Thermodynamic determination of RNA duplex stability in magnesium solutions.

The prediction of RNA secondary structure and thermodynamics from sequence relies on free energy minimization and nearest neighbor parameters. Currently, algorithms used to make these predictions are based on parameters from optical melting studies performed in 1 M NaCl. However, many physiological and biochemical buffers containing RNA include much lower concentrations of monovalent cations and the presence of divalent cations. In order to improve these algorithms, thermodynamic data was previously collected for RNA duplexes in solutions containing 71, 121, 221, and 621 mM Na+. From this data, correction factors for free energy (ΔG°37) and melting temperature (Tm) were derived. Despite these newly derived correction factors for sodium, the stabilizing effects of magnesium have been ignored. Here, the same RNA duplexes were melted in solutions containing 0.5, 1.5, 3.0, and 10.0 mM Mg2+ in the absence of monovalent cations. Correction factors for Tm and ΔG°37 were derived to scale the current parameters to a range of magnesium concentrations. The Tm correction factor predicts the melting temperature within 1.2°C, and the ΔG°37 correction factor predicts the free energy within 0.30 kcalmol. These newly derived magnesium correction factors can be incorporated into algorithms that predict RNA secondary structure and stability from sequence.

A Saccharomyces cerevisiae model and screen to define the functional consequences of oncogenic histone missense mutations.

Somatic missense mutations in histone genes turn these essential proteins into oncohistones, which can drive oncogenesis. Understanding how missense mutations alter histone function is challenging in mammals as mutations occur in a single histone gene. For example, described oncohistone mutations predominantly occur in the histone H3.3 gene, despite the human genome encoding 15 H3 genes. To understand how oncogenic histone missense mutations alter histone function, we leveraged the budding yeast model, which contains only 2 H3 genes, to explore the functional consequences of oncohistones H3K36M, H3G34W, H3G34L, H3G34R, and H3G34V. Analysis of cells that express each of these variants as the sole copy of H3 reveals that H3K36 mutants show different drug sensitivities compared to H3G34 mutants. This finding suggests that changes to proximal amino acids in the H3 N-terminal tail alter distinct biological pathways. We exploited the caffeine-sensitive growth of H3K36-mutant cells to perform a high copy suppressor screen. This screen identified genes linked to histone function and transcriptional regulation, including Esa1, a histone H4/H2A acetyltransferase; Tos4, a forkhead-associated domain-containing gene expression regulator; Pho92, an N6-methyladenosine RNA-binding protein; and Sgv1/Bur1, a cyclin-dependent kinase. We show that the Esa1 lysine acetyltransferase activity is critical for suppression of the caffeine-sensitive growth of H3K36R-mutant cells while the previously characterized binding interactions of Tos4 and Pho92 are not required for suppression. This screen identifies pathways that could be altered by oncohistone mutations and highlights the value of yeast genetics to identify pathways altered by such mutations.

Targeting MLL Methyltransferases Enhances the Antitumor Effects of PI3K Inhibition in Hormone Receptor-positive Breast Cancer.

The high frequency of aberrant PI3K pathway activation in hormone receptor-positive (HR+) breast cancer has led to the development, clinical testing, and approval of the p110α-selective PI3K inhibitor alpelisib. The limited clinical efficacy of alpelisib and other PI3K inhibitors is partially attributed to the functional antagonism between PI3K and estrogen receptor (ER) signaling, which is mitigated via combined PI3K inhibition and endocrine therapy. We and others have previously demonstrated chromatin-associated mechanisms by which PI3K supports cancer development and antagonizes ER signaling through the modulation of the H3K4 methylation axis, inhibition of KDM5A promoter H3K4 demethylation and KMT2D/MLL4-directed enhancer H3K4 methylation. Here we show that inhibition of the H3K4 histone methyltransferase MLL1 in combination with PI3K inhibition impairs HR+ breast cancer clonogenicity and cell proliferation. While combined PI3K/MLL1 inhibition reduces PI3K/AKT signaling and H3K4 methylation, MLL1 inhibition increases PI3K/AKT signaling through the dysregulation of gene expression associated with AKT activation. These data reveal a feedback loop between MLL1 and AKT whereby MLL1 inhibition reactivates AKT. We show that combined PI3K and MLL1 inhibition synergizes to cause cell death in in vitro and in vivo models of HR+ breast cancer, which is enhanced by the additional genetic ablation of the H3K4 methyltransferase and AKT target KMT2D/MLL4. Together, our data provide evidence of a feedback mechanism connecting histone methylation with AKT and may support the preclinical development and testing of pan-MLL inhibitors. Significance: Here the authors leverage PI3K/AKT-driven chromatin modification to identify histone methyltransferases as a therapeutic target. Dual PI3K and MLL inhibition synergize to reduce clonogenicity and cell proliferation, and promote in vivo tumor regression. These findings suggest patients with PIK3CA-mutant, HR+ breast cancer may derive clinical benefit from combined PI3K/MLL inhibition.

