Engineered communications for microbial robotics

  • Ron Weiss
  • Thomas F. KnightJr.
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2054)

Abstract

Multicellular organisms create complex patterned structures from identical, unreliable components. Learning how to engineer such robust behavior is important to both an improved understanding of computer science and to a better understanding of the natural developmental process. Earlier work by our colleagues and ourselves on amorphous computing demonstrates in simulation how one might build complex patterned behavior in this way. This work reports on our first efforts to engineer microbial cells to exhibit this kind of multicellular pattern directed behavior.

We describe a specific natural system, the Lux operon of Vibrio fischeri, which exhibits density dependent behavior using a well characterized set of genetic components. We have isolated, sequenced, and used these components to engineer intercellular communication mechanisms between living bacterial cells.

In combination with digitally controlled intracellular genetic circuits, we believe this work allows us to begin the more difficult process of using these communication mechanisms to perform directed engineering of multicellular structures, using techniques such as chemical diffusion dependent behavior. These same techniques form an essential part of our toolkit for engineering with life, and are widely applicable in the field of microbial robotics, with potential applications in medicine, environmental monitoring and control, engineered crop cultivation, and molecular scale fabrication.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    H Abelson, D Allen, D Coore, C Hanson, G Homsy, TF Knight, R Nagpal, E Rauch, GJ sussman, and R Weiss, Amorphous computing, Tech. Report AI Memo No. 1665, MIT Artificial Intelligence Laboratory, 1999.Google Scholar
  2. 2.
    FM Ausubel, R Brent, RE Kingston, DD Moore, JG Seidman, JA Smith, and K Struhl, Short protocols in molecular biology, Wiley, 1999.Google Scholar
  3. 3.
    D Coore, Botanical computing: A developmental approach to generating interconnect topologies on an amorphous computer, Ph.D. thesis, Massachusetts Institute of Technology, 1998.Google Scholar
  4. 4.
    D Coore, R Nagpal, and R Weiss, Paradigms for structure in an amorphous computing, Tech. Report AI Memo No. 1614, MIT Artificial Intelligence Laboratory, 1997.Google Scholar
  5. 5.
    T deKievit, PC Seed, J Nezezon, L Passador, and BH Iglewski, Rsal, a novel repressor of virulence gene expression in pseudomonas aeruginosa, J. Bacteriol 181 (1999), 2175–2184.Google Scholar
  6. 6.
    JH Devine, Countryman, and TO Baldwin, Nucleotide sequence of the luxr and luxi genes and structure of the primary regulatory region of the lux regulon of vibrio fischeri atcc7744, Biochemistry, vol. 27, 1988, GENBANK M19039 (strain ATCC 7744), pp. 837–842.CrossRefGoogle Scholar
  7. 7.
    JH Devine, GS Shadel, and TO Baldwin, Identification of the operator of the lux regulon from the vibrio fischeri strain atcc7744, Proc. Natl. Acad. Sci. USA, vol. 86, 1989, genbank M25751 (strain MJ-1) and M25752 (strain ATCC 7744, subset of M19039), pp. 5688–92.CrossRefGoogle Scholar
  8. 8.
    M Dworkin, Cell-cell interactions in the myxobacteria, Symp. Soc. Gen. Microbiol., vol. 25, 1973, pp. 135–147.Google Scholar
  9. 9.
    M Dworkin and D Kaiser, Cell interactions in myxobacterial growth and development, Science 230 (1985), 18–24.CrossRefGoogle Scholar
  10. 10.
    A Eberhard, AL Burlingame, C Eberhard, GL Kenyon, KH Nealson, and NJ Oppenheimer, Structural identification of autoinducer of photobacterium fischeri luciferase, Biochemistry, vol. 20, 1981, pp. 2444–2449.CrossRefGoogle Scholar
  11. 11.
    M Elowitz and S Leibler, A synthetic oscillatory network of transcriptional regulators, Nature 403 (2000), 335–338.CrossRefGoogle Scholar
  12. 12.
