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

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          Abstract

          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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          Most cited references58

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          The regulation of bacterial transcription initiation.

          Bacteria use their genetic material with great effectiveness to make the right products in the correct amounts at the appropriate time. Studying bacterial transcription initiation in Escherichia coli has served as a model for understanding transcriptional control throughout all kingdoms of life. Every step in the pathway between gene and function is exploited to exercise this control, but for reasons of economy, it is plain that the key step to regulate is the initiation of RNA-transcript formation.
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            Gene regulatory network growth by duplication.

            We are beginning to elucidate transcriptional regulatory networks on a large scale and to understand some of the structural principles of these networks, but the evolutionary mechanisms that form these networks are still mostly unknown. Here we investigate the role of gene duplication in network evolution. Gene duplication is the driving force for creating new genes in genomes: at least 50% of prokaryotic genes and over 90% of eukaryotic genes are products of gene duplication. The transcriptional interactions in regulatory networks consist of multiple components, and duplication processes that generate new interactions would need to be more complex. We define possible duplication scenarios and show that they formed the regulatory networks of the prokaryote Escherichia coli and the eukaryote Saccharomyces cerevisiae. Gene duplication has had a key role in network evolution: more than one-third of known regulatory interactions were inherited from the ancestral transcription factor or target gene after duplication, and roughly one-half of the interactions were gained during divergence after duplication. In addition, we conclude that evolution has been incremental, rather than making entire regulatory circuits or motifs by duplication with inheritance of interactions.
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              The Genomes On Line Database (GOLD) in 2007: status of genomic and metagenomic projects and their associated metadata

              The Genomes On Line Database (GOLD) is a comprehensive resource that provides information on genome and metagenome projects worldwide. Complete and ongoing projects and their associated metadata can be accessed in GOLD through pre-computed lists and a search page. As of September 2007, GOLD contains information on more than 2900 sequencing projects, out of which 639 have been completed and their sequence data deposited in the public databases. GOLD continues to expand with the goal of providing metadata information related to the projects and the organisms/environments towards the Minimum Information about a Genome Sequence’ (MIGS) guideline. GOLD is available at http://www.genomesonline.org and has a mirror site at the Institute of Molecular Biology and Biotechnology, Crete, Greece at http://gold.imbb.forth.gr/
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                May 2009
                May 2009
                5 March 2009
                5 March 2009
                : 37
                : 8
                : 2493-2503
                Affiliations
                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
                Author notes
                *To whom correspondence should be addressed. Tel: +1 217 244 2247; Fax: +1 217 333 5052; Email: chris@ 123456scs.uiuc.edu Correspondence may also be addressed to Eric J. Alm. Tel: +1 617 253 2726; Fax: +617 258 6775; Email: ejalm@ 123456mit.edu
                Article
                gkp079
                10.1093/nar/gkp079
                2677863
                19264798
                0896c0b9-9946-412a-be63-b9c8c6d5378c
                © 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.

                History
                : 2 January 2009
                : 26 January 2009
                : 28 January 2009
                Categories
                Computational Biology

                Genetics
                Genetics

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