Multi-scale models for gene network engineering

With current advances in biological knowledge, the potential exists for engineering novel gene regulatory networks, which allow the timely control of protein expression. Genome projects identify the components of gene networks in biological organisms, gene after gene, and DNA microarray experiments discover the network connections. Yet, the static pictures these experiments give cannot provide insight on the dynamic behavior of gene networks. The large number of components and interactions involved in dynamic gene regulation warrants a quantitative, computational perspective for investigating the dynamic behavior. The challenge lies with the fact that the timescales of phenomena involved in transcription/translation span multiple orders of magnitude. In this paper, multi-scale simulation methods developed to model gene regulatory networks are discussed. Details are provided for modeling biomolecular systems away from the thermodynamic limit and a hybrid algorithm is presented for simulating stochastic systems that contain both discrete and continuous representations. These simulations can provide useful insight for rationally engineering the components and the connections of novel gene network modules. Two examples, the bistable switch and the oscillator, are discussed. These examples demonstrate that ensembles of stochastic trajectories can provide insight into the dynamics of biomolecular interaction networks. This insight can guide the changes needed for the network to exhibit the desired dynamic behavior. 2005 Elsevier Ltd. All rights reserved.

[1]  D. Gillespie.  The chemical Langevin equation , 2000 .

[2]  K. Matthews,et al.  Operator DNA sequence variation enhances high affinity binding by hinge helix mutants of lactose repressor protein. , 2000, Biochemistry.

[3]  M. Wall,et al.  Design of gene circuits: lessons from bacteria , 2004, Nature Reviews Genetics.

[4]  René Thomas,et al.  Hardware (DNA) circuits. , 2003, Comptes rendus biologies.

[5]  Hidde de Jong,et al.  Modeling and Simulation of Genetic Regulatory Systems: A Literature Review , 2002, J. Comput. Biol..

[6]  Naren Ramakrishnan,et al.  Modeling regulatory networks at Virginia Tech. , 2003, Omics : a journal of integrative biology.

[7]  William S Hlavacek,et al.  Design principles for regulator gene expression in a repressible gene circuit. , 2003, Journal of molecular biology.

[8]  H H McAdams,et al.  Towards a circuit engineering discipline. , 2000, Current biology : CB.

[9]  James M. Bower,et al.  Computational modeling of genetic and biochemical networks , 2001 .

[10]  Muruhan Rathinam,et al.  Stiffness in stochastic chemically reacting systems: The implicit tau-leaping method , 2003 .

[11]  M. S. Ko.  Induction mechanism of a single gene molecule: stochastic or deterministic? , 1992, BioEssays : news and reviews in molecular, cellular and developmental biology.

[12]  M A Savageau,et al.  Irreversibility in unbranched pathways: preferred positions based on regulatory considerations. , 2001, Biophysical journal.

[13]  I. Prigogine,et al.  Formative Processes. (Book Reviews: Self-Organization in Nonequilibrium Systems. From Dissipative Structures to Order through Fluctuations) , 1977 .

[14]  Wei Tong,et al.  Analyzing the Biology on the System Level , 2004, Genomics, proteomics & bioinformatics.

[15]  R. Weiss,et al.  Directed evolution of a genetic circuit , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[16]  D. Bray,et al.  A free-energy-based stochastic simulation of the Tar receptor complex. , 1999, Journal of molecular biology.

[17]  D. A. Baxter,et al.  Effects of macromolecular transport and stochastic fluctuations on dynamics of genetic regulatory systems. , 1999, The American journal of physiology.

[18]  Howard M. Salis,et al.  Numerical simulation of stochastic gene circuits , 2005, Comput. Chem. Eng..

[19]  Yiannis Kaznessis,et al.  Inferring Gene Regulatory Relationships by Combining Target–target Pattern Recognition and Regulator-specific Motif Examination , 2022 .

[20]  J. Tyson,et al.  Modelling the controls of the eukaryotic cell cycle. , 2003, Biochemical Society transactions.

[21]  A. Ninfa,et al.  Development of Genetic Circuitry Exhibiting Toggle Switch or Oscillatory Behavior in Escherichia coli , 2003, Cell.

[22]  Michael A. Gibson,et al.  Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels , 2000 .

[23]  J. S. Parkinson,et al.  A model of excitation and adaptation in bacterial chemotaxis. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[24]  A. Fernie,et al.  Metabolite profiling: from diagnostics to systems biology , 2004, Nature Reviews Molecular Cell Biology.

[25]  J. Doyle,et al.  Reverse Engineering of Biological Complexity , 2002, Science.

[26]  城塚 正,et al.  Chemical Engineering Scienceについて , 1962 .

[27]  Z. Szallasi,et al.  Modeling the normal and neoplastic cell cycle with "realistic Boolean genetic networks": their application for understanding carcinogenesis and assessing therapeutic strategies. , 1998, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

[28]  C. Rao,et al.  Control motifs for intracellular regulatory networks. , 2001, Annual review of biomedical engineering.

[29]  Ramon Gonzalez,et al.  DNA Microarrays: Experimental Issues, Data Analysis, and Application to Bacterial Systems , 2004, Biotechnology progress.

