Bistability

Last updated

A graph of the potential energy of a bistable system; it has two local minima
x
1
{\displaystyle x_{1}}
and
x
2
{\displaystyle x_{2}}
. A surface shaped like this with two "low points" can act as a bistable system; a ball resting on the surface can only be stable at those two positions, such as balls marked "1" and "2". Between the two is a local maximum
x
3
{\displaystyle x_{3}}
. A ball located at this point, ball 3, is in equilibrium but unstable; the slightest disturbance will cause it to move to one of the stable points. Bistability graph.svg
A graph of the potential energy of a bistable system; it has two local minima and . A surface shaped like this with two "low points" can act as a bistable system; a ball resting on the surface can only be stable at those two positions, such as balls marked "1" and "2". Between the two is a local maximum . A ball located at this point, ball 3, is in equilibrium but unstable; the slightest disturbance will cause it to move to one of the stable points.

In a dynamical system, bistability means the system has two stable equilibrium states. [1] A bistable structure can be resting in either of two states. An example of a mechanical device which is bistable is a light switch. The switch lever is designed to rest in the "on" or "off" position, but not between the two. Bistable behavior can occur in mechanical linkages, electronic circuits, nonlinear optical systems, chemical reactions, and physiological and biological systems.

Contents

In a conservative force field, bistability stems from the fact that the potential energy has two local minima, which are the stable equilibrium points. [2] These rest states need not have equal potential energy. By mathematical arguments, a local maximum, an unstable equilibrium point, must lie between the two minima. At rest, a particle will be in one of the minimum equilibrium positions, because that corresponds to the state of lowest energy. The maximum can be visualized as a barrier between them.

A system can transition from one state of minimal energy to the other if it is given enough activation energy to penetrate the barrier (compare activation energy and Arrhenius equation for the chemical case). After the barrier has been reached, assuming the system has damping, it will relax into the other minimum state in a time called the relaxation time.

Bistability is widely used in digital electronics devices to store binary data. It is the essential characteristic of the flip-flop, a circuit which is a fundamental building block of computers and some types of semiconductor memory. A bistable device can store one bit of binary data, with one state representing a "0" and the other state a "1". It is also used in relaxation oscillators, multivibrators, and the Schmitt trigger. Optical bistability is an attribute of certain optical devices where two resonant transmissions states are possible and stable, dependent on the input. Bistability can also arise in biochemical systems, where it creates digital, switch-like outputs from the constituent chemical concentrations and activities. It is often associated with hysteresis in such systems.

Mathematical modelling

In the mathematical language of dynamic systems analysis, one of the simplest bistable systems is[ citation needed ]

This system describes a ball rolling down a curve with shape , and has three equilibrium points: , , and . The middle point is marginally stable ( is stable but will not converge to ), while the other two points are stable. The direction of change of over time depends on the initial condition . If the initial condition is positive (), then the solution approaches 1 over time, but if the initial condition is negative (), then approaches −1 over time. Thus, the dynamics are "bistable". The final state of the system can be either or , depending on the initial conditions. [3]

The appearance of a bistable region can be understood for the model system which undergoes a supercritical pitchfork bifurcation with bifurcation parameter .

In biological and chemical systems

Three-dimensional invariant measure for cellular-differentiation featuring a two-stable mode. The axes denote cell counts for three types of cells: progenitor (
z
{\displaystyle z}
), osteoblast (
y
{\displaystyle y}
), and chondrocyte (
x
{\displaystyle x}
). Pro-osteoblast stimulus promotes P-O transition. Stimuli.pdf
Three-dimensional invariant measure for cellular-differentiation featuring a two-stable mode. The axes denote cell counts for three types of cells: progenitor (), osteoblast (), and chondrocyte (). Pro-osteoblast stimulus promotes P→O transition.

