Toehold-mediated strand displacement is the most abundantly used method to achieve dynamic switching in DNA-based nanotechnology. An 'invader' strand binds to the 'toehold' overhang of a target strand and replaces a targetbound 'incumbent' strand. Hereby, complementarity of the invader to the single-stranded toehold provides the energetic bias of the reaction. Despite the widespread use of strand displacement reactions for realizing dynamic DNA nanostructures, variants on the basic motif have not been completely characterized. Here we introduce a simple thermodynamic model, which is capable of quantitatively describing the kinetics of strand displacement reactions in the presence of mismatches, using a minimal set of parameters. Furthermore, our model highlights that base pair fraying and internal loop formation are important mechanisms when involving mismatches in the displacement process. Our model should provide a helpful tool for the rational design of strand-displacement reaction networks.

Here we show a general approach to achieve dissipative control over toehold‐mediated strand‐displacement, the most widely employed reaction in the field of DNA nanotechnology. The approach relies on rationally re‐engineering the classic strand displacement reaction such that the high‐energy invader strand (fuel) is converted into a low‐energy waste product through an energy‐dissipating reaction allowing the spontaneous return to the original state over time. We show that such dissipative control over the toehold‐mediated strand displacement process is reversible (up to 10 cycles), highly controllable and enables unique temporal activation of DNA systems. We show here two possible applications of this strategy: the transient labelling of DNA structures and the additional temporal control of cascade reactions.

Here, we demonstrate a strategy to rationally program a delayed onset of toehold-mediated DNA strand displacement reactions (SDRs). The approach is based on blocker strands that efficiently inhibit the strand displacement by binding to the toehold domain of the target DNA. Specific enzymatic degradation of the blocker strand subsequently enables SDR. The kinetics of the blocker enzymatic degradation thus controls the time at which the SDR starts. By varying the concentration of the blocker strand and the concentration of the enzyme, we show that we can finely tune and modulate the delayed onset of SDR. Additionally, we show that the strategy is versatile and can be orthogonally controlled by different enzymes each specifically targeting a different blocker strand. We designed and established three different delayed SDRs using RNase H and two DNA repair enzymes (formamidopyrimidine DNA glycosylase and uracil-DNA glycosylase) and corresponding blockers. The achieved temporal delay can be programed with high flexibility without undesired leak and can be conveniently predicted using kinetic modeling. Finally, we show three possible applications of the delayed SDRs to temporally control the ligand release from a DNA nanodevice, the inhibition of a target protein by a DNA aptamer, and the output signal generated by a DNA logic circuit.

CRISPR-Cas effector complexes recognise nucleic acid targets by base pairing with their crRNA which enables easy re-programming of the target specificity in rapidly emerging genome engineering applications. However, undesired recognition of off-targets, that are only partially complementary to the crRNA, occurs frequently and represents a severe limitation of the technique. Off-targeting lacks comprehensive quantitative understanding and prediction. Here, we present a detailed analysis of the target recognition dynamics by the Cascade surveillance complex on a set of mismatched DNA targets using single-molecule supercoiling experiments. We demonstrate that the observed dynamics can be quantitatively modelled as a random walk over the length of the crRNA-DNA hybrid using a minimal set of parameters. The model accurately describes the recognition of targets with single and double mutations providing an important basis for quantitative off-target predictions. Importantly the model intrinsically accounts for observed bias regarding the position and the proximity between mutations and reveals that the seed length for the initiation of target recognition is controlled by DNA supercoiling rather than the Cascade structure.

CRISPR-Cas effector complexes recognise nucleic acid targets by base pairing with their crRNA which enables easy re-programming of the target specificity in rapidly emerging genome engineering applications. However, undesired recognition of off-targets, that are only partially complementary to the crRNA, occurs frequently and represents a severe limitation of the technique. Off-targeting lacks comprehensive quantitative understanding and prediction. Here, we present a detailed analysis of the target recognition dynamics by the Cascade surveillance complex on a set of mismatched DNA targets using single-molecule supercoiling experiments. We demonstrate that the observed dynamics can be quantitatively modelled as a random walk over the length of the crRNA-DNA hybrid using a minimal set of parameters. The model accurately describes the recognition of targets with single and double mutations providing an important basis for quantitative off-target predictions. Importantly the model intrinsically accounts for observed bias regarding the position and the proximity between mutations and reveals that the seed length for the initiation of target recognition is controlled by DNA supercoiling rather than the Cascade structure.