Structural basis for tRNA mimicry by mascRNA and menRNA
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Chemical reactivity of RNA and its modifications with hydrazine
RNA modifications are essential for the regulation of cellular processes and have a key role in diseases such as cancer and neurological disorders. A major challenge in the analysis of RNA modification is the differentiation between isomers, including methylated nucleosides as well as uridine and pseudouridine. A solution is their differential chemical reactivity which enables isomer discrimination by mass spectrometry (MS) or sequencing. In this study, we systematically determine the chemical reactivity of hydrazine with RNA and its native modifications in an aniline-free environment. We optimize the conditions to achieve nearly full conversion of all uridines while avoiding RNA cleavage. We apply the conditions to native tRNAPhe which allows discrimination of pseudouridine and uridine by MALDI-MS. Furthermore, we determine the identity of the reaction product of hydrazine with various modified nucleosides using high resolution mass spectrometry and quantify the reaction yield in native tRNA from E. coli and human cells under various hydrazine conditions. Most modified nucleosides react quantitatively at lower hydrazine concentration while uridines do not decompose under these conditions. Thus, this study paves the way to exploit aniline-free hydrazine reactions in the detection of RNA modifications through MS and potentially even long-read RNA sequencing.
Simultaneous entry as an adaptation to virulence in a novel satellite-helper system infecting Streptomyces species
Satellites are mobile genetic elements that are dependent upon the replication machinery of their helper viruses. Bacteriophages have provided many examples of satellite nucleic acids that utilize their helper morphogenic genes for propagation. Here we describe two novel satellite-helper phage systems, Mulch and Flayer, that infect Streptomyces species. The satellites in these systems encode for encapsidation machinery but have an absence of key replication genes, thus providing the first example of bacteriophage satellite viruses. We also show that codon usage of the satellites matches the tRNA gene content of the helpers. The satellite in one of these systems, Flayer, does not appear to integrate into the host genome, which represents the first example of a virulent satellite phage. The Flayer satellite has a unique tail adaptation that allows it to attach to its helper for simultaneous co-infection. These findings demonstrate an ever-increasing array of satellite strategies for genetic dependence on their helpers in the evolutionary arms race between satellite and helper phages.
A microscale thermophoresis-based enzymatic RNA methyltransferase assay enables the discovery of DNMT2 inhibitors
RNA methyltransferases (MTases) have recently become increasingly important in drug discovery. Yet, most frequently utilized RNA MTase assays are limited in their throughput and hamper this rapidly evolving field of medicinal chemistry. This study developed a microscale thermophoresis (MST)-based split aptamer assay for enzymatic MTase investigations, improving current methodologies by offering a non-proprietary, cost-effective, and highly sensitive approach. Our findings demonstrate the assay’s effectiveness across different RNA MTases, including inhibitor characterization of METTL3/14, DNMT2, NSUN2, and S. aureus TrmD, enabling future drug discovery efforts. Using this concept, a pilot screening on the cancer drug target DNMT2 discovered several hit compounds with micromolar potency.
Chromosomal 3p loss and 8q gain drive vasculogenic mimicry via HIF-2α and VE-cadherin activation in uveal melanoma
Uveal melanoma (UM) is the most common primary intraocular malignant tumor in adults and is where Vasculogenic Mimicry (VM) was first described. VM enables aggressive cancer cells to independently form blood networks, complicating treatment for patients exhibiting VM. Previous studies linked VE-Cadherin phosphorylation at Y658 to gene expression via Focal Adhesion Kinase (FAK), enhancing the Kaiso/β-catenin/TCF-4 complex associated with VE-Cadherin and thereby promoting VM. Recently, an allosteric HIF-2α inhibitor (Belzutifan) was FDA-approved for VHL-associated ccRCCs. In this research, we elucidate the primary causes of VM formation in UM patients with chromosome 3p loss and chromosome 8q gain, identifying VHL, BAP1, and FAK as important factors driving VM and worsening prognosis. These factors promote abnormal activation of HIF-2α and VE-Cadherin under basal hypoxic conditions, leading to VM formation. Cytoscan 750k experiments on the MUM 2B cell line reveal a loss of chromosome 3p, where the VHL, BAP1, and CTNNB1 genes are located, and a gain of chromosome 8q (FAK), whereas the MUM 2C cell line shows a gain of chromosome 3p. This provides an outstanding cross-sectional model from patient samples to established cell lines for VM studies. LC-MS experiments demonstrate that VE-Cad/ENG expression is related to FAK activity in UM cell lines. Finally, using a combination of Belzutifan (HIF-2α inhibitor) and FAK inhibitor (FAKi), we observed a significant reduction in UM xenografts. Our results lead us to propose combining Belzutifan and FAKi as a personalized treatment strategy for UM patients. This approach inhibits VM formation and counters the initial hypoxic conditions resulting from chromosome 3p loss and chromosome 8q gain in UM patients, instilling confidence in the potential of this treatment strategy.
The design space of E(3)-equivariant atom-centred interatomic potentials
Molecular dynamics simulation is an important tool in computational materials science and chemistry, and in the past decade it has been revolutionized by machine learning. This rapid progress in machine learning interatomic potentials has produced a number of new architectures in just the past few years. Particularly notable among these are the atomic cluster expansion, which unified many of the earlier ideas around atom-density-based descriptors, and Neural Equivariant Interatomic Potentials (NequIP), a message-passing neural network with equivariant features that exhibited state-of-the-art accuracy at the time. Here we construct a mathematical framework that unifies these models: atomic cluster expansion is extended and recast as one layer of a multi-layer architecture, while the linearized version of NequIP is understood as a particular sparsification of a much larger polynomial model. Our framework also provides a practical tool for systematically probing different choices in this unified design space. An ablation study of NequIP, via a set of experiments looking at in- and out-of-domain accuracy and smooth extrapolation very far from the training data, sheds some light on which design choices are critical to achieving high accuracy. A much-simplified version of NequIP, which we call BOTnet (for body-ordered tensor network), has an interpretable architecture and maintains its accuracy on benchmark datasets.
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