Noise Contributions in an Inducible Genetic Switch: A Whole-Cell Simulation Study

Stochastic expression of genes produces heterogeneity in clonal populations of bacteria under identical conditions. We analyze and compare the behavior of the inducible lac genetic switch using well-stirred and spatially resolved simulations for Escherichia coli cells modeled under fast and slow-growth conditions. Our new kinetic model describing the switching of the lac operon from one phenotype to the other incorporates parameters obtained from recently published in vivo single-molecule fluorescence experiments along with in vitro rate constants. For the well-stirred system, investigation of the intrinsic noise in the circuit as a function of the inducer concentration and in the presence/absence of the feedback mechanism reveals that the noise peaks near the switching threshold. Applying maximum likelihood estimation, we show that the analytic two-state model of gene expression can be used to extract stochastic rates from the simulation data. The simulations also provide mRNA–protein probability landscapes, which demonstrate that switching is the result of crossing both mRNA and protein thresholds. Using cryoelectron tomography of an E. coli cell and data from proteomics studies, we construct spatial in vivo models of cells and quantify the noise contributions and effects on repressor rebinding due to cell structure and crowding in the cytoplasm. Compared to systems without spatial heterogeneity, the model for the fast-growth cells predicts a slight decrease in the overall noise and an increase in the repressors rebinding rate due to anomalous subdiffusion. The tomograms for E. coli grown under slow-growth conditions identify the positions of the ribosomes and the condensed nucleoid. The smaller slow-growth cells have increased mRNA localization and a larger internal inducer concentration, leading to a significant decrease in the lifetime of the repressor–operator complex and an increase in the frequency of transcriptional bursts.

[1]  Michail Stamatakis,et al.  Comparison of deterministic and stochastic models of the lac operon genetic network. , 2009, Biophysical journal.

[2]  Mark Bates,et al.  Three-Dimensional Super-Resolution Imaging by Stochastic Optical Reconstruction Microscopy , 2008, Science.

[3]  J. Hasty,et al.  Noise-based switches and amplifiers for gene expression. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[4]  O. Sliusarenko,et al.  Spatial organization of the flow of genetic information in bacteria , 2010, Nature.

[5]  Jeffrey W. Smith,et al.  Stochastic Gene Expression in a Single Cell , .

[6]  Ertugrul M. Ozbudak,et al.  Predicting stochastic gene expression dynamics in single cells. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[7]  C. Woldringh,et al.  Morphological analysis of the division cycle of two Escherichia coli substrains during slow growth , 1977, Journal of bacteriology.

[8]  J. Keasling,et al.  Mathematical Model of the lac Operon: Inducer Exclusion, Catabolite Repression, and Diauxic Growth on Glucose and Lactose , 1997, Biotechnology progress.

[9]  A. Seluanov,et al.  FtsY, the Prokaryotic Signal Recognition Particle Receptor Homologue, Is Essential for Biogenesis of Membrane Proteins* , 1997, The Journal of Biological Chemistry.

[10]  A. Kepes Études cinétiques sur la galactoside-perméase d'Escherichia coli , 1960 .

[11]  Y. Akiyama Quality control of cytoplasmic membrane proteins in Escherichia coli. , 2009, Journal of biochemistry.

[12]  A. Driessen,et al.  Protein translocation across the bacterial cytoplasmic membrane. , 2008, Annual review of biochemistry.

[13]  P. R. ten Wolde,et al.  Green's-function reaction dynamics: a particle-based approach for simulating biochemical networks in time and space. , 2005, The Journal of chemical physics.

[14]  Peter G Wolynes,et al.  Stochastic gene expression as a many-body problem , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[15]  D. Tranchina,et al.  Stochastic mRNA Synthesis in Mammalian Cells , 2006, PLoS biology.

[16]  M. Thattai,et al.  Stochastic Gene Expression in Fluctuating Environments , 2004, Genetics.

[17]  R. Aebersold,et al.  Visual proteomics of the human pathogen Leptospira interrogans , 2009, Nature Methods.

[18]  U. Alon,et al.  Detailed map of a cis-regulatory input function , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[19]  K. Matthews,et al.  Macromolecular binding equilibria in the lac repressor system: studies using high-pressure fluorescence spectroscopy. , 1990, Biochemistry.

[20]  P. R. ten Wolde,et al.  Spatio-temporal correlations can drastically change the response of a MAPK pathway , 2009, Proceedings of the National Academy of Sciences.

[21]  Jose M. G. Vilar,et al.  Modeling network dynamics: the lac operon, a case study , 2004 .

[22]  Y. Ohshima,et al.  Binding of an inducer to the lac repressor. , 1974, Journal of molecular biology.

[23]  P. Bork,et al.  Proteome Organization in a Genome-Reduced Bacterium , 2009, Science.

[24]  P. Swain,et al.  Gene Regulation at the Single-Cell Level , 2005, Science.

[25]  Jeroen S. van Zon,et al.  Diffusion of transcription factors can drastically enhance the noise in gene expression. , 2006, Biophysical journal.

