Engineered Cell–Cell Communication and Its Applications

  • Stephen Payne
  • Lingchong YouEmail author
Part of the Advances in Biochemical Engineering/Biotechnology book series (ABE, volume 146)


Over the past several decades, biologists have become more appreciative of the fundamental role of intercellular communication in natural systems spanning prokaryotic biofilms to eukaryotic developmental systems and neurological networks. From an engineering perspective, the use of cell–cell communication provides an opportunity to engineer more complex and robust functions using cellular components. Indeed, this strategy has been adopted in synthetic biology in the creation of diverse gene circuits that program spatiotemporal dynamics in one or multiple populations. Gene circuits such as these may offer insights regarding basic biological questions and motifs or serve as a basis for novel applications.

Graphical Abstract


Synthetic Biology Quorum Sense Logic Gate Cell Communication Quorum Sense System 
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.



Related research in the You lab is supported by NIH (1R01-GM098642), a DuPont Young Professorship (LY), a National Science Foundation CAREER award (LY), a David and Lucile Packard Fellowship (LY), North Carolina Biotechnology Center (2012-MRG-1102), and the Office of Naval Research (N00014-12-1-0631).


  1. 1.
    Rokas A (2008) The origins of multicellularity and the early history of the genetic toolkit for animal development. Annu Rev Genet 42:235–251CrossRefGoogle Scholar
  2. 2.
    Ispolatov I, Ackermann M, Doebeli M (2012) Division of labour and the evolution of multicellularity. Proc Biol Sci 279(1734):1768–1776CrossRefGoogle Scholar
  3. 3.
    LeRoith D, Shemer J, Roberts CT Jr (1992) Evolutionary origins of intercellular communication systems: implications for mammalian biology. Horm Res 38(2):1–6CrossRefGoogle Scholar
  4. 4.
    Choudhary S, Schmidt-Dannert C (2010) Applications of quorum sensing in biotechnology. Appl Microbiol Biotechnol 86(5):1267–1279CrossRefGoogle Scholar
  5. 5.
    Elowitz MB, Leibler S (2000) A synthetic oscillatory network of transcriptional regulators. Nature 403(6767):335–338CrossRefGoogle Scholar
  6. 6.
    Gardner TS, Cantor CR, Collins JJ (2000) Construction of a genetic toggle switch in Escherichia coli. Nature 403(6767):339–342CrossRefGoogle Scholar
  7. 7.
    Yokobayashi Y, Weiss R, Arnold FH (2002) Directed evolution of a genetic circuit. Proc Natl Acad Sci U S A 99(26):16587–16591CrossRefGoogle Scholar
  8. 8.
    Guet CC et al (2002) Combinatorial synthesis of genetic networks. Science 296(5572):1466–1470CrossRefGoogle Scholar
  9. 9.
    Chuang JS (2012) Engineering multicellular traits in synthetic microbial populations. Curr Opin Chem Biol 16:370–378Google Scholar
  10. 10.
    Pai A et al (2009) Engineering multicellular systems by cell–cell communication. Curr Opin Biotechnol 20(4):461–470CrossRefGoogle Scholar
  11. 11.
    Xavier JB (2011) Social interaction in synthetic and natural microbial communities. Mol Syst Biol 7:483CrossRefGoogle Scholar
  12. 12.
    Tsao C-Y, Quan DN, Bentley WE (2012) Development of the quorum sensing biotechnological toolbox. Curr Opin Chem Eng 1(4):396–402CrossRefGoogle Scholar
  13. 13.
    Shong J, Jimenez Diaz MR, Collins CH (2012) Towards synthetic microbial consortia for bioprocessing. Curr Opin Biotechnol 2:1–5Google Scholar
  14. 14.
    Waters CM, Bassler BL (2005) Quorum sensing: cell-to-cell communication in bacteria. Annu Rev Cell Dev Biol 21:319–346CrossRefGoogle Scholar
  15. 15.
    Parsek MR, Greenberg EP (2000) Acyl-homoserine lactone quorum sensing in gram-negative bacteria: a signaling mechanism involved in associations with higher organisms. Proc Natl Acad Sci U S A 97(16):8789–8793CrossRefGoogle Scholar
  16. 16.
    Schaefer AL et al (2008) A new class of homoserine lactone quorum-sensing signals. Nature 454(7204):595–599CrossRefGoogle Scholar