Bistability is key for understanding basic phenomena of cellular functioning, such as decision-making processes in cell cycle progression, cellular differentiation, [5] and apoptosis. It is also involved in loss of cellular homeostasis associated with early events in cancer onset and in prion diseases as well as in the origin of new species (speciation). [6]

Bistability can be generated by a positive feedback loop with an ultrasensitive regulatory step. Positive feedback loops, such as the simple X activates Y and Y activates X motif, essentially link output signals to their input signals and have been noted to be an important regulatory motif in cellular signal transduction because positive feedback loops can create switches with an all-or-nothing decision. [7] Studies have shown that numerous biological systems, such as Xenopus oocyte maturation, [8] mammalian calcium signal transduction, and polarity in budding yeast, incorporate multiple positive feedback loops with different time scales (slow and fast). [7] Having multiple linked positive feedback loops with different time scales ("dual-time switches") allows for (a) increased regulation: two switches that have independent changeable activation and deactivation times; and (b) noise filtering. [7]

Bistability can also arise in a biochemical system only for a particular range of parameter values, where the parameter can often be interpreted as the strength of the feedback. In several typical examples, the system has only one stable fixed point at low values of the parameter. A saddle-node bifurcation gives rise to a pair of new fixed points emerging, one stable and the other unstable, at a critical value of the parameter. The unstable solution can then form another saddle-node bifurcation with the initial stable solution at a higher value of the parameter, leaving only the higher fixed solution. Thus, at values of the parameter between the two critical values, the system has two stable solutions. An example of a dynamical system that demonstrates similar features is

where is the output, and is the parameter, acting as the input. [9]

Bistability can be modified to be more robust and to tolerate significant changes in concentrations of reactants, while still maintaining its "switch-like" character. Feedback on both the activator of a system and inhibitor make the system able to tolerate a wide range of concentrations. An example of this in cell biology is that activated CDK1 (Cyclin Dependent Kinase 1) activates its activator Cdc25 while at the same time inactivating its inactivator, Wee1, thus allowing for progression of a cell into mitosis. Without this double feedback, the system would still be bistable, but would not be able to tolerate such a wide range of concentrations. [10]

Bistability has also been described in the embryonic development of Drosophila melanogaster (the fruit fly). Examples are anterior-posterior [11] and dorso-ventral [12] [13] axis formation and eye development. [14]

A prime example of bistability in biological systems is that of Sonic hedgehog (Shh), a secreted signaling molecule, which plays a critical role in development. Shh functions in diverse processes in development, including patterning limb bud tissue differentiation. The Shh signaling network behaves as a bistable switch, allowing the cell to abruptly switch states at precise Shh concentrations. gli1 and gli2 transcription is activated by Shh, and their gene products act as transcriptional activators for their own expression and for targets downstream of Shh signaling. [15] Simultaneously, the Shh signaling network is controlled by a negative feedback loop wherein the Gli transcription factors activate the enhanced transcription of a repressor (Ptc). This signaling network illustrates the simultaneous positive and negative feedback loops whose exquisite sensitivity helps create a bistable switch.

Bistability can only arise in biological and chemical systems if three necessary conditions are fulfilled: positive feedback, a mechanism to filter out small stimuli and a mechanism to prevent increase without bound. [6]

Bistable chemical systems have been studied extensively to analyze relaxation kinetics, non-equilibrium thermodynamics, stochastic resonance, as well as climate change. [6] In bistable spatially extended systems the onset of local correlations and propagation of traveling waves have been analyzed. [16] [17]

Bistability is often accompanied by hysteresis. On a population level, if many realisations of a bistable system are considered (e.g. many bistable cells (speciation) [18] ), one typically observes bimodal distributions. In an ensemble average over the population, the result may simply look like a smooth transition, thus showing the value of single-cell resolution.

A specific type of instability is known as modehopping, which is bi-stability in the frequency space. Here trajectories can shoot between two stable limit cycles, and thus show similar characteristics as normal bi-stability when measured inside a Poincare section.

In mechanical systems

A ratchet in action. Each tooth in the ratchet together with the regions to either side of it constitutes a simple bistable mechanism. Ratchet example.gif
A ratchet in action. Each tooth in the ratchet together with the regions to either side of it constitutes a simple bistable mechanism.

Bistability as applied in the design of mechanical systems is more commonly said to be "over centre"—that is, work is done on the system to move it just past the peak, at which point the mechanism goes "over centre" to its secondary stable position. The result is a toggle-type action- work applied to the system below a threshold sufficient to send it 'over center' results in no change to the mechanism's state.

Springs are a common method of achieving an "over centre" action. A spring attached to a simple two position ratchet-type mechanism can create a button or plunger that is clicked or toggled between two mechanical states. Many ballpoint and rollerball retractable pens employ this type of bistable mechanism.

