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The physics of bacterial decision making.

Ben-Jacob E, Lu M, Schultz D, Onuchic JN - Front Cell Infect Microbiol (2014)

Bottom Line: In addition, the unique architecture of the gate allows filtering of external noise and robustness against variations in circuit parameters and internal noise.We illustrate that a physics approach can be very valuable in investigating the decision process and in identifying its general principles.We also show that both cell-cell variability and noise have important functional roles in the collectively controlled individual decisions.

View Article: PubMed Central - PubMed

Affiliation: Center for Theoretical Biological Physics, Rice University Houston, TX, USA ; Department of Biosciences, Rice University Houston, TX, USA ; School of Physics and Astronomy and The Sagol School of Neuroscience, Tel-Aviv University Tel-Aviv, Israel.

ABSTRACT
The choice that bacteria make between sporulation and competence when subjected to stress provides a prototypical example of collective cell fate determination that is stochastic on the individual cell level, yet predictable (deterministic) on the population level. This collective decision is performed by an elaborated gene network. Considerable effort has been devoted to simplify its complexity by taking physics approaches to untangle the basic functional modules that are integrated to form the complete network: (1) A stochastic switch whose transition probability is controlled by two order parameters-population density and internal/external stress. (2) An adaptable timer whose clock rate is normalized by the same two previous order parameters. (3) Sensing units which measure population density and external stress. (4) A communication module that exchanges information about the cells' internal stress levels. (5) An oscillating gate of the stochastic switch which is regulated by the timer. The unique circuit architecture of the gate allows special dynamics and noise management features. The gate opens a window of opportunity in time for competence transitions, during which the circuit generates oscillations that are translated into a chain of short intervals with high transition probability. In addition, the unique architecture of the gate allows filtering of external noise and robustness against variations in circuit parameters and internal noise. We illustrate that a physics approach can be very valuable in investigating the decision process and in identifying its general principles. We also show that both cell-cell variability and noise have important functional roles in the collectively controlled individual decisions.

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Global presentation of the sporulation/competence decision system. (A) Representation of the complete network. (B) Schematic representation showing the 5 modules that constitute the network. (C) This three-elements switch is comprised of: 1. a self-activator gene (ComK) whose value determines the transitions—the cell enters into competence above threshold level of ComK (this is why it is called competence master regulator). 2. A regulator gene (ComS) whose level is determined by input from the sensing and communication units. 3. A degrader complex (MecA) which degrades both the ComK protein and the ComS peptide in a competitive manner. The red parallel lines indicate regulation by degradation. (D) This two-element timer is comprised of: 1. the sporulation master regulator gene (Spo0A) which is self-activated by Spo0A* (the phosphorylated Spo0A) (Novák and Tyson, 2008; Kuchina, 2011). Once the level of Spo0A* exceeds a threshold value, the cell commits to sporulation (the sporulation process begins and cannot be reversed). This is why Spo0A is called the sporulation master regulator. In addition to Spo0A, the adaptable timer is comprised of a regulator Spo0B which regulates the clock rate—the rate of accumulation of Spo0A*—according to the rate its protein is phosphorylated by input from the stress sensing unit and the communication unit. When the level of Spo0B* is decreased (the stress is lifted), Spo0A* can phosphorylate Spo0B. This process leads to decrease in the level of Spo0A* meaning reversing the timer. (E) This three-element gate allows transition into competence only within a “window of opportunity” between two values of Spo0A*. The special architecture of the circuit leads to generation of oscillatory behavior within the window of opportunity. As is shown in details further below (see Section The Decision Gate), within each oscillation the gate opens for a short time during which the inhibition of the stochastic switch is lifted.
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Figure 4: Global presentation of the sporulation/competence decision system. (A) Representation of the complete network. (B) Schematic representation showing the 5 modules that constitute the network. (C) This three-elements switch is comprised of: 1. a self-activator gene (ComK) whose value determines the transitions—the cell enters into competence above threshold level of ComK (this is why it is called competence master regulator). 2. A regulator gene (ComS) whose level is determined by input from the sensing and communication units. 3. A degrader complex (MecA) which degrades both the ComK protein and the ComS peptide in a competitive manner. The red parallel lines indicate regulation by degradation. (D) This two-element timer is comprised of: 1. the sporulation master regulator gene (Spo0A) which is self-activated by Spo0A* (the phosphorylated Spo0A) (Novák and Tyson, 2008; Kuchina, 2011). Once the level of Spo0A* exceeds a threshold value, the cell commits to sporulation (the sporulation process begins and cannot be reversed). This is why Spo0A is called the sporulation master regulator. In addition to Spo0A, the adaptable timer is comprised of a regulator Spo0B which regulates the clock rate—the rate of accumulation of Spo0A*—according to the rate its protein is phosphorylated by input from the stress sensing unit and the communication unit. When the level of Spo0B* is decreased (the stress is lifted), Spo0A* can phosphorylate Spo0B. This process leads to decrease in the level of Spo0A* meaning reversing the timer. (E) This three-element gate allows transition into competence only within a “window of opportunity” between two values of Spo0A*. The special architecture of the circuit leads to generation of oscillatory behavior within the window of opportunity. As is shown in details further below (see Section The Decision Gate), within each oscillation the gate opens for a short time during which the inhibition of the stochastic switch is lifted.

