Cargando…

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

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 the...

Descripción completa

Detalles Bibliográficos
Autores principales: Desai, Tasha A., Rodionov, Dmitry A., Gelfand, Mikhail S., Alm, Eric J., Rao, Christopher V.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2677863/
https://www.ncbi.nlm.nih.gov/pubmed/19264798
http://dx.doi.org/10.1093/nar/gkp079
_version_ 1782166799526133760
author Desai, Tasha A.
Rodionov, Dmitry A.
Gelfand, Mikhail S.
Alm, Eric J.
Rao, Christopher V.
author_facet Desai, Tasha A.
Rodionov, Dmitry A.
Gelfand, Mikhail S.
Alm, Eric J.
Rao, Christopher V.
author_sort Desai, Tasha A.
collection PubMed
description 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.
format Text
id pubmed-2677863
institution National Center for Biotechnology Information
language English
publishDate 2009
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-26778632009-05-15 Engineering transcription factors with novel DNA-binding specificity using comparative genomics Desai, Tasha A. Rodionov, Dmitry A. Gelfand, Mikhail S. Alm, Eric J. Rao, Christopher V. Nucleic Acids Res Computational Biology 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. Oxford University Press 2009-05 2009-03-05 /pmc/articles/PMC2677863/ /pubmed/19264798 http://dx.doi.org/10.1093/nar/gkp079 Text en © 2009 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ 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.
spellingShingle Computational Biology
Desai, Tasha A.
Rodionov, Dmitry A.
Gelfand, Mikhail S.
Alm, Eric J.
Rao, Christopher V.
Engineering transcription factors with novel DNA-binding specificity using comparative genomics
title Engineering transcription factors with novel DNA-binding specificity using comparative genomics
title_full Engineering transcription factors with novel DNA-binding specificity using comparative genomics
title_fullStr Engineering transcription factors with novel DNA-binding specificity using comparative genomics
title_full_unstemmed Engineering transcription factors with novel DNA-binding specificity using comparative genomics
title_short Engineering transcription factors with novel DNA-binding specificity using comparative genomics
title_sort engineering transcription factors with novel dna-binding specificity using comparative genomics
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2677863/
https://www.ncbi.nlm.nih.gov/pubmed/19264798
http://dx.doi.org/10.1093/nar/gkp079
work_keys_str_mv AT desaitashaa engineeringtranscriptionfactorswithnoveldnabindingspecificityusingcomparativegenomics
AT rodionovdmitrya engineeringtranscriptionfactorswithnoveldnabindingspecificityusingcomparativegenomics
AT gelfandmikhails engineeringtranscriptionfactorswithnoveldnabindingspecificityusingcomparativegenomics
AT almericj engineeringtranscriptionfactorswithnoveldnabindingspecificityusingcomparativegenomics
AT raochristopherv engineeringtranscriptionfactorswithnoveldnabindingspecificityusingcomparativegenomics