Origins of Stochasticity and Burstiness in High-Dimensional Biochemical Networks

Springer Science and Business Media LLC - Tập 2009 - Trang 1-14 - 2008
Simon Rosenfeld1
1Division of Cancer Prevention (DCP), National Cancer Institute, Bethesda, USA

Tóm tắt

Two major approaches are known in the field of stochastic dynamics of intracellular biochemical networks. The first one places the focus of attention on the fact that many biochemical constituents vitally important for the network functionality may be present only in small quantities within the cell, and therefore the regulatory process is essentially discrete and prone to relatively big fluctuations. The second approach treats the regulatory process as essentially continuous. Complex pseudostochastic behavior in such processes may occur due to multistability and oscillatory motions within limit cycles. In this paper we outline the third scenario of stochasticity in the regulatory process. This scenario is only conceivable in high-dimensional highly nonlinear systems. In particular, we show that burstiness, a well-known phenomenon in the biology of gene expression, is a natural consequence of high dimensionality coupled with high nonlinearity. In mathematical terms, burstiness is associated with heavy-tailed probability distributions of stochastic processes describing the dynamics of the system. We demonstrate how the "shot" noise originates from purely deterministic behavior of the underlying dynamical system. We conclude that the limiting stochastic process may be accurately approximated by the "heavy-tailed" generalized Pareto process which is a direct mathematical expression of burstiness.

