Skip to main content
SpringerLink
Log in

Evolutionary Principles Underlying Structure and Response Dynamics of Cellular Networks

  • Chapter
  • First Online:
Evolutionary Systems Biology

Part of the book series: Advances in Experimental Medicine and Biology ((volume 751))

Abstract

The network view in systems biology, in conjunction with the continuing development of experimental technologies, is providing us with the key structural and dynamical features of both cell-wide and pathway-level regulatory, signaling and metabolic systems. These include for example modularity and presence of hub proteins at the structural level and ultrasensitivity and feedback control at the level of dynamics. The uncovering of such features, and the seeming commonality of some of them, makes many systems biologists believe that these could represent design principles that underpin cellular systems across organisms. Here, we argue that such claims on any observed feature requires an understanding of how it has emerged in evolution and how it can shape subsequent evolution. We review recent and past studies that aim to achieve such evolutionary understanding for observed features of cellular networks. We argue that this evolutionary framework could lead to deciphering evolutionary origin and relevance of proposed design principles, thereby allowing to predict their presence or absence in an organism based on its environment and biochemistry and their effect on its future evolution.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Akman OE, Rand DA Brown PE, Millar AJ (2010) Robustness from flexibility in the fungal circadian clock. BMC Syst Biol 4. doi:10.1186/1752–0509–4–88

    Google Scholar 

  2. Albert R, Jeong H, Barabasi AL (2000) Error and attack tolerance of complex networks. Nature 406(6794). doi:10.1038/35019019

    Google Scholar 

  3. Alon U, Surette MG, Barkai N Leibler S (1999) Robustness in bacterial chemotaxis. Nature 406(6715). doi:10.1038/16483

    Google Scholar 

  4. Alonso JM, Stepanova AN, Leisse TJ, Kim CJ, Chen H, Shinn P, Stevenson DK, et al (2003) Genome-wide insertional mutagenesis of Arabidopsis thaliana. Science (New York, NY) 301(5633). doi:10.1126/science.1086391

    Google Scholar 

  5. Anderson RM, May RM (1991) Infectious diseases of humans: dynamics and control Oxford University Press, Oxford, New York p. 757

    Google Scholar 

  6. Artzy-Randrup Y, Fleishman SJ, Ben-Tal N, Stone L (2004) Comment on network motifs: simple building blocks of complex networks and superfamilies of evolved and designed networks. Science (New York, NY) 305(5687). doi:10.1126/science.1099334

    Google Scholar 

  7. Azevedo RB, Lohaus R, Srinivasan S, Dang KK, Burch CL (2006) Sexual reproduction selects for robustness and negative epistasis in artificial gene networks. Nature 440(7080). doi:10.1038/nature04488

    Google Scholar 

  8. Bagheri HC, Wagner GP (2004) Evolution of dominance in metabolic pathways. Genetics 168(3). doi:10.1534/genetics.104.028696

    Google Scholar 

  9. Barabasi AL, Albert R (1999) Emergence of Scaling in Random Networks. Science (New York, NY) 286(5439):509–512

    Google Scholar 

  10. Barabási A-L, Oltvai ZN (2004) Network biology: understanding the cell’s functional organization. Nat Rev Genet 5(2). doi:10.1038/nrg1272

    Google Scholar 

  11. Barik D, Baumann WT, Paul MR, Novak B, Tyson JJ (2010) A model of yeast cell-cycle regulation based on multisite phosphorylation. Mol Syst Biol 6. doi:10.1038/msb.2010.55

    Google Scholar 

  12. Barkai N, Leibler S (1997) Robustness in simple biochemical networks. Nature 387 (6636):913–917

    PubMed  CAS  Google Scholar 

  13. Bashor CJ, Helman NC, Yan S, Lim WA (2008) Using engineered scaffold interactions to reshape MAP kinase pathway signaling dynamics. Science (New York, NY) 319(5869). doi:10.1126/science.1151153

    Google Scholar 

  14. Batchelor E, Goulian M (2003) Robustness and the cycle of phosphorylation and dephosphorylation in a two-component regulatory system. Proc Natl Acad Sci USA 100(2). doi:10.1073/pnas.0234782100

