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Expanding the landscape of biological computation with synthetic multicellular consortia

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Abstract

Computation is an intrinsic attribute of biological entities. All of them gather and process information and respond in predictable ways to an uncertain external environment. Are these computations similar to those performed by artificial systems? Can a living computer be constructed following standard engineering practices? Despite the similarities between molecular networks associated to information processing and the wiring diagrams used to represent electronic circuits, major differences arise. Such differences are specially relevant while engineering molecular circuits in order to build novel functionalities. Among others, wiring molecular components within a cell becomes a great challenge as soon as the complexity of the circuit becomes larger than simple gates. An alternative approach has been recently introduced based on a non-standard approach to cellular computation. By breaking some standard assumptions of engineering design, it allows the synthesis of multicellular engineered circuits able to perform complex functions and open a novel form of computation. Here we review previous studies dealing with both natural and synthetic forms of computation. We compare different systems spanning many spatial and temporal scales and outline a possible “space” of biological forms of computation. We suggest that a novel approach to build synthetic devices using multicellular consortia allows expanding this space in new directions.

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References

  • Adamatzky A (2007) Physarum machines: encapsulating reaction–diffusion to compute. Naturwissenschaften 94:975–980

    Article  Google Scholar 

  • Amos M (2004) Cellular computing. Oxford University Press, New York

    MATH  Google Scholar 

  • Arbib M (1995) The handbook of brain theory and neural networks. MIT Press, Cambridge

    Google Scholar 

  • Ausländer S, Wieland M, Fussenegger M (2012a) Smart medication through combination of synthetic biology and cell microencapsulation. Metab Eng 14:252–260

    Article  Google Scholar 

  • Ausländer S, Ausländer D, Muller M, Wieland M, Fussenegger M (2012b) Programmable single-cell mammalian biocomputers. Nat Biotechnol 487:123–127

    Google Scholar 

  • Bassett DS, Greenfield DL, Meyer-Lindenberg A et al (2010) Efficient physical embedding of complex information processing networks in brains and computer circuits. PLoS Comput Biol 6:e1000748

    Article  Google Scholar 

  • Basu S, Gerchman Y, Collins CH, Arnold FH, Weiss R (2005) A synthetic multicellular system for programmed pattern formation. Nat Biotechnol 434:1130–1134

    Article  Google Scholar 

  • Benenson Y (2009) Biocomputers: from test tubes to live cells. Mol BioSyst 5:675–685

    Article  Google Scholar 

  • Benenson Y (2012) Biomolecular computing systems: principles, progress and potential. Nat Rev Genet 13:455–468

    Article  Google Scholar 

  • Bennett CH (1982) The thermodynamics of computation—a review. Int J Theor Phys 21:905–940

    Article  Google Scholar 

  • Bray D (1995) Protein molecules as computational elements in living cells. Nat Biotechnol 376:307–312

    Article  Google Scholar 

  • Brenner S (2012) Turing centenary: life’s code script. Nat Biotechnol 482:461

    Article  Google Scholar 

  • Brenner K, Karig DK, Weiss R, Arnold FH (2007) Engineered bidirectional communication mediates a consensus in a microbial biofilm consortium. Proc Natl Acad Sci USA 104:17300–17304

    Article  Google Scholar 

  • Brenner K et al. (2008) Engineering microbial consortia: a new frontier in synthetic biology. Trends Biotechnol 28:483–489

    Article  Google Scholar 

  • Bryant B (2012) Chromatin computation. PLoS One 7(5):e35703

    Article  Google Scholar 

  • Camazine S, Deneubourg J-L, Franks NR, Theraulaz G, Bonabeau E (2003) Self-organization in biological systems. Princeton University Press, Princeton

    MATH  Google Scholar 

  • Chuang JS (2012) Engineering multicellular traits in synthetic microbial populations. Curr Optim Chem Biol 16:370–378

    Article  Google Scholar 

  • Deneubourg JL (1989) Collective patterns and decision-making. Ethol Ecol Evol 1:295–311

    Article  Google Scholar 

  • Deneubourg JL, Goss S, Franksm N, Pasteels JM (1989) The blind leading the blind: modeling chemically mediated army ant raid patterns. J Insect Behav 2:719–724

    Article  Google Scholar 

  • Dussutour A, Latty T, Beekman M (2010) Amoeboid organism solves complex nutritional challenges. Proc Natl Acad Sci USA 107:4607–4611

    Article  Google Scholar 

  • Enderton H (2001) A mathematical introduction to logic, 2nd edn. Harcourt Academic Press, New York

    Google Scholar 

  • Fernando CT, Liekens AM, Bingle LE, Beck C, Lenser T, Stekel DJ, Rowe JE (2009) Molecular circuits for associative learning in single-celled organisms. J R Soc Interface 6:463–469

    Article  Google Scholar 

  • Friedland AE et al. (2009) Synthetic gene networks that count. Sci Agric 324:1199–1202

