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SPECIAL TOPIC — Soft matter and biological physics
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SPECIAL TOPIC—Soft matter and biological physics |
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Noise decomposition algorithm and propagation mechanism in feed-forward gene transcriptional regulatory loop |
Rong Gui(桂容)1, Zhi-Hong Li(李治泓)1, Li-Jun Hu(胡丽君)1, Guang-Hui Cheng(程光晖)2, Quan Liu(刘泉)1, Juan Xiong(熊娟)1, Ya Jia(贾亚)3, Ming Yi(易鸣)1,4 |
1. Department of Physics, College of Science, Huazhong Agricultural University, Wuhan 430070, China; 2. Department of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan 430048, China; 3. Department of Physics and Institute of Biophysics, Central China Normal University, Wuhan 430079, China; 4. Institute of Applied Physics, Huazhong Agricultural University, Wuhan 430070, China |
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Abstract Feed-forward gene transcriptional regulatory networks, as a set of common signal motifs, are widely distributed in the biological systems. In this paper, the noise characteristics and propagation mechanism of various feed-forward gene transcriptional regulatory loops are investigated, including (i) coherent feed-forward loops with AND-gate, (ii) coherent feed-forward loops with OR-gate logic, and (iii) incoherent feed-forward loops with AND-gate logic. By introducing logarithmic gain coefficient and using linear noise approximation, the theoretical formulas of noise decomposition are derived and the theoretical results are verified by Gillespie simulation. From the theoretical and numerical results of noise decomposition algorithm, three general characteristics about noise transmission in these different kinds of feed-forward loops are observed. i) The two-step noise propagation of upstream factor is negative in the incoherent feed-forward loops with AND-gate logic, that is, upstream factor can indirectly suppress the noise of downstream factors. ii) The one-step propagation noise of upstream factor is non-monotonic in the coherent feed-forward loops with OR-gate logic. iii) When the branch of the feed-forward loop is negatively controlled, the total noise of the downstream factor monotonically increases for each of all feed-forward loops. These findings are robust to variations of model parameters. These observations reveal the universal rules of noise propagation in the feed-forward loops, and may contribute to our understanding of design principle of gene circuits.
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Received: 27 September 2017
Revised: 14 November 2017
Accepted manuscript online:
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PACS:
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87.18.Tt
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(Noise in biological systems)
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87.16.dj
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(Dynamics and fluctuations)
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02.50.-r
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(Probability theory, stochastic processes, and statistics)
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Fund: Project supported by the Fundamental Research Funds for the Central Universities, China (Grant Nos. 2662015QC041 and 2662014BQ069), the Huazhong Agricultural University Scientific & Technological Self-innovation Foundation, China (Grant No. 2015RC021), and the National Natural Science Foundation of China (Grant Nos. 11675060, 91730301, 11547244, and 11474117). |
Corresponding Authors:
Ming Yi
E-mail: yiming@mail.hzau.edu.cn
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About author: 87.18.Tt; 87.16.dj; 02.50.-r |
Cite this article:
Rong Gui(桂容), Zhi-Hong Li(李治泓), Li-Jun Hu(胡丽君), Guang-Hui Cheng(程光晖), Quan Liu(刘泉), Juan Xiong(熊娟), Ya Jia(贾亚), Ming Yi(易鸣) Noise decomposition algorithm and propagation mechanism in feed-forward gene transcriptional regulatory loop 2018 Chin. Phys. B 27 028706
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[1] |
Shen-Orr S S, Milo R, Mangan S and Alon U 2002 Nat. Genet. 31 64
|
[2] |
Paulsson J 2004 Nature 427 415
|
[3] |
Lev S T 2014 Rep. Prog. Phys. 77 026601
|
[4] |
Harada Y, Funatsu T, Murakami K, Nonoyama Y, Ishihama A and Yanagida T 1999 Biophys. J. 76 709
|
[5] |
