Optically programming DNA computing in microflow reactors.

The programmability and the integration of biochemical processing protocols are addressed for DNA computing using photochemical and microsystem techniques. A magnetically switchable selective transfer module (STM) is presented which implements the basic sequence-specific DNA filtering operation under constant flow. Secondly, a single steady flow system of STMs is presented which solves an arbitrary instance of the maximal clique problem of given maximum size N. Values of N up to about 100 should be achievable with current lithographic techniques. The specific problem is encoded in an initial labeling pattern of each module with one of 2N DNA oligonucleotides, identical for all instances of maximal clique. Thirdly, a method for optically programming the DNA labeling process via photochemical lithography is proposed, allowing different problem instances to be specified. No hydrodynamic switching of flows is required during operation -- the STMs are synchronously clocked by an external magnet. An experimental implementation of this architecture is under construction and will be reported elsewhere.

[1]  David S. Johnson,et al.  Computers and In stractability: A Guide to the Theory of NP-Completeness. W. H Freeman, San Fran , 1979 .

[2]  A D Ellington,et al.  The fidelity of template-directed oligonucleotide ligation and its relevance to DNA computation. , 1998, Nucleic acids research.

[3]  L M Adleman,et al.  Molecular computation of solutions to combinatorial problems. , 1994, Science.

[4]  S. P. Fodor,et al.  Light-directed, spatially addressable parallel chemical synthesis. , 1991, Science.

[5]  Shi V. Liu Debating controversies can enhance creativity , 2000, Nature.

[6]  A. Condon,et al.  Demonstration of a word design strategy for DNA computing on surfaces. , 1997, Nucleic acids research.

[7]  D. Fogel Evolutionary algorithms in theory and practice , 1997, Complex..

[8]  F Guarnieri,et al.  Maya Blue Paint: An Ancient Nanostructured Material , 1996, Science.

[9]  S. Mangru,et al.  Dynamic DNA hybridization on a chip using paramagnetic beads. , 1999, Analytical chemistry.

[10]  J P Klein,et al.  A biomolecular implementation of logically reversible computation with minimal energy dissipation , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[11]  J Reif,et al.  Micro flow bio-molecular computation. , 1999, Bio Systems.

[12]  Eric Bach,et al.  DNA Models and Algorithms for NP-Complete Problems , 1998, J. Comput. Syst. Sci..

[13]  J. McCaskill,et al.  End-specific covalent photo-dependent immobilisation of synthetic DNA to paramagnetic beads. , 2000, Nucleic acids research.

[14]  J. McCaskill,et al.  Spatially resolved in vitro molecular ecology. , 1997, Biophysical chemistry.

[15]  Masami Hagiya,et al.  State Transitions by Molecules State Transitions by Molecules , 1998 .

[16]  P. Yager,et al.  Microfluidic Diffusion-Based Separation and Detection , 1999, Science.

[17]  Lloyd M. Smith,et al.  DNA Computing on Surfaces : the Chemical Implementation , 2000 .

[18]  A Manz,et al.  Chemical amplification: continuous-flow PCR on a chip. , 1998, Science.

[19]  G. S. Manning The molecular theory of polyelectrolyte solutions with applications to the electrostatic properties of polynucleotides , 1978, Quarterly Reviews of Biophysics.

[20]  Martyn Amos,et al.  The Complexity and Viability of DNA Computations , 1997, BCEC.

[21]  Charles H. Bennett,et al.  The thermodynamics of computation—a review , 1982 .

[22]  P D Kaplan,et al.  DNA solution of the maximal clique problem. , 1997, Science.

[23]  D K Gifford,et al.  Design and implementation of computational systems based on programmed mutagenesis. , 1999, Bio Systems.

[24]  J. Schwartz,et al.  Theory of Self-Reproducing Automata , 1967 .

[25]  R J Lipton,et al.  DNA solution of hard computational problems. , 1995, Science.

[26]  Kozo Kinoshita,et al.  Ligation errors in DNA computing. , 1999, Bio Systems.

[27]  L F Landweber,et al.  Molecular computation: RNA solutions to chess problems , 2000, Proc. Natl. Acad. Sci. USA.

[28]  L F Landweber,et al.  Chess games: a model for RNA based computation. , 1999, Bio Systems.