Natural Computing

, Volume 12, Issue 4, pp 485–497 | Cite as

Expanding the landscape of biological computation with synthetic multicellular consortia

  • Ricard V. Solé
  • Javier Macia


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.


Synthetic biology Cell computing Circuit design Evolution Robustness 



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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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.ICREA-Complex Systems LabUniversitat Pompeu FabraBarcelonaSpain
  2. 2.Institut de Biologia Evolutiva, UPF–CSICBarcelonaSpain
  3. 3.Santa Fe InstituteSanta FeUSA

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