    Google Scholar 

  15. Bergman A, Siegal ML (2003) Evolutionary capacitance as a general feature of complex gene networks. Nature 424(6948). doi:10.1038/nature01765

    Google Scholar 

  16. Berg HC, Brown DA (1972) Chemotaxis in Escherichia coli analyzed by three-dimensional tracking. Nature 239:500–504

    PubMed  CAS  Google Scholar 

  17. Bischofs IB, Hug JA, Liu AW, Wolf DM, Arkin AP (2009) Complexity in bacterial cell-cell communication: quorum signal integration and subpopulation signaling in the bacillus subtilis phosphorelay. Proc Natl Acad Sci USA 106(16). doi:10.1073/pnas.0810878106

    Google Scholar 

  18. Bhavsar AP, Guttman JA, Finlay BB (2007) Manipulation of host-cell pathways by bacterial pathogens. Nature 449(7164). doi:10.1038/nature06247

    Google Scholar 

  19. Blank LM, Kuepfer L, Sauer U (2005) Large-scale 13C-flux analysis reveals mechanistic principles of metabolic network robustness to null mutations in yeast. Genome Biol 6(6). doi:10.1186/gb-2005–6–6-r49

    Google Scholar 

  20. Bray D (2003) molecular networks: the top-down view. Science (New York, NY) 301(5641). doi:10.1126/science.1089118

    Google Scholar 

  21. Bray D, Levin MD, Lipkow K (2007) The chemotactic behavior of computer-based surrogate bacteria. Curr Biol 17(1). doi:10.1016/j.cub.2006.11.027

    Google Scholar 

  22. Celani A, Vergassola M (2010) Bacterial strategies for chemotaxis response. Proc Natl Acad Sci USA. doi:10.1073/pnas.0909673107

    PubMed  Google Scholar 

  23. Chickarmane V, Kholodenko BN, Sauro HM (2007) Oscillatory dynamics arising from competitive inhibition and multisite phosphorylation. J Theor Biol 244(1). doi:10.1016/j.jtbi.2006.05.013

    Google Scholar 

  24. Clark DA, Grant LC (2005) The bacterial chemotactic response reflects a compromise between transient and steady-state behavior. Proc Natl Acad Sci USA 102(26). doi:10.1073/pnas.0407659102

    Google Scholar 

  25. Cluzel P, Surette M, Leibler S (2000) An ultrasensitive bacterial motor revealed by monitoring signaling proteins in single cells. Science 287(5458):1652–1655

    PubMed  CAS  Google Scholar 

  26. Cooper VS, Lenski RE (2000) The population genetics of ecological specialization in evolving Escherichia coli populations. Nature 407(6805). doi:10.1038/35037572

    Google Scholar 

  27. Cordero OX, Hogeweg P (2006) Feed-forward loop circuits as a side effect of genome evolution. Mol Biol Evol 23(10). doi:10.1093/molbev/msl060

    Google Scholar 

  28. Cornish-Bowden A (1987) Dominance is not inevitable. J Theor Biol 125(3):333–338

    PubMed  CAS  Google Scholar 

  29. de Gennes P-G (2004) Chemotaxis: the role of internal delays. Eur Biophys J 33(8). doi:10.1007/s00249–004–0426-z

    Google Scholar 

  30. Del Vecchio D, Ninfa AJ, Sontag ED (2008) Modular cell biology: retroactivity and insulation. Mol Syst Biol 4. doi:10.1038/msb4100204

    Google Scholar 

  31. de Wit PJGM (2007) How plants recognize pathogens and defend themselves. Cell Mol Life Sci 64(21). doi:10.1007/s00018–007–7284–7

    Google Scholar 

  32. Egbert MD, Barandiaran XE, Di Paolo EA (2010) A minimal model of metabolism-based chemotaxis. PLoS Comput Biol 6(12). doi:10.1371/journal.pcbi.1001004

    Google Scholar 

  33. Endres RG, Wingreen NS (2006) Precise adaptation in bacterial chemotaxis through assistance neighborhoods. Proc Natl Acad Sci USA 103(35). doi:10.1073/pnas.0603101103

