Biology subjects

Denny, S. K.

Publications and source records attributed to Denny, S. K..

5 recordsLinked to original sources

bioRxiv2026

Engineered Allosteric Control Enhances Specificity and Potency of CRISPR-CasX-based Epigenetic Repressors

Epigenetic silencers are targeted therapeutics capable of persistently silencing genes without altering DNA sequence. However, many current silencers rely on direct fusion of a constitutively active DNA methyltransferase catalytic domain, that may cause off-target DNA methylation and cellular toxicity. In contrast, endogenous DNA methyltransferases contain a regulatory domain (ADD) that requires recognition of a permissive histone state before DNA methylation can occur. We reinstate this sequential proofreading logic in a compact CasX-based epigenetic repressor, generating Epigenetic Long-term CasX Repressors (ELXRs) that read local chromatin state before writing DNA methylation. In ELXRs, a repressor domain converts active chromatin into a state that unlocks the allosteric DNA methyltransferase. This creates a sequential, multi-gated process that preferentially restricts DNA methylation to the target site. Surprisingly, implementing this proofreading mechanism improved not only specificity, but also activity. ELXRs decreased off-target methylation up to 10-fold and rescued DNMT3A-dependent growth defects, with transcriptome profiling showing up to 150-fold fewer dysregulated genes, while also increasing on-target repression up to 4-fold across multiple loci. In mouse models, lipid nanoparticle delivery produced potent, durable PCSK9 silencing with precise promoter methylation. Together, these results demonstrate that coupling molecular recognition to effector activity through sequential proofreading can simultaneously improve specificity and potency.

molecular biology↗

bioRxiv2022

Dissecting the energetic architecture within an RNA tertiary structural motif via high-throughput thermodynamic measurements

Structured RNAs and RNA/protein complexes perform critical cellular functions. They often contain structurally conserved tertiary contact "motifs," whose occurrence simplifies the RNA folding landscape. Prior studies have focused on the conformational and energetic modularity of intact motifs. Here we turn to the dissection of one common motif, the 11nt receptor (11ntR), using quantitative analysis of RNA on a massively parallel array (RNA-MaP) to measure the binding of all single and double 11ntR mutants to GAAA and GUAA tetraloops, thereby probing the energetic architecture of the motif. While the 11ntR behaves as a motif, its cooperativity is not absolute. Instead, we uncovered a gradient from high cooperativity amongst base paired and neighboring residues to additivity between distant residues. As expected, substitutions at residues in direct contact with the GAAA tetraloop resulted in the largest decreases to binding, and energetic penalties of mutations were substantially smaller for binding to the alternate GUAA tetraloop, which lacks tertiary contacts present with the canonical GAAA tetraloop. However, we found that the energetic consequences of base partner substitutions are not, in general, simply described by base pair type or isostericity. We also found exceptions to the previously established stability-abundance relationship for 11ntR sequence variants. These findings of "exceptions to the rule" highlight the power of systematic high-throughput approaches to uncover novel variants for future study in addition to providing an energetic map of a functional RNA. Significance StatementProperly folded RNAs perform essential biological processes. Many RNAs contain tertiary contact "motifs" whose structural and energetic properties are conserved across different RNAs. This study delves into the nature of an RNA motif. We determined the effects of mutations on the energetic properties of a common tertiary contact motif, referred to as the 11-nucleotide receptor. As deep study of the energetic architecture of this and other RNAs requires thermodynamic measurements for many sequence variants, we used RNA-MaP, a quantitative, high-throughput method, to obtain binding free energies for all single and double mutants of the motif. Our results revealed the energetic architecture of this motif and identified rare variants with unexpected properties.

biophysics↗

bioRxiv2019

Quantitative high-throughput tests of ubiquitous RNA secondary structure prediction algorithms via RNA/protein binding