Tài liệu tham khảo

Schlitt T, Brazma A: Modelling gene networks at different organisational levels. FEBS Letters 2005, 579(8):1859-1866. 10.1016/j.febslet.2005.01.073 Bork P, Jensen LJ, von Mering C, Ramani AK, Lee I, Marcotte EM: Protein interaction networks from yeast to human. Current Opinion in Structural Biology 2004, 14(3):292-299. 10.1016/j.sbi.2004.05.003 Fiehn O: Metabolomics—the link between genotypes and phenotypes. Plant Molecular Biology 2002, 48(1-2):155-171. Raman R, Raguram S, Venkataraman G, Paulson JC, Sasisekharan R: Glycomics: an integrated systems approach to structure-function relationships of glycans. Nature Methods 2005, 2(11):817-824. 10.1038/nmeth807 Krauss G: Biochemistry of Signal Transduction and Regulation. Wiley-VCH, New York, NY, USA; 1999. May RM: Will a large complex system be stable? Nature 1972, 238(5364):413-414. 10.1038/238413a0 Golding I, Cox EC: RNA dynamics in live Escherichia coli cells. Proceedings of the National Academy of Sciences of the United States of America 2004, 101(31):11310-11315. 10.1073/pnas.0404443101 Golding I, Paulsson J, Zawilski SM, Cox EC: Real-time kinetics of gene activity in individual bacteria. Cell 2005, 123(6):1025-1036. 10.1016/j.cell.2005.09.031 Kærn M, Menzinger M, Hunding A: A chemical flow system mimics waves of gene expression during segmentation. Biophysical Chemistry 2000, 87(2-3):121-126. 10.1016/S0301-4622(00)00181-2 Yu J, Xiao J, Ren X, Lao K, Xie XS: Probing gene expression in live cells, one protein molecule at a time. Science 2006, 311(5767):1600-1603. 10.1126/science.1119623 Paulsson J: Summing up the noise in gene networks. Nature 2004, 427(6973):415-418. 10.1038/nature02257 Paulsson J: Prime movers of noisy gene expression. Nature Genetics 2005, 37(9):925-926. 10.1038/ng0905-925 Goldbeter A: Complex oscillatory phenomena, including multiple oscillations, in regulated biochemical systems. Biomedica Biochimica Acta 1985, 44(6):881-889. Goldbeter A: Computational approaches to cellular rhythms. Nature 2002, 420(6912):238-245. 10.1038/nature01259 Kepler TB, Elston TC: Stochasticity in transcriptional regulation: origins, consequences, and mathematical representations. Biophysical Journal 2001, 81(6):3116-3136. 10.1016/S0006-3495(01)75949-8 Raser JM, O'Shea EK: Noise in gene expression: origins, consequences, and control. Science 2005, 309(5743):2010-2013. 10.1126/science.1105891 Arnold L: Qualitative theory of stochastic non-linear systems. In Stochastic Nonlinear Systems. Edited by: Arnold L, Lefever R. Springer, Berlin, Germany; 1981:86-99. Kurtz TG: The relationship between stochastic and deterministic models for chemical reactions. The Journal of Chemical Physics 1972, 57(7):2976-2978. 10.1063/1.1678692 Kurtz TG: Solutions of ordinary differential equations as limits of pure jump Markov processes. Journal of Applied Probability 1972, 7(1):49-58. Pollett PK, Vassallo A: Diffusion approximation for some simple chemical reaction schemes. Advances in Applied Probability 1992, 24(4):875-893. 10.2307/1427717 Hoffmann A, Levchenko A, Scott ML, Baltimore D:The IB-NF-B signaling module: temporal control and selective gene activation. Science 2002, 298(5596):1241-1245. 10.1126/science.1071914 de Jong H, Geiselmann J, Hernandez C, Page M: Genetic network analyzer: qualitative simulation of genetic regulatory networks. Bioinformatics 2003, 19(3):336-344. 10.1093/bioinformatics/btf851 Mendes P: GEPASI: a software package for modelling the dynamics, steady states and control of biochemical and other systems. Computer Applications in the Biosciences 1993, 9(5):563-571. Voit EO: Computational Analysis of Biochemical Systems: A Practical Guide for Biochemists and Molecular Biologists. Cambridge University Press, Cambridge, UK; 2000. Barabási A-L, Oltvai ZN: Network biology: understanding the cell's functional organization. Nature Reviews Genetics 2004, 5(2):101-113. 10.1038/nrg1272 Just W, Kantz H, Rodenbeck C, Helm M: Stochastic modeling: replacing fast degrees of freedom. Journal of Physics A 2001, 34(15):3199-3213. 10.1088/0305-4470/34/15/302 Just W, Gelfert K, Baba N, Riegert A, Kantz H: Elimination of fast chaotic degrees of freedom: on the accuracy of the born approximation. Journal of Statistical Physics 2003, 112(1-2):277-292. Mori H, Fujisaka H, Shigematsu H: A new expansion of the master equation. Progress in Theoretical Physics 1974, 51(1):109-122. 10.1143/PTP.51.109 Zwanzig R: Ensemble method in the theory of Irreversibility. The Journal of Chemical Physics 1960, 33(5):1338-1341. 10.1063/1.1731409 Rosenfeld S: Stochastic cooperativity in non-linear dynamics of genetic regulatory networks. Mathematical Biosciences 2007, 210(1):121-142. 10.1016/j.mbs.2007.05.006 Savageau MA: Biochemical systems analysis I. Some mathematical properties of the rate law for the component enzymatic reactions. Journal of Theoretical Biology 1969, 25(3):365-369. 10.1016/S0022-5193(69)80026-3 Savageau MA, Voit EO: Recasting nonlinear differential equations as S-systems: a canonical nonlinear form. Mathematical Biosciences 1987, 87(1):83-115. 