Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Synthetic approaches to study transcriptional networks and noise in mammalian systems

Synthetic approaches to study transcriptional networks and noise in mammalian systems

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Systems Biology — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Synthetic biology aims to build new functional organisms and to rationally re-design existing ones by applying the engineering principle of modularity. Apart from building new life forms to perform technical applications, the approach of synthetic biology is useful to dissect complex biological phenomena into simple and easy to understand synthetic modules. Synthetic gene networks have been successfully implemented in prokaryotes and lower eukaryotes, with recent approaches moving ahead towards the mammalian environment. However, synthetic circuits in higher eukaryotes present a more challenging scenario, since its reliability is compromised because of the strong stochastic nature of transcription. Here, the authors review recent approaches that take advantage of the noisy response of synthetic regulatory circuits to learn key features of the complex machinery that orchestrates transcription in higher eukaryotes. Understanding the causes and consequences of biological noise will allow us to design more reliable mammalian synthetic circuits with revolutionary medical applications.

References

    1. 1)
      • 31. Ardehali, M.B., Lis, J.T.: ‘Tracking rates of transcription and splicing in vivo’, Nat. Struct. Mol. Biol., 2009, 16, pp. 11231124.
    2. 2)
      • 32. Chandran, D., Copeland, W., Sleight, S., Sauro, H.: ‘Mathematical modeling and synthetic biology’, Drug Discov. Today: Disease Models, 2008, 5, pp. 299309.
    3. 3)
      • 11. Blake, W.J., Kaern, M., Cantor, C.R., Collins, J.J.: ‘Noise in eukaryotic gene expression’, Nature, 2003, 422, pp. 633637.
    4. 4)
      • 15. Peccoud, J., Ycart, B.: ‘Markovian modeling of gene-product synthesis’, Theor. Population Biol., 1995, 48, pp. 222234.
    5. 5)
      • 69. Gossen, M.: ‘Tight control of gene expression in mammalian cells by tetracycline-responsive promoters’. Proc. National Academy of Sciences of the United States of America, 1992, vol. 89, June, pp. 55475551.
    6. 6)
      • 33. Pedraza, J., van Oudenaarden, A.: ‘Noise propagation in gene networks’, Sci. Signalling, 2005, 307, (March), pp. 19651969.
    7. 7)
      • 61. Xiang, S., Fruehauf, J., Li, C.J.: ‘Short hairpin RNA-expressing bacteria elicit RNA interference in mammals’, Nat. Biotechnol., 2006, 24, pp. 697702.
    8. 8)
      • 51. Rosenfeld, N., Elowitz, M.B., Alon, U.: ‘Negative autoregulation speeds the response times of transcription networks’, J. Mol. Biol., 2002, 323, pp. 785793.
    9. 9)
      • 8. Elowitz, M.B., Leibler, S.: ‘A synthetic oscillatory network of transcriptional regulators’, Nature, 2000, 403, pp. 335338.
    10. 10)
      • 45. Weber, W., Fussenegger, M.: ‘Engineering of synthetic mammalian gene networks’, Chem.Biol., 2009, 16, pp. 287297.
    11. 11)
      • 36. Serizawa, S., Miyamichi, K., Nakatani, H., et al: ‘Negative feedback regulation ensures the one receptor-one olfactory neuron rule in mouse’, Science, 2003, 302, pp. 20882094.
    12. 12)
      • 6. Benner, S.A., Sismour, A.M.: ‘Synthetic biology’, Nat. Rev. Genet., 2005, 6, pp. 533543.
    13. 13)
      • 55. Steuer, R., Zhou, C., Kurths, J.: ‘Constructive effects of uctuations in genetic and biochemical regulatory systems’, Biosystems, 2003, 72, pp. 241251.
    14. 14)
      • 60. Anderson, J.C., Clarke, E.J., Arkin, A.P., Voigt, C.A.: ‘Environmentally controlled invasion of cancer cells by engineered bacteria’, J. Mol. Biol., 2006, 355, pp. 619627.
    15. 15)
      • 42. Burrill, D.R., Inniss, M.C., Boyle, P.M., Silver, P.A.: ‘Synthetic memory circuits for tracking human cell fate’, Genes  Dev., 2012, 26, pp. 14861497.
