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Computational studies of gene regulatory networks: in numero molecular biology

Key Points

  • Post-genomic research will involve analysing the dynamics of gene regulation.

  • Recent advances are making it possible to link experimental investigations with detailed mathematical models.

  • Modelling can be carried out at various levels of detail; the choice depends on the nature of the question to be addressed.

  • Several general results have been derived for classes of regulatory networks, using abstract models not directly linked to any particular experiment.

  • Various natural systems have been modelled, with the aim of better articulating how the underlying dynamics of transcriptional regulation contribute to observed cellular behaviour. The number of studies in which there is a tight connection between modelling and experiment is relatively small.

  • Recently, several synthetic gene regulatory networks have been implemented in living cells:

  • a 'toggle switch' that can be set in one of two states, remaining in a given state once flipped;

  • an oscillator in which the levels of expression of three interacting gene products vary periodically;

  • a tailor-made promoter used to test the hypothesis that negative feedback increases stability in regulatory networks.

  • oTight coupling between modelling and experiment is becoming increasingly accessible, offering the exciting prospect of gaining a detailed understanding of the basic mechanisms at work in controlling the level of expression of gene products. Such an understanding would be of fundamental importance in controlling cellular behaviour for medical or biotechnological purposes.

Abstract

Remarkable progress in genomic research is leading to a complete map of the building blocks of biology. Knowledge of this map is, in turn, setting the stage for a fundamental description of cellular function at the DNA level. Such a description will entail an understanding of gene regulation, in which proteins often regulate their own production or that of other proteins in a complex web of interactions. The implications of the underlying logic of genetic networks are difficult to deduce through experimental techniques alone, and successful approaches will probably involve the union of new experiments and computational modelling techniques.

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Figure 1: Regulatory diagram for the activation of the tumour-suppressor protein p53.
Figure 2: Modelling the λ-bacteriophage circuitry.
Figure 3: Schematic diagrams of three negatively regulated synthetic gene networks.
Figure 4: Graphical interpretation of the toggle switch equations and illustration of the dynamic behaviour of the co-repressive network.
Figure 5: Parameter-space plots and experimental results of the repressilator.
Figure 6: Theoretical predictions and experimental results of an autorepressive gene network.
Figure 7: A synthetic system based on the λ-switch.

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Acknowledgements

This work is supported by The Fetzer Institute (J.H.) and the Office of Naval Research.

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p53

RecA

SsrA

RcsA

FURTHER INFORMATION

Modelling work on eukaryotic cell cycle control

Adam Arkin's home page

Chaos special Focus Issue “Molecular, Metabolic, and Genetic Control” in March

Jeff Hasty's home page

James Collins' home page

James Collins' lab

ENCYCLOPEDIA OF LIFE SCIENCES

Genetic networks

Bacteriophage λ and its relatives

Glossary

NONLINEAR DYNAMICS

In a system governed by nonlinear dynamics, the rate of change of any variable cannot be written as a linear function of the other variables. Most real systems are nonlinear and show interesting behaviours not seen in linear systems (for example, only nonlinear systems can be multistable).

STOCHASTIC

Probabilistic; governed by chance.

FIXED POINT

A point at which the rates of change of all variables in a system are exactly zero. A system precisely at its fixed point (or steady state) will remain there permanently. Small perturbations to a system that is initially poised at a 'stable' fixed point will be accompanied by a return to the stable fixed point.

MULTISTABILITY

The property of having more than one stable fixed point.

OPERATOR

A prokaryotic DNA regulatory element that interacts with a repressor to control the transcription of adjacent genes.

NEGATIVE FEEDBACK

A component of a system is subject to negative feedback when it inhibits its own level of activity. For example, a gene product that acts as a repressor for its own gene is applying negative feedback.

POSITIVE FEEDBACK

A component of a system is subject to positive feedback when it increases its own level of activity. For example, a gene product that activates the expression of its own gene is subject to positive feedback.

COOPERATIVITY

Interaction between binding sites in which the binding of one molecule modifies the ability of a subsequent molecule of the same type to bind to its binding site.

BISTABILITY

The property of having two stable fixed points. See also the definition for multistability.

OPERON

A genetic unit or cluster that consists of one or more genes that are transcribed as a unit and are expressed in a coordinated manner.

PARAMETER SPACE

The set of all possible values of all parameters.

GFP GENE

A gene encoding the green fluorescent protein (GFP). GFP can be transcribed in tandem with another gene of interest, so that one GFP molecule is produced for each molecule of the target protein. The fluorescence level in a cell then provides an indication of the concentration of the protein of interest.

POLYCISTRONIC

A form of gene organization that results in transcription of an mRNA that codes for multiple gene products, each of which is independently translated from the mRNA.

SMALL STABLE RNA TAG

(SsrA). A short peptide tag that is added to the carboxy-terminal end of the incomplete protein product of a stalled ribosome. This trans-translation process, which is catalysed by a small stable RNA (also known as tmRNA (tRNA-like and mRNA-like)), targets the abnormal proteins for proteolysis.

SEPTATION PERIOD

The time that it takes a bacterium to divide.

AUTOREGULATION

The property of a system whereby a component of the system controls its own activity. See also the definitions for positive feedback and negative feedback.

HYSTERESIS

As a parameter that represents some property of a system is increased, the behaviour makes a sudden jump at a particular value of the parameter. But, as the parameter is then decreased, the jump back to the original behaviour does not occur until a much lower value. In the region between the two jumps, the system is bistable.

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Hasty, J., McMillen, D., Isaacs, F. et al. Computational studies of gene regulatory networks: in numero molecular biology. Nat Rev Genet 2, 268–279 (2001). https://doi.org/10.1038/35066056

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