10.1016/0025-5564(87)90035-6 Voit EO: Canonical Nonlinear Modeling. S-System Approach to Understanding Complexity. Van Nostrand Reinhold, New York, NY, USA; 1991. Savageau MA: Biochemical systems analysis III. Dynamic solutions using a power-law approximation. Journal of Theoretical Biology 1970, 26(2):215-226. 10.1016/S0022-5193(70)80013-3 Kimura S, Ide K, Kashihara A, et al.: Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm. Bioinformatics 2005, 21(7):1154-1163. 10.1093/bioinformatics/bti071 Voit EO, Radivoyevitch T: Biochemical systems analysis of genome-wide expression data. Bioinformatics 2000, 16(11):1023-1037. 10.1093/bioinformatics/16.11.1023 Tournier L: Approximation of dynamical systems using S-systems theory: application to biological systems. Proceedings of the International Symposium on Symbolic and Algebraic Computation (ISSAC '05) Beijing, China July 2005 317-324. Kadonaga JT: Regulation of RNA polymerase II transcription by sequence-specific DNA binding factors. Cell 2004, 116(2):247-257. 10.1016/S0092-8674(03)01078-X Lemon B, Tjian R: Orchestrated response: a symphony of transcription factors for gene control. Genes and Development 2000, 14(20):2551-2569. 10.1101/gad.831000 Sorribas A, Savageau MA: Strategies for representing metabolic pathways within biochemical systems theory: reversible pathways. Mathematical Biosciences 1989, 94(2):239-269. 10.1016/0025-5564(89)90066-7 Brenig L: Complete factorisation and analytic solutions of generalized Lotka-Volterra equations. Physics Letters A 1988, 133(7-8):378-382. 10.1016/0375-9601(88)90920-6 Brenig L, Goriely A: Universal canonical forms for time-continuous dynamical systems. Physical Review A 1989, 40(7):4119-4122. 10.1103/PhysRevA.40.4119 Rosenfeld S: Stochastic oscillations in genetic regulatory networks: application to microarray experiments. EURASIP Journal on Bioinformatics and Systems Biology 2006, 2006:-12. Zumdahl S: Chemical Principles. Houghton Mifflin, New York, NY, USA; 2005. Gantmacher FR: Applications of the Theory of Matrices. Wiley-Interscience, New York, NY, USA; 1959. Nikolaev PI, Sokolov DP: Selection of an optimal biochemical reactor for microbiological synthesis. Chemical and Petroleum Engineering 1980, 16(12):707-710. 10.1007/BF01177082 Feinberg M: The existence and uniqueness of steady states for a class of chemical reaction networks. Archive for Rational Mechanics and Analysis 1995, 132(4):311-370. 10.1007/BF00375614 Qian H, Beard DA, Liang S-D: Stoichiometric network theory for nonequilibrium biochemical systems. European Journal of Biochemistry 2003, 270(3):415-421. 10.1046/j.1432-1033.2003.03357.x Ederer M, Gilles ED: Thermodynamically feasible kinetic models of reaction networks. Biophysical Journal 2007, 92(6):1846-1857. 10.1529/biophysj.106.094094 Colquhoun D, Dowsland KA, Beato M, Plested AJR: How to impose microscopic reversibility in complex reaction mechanisms. Biophysical Journal 2004, 86(6):3510-3518. 10.1529/biophysj.103.038679 Yang J, Bruno WJ, Hlavacek WS, Pearson JE: On imposing detailed balance in complex reaction mechanisms. Biophysical Journal 2006, 91(3):1136-1141. 10.1529/biophysj.105.071852 Bell SP, Learned RM, Jantzen HM, Tjian R: Functional cooperativity between transcription factors UBF1 and SL1 mediates human ribosomal RNA synthesis. Science 1988, 241(4870):1192-1197. 10.1126/science.3413483 Ptashne M: Regulated recruitment and cooperativity in the design of biological regulatory systems. Philosophical Transactions of the Royal Society A 2003, 361(1807):1223-1234. 10.1098/rsta.2003.1195 Bradley R: Basic properties of strong mixing conditions. A survey and some open questions. Probability Surveys 2005, 2: 107-144. Cramer H, Leadbetter R: Stationary and Related Stochastic Processes. John Wiley & Sons, New York, NY, USA; 1967. McNeil A, Frey R, Embrechts P: Quantitative Risk Management. Princeton University Press, Princeton, NJ, USA; 2005. Van Kampen NG: Stochastic Processes in Physics and Chemistry. North Holland, Amsterdam, The Netherlands; 2006. Lorenz EN: Deterministic nonperiodic flow. Journal of the Atmospheric Sciences 2006, 20(2):130-141. Gardiner CW: Handbook of Stochastic Methods: For Physics, Chemistry, and the Natural Sciences. Springer, Berlin, Germany; 1983. McAdams HH, Arkin A: Stochastic mechanisms in gene expression. Proceedings of the National Academy of Sciences of the United States of America 1997, 94(3):814-819. 10.1073/pnas.94.3.814 McAdams HH, Arkin A: It's a noisy business! Genetic regulation at the nanomolar scale. Trends in Genetics 1999, 15(2):65-69. 10.1016/S0168-9525(98)01659-X Wu J, Mehta NB, Zhang J: A flexible lognormal sum approximation method. Volume 6. Mitsubishi Electric Research Laboratories; Proceedings of the IEEE Global Telecommunications Conference (GLOBECOM '05) St. Louis, Mo, USA November-December 2005 3413-3417. Perko L: Differential Equations and Dynamical Systems. Springer, Berlin, Germany; 2001.