    16. 16)
      • 49. Austin, D.W., Allen, M.S., McCollum, J.M., et al: ‘Gene network shaping of inherent noise spectra’, Nature, 2006, 439, pp. 608611.
    17. 17)
      • 22. Swinburne, I.A., Silver, P.A.: ‘Intron delays and transcriptional timing during development’, Dev. Cell, 2008, 14, pp. 324330.
    18. 18)
      • 26. Goldbeter, A.: ‘Computational approaches to cellular rhythms’, Nature, 2002, 420, pp. 238245.
    19. 19)
      • 18. Ross, I.L., Browne, C.M., Hume, D.A.: ‘Transcription of individual genes in eukaryotic cells occurs randomly and infrequently’, Immunology  Cell Biol., 1994, 72, pp. 177185.
    20. 20)
      • 19. Newlands, S., Levitt, L.K., Robinson, C.S., et al: ‘Transcription occurs in pulses in muscle fibers’, Genes  Dev., 1998, 12, pp. 27482758.
    21. 21)
      • 1. Purnick, P.E.M., Weiss, R.: ‘The second wave of synthetic biology: from modules to systems’, Nat. Rev. Mol. Cell Biol., 2009, 10, pp. 410422.
    22. 22)
      • 70. Aubel, D., Fussenegger, M.: ‘Mammalian synthetic biology–from tools to therapies’, BioEssays: News  Rev. Mol., Cell. Dev. Biol., 2010, 32, pp. 332345.
    23. 23)
      • 48. Becskei, A.: ‘Engineering stability in gene networks by autoregulation’, Nature, 2000, (June), 405, pp. 590593.
    24. 24)
      • 41. May, T., Butueva, M., Bantner, S., et al: ‘Synthetic gene regulation circuits for control of cell expansion’, Tissue Eng. Part A, 2010, 16, pp. 441452.
    25. 25)
      • 24. Swinburne, I.A., Miguez, D.G., Landgraf, D., Silver, P.A.: ‘Intron length increases oscillatory periods of gene expression in animal cells’, Genes  Dev., 2008, 22, pp. 23422346.
    26. 26)
      • 10. Elowitz, M.B., Levine, A.J., Siggia, E.D., Swain, P.S.: ‘Stochastic gene expression in a single cell’, Science, 2002, 297, pp. 11831186.
    27. 27)
      • 34. Yu, W., Nomura, M., Ikeda, M.: ‘Interactivating feedback loops within the mammalian clock: BMAL1 is negatively autoregulated and upregulated by CRY1, CRY2, and PER2’, Biochem. Biophys. Res. Commun., 2002, 290, pp. 933941.
    28. 28)
      • 23. Manak, J.R., Dike, S., Sementchenko, V., et al: ‘Biological function of unannotated transcription during the early development of Drosophila melanogaster’, Nat. Genetics, 2006, 38, pp. 11511158.
    29. 29)
      • 14. Karlebach, G., Shamir, R.: ‘Modelling and analysis of gene regulatory networks’, Nat. Rev. Mol. Cell Biol., 2008, 9, pp. 770780.
    30. 30)
      • 38. Greber, D., Fussenegger, M.: ‘Mammalian synthetic biology: engineering of sophisticated gene networks’, J. Biotechnol., 2007, 130, pp. 329345.
    31. 31)
      • 25. Lewis, J.: ‘Autoinhibition with transcriptional delay: a simple mechanism for the zebrafish somitogenesis oscillator’, Curr. Biol., 2003, 13, pp. 13981408.
    32. 32)
      • 46. Simpson, M.L., Cox, C.D., Sayler, G.S.: ‘Frequency domain analysis of noise in autoregulated gene circuits’. Proc. National Academy of Sciences of the United States of America, April 2003, vol. 100, pp. 45514556.
    33. 33)
      • 57. Colman-Lerner, A., Gordon, A., Serra, E., et al: ‘Regulated cell-to-cell variation in a cell-fate decision system’, Nature, 2005, 437, pp. 699706.
    34. 34)
      • 5. Mukherji, S., van Oudenaarden, A.: ‘Synthetic biology: understanding biological design from synthetic circuits’, Nat. Rev. Genet., 2009, 10, pp. 859871.