  17. 17.
    Hooshangi S, Bentley WE (2008) From unicellular properties to multicellular behavior: bacteria quorum sensing circuitry and applications. Curr Opin Biotechnol 19(6):550–555CrossRefGoogle Scholar
  18. 18.
    Balagadde FK et al (2008) A synthetic Escherichia coli predator-prey ecosystem. Mol Syst Biol 4:187CrossRefGoogle Scholar
  19. 19.
    Song H et al (2009) Spatiotemporal modulation of biodiversity in a synthetic chemical-mediated ecosystem. Nat Chem Biol 5(12):929–935CrossRefGoogle Scholar
  20. 20.
    Shou W, Ram S, Vilar JM (2007) Synthetic cooperation in engineered yeast populations. Proc Natl Acad Sci U S A 104(6):1877–1882CrossRefGoogle Scholar
  21. 21.
    Hu B et al (2010) An environment-sensitive synthetic microbial ecosystem. PLoS One 5(5):e10619CrossRefGoogle Scholar
  22. 22.
    Kim HJ et al (2008) Defined spatial structure stabilizes a synthetic multispecies bacterial community. Proc Natl Acad Sci U S A 105(47):18188–18193CrossRefGoogle Scholar
  23. 23.
    Brenner K, Arnold FH (2011) Self-organization, layered structure, and aggregation enhance persistence of a synthetic biofilm consortium. PLoS One 6(2):e16791CrossRefGoogle Scholar
  24. 24.
    Chuang JS, Rivoire O, Leibler S (2009) Simpson’s paradox in a synthetic microbial system. Science 323(5911):272–275CrossRefGoogle Scholar
  25. 25.
    Pai A, Tanouchi Y, You L (2012) Optimality and robustness in quorum sensing (QS)-mediated regulation of a costly public good enzyme. Proc Natl Acad Sci U S A 109(48):19810–19815CrossRefGoogle Scholar
  26. 26.
    Pai A, You L (2009) Optimal tuning of bacterial sensing potential. Mol Syst Biol 5:286CrossRefGoogle Scholar
  27. 27.
    Sekine R et al (2011) Tunable synthetic phenotypic diversification on Waddington’s landscape through autonomous signaling. Proc Natl Acad Sci U S A 108(44):17969–17973CrossRefGoogle Scholar
  28. 28.
    Keller EF, Segel LA (1970) Initiation of slime mold aggregation viewed as an instability. J Theor Biol 26(3):399–415CrossRefGoogle Scholar
  29. 29.
    Goldbeter A (2006) Oscillations and waves of cyclic AMP in Dictyostelium: a prototype for spatio-temporal organization and pulsatile intercellular communication. Bull Math Biol 68(5):1095–1109CrossRefGoogle Scholar
  30. 30.
    Harris MP et al (2005) Molecular evidence for an activator-inhibitor mechanism in development of embryonic feather branching. Proc Natl Acad Sci U S A 102(33):11734–11739CrossRefGoogle Scholar
  31. 31.
    Chou CS et al (2010) Spatial dynamics of multistage cell lineages in tissue stratification. Biophys J 99(10):3145–3154CrossRefGoogle Scholar
  32. 32.
    Greco V et al (2009) A two-step mechanism for stem cell activation during hair regeneration. Cell Stem Cell 4(2):155–169CrossRefGoogle Scholar
  33. 33.
    Basu S et al (2005) A synthetic multicellular system for programmed pattern formation. Nature 434(7037):1130–1134CrossRefGoogle Scholar
  34. 34.
    Matsuda M et al (2012) Synthetic signal propagation through direct cell–cell interaction. Sci Signal 5(220):ra31Google Scholar
  35. 35.
    Turing AM (1990) The chemical basis of morphogenesis. 1953. Bull Math Biol 52(1–2):153–197 (discussion 119–152)Google Scholar
  36. 36.
    Liu C et al (2011) Sequential establishment of stripe patterns in an expanding cell population. Science 334(6053):238–241CrossRefGoogle Scholar
  37. 37.
    Saunders RE, Gough JE, Derby B (2008) Delivery of human fibroblast cells by piezoelectric drop-on-demand inkjet printing. Biomaterials 29(2):193–203CrossRefGoogle Scholar
  38. 38.
    Xu T et al (2005) Inkjet printing of viable mammalian cells. Biomaterials 26(1):93–99CrossRefGoogle Scholar
  39. 39.
    Roth EA et al (2004) Inkjet printing for high-throughput cell patterning. Biomaterials 25(17):3707–3715CrossRefGoogle Scholar
  40. 40.
    Choi WS et al (2011) Synthetic multicellular cell-to-cell communication in inkjet printed bacterial cell systems. Biomaterials 32(10):2500–2507CrossRefGoogle Scholar
