Construction of a genetic toggle switch in Escherichia coli
TL;DR: The construction of a genetic toggle switch is presented—a synthetic, bistable gene-regulatory network—in Escherichia coli and a simple theory is provided that predicts the conditions necessary for bistability.
Abstract: It has been proposed' that gene-regulatory circuits with virtually any desired property can be constructed from networks of simple regulatory elements. These properties, which include multistability and oscillations, have been found in specialized gene circuits such as the bacteriophage lambda switch and the Cyanobacteria circadian oscillator. However, these behaviours have not been demonstrated in networks of non-specialized regulatory components. Here we present the construction of a genetic toggle switch-a synthetic, bistable gene-regulatory network-in Escherichia coli and provide a simple theory that predicts the conditions necessary for bistability. The toggle is constructed from any two repressible promoters arranged in a mutually inhibitory network. It is flipped between stable states using transient chemical or thermal induction and exhibits a nearly ideal switching threshold. As a practical device, the toggle switch forms a synthetic, addressable cellular memory unit and has implications for biotechnology, biocomputing and gene therapy.
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TL;DR: In this paper, the authors present a systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life, and show that despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems.
Abstract: In a cell or microorganism, the processes that generate mass, energy, information transfer and cell-fate specification are seamlessly integrated through a complex network of cellular constituents and reactions. However, despite the key role of these networks in sustaining cellular functions, their large-scale structure is essentially unknown. Here we present a systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life. We show that, despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems. This may indicate that metabolic organization is not only identical for all living organisms, but also complies with the design principles of robust and error-tolerant scale-free networks, and may represent a common blueprint for the large-scale organization of interactions among all cellular constituents.
4,497 citations
01 Jan 2001
TL;DR: This analysis of metabolic networks of 43 organisms representing all three domains of life shows that, despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems.
4,357 citations
TL;DR: Network motifs are reviewed, suggesting that they serve as basic building blocks of transcription networks, including signalling and neuronal networks, in diverse organisms from bacteria to humans.
Abstract: Transcription regulation networks control the expression of genes. The transcription networks of well-studied microorganisms appear to be made up of a small set of recurring regulation patterns, called network motifs. The same network motifs have recently been found in diverse organisms from bacteria to humans, suggesting that they serve as basic building blocks of transcription networks. Here I review network motifs and their functions, with an emphasis on experimental studies. Network motifs in other biological networks are also mentioned, including signalling and neuronal networks.
3,076 citations
Cites background from "Construction of a genetic toggle sw..."
...7b ) is useful in this motif as a toggle switch between two different fate...
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TL;DR: This paper reviews formalisms that have been employed in mathematical biology and bioinformatics to describe genetic regulatory systems, in particular directed graphs, Bayesian networks, Boolean networks and their generalizations, ordinary and partial differential equations, qualitative differential equation, stochastic equations, and so on.
Abstract: The spatiotemporal expression of genes in an organism is determined by regulatory systems that involve a large number of genes connected through a complex network of interactions. As an intuitive understanding of the behavior of these systems is hard to obtain, computer tools for the modeling and simulation of genetic regulatory networks will be indispensable. This report reviews formalisms that have been employed in mathematical biology and bioinformatics to describe genetic regulatory systems, in particular directed graphs, Bayesian networks, ordinary and partial differential equations, stochastic equations, Boolean networks and their generalizations, qualitative differential equations, and rule-based formalisms. In addition, the report discusses how these formalisms have been used in the modeling and simulation of regulatory systems.
2,739 citations
TL;DR: Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others, including the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.
2,471 citations
Cites background from "Construction of a genetic toggle sw..."
...This bistable expression pattern has been observed in synthetic systems with positive feedback switches (Becskei et al., 2001; Gardner et al., 2000; Isaacs et al., 2003; Kramer and Fussenegger, 2005) and also in several...
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...This bistable expression pattern has been observed in synthetic systems with positive feedback switches (Becskei et al., 2001; Gardner et al., 2000; Isaacs et al., 2003; Kramer and Fussenegger, 2005) and also in several naturally occurring genetic positive feedback loops (Acar et al., 2005; Maamar…...
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15 Jan 2001
TL;DR: Molecular Cloning has served as the foundation of technical expertise in labs worldwide for 30 years as mentioned in this paper and has been so popular, or so influential, that no other manual has been more widely used and influential.