    35. 35)
      • 4. Andrianantoandro, E., Basu, S., Karig, D.K., Weiss, R.: ‘Synthetic biology: new engineering rules for an emerging discipline’, Mol. Syst. Biol., 2006, 2, pp. 2006.0028.
    36. 36)
      • 17. Karmakar, R., Bose, I.: ‘Graded and binary responses in stochastic gene expression’, Phys. Biol., 2004, 1, pp. 197204.
    37. 37)
      • 58. Weber, W., Fussenegger, M.: ‘Synthetic gene networks in mammalian cells’, Curr. Opin. Biotechnol., 2010, 21, pp. 690696.
    38. 38)
      • 67. Ellis, T., Wang, X., Collins, J.J.: ‘Diversity-based, model-guided construction of synthetic gene networks with predicted functions’, Nat. Biotechnol., 2009, 27, pp. 465471.
    39. 39)
      • 62. Amidi, M., de Raad, M., Crommelin, D.J.A., Hennink, W.E., Mastrobattista, E.: ‘Antigenexpressing immunostimulatory liposomes as a genetically programmable synthetic vaccine’, Syst. Synth. Biol., 2011, 5, pp. 2131.
    40. 40)
      • 28. Adelman, K., La Porta, A., Santangelo, T.J., Lis, J.T., Roberts, J.W., Wang, M.D.: ‘Single molecule analysis of RNA polymerase elongation reveals uniform kinetic behavior’. Proc. National Academy of Sciences of the United States of America, October 2002, vol. 99, pp. 1353813543.
    41. 41)
      • 44. Isaacs, F.J., Hasty, J., Cantor, C.R., Collins, J.J.: ‘Prediction and measurement of an autoregulatory genetic module’. Proc. National Academy of Sciences of the United States of America, June 2003, vol. 100, pp. 77147719.
    42. 42)
      • 39. Xiong, W.: ‘A positive-feedback-based bistable ‘memory module’ that governs a cell fate decision’, Nature, 2003, 426, (November), pp. 460465.
    43. 43)
      • 2. Agapakis, C.M., Silver, P.A.: ‘Synthetic biology: exploring and exploiting genetic modularity through the design of novel biological networks’, Mol. BioSyst., 2009, 5, pp. 704713.
    44. 44)
      • 29. Darzacq, X., Shav-Tal, Y., de Turris, V., et al: ‘In vivo dynamics of RNA polymerase II transcription’, Nat. Struct. Mol. Biol., 2007, 14, pp. 796806.
    45. 45)
      • 66. Zheng, Y., Sriram, G.: ‘Mathematical modeling: bridging the gap between concept and realization in synthetic biology’, J. Biomed. Biotechnol., 2010, 2010, pp. 541609.
    46. 46)
      • 37. Angeli, D., Ferrell, J.E., Sontag, E.D.: ‘Detection of multistability, bifurcations, and hysteresis in a large class of biological positive-feedback systems’. Proc. National Academy of Sciences of the United States of America, February 2004, vol. 101, pp. 18221827.
    47. 47)
      • 7. Gardner, T.S., Cantor, C.R., Collins, J.J.: ‘Construction of a genetic toggle switch in Escherichia coli’, Nature, 2000, 403, pp. 339342.
    48. 48)
      • 16. Pedraza, J.M., Paulsson, J.: ‘Effects of molecular memory and bursting on fluctuations in gene expression’, Science, 2008, 319, pp. 339343.
    49. 49)
      • 21. Hager, G.L., McNally, J.G., Misteli, T.: ‘Transcription dynamics’, Mol. Cell, 2009, 35, pp. 741753.
    50. 50)
      • 50. Dublanche, Y., Michalodimitrakis, K., Kümmerer, N., Foglierini, M., Serrano, L.: ‘Noise in transcription negative feedback loops: simulation and experimental analysis’, Mol. Syst. Biol., 2006, 2, pp. 41.
    51. 51)
      • 63. Gonzalez-Nicolini, V., Fux, C., Fussenegger, M.: ‘A novel mammalian cell-based approach for the discovery of anticancer drugs with reduced cytotoxicity on non-dividing cells’, Invest. New Drugs, 2004, 22, pp. 253262.