    Article  Google Scholar 

  • Goni-Moreno A, Amos M (2012) Continuous computation in engineered gene circuits. Biosyst Eng 109:52–56

    Article  Google Scholar 

  • Haken H (1979) Pattern formation and pattern recognition: an attempt at a synthesis. In: Haken H (ed) Pattern formation by dynamic systems and pattern recognition. Springer, Berlin, pp 2–13

    Chapter  Google Scholar 

  • Haken H (2004) Synergetics: an introduction. Springer, Berlin

    Book  Google Scholar 

  • Hogeweg P (2002) Computing an organism: on the interface between informatic and dynamic processes. Biosyst Eng 64:97–109

    Article  Google Scholar 

  • Hopfield M (1994) Physics, computation, and why biology looks so different. J Theor Biol 171:53–60

    Article  Google Scholar 

  • Istrail S, Ben-Tabou S, Davidson EH (2007) The regulatory genome and the computer. Dev Biol 310:187–195

    Article  Google Scholar 

  • Kauffman SA (1993) The origins of order. Oxford University Press, New York

    Google Scholar 

  • Kinkhabwala A, Bastiaens P (2010) Spatial aspects of intracellular information processing. Curr Opin Genet Dev 20:31–40

    Article  Google Scholar 

  • Kitano H (2004) Biological robustness. Nat Rev Genet 5:826–837

    Article  Google Scholar 

  • Kitano H (2007) Towards a theory of biological robustness. Mol Syst Biol 3:4100179

    Article  Google Scholar 

  • Kobayashi H, Kaern M, Araki M, Chung K, Gardner TS, Cantor CR, Collins JJ (2004) Programmable cells: interfacing natural and engineered gene networks. Proc Natl Acad Sci USA 101:8414–8419

    Article  Google Scholar 

  • Kramer BP, Fischer C, Fussenegger M (2004) BioLogic gates enable logical transcription control in mammalian cells. Biotechnol Bioeng 87:478–484

    Article  Google Scholar 

  • Kwok R (2010) Five hard truths for synthetic biology. Nat Biotechnol 463:288–290

    Article  Google Scholar 

  • Lazebnik Y (2002) Can a biologist fix a radio?—or what i learned while studying apoptosis. Cancer Cell 2:179–182

    Article  Google Scholar 

  • Macia J, Solé RV (2009) Distributed robustness in cellular networks: insights from synthetic evolved circuits. J R Soc Interface 6:393–400

    Article  Google Scholar 

  • Macia J, Posas F, Solé RV (2012) Distributed computation: the new wave of synthetic biology devices. Trends Biotechnol 30:342–349

    Article  Google Scholar 

  • Marchisio MA, Stelling J (2009) Computational design tools for synthetic biology. Curr Opin Biotechnol 20:479–485

    Article  Google Scholar 

  • McGhee GR (2006) The geometry of evolution: adaptive landscapes and theoretical morphospaces. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Moon TS, Clarke EJ, Groban ES, Tamsir A, Clark RM, Eames M, Kortemme T, Voigt CA (2011) Construction of a genetic multiplexer to toggle between chemosensory pathways in Escherichia coli. J Mol Biol. 406:215–27

    Article  Google Scholar 

  • Moses ME, Forrest S, Davis AL, Lodder MA, Brown JH (2008) Scaling theory of information networks. J R Soc Interface 5:1469–1480

    Article  Google Scholar 

  • Morris SC (2004) Life’s solution: inevitable humans in a lonely universe. Cambridge University Press, Cambridge

    Google Scholar 

  • Nelson ME, Bower JM (1990) Brain maps and parallel computers. Trends Neurosci 13:403–408

    Article  Google Scholar 

  • Nurse P (2008) Life, logic and information. Nature 454:424–426

    Article  Google Scholar 

  • Perkins TJ, Swain PS (2009) Strategies for cellular decision-making. Mol Syst Biol 5:326

    Google Scholar 

  • Purnick PEM, Weiss R (2009) The second wave of synthetic biology: from modules to systems. Nat Rev Mol Cell Biol 10:410–422

    Article  Google Scholar 

  • Ratcliff WC, Denison RF, Borrello M, Travisano M (2012) Experimental evolution of multicellularity. Proc Natl Acad Sci USA 109:1595–1600

    Article  Google Scholar 

  • Reed MA, Tour MJ (2000) Computing with molecules. Sci Am 282:86–93

    Article  Google Scholar 

  • Regot S, Macia J, Conde N, Furukawa K et al. (2011) Distributed biological computation with multicellular engineered networks. Nat Biotechnol 469:207–211

    Article  Google Scholar 

  • Ruder WC, Lu T, Collins JJ (2011) Synthetic biology moving into the clinic. Sci Agric 333:1248–1252

    Article  Google Scholar 

  • Sauro HH, Khodolenko BN (2004) Quantitative analysis of signaling networks. Prog Biophys Mol Biol 86:5–43