  41. 41.
    Tabor JJ et al (2009) A synthetic genetic edge detection program. Cell 137(7):1272–1281CrossRefGoogle Scholar
  42. 42.
    Tamsir A, Tabor JJ, Voigt CA (2011) Robust multicellular computing using genetically encoded NOR gates and chemical ‘wires’. Nature 469(7329):212–215CrossRefGoogle Scholar
  43. 43.
    Regot S et al (2011) Distributed biological computation with multicellular engineered networks. Nature 469(7329):207–211CrossRefGoogle Scholar
  44. 44.
    Moon TS et al (2012) Genetic programs constructed from layered logic gates in single cells. Nature 491(7423):249–253CrossRefGoogle Scholar
  45. 45.
    Brenner K et al (2007) Engineered bidirectional communication mediates a consensus in a microbial biofilm consortium. Proc Natl Acad Sci U S A 104(44):17300–17304CrossRefGoogle Scholar
  46. 46.
    Levskaya A et al (2005) Synthetic biology: engineering Escherichia coli to see light. Nature 438(7067):441–442CrossRefGoogle Scholar
  47. 47.
    You L et al (2004) Programmed population control by cell–cell communication and regulated killing. Nature 428(6985):868–871CrossRefGoogle Scholar
  48. 48.
    Balagadde FK et al (2005) Long-term monitoring of bacteria undergoing programmed population control in a microchemostat. Science 309(5731):137–140CrossRefGoogle Scholar
  49. 49.
    Anderson JC et al (2006) Environmentally controlled invasion of cancer cells by engineered bacteria. J Mol Biol 355(4):619–627CrossRefGoogle Scholar
  50. 50.
    Xie Z et al (2011) Multi-input RNAi-based logic circuit for identification of specific cancer cells. Science 333(6047):1307–1311CrossRefGoogle Scholar
  51. 51.
    Danino T et al (2010) A synchronized quorum of genetic clocks. Nature 463(7279):326–330CrossRefGoogle Scholar
  52. 52.
    Prindle A et al (2012) A sensing array of radically coupled genetic ‘biopixels’. Nature 481(7379):39–44CrossRefGoogle Scholar
  53. 53.
    Smyth AR et al (2010) Garlic as an inhibitor of Pseudomonas aeruginosa quorum sensing in cystic fibrosis—a pilot randomized controlled trial. Pediatr Pulmonol 45(4):356–362Google Scholar
  54. 54.
    Kohler T et al (2010) Quorum sensing inhibition selects for virulence and cooperation in Pseudomonas aeruginosa. PLoS Pathog 6(5):e1000883CrossRefGoogle Scholar
  55. 55.
    Roy V, Adams BL, Bentley WE (2011) Developing next generation antimicrobials by intercepting AI-2 mediated quorum sensing. Enzyme Microb Technol 49(2):113–123CrossRefGoogle Scholar
  56. 56.
    Gamby S et al (2012) Altering the communication networks of multispecies microbial systems using a diverse toolbox of AI-2 analogues. ACS Chem Biol 7:1023–1030Google Scholar
  57. 57.
    Chen G et al (2011) A strategy for antagonizing quorum sensing. Mol Cell 42(2):199–209CrossRefGoogle Scholar
  58. 58.
    Roy V et al (2010) Cross species quorum quenching using a native AI-2 processing enzyme. ACS Chem Biol 5(2):223–232CrossRefGoogle Scholar
  59. 59.
    Saeidi N et al (2011) Engineering microbes to sense and eradicate Pseudomonas aeruginosa, a human pathogen. Mol Syst Biol 7:521CrossRefGoogle Scholar
  60. 60.
    Hong SH et al (2012) Synthetic quorum-sensing circuit to control consortial biofilm formation and dispersal in a microfluidic device. Nat Commun 3:613CrossRefGoogle Scholar
  61. 61.
    Duan F, March JC (2010) Engineered bacterial communication prevents Vibrio cholerae virulence in an infant mouse model. Proc Natl Acad Sci U S A 107(25):11260–11264CrossRefGoogle Scholar
  62. 62.
    Romero PA, Arnold FH (2009) Exploring protein fitness landscapes by directed evolution. Nat Rev Mol Cell Biol 10(12):866–876CrossRefGoogle Scholar
  63. 63.
    Collins CH, Leadbetter JR, Arnold FH (2006) Dual selection enhances the signaling specificity of a variant of the quorum-sensing transcriptional activator LuxR. Nat Biotechnol 24(6):708–712CrossRefGoogle Scholar
  64. 64.
