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Gene regulatory networks (GRNs) determine cellular behaviour, and ultimately the functioning of single- and multicellular organisms. Transcription factors regulate gene expression by binding to DNA or via remodelling chromatin. Recent advances in biotechnological methods have made it possible to precisely characterise the binding of transcription factors to single consensus binding sites. Advanced sequencing methods allow the efficient discovery of de novo binding consensus sequences, and thus provide insight into the evolution of GRNs. However, clusters of transcription factor binding sites have been poorly studied despite their prevalence in eukaryotic genomes. Widely-used methods of GRN interrogation lack the sensitivity for transient binding events with low-affinity binding sites.
In my PhD, using the MITOMI platform I showed that two orthologs of the transcription factor Pho4 from S. cerevisiae and C. glabrata that have evolved distinct regulation have similar 3D structure and DNA binding preferences over a wide affinity range.
I have developed the iMITOMI assay that preserves the unique advantages of the original MITOMI platform, and thus too has the ability to rapidly characterise transient binding events with high-throughput. In addition, iMITOMI enables the study of transcription factor binding site clusters. We have studied in detail the interactions of Pho4 and Zif268 with clusters of one to six binding sites. The individual binding sites had affinities one to two orders of magnitude below the affinity of the corresponding consensus sequence. We discovered that clusters of low-affinity binding sites could give rise to transcription factor occupancies comparable to or higher than those of single-consensus sequences. Our results demonstrate that low-affinity binding site clusters give rise to high occupancy levels. These have significant implications for the biophysical characterisation of transcription factor binding, the de novo evolution of enhancers and promoters, and the development of synthetic promoters.
Sebastian Maerkl, Shiyu Cheng, Maria Lopez Malo, Amir Shahein, Ivan Istomin, Evan James Olson