    Google Scholar 

  34. Espinosa-Soto C, Wagner A (2010) Specialization can drive the evolution of modularity. PLoS Comput Biol 6(3). doi:10.1371/journal.pcbi.1000719

    Google Scholar 

  35. Fisher RA (1928) The possible modification of the response of the wild type to recurrent mutations. Am Nat:115–126

    Google Scholar 

  36. Force A, Cresko WA, Pickett FB, Proulx SR, Amemiya C, Lynch M (2005) The origin of subfunctions and modular gene regulation. Genetics 170(1). doi:10.1534/genetics.104.027607

    Google Scholar 

  37. Foster KR (2011) The sociobiology of molecular systems. Nature Rev Genet 12(3). doi:10.1038/nrg2903

    Google Scholar 

  38. Foster KR, Shaulsky G, Strassmann JE, Queller DC, Thompson CRL (2004) Pleiotropy as a mechanism to stabilize cooperation. Nature 431(7009). doi:10.1038/nature02894

    Google Scholar 

  39. Freschi L, Courcelles M, Thibault P, Michnick SW, Landry CR (2011) Phosphorylation network rewiring by gene duplication. Mol Syst Biol 7. doi:10.1038/msb.2011.43

    Google Scholar 

  40. Gerhart J, Kirschner M (2007) The theory of facilitated variation. Proc Natl Acad Sci USA 104(1):8582

    PubMed  CAS  Google Scholar 

  41. Giaever G, Chu AM, Ni L, Connelly C, Riles L, Véronneau S, Dow S others (2002) Functional profiling of the Saccharomyces cerevisiae genome. Nature 418(6896). doi:10.1038/nature00935

    Google Scholar 

  42. Goldbeter A, Koshland DE (1981) An amplified sensitivity arising from covalent modification in biological systems. Proc Natl Acad Sci USA 78(11) 6840–6844

    PubMed  CAS  Google Scholar 

  43. Goldstein RA, Soyer OS (2008) Evolution of taxis responses in virtual bacteria: non-adaptive dynamics. PLoS Comput Biol 4(5). doi:10.1371/journal.pcbi.1000084

    Google Scholar 

  44. Gomez-Uribe S, Verghese GC, Mirny LA (2007) Operating regimes of signaling cycles: statics, dynamics, and noise filtering. PLoS Comput Biol 3(12) 2487–2497

    CAS  Google Scholar 

  45. Gonze D, Halloy J, Goldbeter A (2002) Robustness of circadian rhythms with respect to molecular noise. Proc Natal Acad Sci USA 99(2). doi:10.1073/pnas.022628299

    Google Scholar 

  46. Gould SJ (1985) Not necessarily a wing: Which came first, the function or the form? Nat History 94:10, p12

    Google Scholar 

  47. Gould SJ, Vrba ES (1982) Exaptation-a missing term in the science of form. Paleobiology: 4–15

    Google Scholar 

  48. Groban ES, Clarke EJ, Salis HM, Miller SM, Voigt CA (2009) Kinetic buffering of cross talk between bacterial two-component sensors. J Mol Biol 390(3). doi:10.1016/j.jmb.2009.05.007

    Google Scholar 

  49. Grossniklaus U, Madhusudhan MS, Nanjundiah V (1996) Nonlinear enzyme kinetics can lead to high metabolic flux control coefficients: implications for the evolution of dominance. J Theor Biol 182(3). doi:10.1006/jtbi.1996.0167

    Google Scholar 

  50. Gu Z, Steinmetz LM, Gu X, Scharfe C, Davis RW, Li WH (2003) Role of duplicate genes in genetic robustness against null mutations. Nature 421(6918). doi:10.1038/nature01198

    Google Scholar 

  51. Guelzim N, Bottani S, Bourgine P, Képès F (2002) Topological and causal structure of the yeast transcriptional regulatory network. Nat Genet 31(1). doi:10.1038/ng873

    Google Scholar 

  52. Hamer R, Chen PY, Armitage JP Reinert G, Deane CM (2010) Deciphering chemotaxis pathways using cross species comparisons. BMC Syst Biol 4. doi:10.1186/1752–0509–4–3