[26]  Michael A Thompson,et al.  Super-resolution imaging in live Caulobacter crescentus cells using photoswitchable EYFP , 2008, Nature Methods.

[27]  Masaru Tomita,et al.  A new multicompartmental reaction-diffusion modeling method links transient membrane attachment of E. coli MinE to E-ring formation , 2009, Systems and Synthetic Biology.

[28]  Vahid Shahrezaei,et al.  Analytical distributions for stochastic gene expression , 2008, Proceedings of the National Academy of Sciences.

[29]  M. Caruthers,et al.  Binding of synthetic lactose operator DNAs to lactose represessors. , 1977, Proceedings of the National Academy of Sciences of the United States of America.

[30]  Davi R. Ortega,et al.  Universal architecture of bacterial chemoreceptor arrays , 2009, Proceedings of the National Academy of Sciences.

[31]  T. Elston,et al.  Stochasticity in gene expression: from theories to phenotypes , 2005, Nature Reviews Genetics.

[32]  D. Bray,et al.  Stochastic simulation of chemical reactions with spatial resolution and single molecule detail , 2004, Physical biology.

[33]  C. Condon Maturation and degradation of RNA in bacteria. , 2007, Current opinion in microbiology.

[34]  A. Kepes The β-galactoside permease ofEscherichia coli , 1971, The Journal of Membrane Biology.

[35]  Brian Drawert,et al.  The diffusive finite state projection algorithm for efficient simulation of the stochastic reaction-diffusion master equation. , 2010, The Journal of chemical physics.

[36]  Jerome T. Mettetal,et al.  Stochastic switching as a survival strategy in fluctuating environments , 2008, Nature Genetics.

[37]  Benno Müller-Hill,et al.  Induction of the lac promoter in the absence of DNA loops and the stoichiometry of induction , 2006, Nucleic acids research.

[38]  Andreas Hellander,et al.  An adaptive algorithm for simulation of stochastic reaction-diffusion processes , 2010, J. Comput. Phys..

[39]  Pierre Boulanger,et al.  Coarse-grained molecular simulation of diffusion and reaction kinetics in a crowded virtual cytoplasm. , 2008, Biophysical journal.

[40]  B. Müller-Hill,et al.  The three operators of the lac operon cooperate in repression. , 1990, The EMBO journal.

[41]  T. Funatsu,et al.  Single molecule tracking of quantum dot-labeled mRNAs in a cell nucleus. , 2009, Biochemical and biophysical research communications.

[42]  Kirsten L. Frieda,et al.  A Stochastic Single-Molecule Event Triggers Phenotype Switching of a Bacterial Cell , 2008, Science.

[43]  M. Müller,et al.  The functional integration of a polytopic membrane protein of Escherichia coli is dependent on the bacterial signal-recognition particle. , 1995, European journal of biochemistry.

[44]  J M Rosenberg,et al.  Kinetic studies of inducer binding to lac repressor.operator complex. , 1980, The Journal of biological chemistry.

[45]  Johan Hattne,et al.  Stochastic reaction-diffusion simulation with MesoRD , 2005, Bioinform..

[46]  P. Maloney,et al.  Quantitative aspects of active transport by the lactose transport system of Escherichia coli. , 1973, Biochimica et biophysica acta.

[47]  M. Lewis,et al.  The lac repressor. , 2005, Comptes rendus biologies.

[48]  A. Riggs,et al.  Interaction of effecting ligands with lac repressor and repressor-operator complex. , 1975, Biochemistry.

[49]  Gregory Stephanopoulos,et al.  On physiological multiplicity and population heterogeneity of biological systems , 1996 .

[50]  A. Kuhn,et al.  Membrane integration of E. coli model membrane proteins. , 2004, Biochimica et biophysica acta.

[51]  Daniel T Gillespie,et al.  Stochastic simulation of chemical kinetics. , 2007, Annual review of physical chemistry.

[52]  Nir Friedman,et al.  Linking stochastic dynamics to population distribution: an analytical framework of gene expression. , 2006, Physical review letters.

[53]  M. Thattai,et al.  Intrinsic noise in gene regulatory networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[54]  M. Ehrenberg,et al.  Stochastic focusing: fluctuation-enhanced sensitivity of intracellular regulation. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[55]  Johan Paulsson,et al.  Models of stochastic gene expression , 2005 .

[56]  Paulien Hogeweg,et al.  The Effect of Stochasticity on the Lac Operon: An Evolutionary Perspective , 2007, PLoS Comput. Biol..

[57]  Kenneth H Downing,et al.  Three-dimensional analysis of the structure and ecology of a novel, ultra-small archaeon , 2009, The ISME Journal.

[58]  M. Lewis,et al.  A closer view of the conformation of the Lac repressor bound to operator , 2000, Nature Structural Biology.

[59]  V. Shahrezaei,et al.  The stochastic nature of biochemical networks. , 2008, Current opinion in biotechnology.

