| Many gene regulatory motifs in both prokaryotes and eukaryotes involve physical manipulations of the genetic material, often on length scales short enough that the mechanical properties of the DNA significantly impact gene expression. One class of such manipulations, called "action at a distance", includes transcription factor-mediated DNA looping, in which a binding site some distance away on the DNA is brought into close proximity with the transcription machinery at the promoter. DNA looping is a key component of several important regulatory systems in bacteria, and is crucial to the combinatorial control that is common at eukaryotic promoters regulated by more transcription factors than can physically bind adjacent to the promoter. Here we use a prototypical DNA looping protein, the Lac repressor from E. coli, to explore questions regarding the role of DNA mechanics in DNA looping and combinatorial control, particularly concerning the role of sequence flexibility in short-length-scale looping. We combine a statistical mechanical model of looping by the Lac repressor with a single-molecule technique called tethered particle motion that allows us to quantify this looping, and the systematic tuning of four biologically relevant and experimentally tractable parameters: loop length, loop sequence, repressor-DNA affinity, and repressor concentration. We show that this combination is a powerful approach to measuring repressor-DNA binding affinities and sequence-dependent DNA flexibilities in a way that is orthogonal, and therefore complementary, to conventional ensemble assays. Our results show that the sequence dependence to looping is more complicated than has been observed in other contexts, suggesting that "sequence flexibility" as a general term is misleading, and, we argue, that the measurement of sequence flexibilities depend more strongly than previously appreciated on the shape of the deformation used to make the measurement. Finally, we present preliminary results with a more complicated system that is a case study for broader issues in combinatorial control, and a new hidden Markov model approach, based on variational Bayesian inference, to analyze these more complicated systems, which we hope will allow more precise dissections of, and more robust extraction of kinetic parameters from, tethered particle motion assays. |