    Google Scholar 

  53. Hao N, Nayak S, Behar M, Shanks RH, Nagiec MJ, Errede B, Hasty J, Elston TC, Dohlman HG (2008) Regulation of cell signaling dynamics by the protein kinase-scaffold Ste5. Mol Cell 30(5). doi:10.1016/j.molcel.2008.04.016

    Google Scholar 

  54. Harrison R, Papp B, Pál C, Oliver SG, Delneri D (2007) Plasticity of genetic interactions in metabolic networks of yeast. Proc Natal Acad Sci USA 104(7). doi:10.1073/pnas.0607153104

    Google Scholar 

  55. Hartwell LH, Hopfield JJ, Leibler S, Murray AW (1999) From molecular to modular cell biology. Nature 402(6761). doi:10.1038/35011540

    Google Scholar 

  56. Haseltine EL, Arnold FH (2007) Synthetic gene circuits: design with directed evolution. Ann Rev Biophys Biomol Struct 36. doi:10.1146/annurev.biophys.36.040306.132600

    Google Scholar 

  57. Heinrich R, Schuster S (1996) The regulation of cellular systems. Springer, US

    Google Scholar 

  58. Heinrich R, Montero F, Klipp E, Waddell TG, Melendez-Hevia E (1997) Theoretical approaches to the evolutionary optimization of glycolysis: thermodynamic and kinetic constraints. Eur J Biochem/FEBS 243(1–2):191

    CAS  Google Scholar 

  59. Heinrich R, Schuster S, Holzhütter HG (1991) Mathematical analysis of enzymic reaction systems using optimization principles. Eur J Biochem 201(1):1–21

    PubMed  CAS  Google Scholar 

  60. Hintze A, Adami C (2008) Evolution of complex modular biological networks. PLoS Comput Biol 4(2):e23

    PubMed  Google Scholar 

  61. Hoffmann A, Levchenko A Scott ML, Baltimore D (2002) The Ikappab-Nf-Kappab signaling module: temporal control and selective gene activation. Science (New York, NY) 298(5596). doi:10.1126/science.1071914

    Google Scholar 

  62. Hong RL, Sommer RJ (2006) Chemoattraction in pristionchus nematodes and implications for insect recognition. Curr Biol 16(23). doi:10.1016/j.cub.2006.10.031

    Google Scholar 

  63. Ingolia NT (2004) Topology and robustness in the drosophila segment polarity network. PLoS Biol 2(6). doi:10.1371/journal.pbio.0020123

    Google Scholar 

  64. Jeong H, Tombor B, Albert R, Oltvai ZN, Barabási AL (2000) The large-scale organization of metabolic networks. Nature 407(6804):651–654

    PubMed  CAS  Google Scholar 

  65. Kacser H, Burns JA (1981) The molecular basis of dominance. Genetics 97(3–4):639–666

    PubMed  CAS  Google Scholar 

  66. Kacser H, Beeby R (1984) Evolution of catalytic proteins or on the origin of enzyme species by means of natural selection. J Mol Evol 20(1):38–51

    PubMed  CAS  Google Scholar 

  67. Kalir S, Mangan S, Alon U (2005) A coherent feed-forward loop with a SUM input function prolongs flagella expression in Escherichia coli. Mol Syst Biol 1. doi:10.1038/msb4100010

    Google Scholar 

  68. Kamath RS, Fraser AG, Dong Y, Poulin G, Durbin R, Gotta M, Kanapin A, others (2003) Systematic functional analysis of the Caenorhabditis elegans genome using Rnai. Nature 421(6920):231–237

    Google Scholar 

  69. Kaneko K (2007) Evolution of robustness to noise and mutation in gene expression dynamics. PloS One 2(5). doi:10.1371/journal.pone.0000434

    Google Scholar 

  70. Kaneko K (2011) Proportionality between variances in gene expression induced by noise and mutation: consequence of evolutionary robustness. BMC Evol Biol 11. doi:10.1186/1471–2148–11–27

