Effects of gene length on the dynamics of gene expression

In Escherichia coli, the nucleotide length of a gene is bound to affect its expression dynamics. From simulations of a stochastic model of gene expression at the nucleotide and codon levels we show that, within realistic parameter values, the nucleotide length affects RNA and protein mean levels, as well as the expected transient time for RNA and protein numbers to change, following a signal. Fluctuations in RNA and protein numbers are found to be minimized for a small range of lengths, which matches the means of the distributions of lengths found in E. coli of both essential and non-essential genes. The variance of the length distribution for essential genes is found to be smaller than for non-essential genes, implying that these distributions are far from random. Finally, gene lengths are shown to affect the kinetics of a genetic switch, namely, the correlation between temporal proteins numbers, the stability of the two noisy attractors of the switch, and how biased is the choice of noisy attractor. The stability increases with gene length due to increased 'memory' about the previous states of the switch. We argue that, by affecting the dynamics of gene expression and of genetic circuits, gene lengths are subject to selection.

[1]  Olli Yli-Harja,et al.  Stochastic sequence-level model of coupled transcription and translation in prokaryotes , 2011, BMC Bioinformatics.

[2]  A. Arkin,et al.  Motifs, modules and games in bacteria. , 2003, Current opinion in microbiology.

[3]  S. Greive,et al.  Thinking quantitatively about transcriptional regulation , 2005, Nature Reviews Molecular Cell Biology.

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

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

[6]  Roger Brent,et al.  A Fishing Buddy for Hypothesis Generators , 2005, Science.

[7]  A. van Oudenaarden,et al.  Single molecule fluorescent in situ hybridization (smFISH) of C. elegans worms and embryos. , 2012, WormBook : the online review of C. elegans biology.

[8]  M Kandhavelu,et al.  Single-molecule dynamics of transcription of the lar promoter , 2012, Physical biology.

[9]  D. Gillespie Exact Stochastic Simulation of Coupled Chemical Reactions , 1977 .

[10]  Arkady B. Khodursky,et al.  Global analysis of mRNA decay and abundance in Escherichia coli at single-gene resolution using two-color fluorescent DNA microarrays , 2002, Proceedings of the National Academy of Sciences of the United States of America.

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

[12]  S Chowdhury,et al.  An interacting multiple model filter‐based autofocus strategy for confocal time‐lapse microscopy , 2012, Journal of microscopy.

[13]  Andre S. Ribeiro,et al.  SGN Sim, a Stochastic Genetic Networks Simulator , 2007, Bioinform..

[14]  Antti Häkkinen,et al.  Dynamical effects of transcriptional pause-prone sites , 2010, Comput. Biol. Chem..

[15]  C. A. Thomas,et al.  Visualization of Bacterial Genes in Action , 1970, Science.

[16]  W. McClure,et al.  Mechanism and control of transcription initiation in prokaryotes. , 1985, Annual review of biochemistry.

[17]  S Falkow,et al.  FACS-optimized mutants of the green fluorescent protein (GFP). , 1996, Gene.

[18]  G. Dougan,et al.  Cooperation Between Translating Ribosomes and RNA Polymerase in Transcription Elongation , 2010, Science.

[19]  Andre S Ribeiro,et al.  Studying genetic regulatory networks at the molecular level: delayed reaction stochastic models. , 2007, Journal of theoretical biology.

[20]  C. Hayes,et al.  Beyond ribosome rescue: tmRNA and co‐translational processes , 2010, FEBS letters.

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

[22]  Rui Zhu,et al.  A General Modeling Strategy for Gene Regulatory Networks with Stochastic Dynamics , 2006, J. Comput. Biol..

[23]  S. Kauffman,et al.  Noisy attractors and ergodic sets in models of gene regulatory networks. , 2007, Journal of theoretical biology.

[24]  Steven M. Block,et al.  Sequence-Resolved Detection of Pausing by Single RNA Polymerase Molecules , 2006, Cell.

