determines the way bacteria decide between the two phenotypes. The AbrB-Rock decison gate is at the core of the sporulation-competence interplay22,23. However, the operational principles of this gate, which couples the opening of the stochastic switch with the state of the timer, are still not understood and subject to an ongoing debate.

Here we reveal the connection between the distinct circuit architecture of this gate and its special dynamics and noise management characteristics. Our starting point is the realization that the gate has intriguing dynamics since AbrB forms, together with Spo0A* and Spo0E, a special repressilator-like motif24. This leads to new operational principles: 1. “Inhibition of inhibition” – inhibition of the gate by Spo0A* and inhibition of ComK by the gate. 2. “Window of opportunity” with oscillating dynamics that generates a chain of short intervals with high probability of transition into competence – a chain of opportunities. We propose that the “inhibition of inhibition” and the “chain of opportunities” are essential principles for collective decision-making in general.

Global view of the decision-making system: Considerable research effort has been devoted to untangling the components of the genetic decision–making system which allows an individual cell to decide whether to wait, go through a competence cycle or commit to sporulation. It is now understood that the decision follows an elaborate assessment of its individual stress level, the colony density, stress signals from other cells and a memory of previously encountered stress and colony state. Years of intensive experimental studies identified the tens of key regulatory genes and measured several of the associated physiological parameters that are involved in the sporulation-competence decision process of the domesticated B. subtilis 168. More recently, these findings led to the development of tractable quantitative model of some of the elements (or module circuits) of this highly interconnected genetic network shown in Figure 1.

Figure 1 Global presentation of the sporulation/competence decision system. (A) Representation of the complete network. The sporulation module is shown on the left (red) and the competence module is shown on the right (orange). The other modules process and transmit information between these two modules, coordinating the decision between sporulation and competence. (B) Representation of the module composed by Spo0E, AbrB and Rok as the decision gate, processing information from the sporulation module and gating the competence module. Full size image

In this approach the operation of the competence module is modeled as a stochastic switch whose transition rate is controlled by a quorum sensing unit and the operation of the sporulation module as an adaptable timer whose clock rate is adjusted by stress signals and signals sent from other cells. More specifically, Spo0A* accumulation is determined by a cascade of kinases transferring phosphate to the sporulation master regulator Spo0A25,26,27,28,29. Phosphate is transferred down the relay, leading to the accumulation of Spo0A*. The outcome is that the clock rate of the sporulation timer is adjusted by the cell stress. Spo0A* acts as a transcriptional activator of both Spo0A and Spo0F via the sigma factor σH.

The competence stochastic switch consists of a self-activator master regulator ComK and a degradation complex MecA/ClpP/ClpC which continuously acts to keep ComK at low levels30,31. This degradation is regulated by competitive binding of peptide ComS. It has been proposed that the ComK-ComS-MecA circuit can act as an excitable system, a bi-stable system or both, depending on parameters3,4,6,7,32. The transition probability is regulated by the cell density in response to the level of quorum sensing pheromone ComX33 which activates the production of ComS via the competence and the ComP-ComA two component quorum sensing system.

The interplay between the timer and stochastic switch master modules is regulated by the operation of the Rap communication module and the AbrB-Rok decision gate. The Rap module34,35 acts as the central cell-cell communication and information possessing system of the decision-making network. Generally speaking, Rap decreases the clock rate of the sporulation timer and increases the waiting time of the competence switch by dephosphorylation of Spo0F* and inactivation of ComA, respectively. The module is up-regulated by the quorum sensing signal (via ComA) and down-regulated by the external peptide pheromones secreted by the neighboring cells and the cell itself. Rap is also regulated by Spo0A* which enhances the production of some of the pheromones (e.g. PhrC) via σH. More recently, it was discovered that the Rap system provides the means to prevent sporulation during competence. ComK activates RapH, which dephosphorylate phosphorelay component Spo0F35.

The AbrB-Rok gate, described in greater details in the next section, acts as an inhibitory gate (repressor) of ComK, which blocks competence transitions, unless high levels of Spo0A* make the levels of both AbrB and Rok sufficiently low, as detailed further below.

The AbrB-Rok decision gate: Previously, Schultz et al14 proposed that the combined task of the AbrB-Rok module is gating the competence transitions to be allowed only between two values of Spo0A* - the “window of opportunity”. AbrB is repressed by the sporulation master regulator Spo0A* and also by itself, in a negative feedback loop that prevents overexpression. Due to the instability of the protein, AbrB concentration responds quickly to transcriptional repression, dropping its levels quickly in the presence of Spo0A*. Lower AbrB concentrations allow increase in the expression of Spo0E, a phosphatase that acts directly on Spo0A*, slowing down its accumulation.

The Spo0A-AbrB-Spo0E part of the decision gate regulates the clock rate of the sporulation timer (the rate of accumulation of Spo0A*). Since Spo0A* is dephosphorylated by Spo0E which is inhibited by AbrB which is inhibited by Spo0A*, these three genes form a special repressilator circuit24. Hence, the clock rate is regulated via a special repressilator-like dynamic. For some input signals, this repressilator can cause the concentration of the components of the decision module to oscillate. The oscillations of the protein levels lead to short intervals with elevated probability of transition into competence (“chain of opportunities”) when the levels of both AbrB and Rock are below some threshold.

The repressilator is a well studied network motif consisting of three genes that repress each other in sequence and in a loop - A represses B, B represses C, C represses A (ABC for short). This circuit, when implemented experimentally in a cell, showed oscillatory behavior. The Spo0A*-AbrB-Spo0E (ABE for short) circuit is a variant of the classical repressilator, where one of the repressions (Spo0E- Spo0A*) is mediated via dephosphorylation, rather than a transcriptional repression and two of the components show regulatory feedback loops, one negative (AbrB represses its own transcription) and one positive (Spo0A* activates its own transcription indirectly through σH transcription activation of Spo0A). In addition, unlike the classical repressilator, the circuit studied here is driven by an input signal: the rate of phosphorylation of Spo0A that is determined by the stress level. As we show in the next sections, the outcome of this driven repressilator is not only directly responsible for entrance into sporulation, but it also intermediates the sporulation pathway and the competence pathway by translating oscillations in the driven repressilator into windows of opportunity.