An even more common example of an over-center device is an ordinary electric wall switch. These switches are often designed to snap firmly into the "on" or "off" position once the toggle handle has been moved a certain distance past the center-point.

A ratchet-and-pawl is an elaboration—a multi-stable "over center" system used to create irreversible motion. The pawl goes over center as it is turned in the forward direction. In this case, "over center" refers to the ratchet being stable and "locked" in a given position until clicked forward again; it has nothing to do with the ratchet being unable to turn in the reverse direction.

See also

Related Research Articles

<span class="mw-page-title-main">Hysteresis</span> Dependence of the state of a system on its history

Hysteresis is the dependence of the state of a system on its history. For example, a magnet may have more than one possible magnetic moment in a given magnetic field, depending on how the field changed in the past. Plots of a single component of the moment often form a loop or hysteresis curve, where there are different values of one variable depending on the direction of change of another variable. This history dependence is the basis of memory in a hard disk drive and the remanence that retains a record of the Earth's magnetic field magnitude in the past. Hysteresis occurs in ferromagnetic and ferroelectric materials, as well as in the deformation of rubber bands and shape-memory alloys and many other natural phenomena. In natural systems, it is often associated with irreversible thermodynamic change such as phase transitions and with internal friction; and dissipation is a common side effect.

<span class="mw-page-title-main">Relaxation oscillator</span> Oscillator that produces a nonsinusoidal repetitive waveform

In electronics a relaxation oscillator is a nonlinear electronic oscillator circuit that produces a nonsinusoidal repetitive output signal, such as a triangle wave or square wave. The circuit consists of a feedback loop containing a switching device such as a transistor, comparator, relay, op amp, or a negative resistance device like a tunnel diode, that repetitively charges a capacitor or inductor through a resistance until it reaches a threshold level, then discharges it again. The period of the oscillator depends on the time constant of the capacitor or inductor circuit. The active device switches abruptly between charging and discharging modes, and thus produces a discontinuously changing repetitive waveform. This contrasts with the other type of electronic oscillator, the harmonic or linear oscillator, which uses an amplifier with feedback to excite resonant oscillations in a resonator, producing a sine wave.

<span class="mw-page-title-main">Positive feedback</span> Feedback loop that increases an initial small effect

Positive feedback is a process that occurs in a feedback loop which exacerbates the effects of a small disturbance. That is, the effects of a perturbation on a system include an increase in the magnitude of the perturbation. That is, A produces more of B which in turn produces more of A. In contrast, a system in which the results of a change act to reduce or counteract it has negative feedback. Both concepts play an important role in science and engineering, including biology, chemistry, and cybernetics.

<span class="mw-page-title-main">Gene regulatory network</span> Collection of molecular regulators

A generegulatory network (GRN) is a collection of molecular regulators that interact with each other and with other substances in the cell to govern the gene expression levels of mRNA and proteins which, in turn, determine the function of the cell. GRN also play a central role in morphogenesis, the creation of body structures, which in turn is central to evolutionary developmental biology (evo-devo).

<span class="mw-page-title-main">Schmitt trigger</span> Electronic comparator circuit with hysteresis

In electronics, a Schmitt trigger is a comparator circuit with hysteresis implemented by applying positive feedback to the noninverting input of a comparator or differential amplifier. It is an active circuit which converts an analog input signal to a digital output signal. The circuit is named a trigger because the output retains its value until the input changes sufficiently to trigger a change. In the non-inverting configuration, when the input is higher than a chosen threshold, the output is high. When the input is below a different (lower) chosen threshold the output is low, and when the input is between the two levels the output retains its value. This dual threshold action is called hysteresis and implies that the Schmitt trigger possesses memory and can act as a bistable multivibrator. There is a close relation between the two kinds of circuits: a Schmitt trigger can be converted into a latch and a latch can be converted into a Schmitt trigger.

In mathematics, catastrophe theory is a branch of bifurcation theory in the study of dynamical systems; it is also a particular special case of more general singularity theory in geometry.