    Google Scholar 

  71. Kashtan N, Alon U (2005) Spontaneous evolution of modularity and network motifs. Proc Natal Acad Sci USA 102(39). doi:10.1073/pnas.0503610102

    Google Scholar 

  72. Keller EF (2005) Revisiting “scale-free” networks. BioEssays 27(10). doi:10.1002/bies.20294

    Google Scholar 

  73. Kingslover JG, Koehl MAR (1985) Aerodynamics, thermoregulation, and the evolution of insect wings: differential scaling and evolutionary change. Int J Org Evol:488–504

    Google Scholar 

  74. Klipp E, Heinrich R, Holzhütter HG (2002) Prediction of temporal gene expression. Eur J Biochem 269(22)

    Google Scholar 

  75. Kollmann M, Løvdok L, Bartholomé K, Timmer J, Sourjik V (2005) Design principles of a bacterial signalling network. Nature 438(7067). doi:10.1038/nature04228

    Google Scholar 

  76. Kühner S, van Noort V, Betts MJ, Leo-Macias A, Batisse C, Rode M, Yamada T, others (2009) Proteome organization in a genome-reduced bacterium. Science (New York, NY) 326(5957). doi:10.1126/science.1176343

    Google Scholar 

  77. LaPorte DC, Walsh K, Koshland DE (1984) The branch point effect. Ultrasensitivity and subsensitivity to metabolic control. J Biol Chem 259(22) 14068–14075

    CAS  Google Scholar 

  78. Lee TI, Rinaldi NJ, Robert F, Odom DT, Bar-Joseph Z, Gerber GK, Hannett NM, Harbison CT, Thompson CM, Simon I (2002) Transcriptional regulatory networks in Saccharomyces cerevisiae. Science 298(5594):799

    PubMed  CAS  Google Scholar 

  79. Legewie S, Herzel H, Westerhoff HV, Blüthgen N (2008) Recurrent design patterns in the feedback regulation of the mammalian signalling network. Mol Syst Biol 4. doi:10.1038/msb.2008.29

    Google Scholar 

  80. Lipson H, Pollack JB, Suh NP (2002) On the origin of modular variation. Int J Org Evol 56(8):1549–1556

    Google Scholar 

  81. Lynch M (2007a) The frailty of adaptive hypotheses for the origins of organismal complexity. Proc Natal Acad Sci USA (1):8597–8604

    Google Scholar 

  82. Lynch M (2007b) The evolution of genetic networks by non-adaptive processes. Nat Rev Genet 8(10). doi:10.1038/nrg2192

    Google Scholar 

  83. Mangan S, Alon U (2003) Structure and function of the feed-forward loop network motif. Proc Natal Acad Sci USA 100(21):11980

    CAS  Google Scholar 

  84. Mangan S, Itzkovitz S, Zaslaver A, Alon U (2006) The incoherent feed-forward loop accelerates the response-time of the gal system of Escherichia coli. J Mol Biol 356(5). doi:10.1016/j.jmb.2005.12.003

    Google Scholar 

  85. Marques JT, Carthew RW (2007) A call to arms: coevolution of animal viruses and host innate immune responses. Trends Genet 23(7). doi:10.1016/j.tig.2007.04.004

    Google Scholar 

  86. Milo R, Shen-Orr S, Itzkovitz S Kashtan N, Chklovskii D, Alon U (2002) Network motifs: simple building blocks of complex networks. Science (New York, NY) 298(5594):824

    Google Scholar 

  87. Moriya H, Shimizu-Yoshida Y, Kitano H (2006) In vivo robustness analysis of cell division cycle genes in Saccharomyces cerevisiae. PLoS Genet 2(7). doi:10.1371/journal.pgen.0020111

    Google Scholar 

  88. Navlakha S, Kingsford C (2011) Network archaeology: uncovering ancient networks from present-day interactions. PLoS Comput Biol 7(4). doi:10.1371/journal.pcbi.1001119

    Google Scholar 

  89. Nesse RM, Stearns SC (2008) The great opportunity: evolutionary applications to medicine and public health. Evol Appl 1(1):28–48

