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Quantitative measurements of biomolecule associations are central to biological understanding and are needed to build and test predictive and mechanistic models. Given the advances in high-throughput technologies and the projected increase in the availability of binding data, we found it especially timely to evaluate the current standards for performing and reporting binding measurements. A review of 100 studies revealed that in most cases essential controls for establishing the appropriate incubation time and concentration regime were not documented, making it impossible to determine measurement reliability. Moreover, several reported affinities could be concluded to be incorrect, thereby impacting biological interpretations. Given these challenges, we provide a framework for a broad range of researchers to evaluate, teach about, perform, and clearly document high-quality equilibrium binding measurements. We apply this framework and explain underlying fundamental concepts through experimental examples with the RNA-binding protein Puf4.

Adenosine-to-inosine (A-to-I) RNA editing catalyzed by ADAR enzymes occurs in double-stranded RNAs. Despite a compelling need towards predictive understanding of natural and engineered editing events, how the RNA sequence and structure determine the editing efficiency and specificity (i.e., cis -regulation) is poorly understood. We apply a CRISPR/Cas9-mediated saturation mutagenesis approach to generate libraries of mutations near three natural editing substrates at their endogenous genomic loci. We use machine learning to integrate diverse RNA sequence and structure features to model editing levels measured by deep sequencing. We confirm known features and identify new features important for RNA editing. Training and testing XGBoost algorithm within the same substrate yield models that explain 68 to 86 percent of substrate-specific variation in editing levels. However, the models do not generalize across substrates, suggesting complex and context-dependent regulation patterns. Our integrative approach can be applied to larger scale experiments towards deciphering the RNA editing code. The RNA sequence and secondary structure regulate RNA editing by ADAR. Here the authors employ a CRISPR/Cas9-mediated saturation mutagenesis and machine learning to predict RNA editing efficiency of specific substrates.

Both scientists and the public would benefit from improved communication of basic scientific research and from integrating scientists into education outreach, but opportunities to support these efforts are limited. We have developed two low-cost programs--\"Present Your PhD Thesis to a 12-Year-Old\" and \"Shadow a Scientist\"--that combine training in science communication with outreach to area middle schools. We assessed the outcomes of these programs and found a 2-fold benefit: scientists improve their communication skills by explaining basic science research to a general audience, and students' enthusiasm for science and their scientific knowledge are increased. Here we present details about both programs, along with our assessment of them, and discuss the feasibility of exporting these programs to other universities.

Site-directed RNA editing is a promising and potentially safer alternative to genome editing. Previous methods have been developed that recruit the endogenously and ubiquitously expressed ADAR enzymes to initiate site-specific A-to-I edits, but often suffer from low efficacy or dependency on viral delivery. Chemically modified oligonucleotides may be a promising alternative, but the approach still lacks systematic in-depth studies. Furthermore, the best characterized platform uses stereo-pure backbone chemistry, which is not widely used, commercially unavailable and challenging to manufacture. Here, we report on single-stranded oligonucleotides of 30-60 nt length, which are fully chemically stabilized by applying commercially available, classical RNA drug modifications, like 2´-O-methyl, 2´-fluoro, and DNA on a stereo-random phosphate/phosphorothioate backbone. We demonstrate our so-called RESTORE 2.0 oligonucleotides to induce the correction of pathogenic point mutations, efficacy after GalNAc-mediated uptake into human primary hepatocytes, and proof of in-vivo efficacy in mice upon lipid nanoparticle-mediated delivery. The discovered design principles may increase the accessibility of site-directed RNA base editing to expand and support further research in this field. RNA base editing represents an exciting modality in precision genetic medicine. Here the authors develop short, metabolically stable RNA oligonucleotides (RESTORE 2.0) that enable precise and efficient RNA base editing, demonstrating successful in-vivo correction of a disease-causing human mutation.