[25]  K. Keiler Biology of trans-translation. , 2008, Annual review of microbiology.

[26]  C. Kurland,et al.  Codon usage determines translation rate in Escherichia coli. , 1989, Journal of molecular biology.

[27]  Antti Häkkinen,et al.  Delayed Stochastic Model of Transcription at the Single Nucleotide Level , 2009, J. Comput. Biol..

[28]  P. V. von Hippel,et al.  Monitoring RNA transcription in real time by using surface plasmon resonance , 2008, Proceedings of the National Academy of Sciences.

[29]  Ben Lehner Selection to minimise noise in living systems and its implications for the evolution of gene expression , 2008, Molecular systems biology.

[30]  Antti Häkkinen,et al.  In vivo kinetics of transcription initiation of the lar promoter in Escherichia coli. Evidence for a sequential mechanism with two rate-limiting steps , 2011, BMC Systems Biology.

[31]  A. E. Hirsh,et al.  Noise Minimization in Eukaryotic Gene Expression , 2004, PLoS biology.

[32]  Rui Zhu,et al.  Validation of an algorithm for delay stochastic simulation of transcription and translation in prokaryotic gene expression , 2006, Physical biology.

[33]  Robert T Sauer,et al.  Ribosome rescue: tmRNA tagging activity and capacity in Escherichia coli , 2005, Molecular microbiology.

[34]  W. McClure,et al.  Rate-limiting steps in RNA chain initiation. , 1980, Proceedings of the National Academy of Sciences of the United States of America.

[35]  M. Ehrenberg,et al.  Free RNA polymerase and modeling global transcription in Escherichia coli. , 2003, Biochimie.

[36]  J. W. Campbell,et al.  Experimental Determination and System Level Analysis of Essential Genes in Escherichia coli MG1655 , 2003, Journal of bacteriology.

[37]  M. Sørensen,et al.  Absolute in vivo translation rates of individual codons in Escherichia coli. The two glutamic acid codons GAA and GAG are translated with a threefold difference in rate. , 1991, Journal of molecular biology.

[38]  Frederick R. Blattner,et al.  High-Density Microarray-Mediated Gene Expression Profiling of Escherichia coli , 2001, Journal of bacteriology.

[39]  H. Lodish Molecular Cell Biology , 1986 .

[40]  R. Landick The regulatory roles and mechanism of transcriptional pausing. , 2006, Biochemical Society transactions.

[41]  Björn M. Burmann,et al.  A NusE:NusG Complex Links Transcription and Translation , 2010, Science.

[42]  A. Ribeiro,et al.  Effects of coupling strength and space on the dynamics of coupled toggle switches in stochastic gene networks with multiple-delayed reactions. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[43]  Antti Häkkinen,et al.  Effects of Transcriptional Pausing on Gene Expression Dynamics , 2010, PLoS Comput. Biol..

[44]  Tony Pawson,et al.  Multisite phosphorylation of a CDK inhibitor sets a threshold for the onset of DNA replication , 2001, Nature.

[45]  A. Ribeiro Stochastic and delayed stochastic models of gene expression and regulation. , 2010, Mathematical biosciences.

[46]  Olli Yli-Harja,et al.  Dynamics of transcription driven by the tetA promoter, one event at a time, in live Escherichia coli cells , 2012, Nucleic acids research.

[47]  H. Bujard,et al.  Dissecting the functional program of Escherichia coli promoters: the combined mode of action of Lac repressor and AraC activator. , 2001, Nucleic acids research.

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

[49]  Kim Sneppen,et al.  Ribosome collisions and translation efficiency: optimization by codon usage and mRNA destabilization. , 2008, Journal of molecular biology.

[50]  Olli Yli-Harja,et al.  Determining noisy attractors of delayed stochastic gene regulatory networks from multiple data sources , 2009, Bioinform..