Identification and Characterization of New RNA Tetraloop Sequence Families.

There is an abundance of RNA sequence information available due to the efforts of sequencing projects. However, current techniques implemented to solve the tertiary structures of RNA, such as NMR and X-ray crystallography, are difficult and time-consuming. Therefore, biophysical techniques are not able to keep pace with the abundance of sequence information available. Because of this, there is a need to develop quick and efficient ways to predict RNA tertiary structure from sequence. One promising approach is to identify structural patterns within previously solved 3D structures and apply these patterns to new sequences. RNA tetraloops are one of the most common naturally occurring secondary structure motifs. Here, we use RNA Characterization of Secondary Structure Motifs (CoSSMos), Dissecting the Spatial Structure of RNA (DSSR), and a bioinformatic approach to search for and characterize tertiary structure patterns among tetraloops. Not surprising, we identified the well-known GNRA and UNCG tetraloops, as well as the previously identified RNYA tetraloop. However, some previously identified characteristics of these families were not observed in this data set, and some new characteristics were identified. In addition, we also identified and characterized three new tetraloop sequence families: YGAR, UGGU, and RMSA. This new structural information sheds light on the tertiary structure of tetraloops and contributes to the efforts of RNA tertiary structure prediction from sequence.

Thermodynamic characterization and nearest neighbor parameters for RNA duplexes under molecular crowding conditions.

It is essential to study RNA under molecular crowding conditions to better predict secondary structures of RNAs in vivo. No systematic study has been completed to determine the effects of molecular crowding on RNA duplexes of varying lengths and sequence composition. Here, optical melting, circular dichroism, and osmometry data were collected for RNA duplexes in a 20% polyethylene glycol (with an average molecular weight of 200 g/mol) solution (PEG 200), and nearest neighbor parameters were derived using this data. RNA duplexes are destabilized, on average, 1.02 kcal/mol in the presence of 20% PEG 200. The ΔG°37 values predicted by the nearest neighbor parameters for RNA duplexes in 20% PEG 200 were ∼0.65 kcal/mol closer to experimental ΔG°37 values than those predicted by the standard nearest neighbor model. For one DNA sequence in solution with small crowders, the ΔG°37 values predicted by the 20% PEG 200 RNA nearest neighbor parameters were closer to the experimental values than ΔG°37 values predicted by either the RNA or DNA standard nearest neighbor models. This indicates that the nearest neighbor parameters for RNA duplexes in 20% PEG 200 may be generalizable to RNA and DNA duplexes in solutions with small crowding agents.

The effects of varying the substituent and DNA sequence on the stability of 4-substituted DNA-naphthalimide complexes.

DNA duplexes are stabilized by many interactions, one of which is stacking interactions between the nucleic acid bases. These interactions are useful for designing small molecules that bind to DNA. Naphthalimide intercalators have been shown to be valuable anti-cancer agents that stack between the DNA bases and exhibit stabilizing effects. There is a continued need to design intercalators that will exhibit these stabilizing effects while being more selective toward DNA binding. This work investigates 4-substituted naphthalimides with varying functional groups and their interactions with nucleic acid duplexes. Mode of binding was determined via wavelength scans, circular dichroism, and viscosity measurements. Optical melting experiments were used to measure the absorbance of the sample as a function of temperature. The Tm values derived from the DNA duplexes were subtracted from the Tm values derived from the DNA-intercalator complexes, resulting in ΔTm values. The ΔTm values demonstrated that the substituents on the intercalator affect the stability of the DNA-intercalator complex. From the results of this study and comparison to results from previous work, we conclude that the substituent type and position on the core intercalator molecule affect the stability of the complex it forms with DNA.