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Nucleic Acids Research Advance Access published online on March 5, 2009
Nucleic Acids Research, doi:10.1093/nar/gkp079
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Computational Biology

Engineering transcription factors with novel DNA-binding specificity using comparative genomics

Tasha A. Desai1, Dmitry A. Rodionov2,3, Mikhail S. Gelfand3,4, Eric J. Alm5,* and Christopher V. Rao1,*

1Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, 2Burnham Institute for Medical Research, La Jolla, CA 92037, USA, 3Institute for Information Transmission Problems (The A. A. Kharkevich Institute), Russian Academy of Sciences, Moscow 127994, 4Faculty of Bioengineering and Bioinformatics, Moscow State University, Moscow 119992, Russia and 5Department of Biological Engineering and Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

*To whom correspondence should be addressed. Tel: +1 217 244 2247; Fax: +1 217 333 5052; Email: chris{at}scs.uiuc.edu Correspondence may also be addressed to Eric J. Alm. Tel: +1 617 253 2726; Fax: +617 258 6775; Email: ejalm{at}mit.edu

Received January 2, 2009. Revised January 26, 2009. Accepted January 28, 2009.

The transcriptional program for a gene consists of the promoter necessary for recruiting RNA polymerase along with neighboring operator sites that bind different activators and repressors. From a synthetic biology perspective, if the DNA-binding specificity of these proteins can be changed, then they can be used to reprogram gene expression in cells. While many experimental methods exist for generating such specificity-altering mutations, few computational approaches are available, particularly in the case of bacterial transcription factors. In a previously published computational study of nitrogen oxide metabolism in bacteria, a small number of amino-acid residues were found to determine the specificity within the CRP (cAMP receptor protein)/FNR (fumarate and nitrate reductase regulatory protein) family of transcription factors. By analyzing how these amino acids vary in different regulators, a simple relationship between the identity of these residues and their target DNA-binding sequence was constructed. In this article, we experimentally tested whether this relationship could be used to engineer novel DNA–protein interactions. Using Escherichia coli CRP as a template, we tested eight designs based on this relationship and found that four worked as predicted. Collectively, these results in this work demonstrate that comparative genomics can inform the design of bacterial transcription factors.


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