G<sub>2</sub> phase Second growth phase in the eukaryotic cell cycle, prior to mitosis

G2 phase, Gap 2 phase, or Growth 2 phase, is the third subphase of interphase in the cell cycle directly preceding mitosis. It follows the successful completion of S phase, during which the cell’s DNA is replicated. G2 phase ends with the onset of prophase, the first phase of mitosis in which the cell’s chromatin condenses into chromosomes.

<span class="mw-page-title-main">Bifurcation theory</span> Study of sudden qualitative behavior changes caused by small parameter changes

Bifurcation theory is the mathematical study of changes in the qualitative or topological structure of a given family of curves, such as the integral curves of a family of vector fields, and the solutions of a family of differential equations. Most commonly applied to the mathematical study of dynamical systems, a bifurcation occurs when a small smooth change made to the parameter values of a system causes a sudden 'qualitative' or topological change in its behavior. Bifurcations occur in both continuous systems and discrete systems.

In the mathematical area of bifurcation theory a saddle-node bifurcation, tangential bifurcation or fold bifurcation is a local bifurcation in which two fixed points of a dynamical system collide and annihilate each other. The term 'saddle-node bifurcation' is most often used in reference to continuous dynamical systems. In discrete dynamical systems, the same bifurcation is often instead called a fold bifurcation. Another name is blue sky bifurcation in reference to the sudden creation of two fixed points.

<span class="mw-page-title-main">Hopf bifurcation</span> Critical point where a periodic solution arises

In the mathematical theory of bifurcations, a Hopfbifurcation is a critical point where, as a parameter changes, a system's stability switches and a periodic solution arises. More accurately, it is a local bifurcation in which a fixed point of a dynamical system loses stability, as a pair of complex conjugate eigenvalues—of the linearization around the fixed point—crosses the complex plane imaginary axis as a parameter crosses a threshold value. Under reasonably generic assumptions about the dynamical system, the fixed point becomes a small-amplitude limit cycle as the parameter changes.

<span class="mw-page-title-main">Cell cycle checkpoint</span> Control mechanism in the eukaryotic cell cycle

Cell cycle checkpoints are control mechanisms in the eukaryotic cell cycle which ensure its proper progression. Each checkpoint serves as a potential termination point along the cell cycle, during which the conditions of the cell are assessed, with progression through the various phases of the cell cycle occurring only when favorable conditions are met. There are many checkpoints in the cell cycle, but the three major ones are: the G1 checkpoint, also known as the Start or restriction checkpoint or Major Checkpoint; the G2/M checkpoint; and the metaphase-to-anaphase transition, also known as the spindle checkpoint. Progression through these checkpoints is largely determined by the activation of cyclin-dependent kinases by regulatory protein subunits called cyclins, different forms of which are produced at each stage of the cell cycle to control the specific events that occur therein.

A series of biochemical switches control transitions between and within the various phases of the cell cycle. The cell cycle is a series of complex, ordered, sequential events that control how a single cell divides into two cells, and involves several different phases. The phases include the G1 and G2 phases, DNA replication or S phase, and the actual process of cell division, mitosis or M phase. During the M phase, the chromosomes separate and cytokinesis occurs.

<span class="mw-page-title-main">Ultrasensitivity</span>

In molecular biology, ultrasensitivity describes an output response that is more sensitive to stimulus change than the hyperbolic Michaelis-Menten response. Ultrasensitivity is one of the biochemical switches in the cell cycle and has been implicated in a number of important cellular events, including exiting G2 cell cycle arrests in Xenopus laevis oocytes, a stage to which the cell or organism would not want to return.

Within molecular and cell biology, Temporal feedback, also referred to as interlinked or interlocked feedback, is a biological regulatory motif in which fast and slow positive feedback loops are interlinked to create "all or none" switches. This interlinking produces separate, adjustable activation and de-activation times. This type of feedback is thought to be important in cellular processes in which an "all or none" decision is a necessary response to a specific input. The mitotic trigger, polarization in budding yeast, mammalian calcium signal transduction, EGF receptor signaling, platelet activation, and Xenopus oocyte maturation are examples for interlinked fast and slow multiple positive feedback systems.

Biological applications of bifurcation theory provide a framework for understanding the behavior of biological networks modeled as dynamical systems. In the context of a biological system, bifurcation theory describes how small changes in an input parameter can cause a bifurcation or qualitative change in the behavior of the system. The ability to make dramatic change in system output is often essential to organism function, and bifurcations are therefore ubiquitous in biological networks such as the switches of the cell cycle.