DEAD-box proteins are nonprocessive RNA helicases and can function as RNA chaperones, but the mechanisms of their chaperone activity remain incompletely understood. The Neurospora crassa DEAD-box protein CYT-19 is a mitochondrial RNA chaperone that promotes group I intron splicing and has been shown to resolve misfolded group I intron structures, allowing them to refold. Building on previous results, here we use a series of tertiary contact mutants of the Tetrahymena group I intron ribozyme to demonstrate that the efficiency of CYT-19–mediated unfolding of the ribozyme is tightly linked to global RNA tertiary stability. Efficient unfolding of destabilized ribozyme variants is accompanied by increased ATPase activity of CYT-19, suggesting that destabilized ribozymes provide more productive interaction opportunities. The strongest ATPase stimulation occurs with a ribozyme that lacks all five tertiary contacts and does not form a compact structure, and small-angle X-ray scattering indicates that ATPase activity tracks with ribozyme compactness. Further, deletion of three helices that are prominently exposed in the folded structure decreases the ATPase stimulation by the folded ribozyme. Together, these results lead to a model in which CYT-19, and likely related DEAD-box proteins, rearranges complex RNA structures by preferentially interacting with and unwinding exposed RNA secondary structure. Importantly, this mechanism could bias DEAD-box proteins to act on misfolded RNAs and ribonucleoproteins, which are likely to be less compact and more dynamic than their native counterparts.

Genomic methods have been valuable for identifying RNA-binding proteins (RBPs) and the genes, pathways, and processes they regulate. Nevertheless, standard motif descriptions cannot be used to predict all RNA targets or test quantitative models for cellular interactions and regulation. We present a complete thermodynamic model for RNA binding to the S. cerevisiae Pumilio protein PUF4 derived from direct binding data for 6180 RNAs measured using the RNA on a massively parallel array (RNA-MaP) platform. The PUF4 model is highly similar to that of the related RBPs, human PUM2 and PUM1, with one marked exception: a single favorable site of base flipping for PUF4, such that PUF4 preferentially binds to a non-contiguous series of residues. These results are foundational for developing and testing cellular models of RNA-RBP interactions and function, for engineering RBPs, for understanding the biophysical nature of RBP binding and the evolutionary landscape of RNAs and RBPs. Traditional genomic methods identify RNA-binding proteins (RBPs) and the genes they regulate, but do not provide predictive models. The authors used an emerging technology to obtain a complete thermodynamic model for RNA binding to the PUF4 RBP.

The mitochondrial DEAD-box proteins Mss116p of Saccharomyces cerevisiae and CYT-19 of Neurospora crassa are ATP-dependent helicases that function as general RNA chaperones. The helicase core of each protein precedes a C-terminal extension and a basic tail, whose structural role is unclear. Here we used small-angle X-ray scattering to obtain solution structures of the full-length proteins and a series of deletion mutants. We find that the two core domains have a preferred relative orientation in the open state without substrates, and we visualize the transition to a compact closed state upon binding RNA and adenosine nucleotide. An analysis of complexes with large chimeric oligonucleotides shows that the basic tails of both proteins are attached flexibly, enabling them to bind rigid duplex DNA segments extending from the core in different directions. Our results indicate that the basic tails of DEAD-box proteins contribute to RNA-chaperone activity by binding nonspecifically to large RNA substrates and flexibly tethering the core for the unwinding of neighboring duplexes.

Interactions between RNA and proteins are pervasive in biology, driving fundamental processes such as protein translation and participating in the regulation of gene expression. Modeling the energies of RNA–protein interactions is therefore critical for understanding and repurposing living systems but has been hindered by complexities unique to RNA–protein binding. Here, we bring together several advances to complete a calculation framework for RNA–protein binding affinities, including a unified free energy function for bound complexes, automated Rosetta modeling of mutations, and use of secondary structure-based energetic calculations to model unbound RNA states. The resulting Rosetta-Vienna RNP-ΔΔG method achieves root-mean-squared errors (RMSEs) of 1.3 kcal/mol on high-throughput MS2 coat protein–RNA measurements and 1.5 kcal/mol on an independent test set involving the signal recognition particle, human U1A, PUM1, and FOX-1. As a stringent test, the method achieves RMSE accuracy of 1.4 kcal/mol in blind predictions of hundreds of human PUM2–RNA relative binding affinities. Overall, these RMSE accuracies are significantly better than those attained by prior structure-based approaches applied to the same systems. Importantly, Rosetta-Vienna RNP-ΔΔG establishes a framework for further improvements in modeling RNA–protein binding that can be tested by prospective high-throughput measurements on new systems.

Both scientists and the public would benefit from improved communication of basic scientific research and from integrating scientists into education outreach, but opportunities to support these efforts are limited. We have developed two low-cost programs--\"Present Your PhD Thesis to a 12-Year-Old\" and \"Shadow a Scientist\"--that combine training in science communication with outreach to area middle schools. We assessed the outcomes of these programs and found a 2-fold benefit: scientists improve their communication skills by explaining basic science research to a general audience, and students' enthusiasm for science and their scientific knowledge are increased. Here we present details about both programs, along with our assessment of them, and discuss the feasibility of exporting these programs to other universities.