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Experimental efficiency of programmed mutagenesis

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Abstract

Mismatched DNA annealing followed by strand replication can cause the programmed evolution of DNA sequences. We have reported that this process is theoretically equivalent in computational power to a desktop computer by demonstrating a constructive way to encode arbitrary computations as DNA molecules within the framework of programmed mutagenesis, a system that consists solely of cycles of DNA annealing, polymerization, and ligation.1,2) Thus, programmed mutagenesis is theoretically universal and we report here the experimental efficiency of its primitive operations. The measured efficiency of an in vitro programmed mutagenesis system suggests that segregating the products of DNA replication into separate compartments would be an efficient way to implement molecular computation. For computer science, using single DNA molecules to represent the state of a computation holds the promise of a new paradigm of composable molecular computing. For biology, the demonstration that DNA sequences could guide their own evolution under computational rules may have implications as we begin to unravel the mysteries of genome encoding and natural evolution.

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Authors and Affiliations

  1. Massachusetts Institute of Technology, 200 Technology Square, 02139, Cambridge, MA, USA

    Julia Khodor & David K. Gifford

Authors
  1. Julia Khodor
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  2. David K. Gifford
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Correspondence to Julia Khodor.

Additional information

Julia Khodor, Ph.D.: She has just received her Ph.D. in Electrical Engineering and Computer Science from MIT and is now enjoying her time off with her new daughter. She received her B.S. in Mathematics with Computer Science and B.S. in Biology in 1996 and her M.S. in Computer Science in 1998, all from MIT. Her graduate research was in the area of biological computing, primarily focusing on programmed mutagenesis. She is looking forward to the joys and challenges of an academic career.

David K. Gifford, Ph.D.: He is a professor of computer science and electrical engineering at MIT, where he leads a research group investigating issues in computational functional genomics. His research interests include understanding data from high-throughput experimental systems using probabilistic modeling techniques. He received a Ph.D. in computer science from Stanford University.

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Khodor, J., Gifford, D.K. Experimental efficiency of programmed mutagenesis. New Gener Comput 20, 307–315 (2002). https://doi.org/10.1007/BF03037363

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  • DOI: https://doi.org/10.1007/BF03037363

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