Protein output for DNA computing

  • Authors:

  • Christian V. Henkel;Reno S. Bladergroen;Crina I. Balog;André M. Deelder;Tom Head;Grzegorz Rozenberg;Herman P. Spaink

  • Affiliations:

  • Aff1 Aff2 Aff3;Aff1 Aff2;Department of Parasitology, Leiden University Medical Center, Leiden, The Netherlands 2300;Department of Parasitology, Leiden University Medical Center, Leiden, The Netherlands 2300;Department of Mathematical Sciences, Binghamton University, Binghamton, USA 13902-6000;Aff1 Aff3;Aff1 Aff3

  • Venue:
  • Natural Computing: an international journal
  • Year:
  • 2005

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Abstract

In recent years, several strategies for DNA based molecular computing have been investigated. An important area of research is the detection and analysis of output molecules. We demonstrate how DNA computing can be extended with in vivo translation of the output. In the resulting proteins, the information per kilogram is about 15-fold higher than in the original DNA output. The proteins are therefore of correspondingly smaller mass, which facilitates their subsequent detection using highly sensitive mass spectrometry methods. We have tested this approach on an instance of the Minimal Dominating Set problem. The DNA used in the computation was constructed as an open reading frame in a plasmid, under the control of a strong inducible promoter. Sequential application of restriction endonucleases yielded a library of potential solutions to the problem instance. The mixture of plasmids was then used for expression of a protein representation. Using MALDI-TOF mass spectrometry, a protein corresponding to the correct solution could be detected. The results indicate the feasibility of the extension of DNA computing to include protein technology. Our strategy opens up new possibilities for both scaling of DNA computations and implementations that employ output of functional molecules or phenotypes.