A Systems Biology View of Adaptation in Sensory Mechanisms

  • Pablo A. IglesiasEmail author
Conference paper
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 736)


Adaptation, the desensitization to persistent changes in environmental conditions, is present throughout biological sensory mechanisms. Not surprisingly, it has been an active area of research to systems biologists. Here, we consider some of the models proposed to account for adaptation as well as the experiments used to motivate and validate these models. We discuss some salient features of these models including robustness, deadaptation, transient responses, and the response of these systems to more complex temporal stimuli. While most of these models have been used to study chemoattractant-induced responses in bacteria and amoebae, the system-theoretic issues associated with these systems are of importance in a broad spectrum of biological systems.


Response Regulator Sensory Mechanism Bacterial Chemotaxis Flagellar Motor Perfect Adaptation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Hood DC (1998) Lower-level visual processing and models of light adaptation. Ann Rev Psychol 49:503–535CrossRefGoogle Scholar
  2. 2.
    Vladimirov N, Sourjik V (2009) Chemotaxis: how bacteria use memory. Biol Chem 390:1097–1104PubMedCrossRefGoogle Scholar
  3. 3.
    Roberts MA, Papachristodoulou A, Armitage JP (2010) Adaptation and control circuits in bacterial chemotaxis. Biochem Soc Trans 38:1265–1269PubMedCrossRefGoogle Scholar
  4. 4.
    Swaney KF, Huang CH, Devreotes PN (2010) Eukaryotic chemotaxis: a network of signaling pathways controls motility, directional sensing, and polarity. Ann Rev Biophys 39:265–289CrossRefGoogle Scholar
  5. 5.
    Wang Y, Chen CL, Iijima M (2011) Signaling mechanisms for chemotaxis. Dev Growth Differ 53:495–502PubMedCrossRefGoogle Scholar
  6. 6.
    Andrews BW, Yi TM, Iglesias PA (2006) Optimal noise filtering in the chemotactic response of Escherichia coli. PLoS Comput Biol 2:e154Google Scholar
  7. 7.
    Tu Y, Shimizu TS, Berg HC (2008) Modeling the chemotactic response of Escherichia coli to time-varying stimuli. Proc Natl Acad Sci USA 105:14855–14860PubMedCrossRefGoogle Scholar
  8. 8.
    Shimizu TS, Tu Y, Berg HC (2010) A modular gradient-sensing network for chemotaxis in Escherichia coli revealed by responses to time-varying stimuli. Mol Syst Biol 6:382PubMedCrossRefGoogle Scholar
  9. 9.
    Ma W, Trusina A, El-Samad H, Lim WA, Tang C (2009) Defining network topologies that can achieve biochemical adaptation. Cell 138:760–773PubMedCrossRefGoogle Scholar
  10. 10.
    Segel LA, Goldbeter A, Devreotes PN, Knox BE (1986) A mechanism for exact sensory adaptation based on receptor modification. J Theor Biol 120:151–179PubMedCrossRefGoogle Scholar
  11. 11.
    Knox BE, Devreotes PN, Goldbeter A, Segel LA (1986) A molecular mechanism for sensory adaptation based on ligand-induced receptor modification. Proc Natl Acad Sci USA 83:2345–2349PubMedCrossRefGoogle Scholar
  12. 12.
    Francis BA (1980) On robustness of the stability of feedback systems. IEEE Trans Autom Control 25(4):817–818CrossRefGoogle Scholar
  13. 13.
    Csete ME, Doyle JC (2002) Reverse engineering of biological complexity. Science 295:1664–1669PubMedCrossRefGoogle Scholar
  14. 14.
    Spiro PA, Parkinson JS, Othmer HG (1997) A model of excitation and adaptation in bacterial chemotaxis. Proc Natl Acad Sci USA 94:7263–7268PubMedCrossRefGoogle Scholar
  15. 15.
    Yi TM, Huang Y, Simon MI, Doyle J (2000) Robust perfect adaptation in bacterial chemotaxis through integral feedback control. Proc Natl Acad Sci USA 97:4649–4653PubMedCrossRefGoogle Scholar
  16. 16.
    Barkai N, Leibler S (1997) Robustness in simple biochemical networks. Nature 387:913–917PubMedCrossRefGoogle Scholar
  17. 17.
    Alon U, Surette MG, Barkai N, Leibler S (1999) Robustness in bacterial chemotaxis. Nature 397:168–171PubMedCrossRefGoogle Scholar
  18. 18.
    Francis BA, Wonham WM (1975) The internal model principle for linear multivariable regulators. Appl Math Optim 2(2):170–194CrossRefGoogle Scholar
  19. 19.
    Sontag ED (2003) Adaptation and regulation with signal detection implies internal model. Syst Control Lett 50(2):119–126CrossRefGoogle Scholar
  20. 20.
    Andrews BW, Sontag ED, Iglesias PA (2006) Signal detection and approximate adaptation implies an approximate internal model. In: Proc 45th IEEE conference on decision and control, art. no. 4177419, pp 2364–2369Google Scholar
