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Transactions on Computational Systems Biology XII pp 199–228Cite as

Rule-Based Modeling of Transcriptional Attenuation at the Tryptophan Operon

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Part of the book series: Lecture Notes in Computer Science ((TCSB,volume 5945))

Abstract

Transcriptional attenuation at E.coli’s tryptophan operon is a prime example of RNA-mediated gene regulation. In this paper, we present a discrete stochastic model of the fine-grained control of attenuation, based on chemical reactions. Stochastic simulation of our model confirms results that were previously obtained by master or differential equations. Our approach is easier to understand than master equations, although mathematically well founded. It is compact due to rule schemas that define finite sets of chemical reactions. Object-centered languages based on the π-calculus would yield less intelligible models. Such languages are confined to binary interactions, whereas our model heavily relies on reaction rules with more than two reactants, in order to concisely capture the control of attenuation.

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References

  1. Arkin, A., Ross, J., McAdams, H.H.: Stochastic kinetic analysis of developmental pathway bifurcation in phage λ-infected Escherichia coli cells. Genetics 149, 1633–1648 (1998)

    Google Scholar 

  2. Baader, F., Nipkow, T.: Term rewriting and all that. Cambridge University Press, New York (1998)

    Book  MATH  Google Scholar 

  3. Barboric, M., Peterlin, B.M.: A new paradigm in eukaryotic biology: HIV Tat and the control of transcriptional elongation. PLoS Biology 3(2), 0200–2003 (2005)

    Article  Google Scholar 

  4. Beisel, C.L., Smolke, C.D.: Design principles for riboswitch function. PLoS Computational Biology 5(4), e1000363, 04 (2009)

    Article  Google Scholar 

  5. Cardelli, L., Zavattaro, G.: On the computational power of biochemistry. In: Horimoto, K., Regensburger, G., Rosenkranz, M., Yoshida, H. (eds.) AB 2008. LNCS, vol. 5147, pp. 65–80. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  6. Chabrier-Rivier, N., Fages, F., Soliman, S.: The biochemical abstract machine BioCham. In: Danos, V., Schachter, V. (eds.) CMSB 2004. LNCS (LNBI), vol. 3082, pp. 172–191. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  7. Ciocchetta, F., Hillston, J.: Bio-PEPA: a framework for modelling and analysis of biological systems. Theoretical Computer Science (to apppear)

    Google Scholar 

  8. Danos, V., Feret, J., Fontana, W., Krivine, J.: Scalable simulation of cellular signaling networks. In: Shao, Z. (ed.) APLAS 2007. LNCS, vol. 4807, pp. 139–157. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  9. Danos, V., Feret, J., Fontana, W., Harmer, R., Krivine, J.: Rule-based modelling of cellular signalling. In: Caires, L., Vasconcelos, V.T. (eds.) CONCUR 2007. LNCS, vol. 4703, pp. 17–41. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  10. Dematté, L., Priami, C., Romanel, A.: The beta workbench: A tool to study the dynamics of biological systems. Briefings in Bioinformatics 9(5), 437–449 (2008)

    Article  Google Scholar 

  11. Elf, J., Ehrenberg, M.: What makes ribosome-mediated trascriptional attenuation sensitive to amino acid limitation? PLoS Computational Biology 1(1), 14–23 (2005)

    Article  Google Scholar 

  12. Gillespie, D.T.: A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. Journal of Computational Physics 22, 403–434 (1976)

    Article  MathSciNet  Google Scholar 

  13. Gollnick, P.: Trp operon and attenuation. In: Lennarz, W.J., Lane, M.D. (eds.) Encyclopedia of Biological Chemistry, pp. 267–271. Elsevier, New York (2004)

    Chapter  Google Scholar 

  14. Gollnick, P., Babitzke, P., Antson, A., Yanofsky, C.: Complexity in regulation of tryptophan biosynthesis in Bacillus subtilis. Annual Review of Genetics 39(1), 47–68 (2005)

    Article  Google Scholar 

  15. Gutierrez-Preciado, A., Jensen, R.A., Yanofsky, C., Merino, E.: New insights into regulation of the tryptophan biosynthetic operon in Gram-positive bacteria. Trends in Genetics 21(8), 432–436 (2005)

    Article  Google Scholar 

  16. Blinov, M.L., Faeder, J.R., Hlavacek, W.S.: Rule-Based Modeling of Biochemical Systems with BioNetGen. In: Systems Biology. Methods in Molecular Biology, vol. 500, pp. 1–55. Humana Press (2009)

    Google Scholar 

  17. John, M., Lhoussaine, C., Niehren, J., Uhrmacher, A.M.: The attributed pi-calculus with priorities. Transactions on Computational Systems Biology (to appear, 2009)

    Google Scholar 

  18. Nakamura, Y., Roesser, J.R., Yanofsky, C.: Regulation of basal level expression of the tryptophan operon of Escherichia coli. J. Biol. Chem. 264(21), 12284–12288 (1989)

    Google Scholar 

  19. Kasai, T.: Regulation of the expression of the histidine operon in Salmonella typhimurium. Nature 249, 523–527 (1974)

    Article  Google Scholar 

  20. Konan, K.V., Yanofsky, C.: Role of ribosome release in regulation of tna operon expression in Escherichia coli. J. Bacteriol. 181, 1530–1536 (1999)

    Google Scholar 

  21. Krivine, J., Milner, R., Troina, A.: Stochastic bigraphs. In: 24th Conference on the Mathematical Foundations of Programming Semantics. Electronical notes in theoretical computer science, vol. 218, pp. 73–96. Elsevier, Amsterdam (2008)