Nearest-neighbor (NN) rules provide a simple and powerful quantitative framework for RNA structure prediction that is strongly supported for canonical Watson-Crick duplexes from a plethora of thermodynamic measurements. Predictions of RNA secondary structure based on nearest-neighbor (NN) rules are routinely used to understand biological function and to engineer and control new functions in biotechnology. However, NN applications to RNA structural features such as internal and terminal loops rely on approximations and assumptions, with sparse experimental coverage of the vast number of possible sequence and structural features. To test to what extent NN rules accurately predict thermodynamic stabilities across RNAs with non-WC features, we tested their predictions using a quantitative high-throughput assay platform, RNA-MaP. Using a thermodynamic assay with coupled protein binding, we carried out equilibrium measurements for over 1000 RNAs with a range of predicted secondary structure stabilities. Our results revealed substantial scatter and systematic deviations between NN predictions and observed stabilities. Solution salt effects and incorrect or omitted loop parameters contribute to these observed deviations. Our results demonstrate the need to independently and quantitatively test NN computational algorithms to identify their capabilities and limitations. RNA-MaP and related approaches can be used to test computational predictions and can be adapted to obtain experimental data to improve RNA secondary structure and other prediction algorithms.\n\nSignificance statementRNA secondary structure prediction algorithms are routinely used to understand, predict and design functional RNA structures in biology and biotechnology. Given the vast number of RNA sequence and structural features, these predictions rely on a series of approximations, and independent tests are needed to quantitatively evaluate the accuracy of predicted RNA structural stabilities. Here we measure the stabilities of over 1000 RNA constructs by using a coupled protein binding assay. Our results reveal substantial deviations from the RNA stabilities predicted by popular algorithms, and identify factors contributing to the observed deviations. We demonstrate the importance of quantitative, experimental tests of computational RNA structure predictions and present an approach that can be used to routinely test and improve the prediction accuracy.

biophysics↗

bioRxiv2018

A quantitative and predictive model for RNA binding by human Pumilio proteins

High-throughput methodologies have enabled routine generation of RNA target sets and sequence motifs for RNA-binding proteins (RBPs). Nevertheless, quantitative approaches are needed to capture the landscape of RNA/RBP interactions responsible for cellular regulation. We have used the RNA-MaP platform to directly measure equilibrium binding for thousands of designed RNAs and to construct a predictive model for RNA recognition by the human Pumilio proteins PUM1 and PUM2. Despite prior findings of linear sequence motifs, our measurements revealed widespread residue flipping and instances of positional coupling. Application of our thermodynamic model to published in vivo crosslinking data reveals quantitative agreement between predicted affinities and in vivo occupancies. Our analyses suggest a thermodynamically driven, continuous Pumilio binding landscape that is negligibly affected by RNA structure or kinetic factors, such as displacement by ribosomes. This work provides a quantitative foundation for dissecting the cellular behavior of RBPs and cellular features that impact their occupancies.

biochemistry↗

bioRxiv2018

RNA tertiary structure energetics predicted by an ensemble model of the RNA double helix

Over 50% of residues within functional structured RNAs are base-paired in Watson-Crick helices, but it is not fully understood how these helices geometric preferences and flexibility might influence RNA tertiary structure. Here, we show experimentally and computationally that the ensemble fluctuations of RNA helices substantially impact RNA tertiary structure stability. We updated a model for the conformational ensemble of the RNA helix using crystallographic structures of Watson-Crick base pair steps. To test this model, we made blind predictions of the thermodynamic stability of >1500 tertiary assemblies with differing helical sequences and compared calculations to independent measurements from a high-throughput experimental platform. The blind predictions accounted for thermodynamic effects from changing helix sequence and length with unexpectedly tight accuracies (RMSD of 0.34 and 0.77 kcal/mol, respectively). These comparisons lead to a detailed picture of how RNA base pair steps fluctuate within complex assemblies and suggest a new route toward predicting RNA tertiary structure formation and energetics.

biophysics↗