Mitotic exit is an important transition point that signifies the end of mitosis and the onset of new G1 phase for a cell, and the cell needs to rely on specific control mechanisms to ensure that once it exits mitosis, it never returns to mitosis until it has gone through G1, S, and G2 phases and passed all the necessary checkpoints. Many factors including cyclins, cyclin-dependent kinases (CDKs), ubiquitin ligases, inhibitors of cyclin-dependent kinases, and reversible phosphorylations regulate mitotic exit to ensure that cell cycle events occur in correct order with fewest errors. The end of mitosis is characterized by spindle breakdown, shortened kinetochore microtubules, and pronounced outgrowth of astral (non-kinetochore) microtubules. For a normal eukaryotic cell, mitotic exit is irreversible.

A comparator is an electronic component that compares two input voltages. Comparators are closely related to operational amplifiers, but a comparator is designed to operate with positive feedback and with its output saturated at one power rail or the other. If necessary, an op-amp can be pressed into service as a poorly performing comparator, but its slew Rate will be impaired.

<span class="mw-page-title-main">Thomas' cyclically symmetric attractor</span>

In the dynamical systems theory, Thomas' cyclically symmetric attractor is a 3D strange attractor originally proposed by René Thomas. It has a simple form which is cyclically symmetric in the x,y, and z variables and can be viewed as the trajectory of a frictionally dampened particle moving in a 3D lattice of forces. The simple form has made it a popular example.

<span class="mw-page-title-main">James Ferrell</span>

James Ellsworth Ferrell is an American systems biologist. He is a Professor of Chemical and Systems Biology and Biochemistry at Stanford University School of Medicine. He was Chair of the Dept. of Chemical and Systems Biology from its inception in 2006 until 2011.

The Novak–Tyson Model is a non-linear dynamics framework developed in the context of cell-cycle control by Bela Novak and John J. Tyson. It is a prevalent theoretical model that describes a hysteretic, bistable bifurcation of which many biological systems have been shown to express.