Hasty J, Pradines J, Dolnik M and Collins J J 2000 Proc. Natl. Acad. Sci. USA 97 2075
|
[6] |
Swain P S, Elowitz M B and Siggia E D 2002 Proc. Natl. Acad. Sci. USA 99 12795
|
[7] |
McAdams H H and Arkin A 1997 Proc. Natl. Acad. Sci. USA 94 814
|
[8] |
Arkin A, Ross J and McAdams H H 1998 Genetics 149 1633
|
[9] |
Barkai N and Leibler S 2000 Nature 403 267
|
[10] |
Rao C V, Wolf D M and Arkin A P 2002 Nature 420 231
|
[11] |
Raser J M and O'Shea E K 2005 Science 309 2010
|
[12] |
Arkin A, Ross J and Mcadams H H 1998 Genetics 149 1633
|
[13] |
Barkai N and Leibler S 2000 Nature 403 267
|
[14] |
Acar M, Becskei A and van Oudenaarden A 2005 Nature 435 228
|
[15] |
Berridge M J 2001 Novartis Found. Symp. 239 52
|
[16] |
Lewis R S 2001 Ann. Rev. Immunol. 19 497
|
[17] |
Harris S L and Levine A J 2005 Oncogene 24 2899
|
[18] |
Liu X, Wang X, Yang X, Liu S, Jiang L, Qu Y, Hu L, Ouyang Q and Tang C 2015 eLife 4 e03977
|
[19] |
Yang X, Lau K-Y, Sevim V and Tang C 2013 PLoS Biol. 11 e1001673
|
[20] |
Li W L, Yi M and Zou X F 2015 Quantum Biol. 3 55
|
[21] |
Li Y, Yi M and Zou X 2014 Sci. Rep. 4 5764
|
[22] |
Alon U 2007 Nat. Rev. Genet. 8 450
|
[23] |
Austin D W, Allen M S, McCollum J M, Dar R D, Wilgus J R, Sayler G S, Samatova N F, Cox C D and Simpson M L 2006 Nature 439 608
|
[24] |
Becskei A and Serrano L 2000 Nature 405 590
|
[25] |
Hsu C, Jaquet V, Maleki F and Becskei A 2016 J. Mol. Biol. 428 4115
|
[26] |
Hornung G and Barkai N 2008 PLoS Comp. Biol. 4 e8
|
[27] |
Hooshangi S and Weiss R 2006 Chaos 16 026108
|
[28] |
Mangan S and Alon U 2003 Proc. Natl. Acad. Sci. USA 100 11980
|
[29] |
Mangan S, Zaslaver A and Alon U 2003 J. Mol. Biol. 334 197
|
[30] |
Kalir S, Mangan S and Alon U 2005 Mol. Syst. Biol. 1 0006
|
[31] |
Mangan S, Itzkovitz S, Zaslaver A and Alon U 2006 J. Mol. Biol. 356 1073
|
[32] |
Bhaswar G, Rajesh K and Indrani B 2005 Phys. Biol. 2 36
|
[33] |
Kaplan S, Bren A, Dekel E and Alon U 2008 Mol. Syst. Biol. 4 203
|
[34] |
Kittisopikul M and Suel G M 2010 Proc. Natl. Acad. Sci. USA 107 13300
|
[35] |
Goentoro L, Shoval O, Kirschner M W and Alon U 2009 Mol. Cell 36 894
|
[36] |
Erez D, Shmoolik M and Uri A 2005 Phys. Biol. 2 81
|
[37] |
Kim D, Kwon Y K and Cho K H 2008 Bioessays 30 1204
|
[38] |
Guo D and Li C 2009 Phys. Rev. E:Stat. Nonlinear Soft Matter Phys. 79 051921
|
[39] |
Prill R J, Iglesias P A and Levchenko A 2005 PLoS Biol. 3 e343
|
[40] |
Macía J, Widder S and Solé R 2009 BMC Syst. Biol. 3 1
|
[41] |
Wall M E, Dunlop M J and Hlavacek W S 2005 J. Mol. Biol. 349 501
|
[42] |
Sontag E D 2010 IET Syst. Biol. 4 39
|
[43] |
Gui R, Liu Q, Yao Y, Deng H, Ma C, Jia Y and Yi M 2016 Front. Physiol. 7 600
|
[44] |
Bolouri H and Davidson E H 2002 Bioessays 24 1118
|
[45] |
Buchler N E, Gerland U and Hwa T 2003 Proc. Natl. Acad. Sci. USA 100 5136
|
[46] |
Setty Y, Mayo A E, Surette M G and Alon U 2003 Proc. Natl. Acad. Sci. USA 100 7702
|
[47] |
Gillespie D T 1977 J. Phys. Chem. 81 2340
|
[48] |
Brett T and Galla T 2013 Phys. Rev. Lett. 110 250601
|
[49] |
Jia Y and Li J R 1997 Phys. Rev. Lett. 78 994
|
[50] |
Thomas P, Straube A V and Grima R 2012 BMC Syst. Biol. 6 39
|
[51] |
Elf J and Ehrenberg M 2003 Genome Res. 13 2475
|
[52] |
Pedraza J M and van Oudenaarden A 2005 Science 307 1965
|
[53] |
Hornung G and Barkai N 2008 PLoS Comput. Biol. 4 e8
|
[54] |
Paulsson J 2005 Phys. Life Rev. 2 157
|
[55] |
Jia Y, Liu W, Li A, Yang L and Zhan X 2009 Biophys. Chem. 143 60
|
[56] |
Pei Q M, Zhan X, Yang L J, Shen J, Wang L F, Qui K, Liu T, Kirunda J B, Yousif A A, Li A B and Jia Y 2015 Phys. Rev. E 92 012721
|
[57] |
Scott M, Ingalls B and Kaern M 2006 Chaos 16 026107
|
[58] |
Goldbeter A and Koshland D E 1982 Q. Rev. Biophys. 15 555
|
[59] |
Ge M, Jia Y, Xu Y and Yang L 2017 Nonlinear Dyn.
|
[60] |
Lu L, Jia Y, Liu W and Yang L 2017 Complexity 2017 7628537
|
[61] |
Liu B, Yan S W and Geng Y Z 2011 Chin. Phys. B 20 128702
|
[62] |
Yuan L, Liu Z Q, Zhang H M, Ding X L, Yang M H, Gu H G and Ren W 2011 Chin. Phys. B 20 020508
|
[63] |
Wang H Q, Yu L C and Chen Y 2009 Acta Phys. Sin. 58 5070(in Chinese)
|
[64] |
Chen A M, Zhang J J, Yuan Z J and Zhou T S 2009 Acta Phys. Sin. 58 2804(in Chinese)
|
[65] |
Liu S J, Wang Q, Liu B, Yan S W and Sakata F 2011 Chin. Phys. B 20 128703
|
[66] |
Carey L B, van Dijk D, Sloot P M, Kaandorp J A and Segal E 2013 PLoS Biol. 11 e1001528
|
[67] |
Warmflash A and Dinner A R 2008 Proc. Natl. Acad. Sci. USA 105 17262
|
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