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Local Gene Regulation Details a Recognition Code within the LacI Transcriptional Factor Family

Overview of attention for article published in PLoS Computational Biology, November 2010
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Title
Local Gene Regulation Details a Recognition Code within the LacI Transcriptional Factor Family
Published in
PLoS Computational Biology, November 2010
DOI 10.1371/journal.pcbi.1000989
Pubmed ID
Authors

Francisco M. Camas, Eric J. Alm, Juan F. Poyatos

Abstract

The specific binding of regulatory proteins to DNA sequences exhibits no clear patterns of association between amino acids (AAs) and nucleotides (NTs). This complexity of protein-DNA interactions raises the question of whether a simple set of wide-coverage recognition rules can ever be identified. Here, we analyzed this issue using the extensive LacI family of transcriptional factors (TFs). We searched for recognition patterns by introducing a new approach to phylogenetic footprinting, based on the pervasive presence of local regulation in prokaryotic transcriptional networks. We identified a set of specificity correlations--determined by two AAs of the TFs and two NTs in the binding sites--that is conserved throughout a dominant subgroup within the family regardless of the evolutionary distance, and that act as a relatively consistent recognition code. The proposed rules are confirmed with data of previous experimental studies and by events of convergent evolution in the phylogenetic tree. The presence of a code emphasizes the stable structural context of the LacI family, while defining a precise blueprint to reprogram TF specificity with many practical applications.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 3%
United Kingdom 1 3%
Belgium 1 3%
Spain 1 3%
United States 1 3%
Unknown 26 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 32%
Student > Ph. D. Student 8 26%
Professor > Associate Professor 4 13%
Student > Bachelor 3 10%
Professor 2 6%
Other 2 6%
Unknown 2 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 55%
Biochemistry, Genetics and Molecular Biology 6 19%
Environmental Science 2 6%
Immunology and Microbiology 1 3%
Social Sciences 1 3%
Other 2 6%
Unknown 2 6%