    Article  Google Scholar 

  • Shou W, Ram S, Vilar JMG (2006) Synthetic cooperation in engineered yeast populations. Proc Natl Acad Sci USA 104:1877–1882

    Article  Google Scholar 

  • Silva-Rocha R, de Lorenzo V (2011) Implementing an OR–NOT (ORN) logic gate with components of the SOS regulatory network of Escherichia coli. Mol BioSyst 7:2389–2396

    Article  Google Scholar 

  • Sipper M (1999) The emergence of cellular computing. Comput Aided Des 32:18–26

    Google Scholar 

  • Smaldon J, Romero-Campero FJ, Fernandez Trillo F, Gheorghe M, Alexander C, Krasnogor N (2010) A computational study of liposome logic: towards cellular computing from the bottom up. Syst Synth Biol 4:157–179

    Article  Google Scholar 

  • Solé RV, Delgado J (1996) Universal computation in fluid neural networks. Complex Int 2:49–56

    Article  Google Scholar 

  • Solé RV, Bonabeau E, Delgado J, Fernández P, Marin J (2000) Pattern formation and optimization in army ant raids. Artif Life 6:219–226

    Article  Google Scholar 

  • Solé RV, Munteanu A, Rodriguez-Caso C, Macia J (2007) Synthetic protocell biology. From reproduction to computation. Philos Trans R Soc B 362:1727–1739

    Article  Google Scholar 

  • Solé RV, Miramontes O, Goodwin BC (1993) Oscillations and chaos in ant societies. J Theor Biol 161:343–357

    Google Scholar 

  • Solé RV, Valverde S, Rosas-Casals M, Kauffman SA, Farmer D, Eldredge N (2013) The evolutionary ecology of technological innovation. Complex Int 18:15–27

    Article  Google Scholar 

  • Song H et al. (2009) Spatiotemporal modulation of biodiversity in a synthetic-mediated ecosystem. Nat Chem Biol 5:929–935

    Article  Google Scholar 

  • Tamsir A, Tabor JJ, Voigt CA (2010) Robust multicellular computing using genetically encoded NOR gates and chemical wires. Nat Biotechnol 469:212–215

    Article  Google Scholar 

  • Tan CM, Song H, Niemi J, You LC (2007) A synthetic biology challenge: making cells compute. Mol Biosyst 3:343–353

    Article  Google Scholar 

  • Tononi G, Sporns O, Edelman GM (1999) Measures of degeneracy and redundancy in biological networks. Proc Natl Acad Sci USA 96:3257–3262

    Article  Google Scholar 

  • von Neumann J (1956) Probabilistic logics and the synthesis of reliable organisms from unreliable components. In: Shannon CE, McCarthy J (eds) Automata studies. Princeton University Press, Princeton, pp 43–76

    Google Scholar 

  • von Neumann J (1958) The computer and the brain. Yale University Press, London

    MATH  Google Scholar 

  • Weber W, Fussenegger M (2012) Emerging biomedical applications of synthetic biology. Nat Rev Gen 13:21–35

    Google Scholar 

  • Weber W et al (2007) Synthetic ecosystems based on airborne inter and intra-kingdom communication. Proc Natl Acad Sci USA 104:10435–10440

    Article  Google Scholar 

  • Weiss R, Basu S, Hooshangi S, Kalmbach A, Karig D, Mehreja R, Netravali I (2003) Genetic circuit building blocks for cellular computation, communications, and signal processing. Nat Comput 2:47–84

    Article  Google Scholar 

  • Wintermute EH, Silver PA (2010) Dynamics in the mixed microbial concourse. Genes Dev 24:2603–2614

    Article  Google Scholar 

  • You L, Cox RS, Weiss R, Arnold FH (2004) Programmed population control by cell–cell communication and regulated killing. Nature 428:868–871

    Article  Google Scholar 

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Acknowledgements

We would like to thank the members of the Complex Systems Lab as well as to F. Posas, L. de Nadal and JF Sebastian for interesting comments. This work has been supported by a European Research Council Advanced Grant, and Grants from the MINECO FIS2009-12365, the Botin Foundation and by the Santa Fe Institute.

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Authors and Affiliations

  1. ICREA-Complex Systems Lab, Universitat Pompeu Fabra, Dr Aiguader 88, 08003, Barcelona, Spain

    Ricard V. Solé & Javier Macia

  2. Institut de Biologia Evolutiva, UPF–CSIC, Psg Barceloneta 37, 08003, Barcelona, Spain

    Ricard V. Solé & Javier Macia

  3. Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM, 87501, USA

    Ricard V. Solé

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  1. Ricard V. Solé
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Correspondence to Ricard V. Solé.

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Solé, R.V., Macia, J. Expanding the landscape of biological computation with synthetic multicellular consortia. Nat Comput 12, 485–497 (2013). https://doi.org/10.1007/s11047-013-9380-y

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