Mentions: Years of intensive experimental studies identified the tens of key regulatory genes and measured the associated physiological parameters that are involved in the sporulation-competence decision process of domesticated B. subtilis. Considerable effort has been devoted to simplify the complexity of this elaborated network (Figure 4A) by untangling the basic functional modules that are integrated to form the complete network (Schultz et al., 2009, 2013). It is now realized that the key modules are (Figure 4B): (1) a stochastic switch whose transition probability is normalized by signals from other cells; (2) an adaptable timer whose clock rate is normalized by the cell stress and signals from other cells; (3) two sensing units; (4) a communication module; (5) an oscillating gate of the stochastic switch which is regulated by the timer.


The physics of bacterial decision making.

Ben-Jacob E, Lu M, Schultz D, Onuchic JN - Front Cell Infect Microbiol (2014)

Global presentation of the sporulation/competence decision system. (A) Representation of the complete network. (B) Schematic representation showing the 5 modules that constitute the network. (C) This three-elements switch is comprised of: 1. a self-activator gene (ComK) whose value determines the transitions—the cell enters into competence above threshold level of ComK (this is why it is called competence master regulator). 2. A regulator gene (ComS) whose level is determined by input from the sensing and communication units. 3. A degrader complex (MecA) which degrades both the ComK protein and the ComS peptide in a competitive manner. The red parallel lines indicate regulation by degradation. (D) This two-element timer is comprised of: 1. the sporulation master regulator gene (Spo0A) which is self-activated by Spo0A* (the phosphorylated Spo0A) (Novák and Tyson, 2008; Kuchina, 2011). Once the level of Spo0A* exceeds a threshold value, the cell commits to sporulation (the sporulation process begins and cannot be reversed). This is why Spo0A is called the sporulation master regulator. In addition to Spo0A, the adaptable timer is comprised of a regulator Spo0B which regulates the clock rate—the rate of accumulation of Spo0A*—according to the rate its protein is phosphorylated by input from the stress sensing unit and the communication unit. When the level of Spo0B* is decreased (the stress is lifted), Spo0A* can phosphorylate Spo0B. This process leads to decrease in the level of Spo0A* meaning reversing the timer. (E) This three-element gate allows transition into competence only within a “window of opportunity” between two values of Spo0A*. The special architecture of the circuit leads to generation of oscillatory behavior within the window of opportunity. As is shown in details further below (see Section The Decision Gate), within each oscillation the gate opens for a short time during which the inhibition of the stochastic switch is lifted.
© Copyright Policy - open-access
Related In: Results  -  Collection