    52. 52)
      • 64. Weber, W., Fussenegger, M.: ‘Pharmacologic transgene control systems for gene therapy’,  J.  Gene Med., 2006, 8, pp. 535556.
    53. 53)
      • 56. Chabot, J.R., Pedraza, J.M., Luitel, P., van Oudenaarden, A.: ‘Stochastic gene expression out-of-steady-state in the cyanobacterial circadian clock’, Nature, 2007, 450, pp. 12491252.
    54. 54)
      • 54. Ptashne, M.: ‘On the use of the word ‘epigenetic’’, Curr. Biol.: CB, 2007, 17, pp. R233R236.
    55. 55)
      • 13. Cai, L., Friedman, N., Xie, X.S.: ‘Stochastic protein expression in individual cells at the single molecule level’, Nature, 2006, 440, pp. 358362.
    56. 56)
      • 30. Tolic-Norrelykke, S.F.: ‘Diversity in the rates of transcript elongation by single RNA polymerase molecules’, J. Biol. Chem., 2003, 279, pp. 32923299.
    57. 57)
      • 59. Weber, W., Schoenmakers, R., Keller, B., et al: ‘A synthetic mammalian gene circuit reveals antituberculosis compounds’, PNAS, 2008, 105, (29), pp. 99949998.
    58. 58)
      • 68. Nandagopal, N., Elowitz, M.B.: ‘Synthetic biology: integrated gene circuits’, Science, 2011, 333, pp. 12441248.
    59. 59)
      • 43. Becskei, A., Séraphin, B., Serrano, L.: ‘Positive feedback in eukaryotic gene networks: cell differentiation by graded to binary response conversion’,  EMBO J., 2001, 20, pp. 25282535.
    60. 60)
      • 3. Young, E., Alper, H.: ‘Synthetic biology: tools to design, build, and optimize cellular processes’, J. Biomed. Biotechnol., 2010, 2010, pp. 130781.
    61. 61)
      • 35. Geva-Zatorsky, N., Rosenfeld, N., Itzkovitz, S., et al: ‘Oscillations and variability in the p53 system’, Mol. Syst. Biol., 2006, 2, pp. 2006.0033.
    62. 62)
      • 20. Becskei, A., Kaufmann, B.B., van Oudenaarden, A.: ‘Contributions of low molecule number and chromosomal positioning to stochastic gene expression’, Nat. Genetics, 2005, 37, pp. 937944.
    63. 63)
      • 47. Paulsson, J.: ‘Summing up the noise in gene networks’, Nature, 2004, 427, pp. 415418.
    64. 64)
      • 27. Wang, M.D.: ‘Force and velocity measured for single molecules of RNA polymerase’, Science, 1998, 282, pp. 902907.
    65. 65)
      • 53. Kaern, M., Elston, T.C., Blake, W.J., Collins, J.J.: ‘Stochasticity in gene expression: from theories to phenotypes’, Nat. Rev. Genetics, 2005, 6, pp. 451464.
    66. 66)
      • 52. Eldar, A., Elowitz, M.B.: ‘Functional roles for noise in genetic circuits’, Nature, 2010, 467, pp. 167173.
    67. 67)
      • 40. Kramer, B.P., Fussenegger, M.: ‘Hysteresis in a synthetic mammalian gene network’. Proc. National Academy of Sciences of the United States of America, July 2005, vol. 102, pp. 95179522.
    68. 68)
      • 12. Raj, A., Peskin, C.S., Tranchina, D., Vargas, D.Y., Tyagi, S.: ‘Stochastic mRNA synthesis in mammalian cells’, PLoS Biol., 2006, 4, pp. e309.
    69. 69)
      • 9. Raj, A., van Oudenaarden, A.: ‘Nature, nurture, or chance: stochastic gene expression and its consequences’, Cell, 2008, 135, pp. 216226.
    70. 70)
      • 65. Weber, W., Fussenegger, M.: ‘Approaches for trigger-inducible viral transgene regulation in gene-based tissue engineering’, Curr. Opin. Biotechnol., 2004, 15, pp. 383391.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-syb.2012.0026
Loading

Related content

content/journals/10.1049/iet-syb.2012.0026
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address