Plasmid-borne prokaryotic gene expression: sources of variability and quantitative system characterization.

One aim of synthetic biology is to exert systematic control over cellular behavior, either for medical purposes or to "program" microorganisms. An engineering approach to the design of biological controllers demands a quantitative understanding of the dynamics of both the system to be controlled and the controllers themselves. Here we focus on a widely used method of exerting control in bacterial cells: plasmid vectors bearing gene-promoter pairs. We study two variants of the simplest such element, an unregulated promoter constitutively expressing its gene, against the varying genomic background of four Escherichia coli cell strains. Absolute protein numbers and rates of expression vary with both cell strain and plasmid type, as does the variability of expression across the population. Total variability is most strongly coupled to the cell division process, and after cell size is scaled away, plasmid copy number regulation emerges as a significant effect. We present simple models that capture the main features of the system behavior. Our results confirm that complex interactions between plasmids and their hosts can have significant effects on both expression and variability, even in deliberately simplified systems.

[1]  S. Basu,et al.  A synthetic multicellular system for programmed pattern formation , 2005, Nature.

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

[3]  Jeff Hasty,et al.  A synthetic gene network for tuning protein degradation in Saccharomyces cerevisiae , 2007, Molecular systems biology.

[4]  Zoltán Kutalik,et al.  Connection between stochastic and deterministic modelling of microbial growth. , 2005, Journal of theoretical biology.

[5]  J. Lupski,et al.  A temperature-dependent pBR322 copy number mutant resulting from a Tn5 position effect. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Mads Kaern,et al.  The engineering of gene regulatory networks. , 2003, Annual review of biomedical engineering.

[7]  L. Koppes,et al.  Exponential growth of Escherichia coli B/r during its division cycle is demonstrated by the size distribution in liquid culture , 1998, Archives of Microbiology.

[8]  E Fernández-Repollet,et al.  Quantification of EGFP expression on Molt‐4 T cells using calibration standards , 2004, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[9]  Grzegorz Węgrzyn,et al.  Effects of the presence of ColE1 plasmid DNA in Escherichia coli on the host cell metabolism , 2006, Microbial Cell Factories.

[10]  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.

[11]  J. Derisi,et al.  Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise , 2006, Nature.

[12]  Mads Kærn,et al.  Predictable trends in protein noise , 2006, Nature Genetics.

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

[14]  David McMillen,et al.  Biochemical Network Stochastic Simulator (BioNetS): software for stochastic modeling of biochemical networks , 2004, BMC Bioinformatics.

[15]  R Y Tsien,et al.  Understanding, improving and using green fluorescent proteins. , 1995, Trends in biochemical sciences.

[16]  A. van Oudenaarden,et al.  Noise Propagation in Gene Networks , 2005, Science.

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

[18]  E. O’Shea,et al.  Global analysis of protein expression in yeast , 2003, Nature.

[19]  H. Bujard,et al.  Independent and tight regulation of transcriptional units in Escherichia coli via the LacR/O, the TetR/O and AraC/I1-I2 regulatory elements. , 1997, Nucleic acids research.

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

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

[22]  Second-order functions are the simplest correlations between flow cytometric light scatter and bacterial diameter. , 2000, Journal of microbiological methods.

[23]  E. Andrianantoandro,et al.  Synthetic biology: new engineering rules for an emerging discipline , 2006, Molecular systems biology.

[24]  F. Bolivar,et al.  Plasmid vector pBR322 and its special-purpose derivatives--a review. , 1986, Gene.

[25]  Christopher A. Voigt,et al.  Environmental signal integration by a modular AND gate , 2007, Molecular systems biology.

[26]  J. Raser,et al.  Noise in Gene Expression: Origins, Consequences, and Control , 2005, Science.

[27]  C. Tyler-Smith,et al.  Attenuation of green fluorescent protein half-life in mammalian cells. , 1999, Protein engineering.

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

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

[30]  D. Reanney,et al.  Molecular biology: Genetic noise in evolution? , 1984, Nature.

