Transcriptional noise and cellular heterogeneity in mammalian macrophages

Transcriptional noise is known to play a crucial role in heterogeneity in bacteria and yeast. Mammalian macrophages are known to exhibit cell-to-cell variation in their responses to pathogens, but the source of this heterogeneity is not known. We have developed a detailed stochastic model of gene expression that takes into account scaling effects due to cell size and genome complexity. We report the results of applying this model to simulating gene expression variability in mammalian macrophages, demonstrating a possible molecular basis for heterogeneity in macrophage signalling responses. We note that the nature of predicted transcriptional noise in macrophages is different from that in yeast and bacteria. Some molecular interactions in yeast and bacteria are thought to have evolved to minimize the effects of the high-frequency noise observed in these species. Transcriptional noise in macrophages results in slow changes to gene expression levels and would not require the type of spike-filtering circuits observed in yeast and bacteria.

[1]  B. Hinz,et al.  Prostaglandin E2 Upregulates Cyclooxygenase-2 Expression in Lipopolysaccharide-Stimulated RAW 264.7 Macrophages , 2000 .

[2]  S. Shen-Orr,et al.  Networks Network Motifs : Simple Building Blocks of Complex , 2002 .

[3]  S. Carroll,et al.  The regulatory content of intergenic DNA shapes genome architecture , 2004, Genome Biology.

[4]  Jeffrey A. Magee,et al.  Haploinsufficiency at the Nkx3.1 locus. A paradigm for stochastic, dosage-sensitive gene regulation during tumor initiation. , 2003, Cancer cell.

[5]  J. Brockmöller,et al.  Rapid quantification of CYP3A4 expression in human leukocytes by real-time reverse transcription-PCR. , 2002, Clinical chemistry.

[6]  F. Neidhart.  Escherichia coli and Salmonella. , 1996 .

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

[8]  S. Shen-Orr,et al.  Network motifs: simple building blocks of complex networks. , 2002, Science.

[9]  P de Atauri,et al.  Evolution of 'design' principles in biochemical networks. , 2004, Systems biology.

[10]  Jiahuai Han,et al.  Identification of Lps2 as a key transducer of MyD88-independent TIR signalling , 2003, Nature.

[11]  Harvey F. Lodish,et al.  MOLECULAR.CELL.BIOLOGY 5TH.ED , 2003 .

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

[13]  Jeffrey W. Smith,et al.  Stochastic Gene Expression in a Single Cell , 2022 .

[14]  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.

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

[16]  John D. Storey,et al.  Precision and functional specificity in mRNA decay , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[17]  E. Lander,et al.  Human macrophage activation programs induced by bacterial pathogens , 2002, Proceedings of the National Academy of Sciences of the United States of America.

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

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

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

[21]  A. Aderem,et al.  Bacterial lipopolysaccharides prime macrophages for enhanced release of arachidonic acid metabolites , 1986, The Journal of experimental medicine.

[22]  Hamid Bolouri,et al.  Dizzy: Stochastic Simulation of Large-scale Genetic Regulatory Networks , 2005, J. Bioinform. Comput. Biol..

[23]  M. Gerstein,et al.  Genomic analysis of regulatory network dynamics reveals large topological changes , 2004, Nature.

[24]  Hamid Bolouri,et al.  Control of internal and external noise in genetic regulatory networks. , 2004, Journal of theoretical biology.

[25]  Kazunari Miyamichi,et al.  Negative Feedback Regulation Ensures the One Receptor-One Olfactory Neuron Rule in Mouse , 2003, Science.

[26]  R. Flavell,et al.  The adaptor molecule TIRAP provides signalling specificity for Toll-like receptors , 2002, Nature.

[27]  M. Ares,et al.  Perturbation of transcription elongation influences the fidelity of internal exon inclusion in Saccharomyces cerevisiae. , 2003, RNA.

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

[29]  J. Bonfield,et al.  Finishing the euchromatic sequence of the human genome , 2004, Nature.

[30]  S. Shen-Orr,et al.  Network motifs in the transcriptional regulation network of Escherichia coli , 2002, Nature Genetics.

[31]  Uri Alon,et al.  Dynamics of the p53-Mdm2 feedback loop in individual cells , 2004, Nature Genetics.

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

[33]  S. Akira,et al.  Synergy and Cross-Tolerance Between Toll-Like Receptor (TLR) 2- and TLR4-Mediated Signaling Pathways1 , 2000, The Journal of Immunology.

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

[35]  H. S. Warren,et al.  Toll-like receptors. , 2005, Critical care medicine.

[36]  R. Reed,et al.  ORs Rule the Roost in the Olfactory System , 2003, Science.

[37]  S. Gordon.  Alternative activation of macrophages , 2003, Nature Reviews Immunology.

[38]  Hamid Bolouri,et al.  A method for estimating stochastic noise in large genetic regulatory networks , 2005, Bioinform..

[39]  Stephen G Oliver,et al.  Dynamics of Protein Turnover, a Missing Dimension in Proteomics* , 2002, Molecular & Cellular Proteomics.

[40]  David A. Hume,et al.  Probability in transcriptional regulation and its implications for leukocyte differentiation and inducible gene expression , 2000 .

[41]  Kazuyuki Aihara,et al.  Noise-reduction through interaction in gene expression and biochemical reaction processes. , 2004, Journal of theoretical biology.

[42]  M. Magnasco,et al.  Decay rates of human mRNAs: correlation with functional characteristics and sequence attributes. , 2003, Genome research.

[43]  S. Mangan,et al.  Structure and function of the feed-forward loop network motif , 2003, Proceedings of the National Academy of Sciences of the United States of America.

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

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

[46]  E. Davidson,et al.  Transcriptional regulatory cascades in development: Initial rates, not steady state, determine network kinetics , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[47]  D. Gillespie.  Approximate accelerated stochastic simulation of chemically reacting systems , 2001 .

[48]  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.

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

[50]  Nicola J. Rinaldi,et al.  Control of Pancreas and Liver Gene Expression by HNF Transcription Factors , 2004, Science.

[51]  S. Akira,et al.  TRAM is specifically involved in the Toll-like receptor 4–mediated MyD88-independent signaling pathway , 2003, Nature Immunology.

[52]  P. Cresswell,et al.  Recent developments in MHC-class-I-mediated antigen presentation. , 2004, Current opinion in immunology.

[53]  David A. Hume,et al.  Generation of Diversity in the Innate Immune System: Macrophage Heterogeneity Arises from Gene-Autonomous Transcriptional Probability of Individual Inducible Genes1 , 2002, The Journal of Immunology.

[54]  D. Hume,et al.  Probability in transcriptional regulation and its implications for leukocyte differentiation and inducible gene expression. , 2000, Blood.

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

[56]  S. Akira,et al.  Essential role for TIRAP in activation of the signalling cascade shared by TLR2 and TLR4 , 2002, Nature.

[57]  B. Hallet,et al.  Playing Dr Jekyll and Mr Hyde: combined mechanisms of phase variation in bacteria. , 2001, Current opinion in microbiology.

[58]  Shu-Bing Qian,et al.  Quantitating protein synthesis, degradation, and endogenous antigen processing. , 2003, Immunity.

[59]  R. Kornberg,et al.  Quantitation of the RNA Polymerase II Transcription Machinery in Yeast* , 2001, The Journal of Biological Chemistry.

[60]  Eric H. Davidson,et al.  Gene activity in early development , 1968 .