Landscape of DNA binding signatures of myocyte enhancer factor-2B reveals a unique interplay of base and shape readout.

Ana Carolina Dantas Machado, Brendon H Cooper, Xiao Lei, Rosa Di Felice, Lin Chen, Remo Rohs

Journal: Nucleic acids research 2020;48(15):8529-8544

PMID: 32738045

Abstract

Myocyte enhancer factor-2B (MEF2B) has the unique capability of binding to its DNA target sites with a degenerate motif, while still functioning as a gene-specific transcriptional regulator. Identifying its DNA targets is crucial given regulatory roles exerted by members of the MEF2 family and MEF2B's involvement in B-cell lymphoma. Analyzing structural data and SELEX-seq experimental results, we deduced the DNA sequence and shape determinants of MEF2B target sites on a high-throughput basis in vitro for wild-type and mutant proteins. Quantitative modeling of MEF2B binding affinities and computational simulations exposed the DNA readout mechanisms of MEF2B. The resulting binding signature of MEF2B revealed distinct intricacies of DNA recognition compared to other transcription factors. MEF2B uses base readout at its half-sites combined with shape readout at the center of its degenerate motif, where A-tract polarity dictates nuances of binding. The predominant role of shape readout at the center of the core motif, with most contacts formed in the minor groove, differs from previously observed protein-DNA readout modes. MEF2B, therefore, represents a unique protein for studies of the role of DNA shape in achieving binding specificity. MEF2B-DNA recognition mechanisms are likely representative for other members of the MEF2 family.

© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

Address: Quantitative and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.; Molecular and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.; Quantitative and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.; Department of Physics & Astronomy, University of Southern California, Los Angeles, CA 90089, USA.; Molecular and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.; Department of Chemistry, University of Southern California, Los Angeles, CA 90089, USA.; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA.; Quantitative and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.; Department of Physics & Astronomy, University of Southern California, Los Angeles, CA 90089, USA.; Department of Chemistry, University of Southern California, Los Angeles, CA 90089, USA.; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA.; Department of Computer Science, University of Southern California, Los Angeles, CA 90089, USA.
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