[31]  Martin Fussenegger,et al.  A synthetic time-delay circuit in mammalian cells and mice , 2007, Proceedings of the National Academy of Sciences.

[32]  Ron Weiss,et al.  Evolutionary Design of Genetic Circuits and Cell-Cell Communications , 2003, Adv. Complex Syst..

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

[34]  E. O’Shea,et al.  Noise in protein expression scales with natural protein abundance , 2006, Nature Genetics.

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

[36]  D. Ow,et al.  Quantitative real-time polymerase chain reaction for determination of plasmid copy number in bacteria. , 2006, Journal of microbiological methods.

[37]  M. Ehrenberg,et al.  Noise in a minimal regulatory network: plasmid copy number control , 2001, Quarterly Reviews of Biophysics.

[38]  S. Lin-Chao,et al.  High copy number of the pUC plasmid results from a Rom/Rop‐suppressible point mutation in RNA II , 1992, Molecular microbiology.

[39]  M. Elowitz,et al.  Combinatorial Synthesis of Genetic Networks , 2002, Science.

[40]  A. Varshavsky The N‐end rule pathway of protein degradation , 1997, Genes to cells : devoted to molecular & cellular mechanisms.

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

[42]  Ron Weiss,et al.  Genetic circuit building blocks for cellular computation, communications, and signal processing , 2003, Natural Computing.

[43]  G. Demers,et al.  Re-engineering adenovirus regulatory pathways to enhance oncolytic specificity and efficacy , 2001, Nature Biotechnology.

[44]  L. Serrano,et al.  Engineering stability in gene networks by autoregulation , 2000, Nature.

[45]  Leon Glass,et al.  Reverse Engineering the Gap Gene Network of Drosophila melanogaster , 2006, PLoS Comput. Biol..

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

[47]  M. A. Henson Dynamic modeling of microbial cell populations. , 2003, Current opinion in biotechnology.

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

[49]  J. Vieira,et al.  The pUC plasmids, an M13mp7-derived system for insertion mutagenesis and sequencing with synthetic universal primers. , 1982, Gene.

[50]  J. Raser,et al.  Control of Stochasticity in Eukaryotic Gene Expression , 2004, Science.

[51]  R. Weiss,et al.  Optimizing genetic circuits by global sensitivity analysis. , 2004, Biophysical journal.

[52]  André Longtin,et al.  Noise in genetic and neural networks. , 2006, Chaos.

[53]  J E Bailey,et al.  Plasmid presence changes the relative levels of many host cell proteins and ribosome components in recombinant Escherichia coli , 1991, Biotechnology and bioengineering.

[54]  F. Bolivar,et al.  Construction and characterization of new cloning vehicles. I. Ampicillin-resistant derivatives of the plasmid pMB9. , 1977, Gene.

[55]  M. F. Paige,et al.  Construction and application of a single-molecule fluorescence microscope , 2005 .

[56]  Uri Alon,et al.  A fluctuation method to quantify in vivo fluorescence data. , 2006, Biophysical journal.

[57]  P. Swain,et al.  Stochastic Gene Expression in a Single Cell , 2002, Science.

[58]  Ralf Kemkemer,et al.  Increased noise as an effect of haploinsufficiency of the tumor-suppressor gene neurofibromatosis type 1 in vitro , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[59]  Farren J. Isaacs,et al.  Phenotypic consequences of promoter-mediated transcriptional noise. , 2006, Molecular cell.

[60]  D. Volfson,et al.  Origins of extrinsic variability in eukaryotic gene expression , 2006, Nature.

[61]  Christopher A. Voigt,et al.  Genetic parts to program bacteria. , 2006, Current opinion in biotechnology.

[62]  R. Weiss,et al.  Programmed population control by cell–cell communication and regulated killing , 2004, Nature.

[63]  Konstantinos Michalodimitrakis,et al.  Noise in transcription negative feedback loops: simulation and experimental analysis , 2006, Molecular systems biology.