    Google Scholar 

  90. Nikolaou E, Agrafioti I, Stumpf M, Quinn J, Stansfield I, Brown AJ (2009) Phylogenetic diversity of stress signalling pathways in fungi. BMC Evol Biol 9. doi:10.1186/1471–2148–9–44

    Google Scholar 

  91. Nowak MA, Boerlijst MC, Cooke J, Smith JM (1997) Evolution of genetic redundancy. Nature 388(6638). doi:10.1038/40618

    Google Scholar 

  92. Ortega F, Garcés JL, Mas F, Kholodenko BN, Cascante M (2006) Bistability from double phosphorylation in signal transduction. Kinetic and structural requirements. FEBS J 273(17). doi:10.1111/j.1742–4658.2006.05394.x

    Google Scholar 

  93. O’Shaughnessy EC, Palani S, Collins JJ, Sarkar CA (2011) Tunable signal processing in synthetic MAP kinase cascades. Cell 144(1). doi:10.1016/j.cell.2010.12.014

    Google Scholar 

  94. Papp B, Pál C, Hurst LD (2004) Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast. Nature 429(6992). doi:10.1038/nature02636

    Google Scholar 

  95. Papp B, Teusink B, Notebaart RA (2009) A critical view of metabolic network adaptations. HFSP J 3(1). doi:10.2976/1.3020599

    Google Scholar 

  96. Papp B, Notebaart RA, Pál C (2011) Systems-biology approaches for predicting genomic evolution Nat Rev Genet 12(9). doi:10.1038/nrg3033

    Google Scholar 

  97. Parter M, Kashtan N, Alon U (2008) Facilitated variation: how evolution learns from past environments to generalize to new environments. PLoS Comput Biol 4(11). doi:10.1371/journal.pcbi.1000206

    Google Scholar 

  98. Pfeiffer T, Soyer OS, Bonhoeffer S (2005) The evolution of connectivity in metabolic networks. PLoS Biol 3(7). doi:10.1371/journal.pbio.0030228

    Google Scholar 

  99. Porter SL, Wadhams GH, Armitage JP (2008) Rhodobacter sphaeroides: complexity in chemotactic signalling. Trends Microbiol 16(6) doi:10.1016/j.tim.2008.02.006

    Google Scholar 

  100. Prill RJ, Iglesias PA, Levchenko A (2005) Dynamic properties of network motifs contribute to biological network organization. PLoS Biol 3(11). doi:10.1371/journal.pbio.0030343

    Google Scholar 

  101. Rao CV, Kirby JR, Arkin AP (2004) Design and diversity in bacterial chemotaxis: a comparative study in Escherichia coli and Bacillus subtilis. PLoS Biol 2(2). doi:10.1371/journal.pbio.0020049

    Google Scholar 

  102. Ravasz E, Somera AL, Mongru DA, Oltvai ZN, Barabási AL (2002) Hierarchical organization of modularity in metabolic networks. Science (New York, NY) 297(5586). doi:10.1126/science.1073374

    Google Scholar 

  103. Sacks D, Sher A (2002) Evasion of innate immunity by parasitic protozoa. Nat Immunol 3(11):1041–1047

    PubMed  CAS  Google Scholar 

  104. Salathé M, Soyer OS (2008) Parasites lead to evolution of robustness against gene loss in host signaling networks. Mol Syst Biol 4. doi:10.1038/msb.2008.44

    Google Scholar 

  105. Salathé M, May RM, Bonhoeffer S (2005) The evolution of network topology by selective removal. J R Soc Interface 2(5). doi:10.1098/rsif.2005.0072

    Google Scholar 

  106. Santner A, Estelle M (2009) Recent advances and emerging trends in plant hormone signalling. Nature 459(7250). doi:10.1038/nature08122

    Google Scholar 

  107. Schmid-Hempel P, Ebert D (2003) On the evolutionary ecology of specific immune defence. Trend Ecol Evol 18(1):27–32

    Google Scholar 

  108. Schmitt R (2002) Sinorhizobial chemotaxis: a departure from the enterobacterial paradigm. Microbiology (Reading, England) 148Pt 3:627–31

