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Title: Deciphering the protein‐DNA code of bacterial winged helix‐turn‐helix transcription factors
Background

Sequence‐specific binding by transcription factors (TFs) plays a significant role in the selection and regulation of target genes. At the protein:DNA interface, amino acid side‐chains construct a diverse physicochemical network of specific and non‐specific interactions, and seemingly subtle changes in amino acid identity at certain positions may dramatically impact TF:DNA binding. Variation of these specificity‐determining residues (SDRs) is a major mechanism of functional divergence between TFs with strong structural or sequence homology.

Methods

In this study, we employed a combination of high‐throughput specificity profiling by SELEX and Spec‐seq, structural modeling, and evolutionary analysis to probe the binding preferences of winged helix‐turn‐helix TFs belonging to the OmpR sub‐family inEscherichia coli.

Results

We found thatE. coliOmpR paralogs recognize tandem, variably spaced repeats composed of “GT‐A” or “GCT”‐containing half‐sites. Some divergent sequence preferences observed within the “GT‐A” mode correlate with amino acid similarity; conversely, “GCT”‐based motifs were observed for a subset of paralogs with low sequence homology. Direct specificity profiling of a subset of OmpR homologues (CpxR, RstA, and OmpR) as well as predicted “SDR‐swap” variants revealed that individual SDRs may impact sequence preferences locally through direct contact with DNA bases or distally via the DNA backbone.

Conclusions

Overall, our work provides evidence for a common structural “code” for sequence‐specific wHTH‐DNA interactions, and demonstrates that surprisingly modest residue changes can enable recognition of highly divergent sequence motifs. Further examination of SDR predictions will likely reveal additional mechanisms controlling the evolutionary divergence of this important class of transcriptional regulators.

 
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NSF-PAR ID:
10478004
Author(s) / Creator(s):
 ;  
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Quantitative Biology
Volume:
6
Issue:
1
ISSN:
2095-4689
Format(s):
Medium: X Size: p. 68-84
Size(s):
["p. 68-84"]
Sponsoring Org:
National Science Foundation
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