    J Engebrecht, KH Nealson, and M Silverman, Bacterial bioluminescence: isolation and genetic analysis of the functions from vibrio fischeri, Cell, vol. 32, 1983, pp. 773–781.CrossRefGoogle Scholar
  13. 13.
    J Engebrecht and M Silverman, Nucleotide sequence of the regulatory locus controlling expression of the bacterial genes for bioluminescence, Nuc. Acids Res., vol. 15, 1987, GENBANK Y00509 (strain MJ-1), pp. 10455–10467.CrossRefGoogle Scholar
  14. 14.
    C Fuqua and A Eberhard, Signal generation in autoinduction systems: synthesis of acylated homoserine lactones by LuxI-type proteins, 211–230, GM Dunny and Winans, Washington, DC, 1999, pp. 211–230.Google Scholar
  15. 15.
    WC Fuqua, S Winans, and EP Greenberg, Quorum sensing in bacteria: The luxr-luxi family of cell density-responsive transcriptional regulators, J. Bacteriol 176 (1994), 269–275.Google Scholar
  16. 16.
    T Gardner, R Cantor, and J Collins, Construction of a genetic toggle switch in escherichia coli, Nature 403 (2000), 339–342.CrossRefGoogle Scholar
  17. 17.
    KM Gray and EP Greenberg, Sequencing and analysis of luxr and luxi, the luminescence regulatory genes from the squid light organ symbiont vibrio fischeri es114, Molecular Marine Biology and Biotechnology, vol. 1, 1992, GENBANK M96844 (strain ES114), pp. 414–419.Google Scholar
  18. 18.
    EP Greenberg, Quorum sensing in gram-negative bacteria, ASM News, vol. 63, 1997, pp. 371–377.Google Scholar
  19. 19.
    Thomas F. Knight Jr. and Gerald Jay Sussman, Cellular gate technology, First International Conference on Unconventional Models of Computation (CS Calude, J Casti, and MJ Dinneen, eds.), Springer-Verlag, 1998, pp. 257–272.Google Scholar
  20. 20.
    D Kaiser, Regulation of multicellular development in myxobacteria, Microbial Development (1984), 197–218.Google Scholar
  21. 21.
    TF Knight and N Papadakis, Vibrio fischeri lux operon sali digest, GENBANK AF170104 (strain MJ-1), 1999.Google Scholar
  22. 22.
    S Lisser and H Margalit, Compilation of escherichia coli mrna promoter sequences, Nuc. Acids Res. 21 (1993), no. 7, 1507–1516.CrossRefGoogle Scholar
  23. 23.
    Harley H. McAdams and Adam Arkin, Simulation of prokaryotic genetic circuits, Annu. Rev. Biophys. Biomol. Struc. 27 (1998), 199–224.CrossRefGoogle Scholar
  24. 24.
    R Nagpal, Organizing a global coordinate system from local information on an amorphous computer, Tech. Report AI Memo No. 1666, MIT Artificial Intelligence Laboratory, 1999.Google Scholar
  25. 25.
    A Orosz, I Boros, and P Venetianer, Analysis of the complex transcription termination region of the escherichia coli rrnb gene, Eur. J. Biochem, vol. 201, 1991, pp. 653–659.CrossRefGoogle Scholar
  26. 26.
    E Rauch, Discrete, amorphous physical models, Master’s thesis, Massachusetts Institute of Technology, 1999.Google Scholar
  27. 27.
    EG Ruby and KH Nealson, Symbiotic association of photobacterium fischeri with the marine luminous fish monocentris japonica: a model of symboisis based on bacterial studies, Biol. Bull 151 (1976), 574–586.CrossRefGoogle Scholar
  28. 28.
    AM Stevens and EP Greenberg, Transcriptional activation by luxr, in cell-cell signaling in bacteria, Cell-Cell Signaling in Bacteria (GM Dunny and Winans, eds.), American Society for Microbiology, 1999.Google Scholar
  29. 29.
    Ron Weiss and George Homsy, Toward in-vivo digital circuits, Dimacs Workshop on Evolution as Computation (Princeton, NJ), January 1999.Google Scholar
  30. 30.
    Ron Weiss, George Homsy, and Radhika Nagpal, Programming biological cells, Eighth International Conference on Architectural Support for Programming Languages and Operating Systems, Wild and Crazy Ideas Session (San Jose, California), October 1998.Google Scholar
  31. 31.
    MR Winfrey, MA Rott, and AT Wortman, Unraveling dna: Molecular biology for the laboratory, Prentice Hall, 1997.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Ron Weiss
    • 1
  • Thomas F. KnightJr.
    • 1
  1. 1.M.I.T. Artificial Intelligence LaboratoryCambridgeUSA

Personalised recommendations