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In eukaryotes, genomic DNA is extruded into loops by cohesin1. By restraining this process, the DNA-binding protein CCCTC-binding factor (CTCF) generates topologically associating domains (TADs)2,3that have important roles in gene regulation and recombination during development and disease1,4–7. How CTCF establishes TAD boundaries and to what extent these are permeable to cohesin is unclear8. Here, to address these questions, we visualize interactions of single CTCF and cohesin molecules on DNA in vitro. We show that CTCF is sufficient to block diffusing cohesin, possibly reflecting how cohesive cohesin accumulates at TAD boundaries, and is also sufficient to block loop-extruding cohesin, reflecting how CTCF establishes TAD boundaries. CTCF functions asymmetrically, as predicted; however, CTCF is dependent on DNA tension. Moreover, CTCF regulates cohesin’s loop-extrusion activity by changing its direction and by inducing loop shrinkage. Our data indicate that CTCF is not, as previously assumed, simply a barrier to cohesin-mediated loop extrusion but is an active regulator of this process, whereby the permeability of TAD boundaries can be modulated by DNA tension. These results reveal mechanistic principles of how CTCF controls loop extrusion and genome architecture.

Mechanophores are powerful molecular tools used to track bond rupture and characterize mechanical damage in polymers. The majority of mechanophores are known to respond to external stresses, and we report in this study the first precedent of a mechanochemical response to internal, residual stresses that accumulate during polymer vitrification. While internal stress is intrinsic to polymers that can form solids, we demonstrate that it can dramatically affect the mechanochemistry of spiropyran probes and alter their intramolecular isomerization barriers by up to 70 kJ mol–1. This new behavior of spiropyrans (SPs) enables their application for analysis of internal stresses distribution and their mechanochemical characterization on the molecular level. Spectroscopy and imaging based on SP mechanochemistry showed high topological sensitivity and allowed us to discern different levels of internal stress impacting various locations along the polymer chain. The nature of the developed technique allows for wide-field imaging of stress heterogeneities in polymer samples of irregular shapes and dimensions, making it feasible to directly observe molecular-level manifestations of mechanical stresses that accompany the formation of a vast number of solid polymers.

CpG islands recruit MLL1 via the CXXC domain to modulate chromatin structure and regulate gene expression. The amino acid motif of CXXC also plays a pivotal role in MLL1’s structure and function and serves as a target for drug design. In addition, the CpG pattern in an island governs spatially dependent collaboration among CpGs in recruiting epigenetic enzymes. However, current studies using short DNA fragments cannot probe the dynamics of CXXC on long DNA with crowded CpG motifs. Here, we used single-molecule magnetic tweezers to examine the binding dynamics of MLL1’s CXXC domain on a long DNA with a CpG island. The mechanical strand separation assay allows profiling of protein-DNA complexes and reports force-dependent unfolding times. Further design of a hairpin detector reveals the unfolding time of individual CXXC-CpG complexes. Finally, in a proof of concept we demonstrate the inhibiting effect of dimethyl fumarate on the CXXC-DNA complexes by measuring the dose response curve of the unfolding time. This demonstrates the potential feasibility of using single-molecule strand separation as a label-free detector in drug discovery and chemical biology.

Multiplexed single-molecule magnetic tweezers (MT) have recently been employed to probe the RNA synthesis dynamics of RNA-dependent RNA polymerases (RdRp). Here, we present a protocol for simultaneously probing the RNA synthesis dynamics of hundreds of single polymerases with MT. We describe the preparation of a dsRNA construct for probing single RdRp kinetics. We then detail the measurement of RdRp RNA synthesis kinetics using MT. The protocol is suitable for high-throughput probing of RdRp-targeting antiviral compounds for mechanistic function and efficacy.

Pausing by bacterial RNA polymerase (RNAp) is vital in the recruitment of regulatory factors, RNA folding, and coupled translation. While backtracking and intra-structural isomerization have been proposed to trigger pausing, our mechanistic understanding of backtrack-associated pauses and catalytic recovery remains incomplete. Using high-throughput magnetic tweezers, we examine the Escherichia coliRNAp transcription dynamics over a wide range of forces and NTP concentrations. Dwell-time analysis and stochastic modeling identify, in addition to a short-lived elemental pause, two distinct long-lived backtrack pause states differing in recovery rates. We identify two stochastic sources of transcription heterogeneity: alterations in short-pause frequency that underlies elongation-rate switching, and variations in RNA cleavage rates in long-lived backtrack states. Together with effects of force and Gre factors, we demonstrate that recovery from deep backtracks is governed by intrinsic RNA cleavage rather than diffusional Brownian dynamics. We introduce a consensus mechanistic model that unifies our findings with prior models.

Force spectroscopy allows testing the free energy landscapes of molecular interactions. Usually, the dependency of the most probable rupture force on the force rate or the shape of the rupture force histogram is fitted with different models that contain approximations and basic assumptions. We present a simple and model free approach to extract the force-dependent dissociation rates directly from the force curve data. Simulations show that the dissociation rates at any force are given directly by the ratio of the number of detected rupture events to the time this force was acting on the bond. To calculate these total times of acting forces, all force curve data points of all curves measured are taken into account, which significantly increases the amount of information which is considered for data analysis compared to other methods. Moreover, by providing force-dependent dissociation rates this method allows direct testing and validating of any energy landscape model.