Letters to Nature

Nature 429, 423-429 (27 May 2004) | doi:10.1038/nature02551; Received 4 February 2004; Accepted 6 April 2004; Published online 28 April 2004

An autonomous molecular computer for logical control of gene expression

Yaakov Benenson1,2, Binyamin Gil2, Uri Ben-Dor1, Rivka Adar2 & Ehud Shapiro1,2

  1. Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel
  2. Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel

Correspondence to: Ehud Shapiro1,2 Email: Ehud.Shapiro@weizmann.ac.il

Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems1, 2, 3, 4, 5, 6, 7. Recently, simple molecular-scale autonomous programmable computers were demonstrated8, 9, 10, 11, 12, 13, 14, 15 allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for 'logical' control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton12, 13, 14, 15, 16, 17; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes18, 19, 20, 21, 22 associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug.


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