[30]  J. Schnakenberg,et al.  G. Nicolis und I. Prigogine: Self‐Organization in Nonequilibrium Systems. From Dissipative Structures to Order through Fluctuations. J. Wiley & Sons, New York, London, Sydney, Toronto 1977. 491 Seiten, Preis: £ 20.–, $ 34.– , 1978 .

[31]  G. Milstein.  Numerical Integration of Stochastic Differential Equations , 1994 .

[32]  Melvin K. Simmons,et al.  Hybrid simulation of cellular behavior , 2004, Bioinform..

[33]  Eduardo Sontag,et al.  Inference of signaling and gene regulatory networks by steady-state perturbation experiments: structure and accuracy. , 2005, Journal of theoretical biology.

[34]  J. Collins,et al.  Construction of a genetic toggle switch in Escherichia coli , 2000, Nature.

[35]  A. Kierzek,et al.  Bridging the gap between stochastic and deterministic regimes in the kinetic simulations of the biochemical reaction networks. , 2004, Biophysical journal.

[36]  Andrea Ciliberto,et al.  A kinetic model of the cyclin E/Cdk2 developmental timer in Xenopus laevis embryos. , 2003, Biophysical chemistry.

[37]  J. Tyson,et al.  Models of cell cycle control in eukaryotes. , 1999, Journal of biotechnology.

[38]  Michael A Savageau,et al.  Alternative designs for a genetic switch: analysis of switching times using the piecewise power-law representation. , 2002, Mathematical biosciences.

[39]  Jeff Hasty,et al.  Engineered gene circuits , 2002, Nature.

[40]  L. Glass,et al.  Evolving complex dynamics in electronic models of genetic networks. , 2004, Chaos.

[41]  D. Gillespie.  A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions , 1976 .

[42]  F. Garcia-Sanchez,et al.  Towards cooperative frameworks for modeling and integrating biological processes knowledge , 2004, IEEE Transactions on NanoBioscience.

[43]  H. McAdams,et al.  Gene regulation: Towards a circuit engineering discipline , 2000, Current Biology.

[44]  J. Ross,et al.  A Test Case of Correlation Metric Construction of a Reaction Pathway from Measurements , 1997 .

[45]  Yiannis Kaznessis,et al.  Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions. , 2005, The Journal of chemical physics.

[46]  Farren J. Isaacs,et al.  Computational studies of gene regulatory networks: in numero molecular biology , 2001, Nature Reviews Genetics.

[47]  David R. Rigney,et al.  Stochastic Models of Cellular Variability , 1979 .

[48]  J. Collins,et al.  Programmable cells: interfacing natural and engineered gene networks. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[49]  Michael A. Gibson,et al.  Modeling the Activity of Single Genes , 1999 .

[50]  A. Arkin,et al.  Simulation of prokaryotic genetic circuits. , 1998, Annual review of biophysics and biomolecular structure.

[51]  H. Brunner.  Annual Review of Genomics and Human Genetics , 2001, European Journal of Human Genetics.

[52]  John J Tyson,et al.  Monitoring p53's pulse , 2004, Nature Genetics.

[53]  Michael A Savageau,et al.  Quantitative evolutionary design of glucose 6-phosphate dehydrogenase expression in human erythrocytes , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[54]  Tae J. Lee,et al.  Engineering Gene Circuits: Foundations and Applications , 2006 .

[55]  A. Arkin,et al.  Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells. , 1998, Genetics.

[56]  J. Tyson,et al.  Chemical kinetic theory: understanding cell-cycle regulation. , 1996, Trends in biochemical sciences.

[57]  C. W. Gardiner,et al.  Handbook of stochastic methods - for physics, chemistry and the natural sciences, Second Edition , 1986, Springer series in synergetics.

[58]  Statistical and integrative approach for constructing biological network maps. , 2004, Genome informatics. International Conference on Genome Informatics.

[59]  D. Gillespie.  The Chemical Langevin and Fokker−Planck Equations for the Reversible Isomerization Reaction† , 2002 .

[60]  H. McAdams,et al.  Circuit simulation of genetic networks. , 1995, Science.

[61]  J. Rawlings,et al.  Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics , 2002 .

[62]  A. Arkin,et al.  It's a noisy business! Genetic regulation at the nanomolar scale. , 1999, Trends in genetics : TIG.

[63]  M. Elowitz,et al.  A synthetic oscillatory network of transcriptional regulators , 2000, Nature.

[64]  C. Rao,et al.  Stochastic chemical kinetics and the quasi-steady-state assumption: Application to the Gillespie algorithm , 2003 .

[65]  R. Brent,et al.  Modelling cellular behaviour , 2001, Nature.

[66]  Yiannis N Kaznessis,et al.  Model-driven designs of an oscillating gene network. , 2005, Biophysical journal.

[67]  M. Ko,et al.  A stochastic model for gene induction. , 1991, Journal of theoretical biology.

[68]  Linda R. Petzold,et al.  Improved leap-size selection for accelerated stochastic simulation , 2003 .

[69]  J. Liao,et al.  Design of artificial cell-cell communication using gene and metabolic networks. , 2004, Proceedings of the National Academy of Sciences of the United States of America.