    Kambam PK et al (2008) Directed evolution of LuxI for enhanced OHHL production. Biotechnol Bioeng 101(2):263–272CrossRefGoogle Scholar
  65. 65.
    Gross A, Rodel G, Ostermann K (2011) Application of the yeast pheromone system for controlled cell–cell communication and signal amplification. Lett Appl Microbiol 52(5):521–526CrossRefGoogle Scholar
  66. 66.
    Bulter T et al (2004) Design of artificial cell–cell communication using gene and metabolic networks. Proc Natl Acad Sci U S A 101(8):2299–2304CrossRefGoogle Scholar
  67. 67.
    Chen MT, Weiss R (2005) Artificial cell–cell communication in yeast Saccharomyces cerevisiae using signaling elements from Arabidopsis thaliana. Nat Biotechnol 23(12):1551–1555CrossRefGoogle Scholar
  68. 68.
    Weber W et al (2005) Engineered Streptomyces quorum-sensing components enable inducible siRNA-mediated translation control in mammalian cells and adjustable transcription control in mice. J Gene Med 7(4):518–525CrossRefGoogle Scholar
  69. 69.
    Wang WD et al (2008) Construction of an artificial intercellular communication network using the nitric oxide signaling elements in mammalian cells. Exp Cell Res 314(4):699–706CrossRefGoogle Scholar
  70. 70.
    Weber W et al (2009) A synthetic metabolite-based mammalian inter-cell signaling system. Mol Biosyst 5(7):757–763CrossRefGoogle Scholar
  71. 71.
    Bacchus W et al (2012) Synthetic two-way communication between mammalian cells. Nat Biotechnol 30(10):991–996CrossRefGoogle Scholar
  72. 72.
    Weber W, Daoud-El Baba M, Fussenegger M (2007) Synthetic ecosystems based on airborne inter- and intrakingdom communication. Proc Natl Acad Sci U S A 104(25):10435–10440Google Scholar
  73. 73.
    Tan C, Marguet P, You L (2009) Emergent bistability by a growth-modulating positive feedback circuit. Nat Chem Biol 5(11):842–848CrossRefGoogle Scholar
  74. 74.
    Marguet P et al (2010) Oscillations by minimal bacterial suicide circuits reveal hidden facets of host-circuit physiology. PLoS One 5(7):e11909CrossRefGoogle Scholar
  75. 75.
    Elowitz MB et al (2002) Stochastic gene expression in a single cell. Science 297(5584):1183–1186CrossRefGoogle Scholar
  76. 76.
    Eldar A, Elowitz MB (2010) Functional roles for noise in genetic circuits. Nature 467(7312):167–173CrossRefGoogle Scholar
  77. 77.
    Munsky B, Neuert G, van Oudenaarden A (2012) Using gene expression noise to understand gene regulation. Science 336(6078):183–187CrossRefGoogle Scholar
  78. 78.
    Henry CS, Broadbelt LJ, Hatzimanikatis V (2007) Thermodynamics-based metabolic flux analysis. Biophys J 92(5):1792–1805CrossRefGoogle Scholar
  79. 79.
    Varma A, Palsson BO (1993) Metabolic capabilities of Escherichia-Coli.1. Synthesis of biosynthetic precursors and cofactors. J Theor Biol 165(4):477–502CrossRefGoogle Scholar
  80. 80.
    Young JW et al (2012) Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy. Nat Protoc 7(1):80–88CrossRefGoogle Scholar
  81. 81.
    Wyart M, Botstein D, Wingreen NS (2010) Evaluating gene expression dynamics using pairwise RNA FISH data. PLoS Comput Biol 6(11):e1000979CrossRefGoogle Scholar
  82. 82.
    Khalil AS, Collins JJ (2010) Synthetic biology: applications come of age. Nat Rev Genet 11(5):367–379CrossRefGoogle Scholar
  83. 83.
    Cheng AA, Lu TK (2012) Synthetic biology: an emerging engineering discipline. Annu Rev Biomed Eng 14:155–178CrossRefGoogle Scholar
  84. 84.
    Kosuri S et al (2010) Scalable gene synthesis by selective amplification of DNA pools from high-fidelity microchips. Nat Biotechnol 28(12):1295–1299CrossRefGoogle Scholar
  85. 85.
    Ma S, Tang N, Tian J (2012) DNA synthesis, assembly and applications in synthetic biology. Curr Opin Chem Biol 16(3–4):260–267CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Biomedical EngineeringDuke UniversityDurhamUSA
  2. 2.Institute for Genome Sciences and PolicyDuke UniversityDurhamUSA
  3. 3.Center for Systems BiologyDuke UniversityDurhamUSA
  4. 4.CIEMAS 2355DurhamUSA

Personalised recommendations