[60]  F. Jähnig,et al.  Fast measurement of galactoside transport by lactose permease. , 1989, The Journal of biological chemistry.

[61]  J. Elf,et al.  Probing Transcription Factor Dynamics at the Single-Molecule Level in a Living Cell , 2007, Science.

[62]  X. Xie,et al.  Probing Gene Expression in Live Cells, One Protein Molecule at a Time , 2006, Science.

[63]  A. Oudenaarden,et al.  Nature, Nurture, or Chance: Stochastic Gene Expression and Its Consequences , 2008, Cell.

[64]  Jaap A. Kaandorp,et al.  Spatial stochastic modelling of the phosphoenolpyruvate-dependent phosphotransferase (PTS) pathway in Escherichia coli , 2006, Bioinform..

[65]  Paul J. Choi,et al.  Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells , 2010, Science.

[66]  R. Dickerson,et al.  Equilibrium binding of inducer to lac repressor.operator DNA complex. , 1980, The Journal of biological chemistry.

[67]  J. Lippincott-Schwartz,et al.  Imaging Intracellular Fluorescent Proteins at Nanometer Resolution , 2006, Science.

[68]  Robert H. Singer,et al.  Single mRNA Molecules Demonstrate Probabilistic Movement in Living Mammalian Cells , 2003, Current Biology.

[69]  J Gowrishankar,et al.  Why is transcription coupled to translation in bacteria? , 2004, Molecular microbiology.

[70]  Alexander van Oudenaarden,et al.  Variability in gene expression underlies incomplete penetrance , 2009, Nature.

[71]  Daniel S. Banks,et al.  Anomalous diffusion of proteins due to molecular crowding. , 2005, Biophysical journal.

[72]  Tatiana T Marquez-Lago,et al.  Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics. , 2007, The Journal of chemical physics.

[73]  Terence Hwa,et al.  Combinatorial transcriptional control of the lactose operon of Escherichia coli , 2007, Proceedings of the National Academy of Sciences.

[74]  Mark de Berg,et al.  Computational geometry: algorithms and applications , 1997 .

[75]  K. Matthews,et al.  Flexibility in the inducer binding region is crucial for allostery in the Escherichia coli lactose repressor. , 2009, Biochemistry.

[76]  J. Paulsson Summing up the noise in gene networks , 2004, Nature.

[77]  A. Arkin,et al.  Stochastic mechanisms in gene expression. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[78]  P. R. ten Wolde,et al.  Reaction Brownian dynamics and the effect of spatial fluctuations on the gain of a push-pull network. , 2008, The Journal of chemical physics.

[79]  E. Cox,et al.  Real-Time Kinetics of Gene Activity in Individual Bacteria , 2005, Cell.

[80]  U. Alon,et al.  Plasticity of the cis-Regulatory Input Function of a Gene , 2006, PLoS biology.

[81]  Paul R. Selvin,et al.  Myosin V Walks Hand-Over-Hand: Single Fluorophore Imaging with 1.5-nm Localization , 2003, Science.

[82]  Mads Kærn,et al.  Noise in eukaryotic gene expression , 2003, Nature.

[83]  Paul J. Choi,et al.  Stochastic switching in gene networks can occur by a single-molecule event or many molecular steps. , 2010, Journal of molecular biology.

[84]  A. Narang Effect of DNA looping on the induction kinetics of the lac operon. , 2007, Journal of theoretical biology.

[85]  D. A. Mcquarrie Stochastic approach to chemical kinetics , 1967, Journal of Applied Probability.

[86]  P. Swain,et al.  Intrinsic and extrinsic contributions to stochasticity in gene expression , 2002, Proceedings of the National Academy of Sciences of the United States of America.

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

[88]  A. Narang,et al.  The diffusive influx and carrier efflux have a strong effect on the bistability of the lac operon in Escherichia coli. , 2008, Journal of theoretical biology.

[89]  Ertugrul M. Ozbudak,et al.  Regulation of noise in the expression of a single gene , 2002, Nature Genetics.

[90]  John E. Stone,et al.  Long time-scale simulations of in vivo diffusion using GPU hardware , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.

[91]  Switzerland.,et al.  Cellular automation model of reaction-transport processes , 1993, comp-gas/9312002.

[92]  M. Santillán,et al.  Bistable behavior in a model of the lac operon in Escherichia coli with variable growth rate. , 2008, Biophysical journal.

[93]  Adrian H. Elcock,et al.  Diffusion, Crowding & Protein Stability in a Dynamic Molecular Model of the Bacterial Cytoplasm , 2010, PLoS Comput. Biol..

[94]  Julio O. Ortiz,et al.  Structure of hibernating ribosomes studied by cryoelectron tomography in vitro and in situ , 2010, The Journal of cell biology.

[95]  R. Cheong,et al.  Models at the single cell level , 2010, Wiley interdisciplinary reviews. Systems biology and medicine.

[96]  Julio O. Ortiz,et al.  Mapping 70S ribosomes in intact cells by cryoelectron tomography and pattern recognition. , 2006, Journal of structural biology.