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Show All Figures
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Figure 4: Global presentation of the sporulation/competence decision system. (A) Representation of the complete network. (B) Schematic representation showing the 5 modules that constitute the network. (C) This three-elements switch is comprised of: 1. a self-activator gene (ComK) whose value determines the transitions—the cell enters into competence above threshold level of ComK (this is why it is called competence master regulator). 2. A regulator gene (ComS) whose level is determined by input from the sensing and communication units. 3. A degrader complex (MecA) which degrades both the ComK protein and the ComS peptide in a competitive manner. The red parallel lines indicate regulation by degradation. (D) This two-element timer is comprised of: 1. the sporulation master regulator gene (Spo0A) which is self-activated by Spo0A* (the phosphorylated Spo0A) (Novák and Tyson, 2008; Kuchina, 2011). Once the level of Spo0A* exceeds a threshold value, the cell commits to sporulation (the sporulation process begins and cannot be reversed). This is why Spo0A is called the sporulation master regulator. In addition to Spo0A, the adaptable timer is comprised of a regulator Spo0B which regulates the clock rate—the rate of accumulation of Spo0A*—according to the rate its protein is phosphorylated by input from the stress sensing unit and the communication unit. When the level of Spo0B* is decreased (the stress is lifted), Spo0A* can phosphorylate Spo0B. This process leads to decrease in the level of Spo0A* meaning reversing the timer. (E) This three-element gate allows transition into competence only within a “window of opportunity” between two values of Spo0A*. The special architecture of the circuit leads to generation of oscillatory behavior within the window of opportunity. As is shown in details further below (see Section The Decision Gate), within each oscillation the gate opens for a short time during which the inhibition of the stochastic switch is lifted.
Mentions: Years of intensive experimental studies identified the tens of key regulatory genes and measured the associated physiological parameters that are involved in the sporulation-competence decision process of domesticated B. subtilis. Considerable effort has been devoted to simplify the complexity of this elaborated network (Figure 4A) by untangling the basic functional modules that are integrated to form the complete network (Schultz et al., 2009, 2013). It is now realized that the key modules are (Figure 4B): (1) a stochastic switch whose transition probability is normalized by signals from other cells; (2) an adaptable timer whose clock rate is normalized by the cell stress and signals from other cells; (3) two sensing units; (4) a communication module; (5) an oscillating gate of the stochastic switch which is regulated by the timer.

Bottom Line: In addition, the unique architecture of the gate allows filtering of external noise and robustness against variations in circuit parameters and internal noise.We illustrate that a physics approach can be very valuable in investigating the decision process and in identifying its general principles.We also show that both cell-cell variability and noise have important functional roles in the collectively controlled individual decisions.

View Article: PubMed Central - PubMed

Affiliation: Center for Theoretical Biological Physics, Rice University Houston, TX, USA ; Department of Biosciences, Rice University Houston, TX, USA ; School of Physics and Astronomy and The Sagol School of Neuroscience, Tel-Aviv University Tel-Aviv, Israel.

ABSTRACT
The choice that bacteria make between sporulation and competence when subjected to stress provides a prototypical example of collective cell fate determination that is stochastic on the individual cell level, yet predictable (deterministic) on the population level. This collective decision is performed by an elaborated gene network. Considerable effort has been devoted to simplify its complexity by taking physics approaches to untangle the basic functional modules that are integrated to form the complete network: (1) A stochastic switch whose transition probability is controlled by two order parameters-population density and internal/external stress. (2) An adaptable timer whose clock rate is normalized by the same two previous order parameters. (3) Sensing units which measure population density and external stress. (4) A communication module that exchanges information about the cells' internal stress levels. (5) An oscillating gate of the stochastic switch which is regulated by the timer. The unique circuit architecture of the gate allows special dynamics and noise management features. The gate opens a window of opportunity in time for competence transitions, during which the circuit generates oscillations that are translated into a chain of short intervals with high transition probability. In addition, the unique architecture of the gate allows filtering of external noise and robustness against variations in circuit parameters and internal noise. We illustrate that a physics approach can be very valuable in investigating the decision process and in identifying its general principles. We also show that both cell-cell variability and noise have important functional roles in the collectively controlled individual decisions.

Show MeSH