Temperature-Dependent Twist of Double-Stranded RNA Probed by Magnetic Tweezer Experiments and Molecular Dynamics Simulations.

RNA plays critical roles in the transmission and regulation of genetic information and is increasingly used in biomedical and biotechnological applications. Functional RNAs contain extended double-stranded regions, and the structure of double-stranded RNA (dsRNA) has been revealed at high resolution. However, the dependence of the properties of the RNA double helix on environmental effects, notably temperature, is still poorly understood. Here, we use single-molecule magnetic tweezer measurements to determine the dependence of the dsRNA twist on temperature. We find that dsRNA unwinds with increasing temperature, even more than DNA, with ΔTwRNA = -14.4 ± 0.7°/(°C·kbp), compared to ΔTwDNA = -11.0 ± 1.2°/(°C·kbp). All-atom molecular dynamics (MD) simulations using a range of nucleic acid force fields, ion parameters, and water models correctly predict that dsRNA unwinds with rising temperature but significantly underestimate the magnitude of the effect. These MD data, together with additional MD simulations involving DNA and DNA-RNA hybrid duplexes, reveal a linear correlation between the twist temperature decrease and the helical rise, in line with DNA but at variance with RNA experimental data. We speculate that this discrepancy might be caused by some unknown bias in the RNA force fields tested or by as yet undiscovered transient alternative structures in the RNA duplex. Our results provide a baseline to model more complex RNA assemblies and to test and develop new parametrizations for RNA simulations. They may also inspire physical models of the temperature-dependent dsRNA structure.

A kinetic model predicts SpCas9 activity, improves off-target classification, and reveals the physical basis of targeting fidelity.

The S. pyogenes (Sp) Cas9 endonuclease is an important gene-editing tool. SpCas9 is directed to target sites based on complementarity to a complexed single-guide RNA (sgRNA). However, SpCas9-sgRNA also binds and cleaves genomic off-targets with only partial complementarity. To date, we lack the ability to predict cleavage and binding activity quantitatively, and rely on binary classification schemes to identify strong off-targets. We report a quantitative kinetic model that captures the SpCas9-mediated strand-replacement reaction in free-energy terms. The model predicts binding and cleavage activity as a function of time, target, and experimental conditions. Trained and validated on high-throughput bulk-biochemical data, our model predicts the intermediate R-loop state recently observed in single-molecule experiments, as well as the associated conversion rates. Finally, we show that our quantitative activity predictor can be reduced to a binary off-target classifier that outperforms the established state-of-the-art. Our approach is extensible, and can characterize any CRISPR-Cas nuclease - benchmarking natural and future high-fidelity variants against SpCas9; elucidating determinants of CRISPR fidelity; and revealing pathways to increased specificity and efficiency in engineered systems.

Argonaute bypasses cellular obstacles without hindrance during target search.

Argonaute (Ago) proteins are key players in both gene regulation (eukaryotes) and host defense (prokaryotes). Acting on single-stranded nucleic-acid substrates, Ago relies on base pairing between a small nucleic-acid guide and its complementary target sequences for specificity. To efficiently scan nucleic-acid chains for targets, Ago diffuses laterally along the substrate and must bypass secondary structures as well as protein barriers. Using single-molecule FRET in conjunction with kinetic modelling, we reveal that target scanning is mediated through loose protein-nucleic acid interactions, allowing Ago to slide short distances over secondary structures, as well as to bypass protein barriers via intersegmental transfer. Our combined single-molecule experiment and kinetic modelling approach may serve as a platform to dissect search processes and study the effect of sequence on search kinetics for other nucleic acid-guided proteins.

Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules.

Due to their specificity, efficiency, and ease of programming, CRISPR-associated nucleases are popular tools for genome editing. On the genomic scale, these nucleases still show considerable off-target activity though, posing a serious obstacle to the development of therapies. Off targeting is often minimized by choosing especially high-specificity guide sequences, based on algorithms that codify empirically determined off-targeting rules. A lack of mechanistic understanding of these rules has so far necessitated their ad hoc implementation, likely contributing to the limited precision of present algorithms. To understand the targeting rules, we kinetically model the physics of guide-target hybrid formation. Using only four parameters, our model elucidates the kinetic origin of the experimentally observed off-targeting rules, thereby rationalizing the results from both binding and cleavage assays. We favorably compare our model to published data from CRISPR-Cas9, CRISPR-Cpf1, CRISPR-Cascade, as well as the human Argonaute 2 system.

Why Argonaute is needed to make microRNA target search fast and reliable.

MicroRNA (miRNA) interferes with the translation of cognate messenger RNA (mRNA) by finding, preferentially binding, and marking it for degradation. To facilitate the search process, Argonaute (Ago) proteins come together with miRNA, forming a dynamic search complex. In this review we use the language of free-energy landscapes to discuss recent single-molecule and high-resolution structural data in the light of theoretical work appropriated from the study of transcription-factor search. We suggest that experimentally observed internal states of the Ago-miRNA search complex may have the explicit biological function of speeding up search while maintaining specificity.

Cas3-Derived Target DNA Degradation Fragments Fuel Primed CRISPR Adaptation.

Prokaryotes use a mechanism called priming to update their CRISPR immunological memory to rapidly counter revisiting, mutated viruses, and plasmids. Here we have determined how new spacers are produced and selected for integration into the CRISPR array during priming. We show that Cas3 couples CRISPR interference to adaptation by producing DNA breakdown products that fuel the spacer integration process in a two-step, PAM-associated manner. The helicase-nuclease Cas3 pre-processes target DNA into fragments of about 30-100 nt enriched for thymine-stretches in their 3' ends. The Cas1-2 complex further processes these fragments and integrates them sequence-specifically into CRISPR repeats by coupling of a 3' cytosine of the fragment. Our results highlight that the selection of PAM-compliant spacers during priming is enhanced by the combined sequence specificities of Cas3 and the Cas1-2 complex, leading to an increased propensity of integrating functional CTT-containing spacers.

DNA translocations through solid-state plasmonic nanopores.

Nanopores enable label-free detection and analysis of single biomolecules. Here, we investigate DNA translocations through a novel type of plasmonic nanopore based on a gold bowtie nanoantenna with a solid-state nanopore at the plasmonic hot spot. Plasmonic excitation of the nanopore is found to influence both the sensor signal (nanopore ionic conductance blockade during DNA translocation) and the process that captures DNA into the nanopore, without affecting the duration time of the translocations. Most striking is a strong plasmon-induced enhancement of the rate of DNA translocation events in lithium chloride (LiCl, already 10-fold enhancement at a few mW of laser power). This provides a means to utilize the excellent spatiotemporal resolution of DNA interrogations with nanopores in LiCl buffers, which is known to suffer from low event rates. We propose a mechanism based on plasmon-induced local heating and thermophoresis as explanation of our observations.