    Google Scholar 

  22. Kuttler, C., Lhoussaine, C., Niehren, J.: A stochastic pi calculus for concurrent objects. In: Anai, H., Horimoto, K., Kutsia, T. (eds.) AB 2007. LNCS, vol. 4545, pp. 232–246. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  23. Lloyd, J.W.: Foundations of Logic Programming, 2nd edn. Springer, Heidelberg (1987)

    Book  MATH  Google Scholar 

  24. Pedersen, M., Plotkin, G.: A language for biochemical systems. In: Priami, C., et al. (eds.) Trans. on Comput. Syst. Biol. XII. LNCS (LNBI), vol. 5945, pp. 77–145. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  25. Phillips, A., Cardelli, L.: Efficient, correct simulation of biological processes in the stochastic pi-calculus. In: Calder, M., Gilmore, S. (eds.) CMSB 2007. LNCS (LNBI), vol. 4695, pp. 184–199. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  26. Pradalier, S., Credi, A., Garavelli, M., Laneve, C., Zavattaro, G.: Modelization and simulation of nano devices in the nano-kappa calculus. In: Calder, M., Gilmore, S. (eds.) CMSB 2007. LNCS (LNBI), vol. 4695, pp. 168–183. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  27. Ramsey, S., Orrell, D., Bolouri, H.: Dizzy: stochastic simulation of large-scale genetic regulatory networks. Journal of Bioinformatics and Computational Biology 3(2), 415–436 (2005)

    Article  Google Scholar 

  28. Regev, A.: Computational Systems Biology: A Calculus for Biomolecular Knowledge. Tel Aviv University, PhD thesis (2002)

    Google Scholar 

  29. Roesser, J.R., Yanofsky, C.: Ribosome release modulates basal level expression of the trp operon of Escherichia coli. Journal of Biological Chemistry 263(28), 14251–14255 (1988)

    Google Scholar 

  30. Santillan, M., Zeron, E.S.: Dynamic influence of feedback enzyme inhibition and transcription attenuation on the tryptophan operon response to nutritional shifts. Journal of Theoretical Biology 231(2), 287–298 (2004)

    Article  MathSciNet  Google Scholar 

  31. Shieber, S.M.: An Introduction to Unification-Based Approaches to Grammar, vol. 4. CLSI Publications (1986)

    Google Scholar 

  32. Simão, E., Remy, E., Thieffry, D., Chaouiya, C.: Qualitative modelling of regulated metabolic pathways: application to the tryptophan biosynthesis in E.coli. In: ECCB/JBI, pp. 190–196 (2005)

    Google Scholar 

  33. Trun, N., Trempy, J.: Gene expression and regulation. In: Fundamental bacterial genetics, pp. 191–212. Blackwell, Malden (2003)

    Google Scholar 

  34. von Heijne, G., Nilsson, L., Blomberg, C.: Translation and messenger RNA secondary structure. Journal of Theoretical Biology 68, 321–329 (1977)

    Article  Google Scholar 

  35. Yang, J., Monine, M.I., Faeder, J.R., Hlavacek, W.S.: Kinetic monte carlo method for rule-based modeling of biochemical networks. Physical Review E 78(3), 7 (2008)

    Google Scholar 

  36. Yanofsky, C.: Attenuation in the control of expression of bacterial operons. Nature 289, 751–758 (1981)

    Article  Google Scholar 

  37. Yanofsky, C.: Transcription attenuation: once viewed as a novel regulatory strategy. J. Bacteriology 182(1), 1–8 (2000)

    Article  Google Scholar 

  38. Yanofsky, C.: RNA-based regulation of genes of tryptophan synthesis and degradation, in bacteria. RNA - A publication of the RNA Society 13(8), 1141–1154 (2007)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. University of Lille, France

    Céline Kuttler, Cédric Lhoussaine & Mirabelle Nebut

  2. BioComputing group, LIFL & IRI (CNRS UMR 8022 & USR 3078), Italy

    Mirabelle Nebut

Authors
  1. Céline Kuttler
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  2. Cédric Lhoussaine
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  3. Mirabelle Nebut
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Editor information

Editors and Affiliations

  1. Centre for Computational and Systems Biology, The Microsoft Research - University of Trento, Piazza Manci, 17, 38050, Povo (TN), Italy

    Corrado Priami

  2. Groningen Bioinformatics, University of Groningen, Centre, Kerklaan 30, 9751 NN, Haren, The Netherlands

    Rainer Breitling

  3. School of Information Systems, Brunel University, Kingston Lane, UB8 3PH, Uxbridge, UK

    David Gilbert

  4. Computer Science Institute, Brandenburg University of Technology, Walther-Pauer-Str. 2, 03046, Cottbus, Germany

    Monika Heiner

  5. Institute of Computer Science, University of Rostock, Joachim-Jungius-Str.10, 18059, Rostock, Germany

    Adelinde M. Uhrmacher

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Kuttler, C., Lhoussaine, C., Nebut, M. (2010). Rule-Based Modeling of Transcriptional Attenuation at the Tryptophan Operon. In: Priami, C., Breitling, R., Gilbert, D., Heiner, M., Uhrmacher, A.M. (eds) Transactions on Computational Systems Biology XII. Lecture Notes in Computer Science(), vol 5945. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11712-1_6

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  • DOI: https://doi.org/10.1007/978-3-642-11712-1_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11711-4

  • Online ISBN: 978-3-642-11712-1

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