    Google Scholar 

  109. Schnitzer MJ (1993) Theory of continuum random walks and application to chemotaxis. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics 48(4):2553–2568

    PubMed  CAS  Google Scholar 

  110. Shinar G, Milo R, Martínez MR, Alon U (2007) Input output robustness in simple bacterial signaling systems. Proc Natl Acad Sci USA 104(50). doi:10.1073/pnas.0706792104

    Google Scholar 

  111. Siegal ML, Bergman A (2002) Waddington’s canalization revisited: developmental stability and evolution. Proc Natl Acad Sci USA 99(16). doi:10.1073/pnas.102303999

    Google Scholar 

  112. Silva de E Thorne T, Ingram P, Agrafioti I, Swire J, Wiuf C, Stumpf MP (2006) The effects of incomplete protein interaction data on structural and evolutionary inferences. BMC Biol 4. doi:10.1186/1741–7007–4–39

    Google Scholar 

  113. Solé RV, Valverde S (2008) Spontaneous emergence of modularity in cellular networks. J R Soc Interface 5(18). doi:10.1098/rsif.2007.1108

    Google Scholar 

  114. Sourjik V, Berg HC (2002) Binding of the Escherichia coli response regulator chey to its target measured in vivo by fluorescence resonance energy transfer. Proc Natl Acad Sci USA 99(20). doi:10.1073/pnas.192463199

    Google Scholar 

  115. Soyer OS (2007) Emergence and maintenance of functional modules in signaling pathways. BMC Evol Biol 7. doi:10.1186/1471–2148–7–205

    Google Scholar 

  116. Soyer OS, Kuwahara H, Csikász-Nagy A (2009) Regulating the total level of a signaling protein can vary its dynamics in a range from switch like ultrasensitivity to adaptive responses. FEBS J 276. doi:10.1111/j.1742–4658.2009.07054.x

    Google Scholar 

  117. Soyer OS, Goldstein RA (2011) Evolution of response dynamics underlying bacterial chemotaxis. BMC Evol Biol 11. doi:10.1186/1471–2148–11–240

    Google Scholar 

  118. Soyer OS, Bonhoeffer S (2006) Evolution of complexity in signaling pathways. Proc Natl Acad Sci USA 103(44). doi:10.1073/pnas.0604449103

    Google Scholar 

  119. Soyer OS, Pfeiffer T (2010) Evolution under fluctuating environments explains observed robustness in metabolic networks. PLoS Comput Biol 6(8). doi:10.1371/journal.pcbi.1000907

    Google Scholar 

  120. Stumpf MPH, Wiuf C, May RM (2005) Subnets of scale-free networks are not scale-free: sampling properties of networks. Proc Natl Acad Sci USA 102(12):4221

    PubMed  CAS  Google Scholar 

  121. Troein C, Ahrén D, Krogh M, Peterson C (2007) Is transcriptional regulation of metabolic pathways an optimal strategy for fitness? PLoS One 2(9). doi:10.1371/journal.pone.0000855

    Google Scholar 

  122. Troein C, Locke JCW, Turner MS, Millar AJ (2009) Weather and seasons together demand complex biological clocks. Curr Biol 19(22). doi:10.1016/j.cub.2009.09.024

    Google Scholar 

  123. Tyson JJ, Chen KC, Novak B (2003) Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell. Curr Opin Cell Biol 15:221–231

    PubMed  CAS  Google Scholar 

  124. Uetz P, Giot L, Cagney G, Mansfield TA, Judson RS, Knight JR, Lockshon D, Narayan V, Srinivasan M, Pochart P (2000) A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae. Nature 403(6770):623–627

    PubMed  CAS  Google Scholar 

  125. van Noort V, Berend S, Huynen MA (2004) The yeast coexpression network has a small-world, scale-free architecture and can be explained by a simple model. EMBO Rep 5(3). doi:10.1038/sj.embor.7400090

    Google Scholar 

  126. Visser de JA, Hermisson J, Wagner GP, Meyers LA, Bagheri-Chaichian H, Blanchard JL, Chao L, others (2003) Perspective: evolution and detection of genetic robustness. Int J Org Evol 57(9):1959–1972