  21. 21.
    Andrews BW, Sontag ED, Iglesias PA (2008) An approximate internal model principle: applications to nonlinear models of biological systems. In: Proc 17th IFAC world congress 17, DOI:10.3182/20080706-5-KR-1001.0568Google Scholar
  22. 22.
    Koshland DE (1977) A response regulator model in a simple sensory system. Science 196:1055–1063PubMedCrossRefGoogle Scholar
  23. 23.
    Levchenko A, Iglesias PA (2002) Models of eukaryotic gradient sensing: application to chemotaxis of amoebae and neutrophils. Biophys J 82:50–63PubMedCrossRefGoogle Scholar
  24. 24.
    Ma’ayan A, Jenkins AL, Neves S, Hasseldine A, Grace E, Dubin-Thaler B, Eungdamrong EJ, Weng G, Ram PT, Rice JJ, Kershenbaum A, Stolovitzky GA, Blitzer RD, Iyengar R (2005) Formation of regulatory patterns during signal propagation in a Mammalian cellular network. Science 309:1078–1083PubMedCrossRefGoogle Scholar
  25. 25.
    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 356:1073–1081PubMedCrossRefGoogle Scholar
  26. 26.
    Cournac A, Sepulchre JA (2009) Simple molecular networks that respond optimally to time-periodic stimulation. BMC Syst Biol 3:29PubMedCrossRefGoogle Scholar
  27. 27.
    Goentoro L, Shoval O, Kirschner MW, Alon U (2009) The incoherent feedforward loop can provide fold-change detection in gene regulation. Mol Cell 36:894–899PubMedCrossRefGoogle Scholar
  28. 28.
    MacGillavry HD, Stam FJ, Sassen MM, Kegel L, Hendriks WT, Verhaagen J, Smit AB, van Kesteren RE (2009) NFIL3 and cAMP response element-binding protein form a transcriptional feedforward loop that controls neuronal regeneration-associated gene expression. J Neurosci 29:15542–15550PubMedCrossRefGoogle Scholar
  29. 29.
    Osella M, Bosia C, Cora D, Caselle M (2011) The role of incoherent microRNA-mediated feedforward loops in noise buffering. PLoS Comput Biol 7:e1001101PubMedCrossRefGoogle Scholar
  30. 30.
    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 15:221–231PubMedCrossRefGoogle Scholar
  31. 31.
    Yang L, Iglesias PA (2006) Positive feedback may cause the biphasic response observed in the chemoattractant-induced response of Dictyostelium cells. Syst Control Lett 55:329–337PubMedCrossRefGoogle Scholar
  32. 32.
    Krishnan J, Iglesias PA (2003) Analysis of the signal transduction properties of a module of spatial sensing in eukaryotic chemotaxis. Bull Math Biol 65:95–128PubMedCrossRefGoogle Scholar
  33. 33.
    Sontag ED (2010) Remarks on feedforward circuits, adaptation, and pulse memory. IET Syst Biol 4:39–51PubMedCrossRefGoogle Scholar
  34. 34.
    Devreotes PN, Steck TL (1979) Cyclic 3’,5’ AMP relay in Dictyostelium discoideum. II. Requirements for the initiation and termination of the response. J Cell Biol 80:300–309PubMedCrossRefGoogle Scholar
  35. 35.
    Dinauer MC, Steck TL, Devreotes PN (1980) Cyclic 3’,5’-AMP relay in Dictyostelium discoideum IV. Recovery of the cAMP signaling response after adaptation to cAMP. J Cell Biol 86:545–553Google Scholar
  36. 36.
    Beta B, Wyatt D, Rappel WJ, Bodenschatz E (2007) Flow photolysis for spatiotemporal stimulation of single cells. Anal Chem 79:3940–3944PubMedCrossRefGoogle Scholar
  37. 37.
    Xiong Y, Huang CH, Iglesias PA, Devreotes PN (2010) Cells navigate with a local-excitation, global-inhibition-biased excitable network. Proc Natl Acad Sci USA 107:17079–17086PubMedCrossRefGoogle Scholar
  38. 38.
    Block SM, Segall JE, Berg HC (1983) Adaptation kinetics in bacterial chemotaxis. J Bacteriol 154:312–323PubMedGoogle Scholar
  39. 39.
    Krishnan J (2011) Effects of saturation and enzyme limitation in feedforward adaptive signal transduction. IET Syst Biol 5:208PubMedCrossRefGoogle Scholar
  40. 40.
    Mettetal JT, Muzzey D, Gomez-Uribe C, van Oudenaarden A (2008) The frequency dependence of osmo-adaptation in Saccharomyces cerevisiae. Science 319:482–484PubMedCrossRefGoogle Scholar
  41. 41.
    Ferrell JE (2009) Signaling motifs and Weber’s law. Mol Cell 36:724–727PubMedCrossRefGoogle Scholar
  42. 42.
    Shoval O, Goentoro L, Hart Y, Mayo A, Sontag E, Alon U (2010) Fold-change detection and scalar symmetry of sensory input fields. Proc Natl Acad Sci USA 107:15995–16000PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringThe Johns Hopkins UniversityBaltimoreUSA

Personalised recommendations