Abstract: Molecular Cloning has served as the foundation of technical expertise in labs worldwide for 30 years. No other manual has been so popular, or so influential. Molecular Cloning, Fourth Edition, by the celebrated founding author Joe Sambrook and new co-author, the distinguished HHMI investigator Michael Green, preserves the highly praised detail and clarity of previous editions and includes specific chapters and protocols commissioned for the book from expert practitioners at Yale, U Mass, Rockefeller University, Texas Tech, Cold Spring Harbor Laboratory, Washington University, and other leading institutions. The theoretical and historical underpinnings of techniques are prominent features of the presentation throughout, information that does much to help trouble-shoot experimental problems. For the fourth edition of this classic work, the content has been entirely recast to include nucleic-acid based methods selected as the most widely used and valuable in molecular and cellular biology laboratories. Core chapters from the third edition have been revised to feature current strategies and approaches to the preparation and cloning of nucleic acids, gene transfer, and expression analysis. They are augmented by 12 new chapters which show how DNA, RNA, and proteins should be prepared, evaluated, and manipulated, and how data generation and analysis can be handled. The new content includes methods for studying interactions between cellular components, such as microarrays, next-generation sequencing technologies, RNA interference, and epigenetic analysis using DNA methylation techniques and chromatin immunoprecipitation. To make sense of the wealth of data produced by these techniques, a bioinformatics chapter describes the use of analytical tools for comparing sequences of genes and proteins and identifying common expression patterns among sets of genes. Building on thirty years of trust, reliability, and authority, the fourth edition of Mol
215,169 citations
TL;DR: In this article, three classes of GFP mutants having single excitation maxima around 488 nm are shown to be brighter than wild-type GFP following 488-nm excitation.
3,093 citations
TL;DR: This work has analyzed the chemical reactions controlling transcript initiation and translation termination in a single such "genetically coupled" link as a precursor to modeling networks constructed from many such links.
Abstract: In cellular regulatory networks, genetic activity is controlled by molecular signals that determine when and how often a given gene is transcribed. In genetically controlled pathways, the protein product encoded by one gene often regulates expression of other genes. The time delay, after activation of the first promoter, to reach an effective level to control the next promoter depends on the rate of protein accumulation. We have analyzed the chemical reactions controlling transcript initiation and translation termination in a single such “genetically coupled” link as a precursor to modeling networks constructed from many such links. Simulation of the processes of gene expression shows that proteins are produced from an activated promoter in short bursts of variable numbers of proteins that occur at random time intervals. As a result, there can be large differences in the time between successive events in regulatory cascades across a cell population. In addition, the random pattern of expression of competitive effectors can produce probabilistic outcomes in switching mechanisms that select between alternative regulatory paths. The result can be a partitioning of the cell population into different phenotypes as the cells follow different paths. There are numerous unexplained examples of phenotypic variations in isogenic populations of both prokaryotic and eukaryotic cells that may be the result of these stochastic gene expression mechanisms.
1,955 citations
01 Feb 2005
TL;DR: The theory of linear difference equations applied to population growth and the applications of nonlinear difference equations to population biology are explained.
Abstract: Part I. Discrete Process in Biology: 1. The theory of linear difference equations applied to population growth 2. Nonlinear difference equations 3. Applications of nonlinear difference equations to population biology Part II. Continuous Processes and Ordinary Differential Equations: 4. An introduction to continuous models 5. Phase-plane methods and qualitative solutions 6. Applications of continuous models to population dynamics 7. Models for molecular events 8. Limit cycles, oscillations, and excitable systems Part III. Spatially Distributed Systems and Partial Differential Equation Models: 9. An introduction to partial differential equations and diffusion in biological settings 10. Partial differential equation models in biology 11. Models for development and pattern formation in biological systems Selected answers Author index Subject index.
1,925 citations
TL;DR: Controlling the expression of the genes encoding luciferase, the low abundance E.coli protein DnaJ and restriction endonuclease Cfr9I not only demonstrates that high levels of expression can be achieved but also suggests that under conditions of optimal repression only around one mRNA every 3rd generation is produced.
Abstract: Based on parameters governing promoter activity and using regulatory elements of the lac, ara and tet operon transcription control sequences were composed which permit the regulation in Escherichia coli of several gene activities independently and quantitatively. The novel promoter P LtetO-1 allows the regulation of gene expression over an up to 5000-fold range with anhydrotetracycline (aTc) whereas with IPTG and arabinose the activity of Plac/ara-1 may be controlled 1800-fold. Escherichia coli host strains which produce defined amounts of the regulatory proteins, Lac and Tet repressor as well as AraC from chromosomally located expression units provide highly reproducible in vivo conditions. Controlling the expression of the genes encoding luciferase, the low abundance E.coli protein DnaJ and restriction endonuclease Cfr9I not only demonstrates that high levels of expression can be achieved but also suggests that under conditions of optimal repression only around one mRNA every 3rd generation is produced. This potential of quantitative control will open up new approaches in the study of gene function in vivo, in particular with low abundance regulatory gene products. The system will also provide new opportunities for the controlled expression of heterologous genes.
1,761 citations