References

  1. Morris, Christopher G. (1992). Academic Press Dictionary of Science and Technology. Gulf Professional publishing. p. 267. ISBN   978-0122004001.
  2. Nazarov, Yuli V.; Danon, Jeroen (2013). Advanced Quantum Mechanics: A Practical Guide. Cambridge University Press. p. 291. ISBN   978-1139619028.
  3. Ket Hing Chong; Sandhya Samarasinghe; Don Kulasiri & Jie Zheng (2015). "Computational techniques in mathematical modelling of biological switches". Modsim2015: 578–584. For detailed techniques of mathematical modelling of bistability, see the tutorial by Chong et al. (2015) http://www.mssanz.org.au/modsim2015/C2/chong.pdf The tutorial provides a simple example illustration of bistability using a synthetic toggle switch proposed in Collins, James J.; Gardner, Timothy S.; Cantor, Charles R. (2000). "Construction of a genetic toggle switch in Escherichia coli". Nature. 403 (6767): 339–42. Bibcode:2000Natur.403..339G. doi:10.1038/35002131. PMID   10659857. S2CID   345059.. The tutorial also uses the dynamical system software XPPAUT http://www.math.pitt.edu/~bard/xpp/xpp.html to show practically how to see bistability captured by a saddle-node bifurcation diagram and the hysteresis behaviours when the bifurcation parameter is increased or decreased slowly over the tipping points and a protein gets turned 'On' or turned 'Off'.
  4. Kryven, I.; Röblitz, S.; Schütte, Ch. (2015). "Solution of the chemical master equation by radial basis functions approximation with interface tracking". BMC Systems Biology. 9 (1): 67. doi: 10.1186/s12918-015-0210-y . PMC   4599742 . PMID   26449665. Open Access logo PLoS transparent.svg
  5. Ghaffarizadeh A, Flann NS, Podgorski GJ (2014). "Multistable switches and their role in cellular differentiation networks". BMC Bioinformatics. 15 (Suppl 7): S7+. doi: 10.1186/1471-2105-15-s7-s7 . PMC   4110729 . PMID   25078021.
  6. 1 2 3 Wilhelm, T (2009). "The smallest chemical reaction system with bistability". BMC Systems Biology. 3: 90. doi: 10.1186/1752-0509-3-90 . PMC   2749052 . PMID   19737387.
  7. 1 2 3 O. Brandman, J. E. Ferrell Jr., R. Li, T. Meyer, Science 310, 496 (2005).
  8. Ferrell JE Jr.; Machleder EM (1998). "The biochemical basis of an all-or-none cell fate switch in Xenopus oocytes". Science. 280 (5365): 895–8. Bibcode:1998Sci...280..895F. doi:10.1126/science.280.5365.895. PMID   9572732. S2CID   34863795.
  9. Angeli, David; Ferrell, JE; Sontag, Eduardo D (2003). "Detection of multistability, bifurcations, and hysteresis in a large class of biological positive-feedback systems". PNAS. 101 (7): 1822–7. Bibcode:2004PNAS..101.1822A. doi: 10.1073/pnas.0308265100 . PMC   357011 . PMID   14766974.
  10. Ferrell JE Jr. (2008). "Feedback regulation of opposing enzymes generates robust, all-or-none bistable responses". Current Biology. 18 (6): R244–R245. doi:10.1016/j.cub.2008.02.035. PMC   2832910 . PMID   18364225.
  11. Lopes, Francisco J. P.; Vieira, Fernando M. C.; Holloway, David M.; Bisch, Paulo M.; Spirov, Alexander V.; Ohler, Uwe (26 September 2008). "Spatial Bistability Generates hunchback Expression Sharpness in the Drosophila Embryo". PLOS Computational Biology. 4 (9): e1000184. Bibcode:2008PLSCB...4E0184L. doi: 10.1371/journal.pcbi.1000184 . PMC   2527687 . PMID   18818726.
  12. Wang, Yu-Chiun; Ferguson, Edwin L. (10 March 2005). "Spatial bistability of Dpp–receptor interactions during Drosophila dorsal–ventral patterning". Nature. 434 (7030): 229–234. Bibcode:2005Natur.434..229W. doi:10.1038/nature03318. PMID   15759004. S2CID   4415152.
  13. Umulis, D. M.; Mihaela Serpe; Michael B. O’Connor; Hans G. Othmer (1 August 2006). "Robust, bistable patterning of the dorsal surface of the Drosophila embryo". Proceedings of the National Academy of Sciences. 103 (31): 11613–11618. Bibcode:2006PNAS..10311613U. doi: 10.1073/pnas.0510398103 . PMC   1544218 . PMID   16864795.
  14. Graham, T. G. W.; Tabei, S. M. A.; Dinner, A. R.; Rebay, I. (22 June 2010). "Modeling bistable cell-fate choices in the Drosophila eye: qualitative and quantitative perspectives". Development. 137 (14): 2265–2278. doi:10.1242/dev.044826. PMC   2889600 . PMID   20570936.
  15. Lai, K., M.J. Robertson, and D.V. Schaffer, The sonic hedgehog signaling system as a bistable genetic switch. Biophys J, 2004. 86(5): pp. 2748–57.
  16. Elf, J.; Ehrenberg, M. (2004). "Spontaneous separation of bi-stable biochemical systems into spatial domains of opposite phases". Systems Biology. 1 (2): 230–236. doi:10.1049/sb:20045021. PMID   17051695. S2CID   17770042.
  17. Kochanczyk, M.; Jaruszewicz, J.; Lipniacki, T. (July 2013). "Stochastic transitions in a bistable reaction system on the membrane". Journal of the Royal Society Interface. 10 (84): 20130151. doi:10.1098/rsif.2013.0151. PMC   3673150 . PMID   23635492.
  18. Nielsen; Dolganov, Nadia A.; Rasmussen, Thomas; Otto, Glen; Miller, Michael C.; Felt, Stephen A.; Torreilles, Stéphanie; Schoolnik, Gary K.; et al. (2010). Isberg, Ralph R. (ed.). "A Bistable Switch and Anatomical Site Control Vibrio cholerae Virulence Gene Expression in the Intestine". PLOS Pathogens. 6 (9): 1. doi: 10.1371/journal.ppat.1001102 . PMC   2940755 . PMID   20862321.
  19. "Snap bracelets from tape measures - Bistable structures | Experiments | Naked Scientists".