    Google Scholar 

  127. Waddington CH (1942) Canalization of development and the inheritance of acquired characters. Nature 150(3811):563

    Google Scholar 

  128. Wagner A (2000a) Robustness against mutations in genetic networks of yeast. Nat Genet 24(4). doi:10.1038/74174

    Google Scholar 

  129. Wagner A (2000) The role of population size, pleiotropy and fitness effects of mutations in the evolution of overlapping gene functions. Genetics 154(3):1389–401

    PubMed  CAS  Google Scholar 

  130. Wagner A (2005) Distributed robustness versus redundancy as causes of mutational robustness. Bioessays 27(2). doi:10.1002/bies.20170

    Google Scholar 

  131. Wagner GP, Altenberg L (1996) Complex adaptations and the evolution of evolvability. Evolution Int J Org Evol 50(3):967-976

    Google Scholar 

  132. Walhout AJM, Sordella R, Lu X, Hartley JL, Temple GF, Brasch MA, Thierry-Mieg N, Vidal M (2000) Protein interaction mapping in C. Elegans using proteins involved in vulval development. Science 287(5450):116

    Google Scholar 

  133. Wang Z, Zhang J (2009) Abundant indispensable redundancies in cellular metabolic networks. Genome Biol Evol 1:23–33. doi:10.1093/gbe/evp002

    PubMed  Google Scholar 

  134. Wang Z, Zhang J (2011) PNAS plus: impact of gene expression noise on organismal fitness and the efficacy of natural selection. Proc Natl Acad Sci USA 108(16). doi:10.1073/pnas.1100059108

    Google Scholar 

  135. Wessely F, Bartl M, Guthke R, Li P, Schuster S, Kaleta C (2011) Optimal regulatory strategies for metabolic pathways in Escherichia coli depending on protein costs. Mol Syst Biol 7. doi:10.1038/msb.2011.46

    Google Scholar 

  136. Wright S (1934) Physiological and evolutionary theories of dominance. Am Nat 68(714):24–53

    Google Scholar 

  137. Wuichet K, Zhulin IgorB (2010) Origins and diversification of a complex signal transduction system in prokaryotes. Sci Signal 3(128):ra50

    Google Scholar 

  138. Xavier JB, Kim W, Foster KR (2011) A molecular mechanism that stabilizes cooperative secretions in Pseudomonas aeruginosa. Mol Microbiol 79(1). doi:10.1111/j.1365–2958.2010.07436.x

    Google Scholar 

  139. Yi TM, Huang Y, Simon MI, Doyle J (2000) Robust perfect adaptation in bacterial chemotaxis through integral feedback control. Proc Natl Acad Sci USA 97(9):4649–4653

    PubMed  CAS  Google Scholar 

  140. Yu H, Gerstein M (2006) Genomic analysis of the hierarchical structure of regulatory networks. Proc Natl Acad Sci USA 103(40):14724

    PubMed  CAS  Google Scholar 

  141. Zhang Z, Qian W, Zhang J (2009) Positive selection for elevated gene expression noise in yeast Mol Syst Biol 5. doi:10.1038/msb.2009.58

    Google Scholar 

Download references

Acknowledgements

We would like to thank Maureen O’Malley, Juan Poyatos, and Richard Goldstein for their useful comments on this manuscript.

Author information

Authors and Affiliations

  1. Systems Biology Program, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, EX8 5JT, UK

    Arno Steinacher & Orkun S. Soyer

Authors
  1. Arno Steinacher
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Orkun S. Soyer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Orkun S. Soyer .

Editor information

Editors and Affiliations

  1. University of Exeter, Prince of Wales Road, Exeter, EX4 4SB, Devon, United Kingdom

    Orkun S. Soyer

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Steinacher, A., Soyer, O.S. (2012). Evolutionary Principles Underlying Structure and Response Dynamics of Cellular Networks. In: Soyer, O. (eds) Evolutionary Systems Biology. Advances in Experimental Medicine and Biology, vol 751. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3567-9_11

Download citation

Publish with us

Policies and ethics

Search

Navigation