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1.
Using an L7Ae-Tethered, Hydroxyl Radical-Mediated Footprinting Strategy to Identify and Validate Kink-Turns in RNAs.
Lai, SM, Gopalan, V
Methods in molecular biology (Clifton, N.J.). 2021;:147-169
Abstract
Kink-turns are important RNA structural modules that facilitate long-range tertiary interactions and form binding sites for members of the L7Ae family of proteins. Present in a wide variety of functional RNAs, kink-turns play key organizational roles in many RNA-based cellular processes, including translation, modification, and tRNA biogenesis. It is important to determine the contribution of kink-turns to the overall architecture of resident RNAs, as these modules dictate ribonucleoprotein (RNP) assembly and function. This chapter describes a site-directed, hydroxyl radical-mediated footprinting strategy that utilizes L7Ae-tethered chemical nucleases to experimentally validate computationally identified kink-turns in any RNA and under a wide variety of conditions. The work plan described here uses the catalytic RNase P RNA as an example to provide a blueprint for using this footprinting method to map RNA-protein interactions in other RNP complexes.
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2.
The RNA m6A writer METTL14 in cancers: Roles, structures, and applications.
Zhou, H, Yin, K, Zhang, Y, Tian, J, Wang, S
Biochimica et biophysica acta. Reviews on cancer. 2021;(2):188609
Abstract
N6-methyladenosine (m6A) is the most abundant and diverse epigenetic modification of mRNAs in eukaryotes, and it regulates biological metabolism, cell differentiation and cycles, and responses to heat shock stress, cancers and other diseases. RNA methyltransferase-like 3 (METTL3), methyltransferase-like 14 (METTL14) and other proteins possessing methyltransferase (MTase) capability including Wilms tumor 1-associated protein (WTAP), RNA-binding motif protein 15(RBM15), KIAA1429 and zinc finger CCCH-type containing 13 (ZC3H13) constitute the m6A writer complex. Although METTL3 is the catalytic subunit, its activity is strongly dependent on METTL14, which is crucial in maintaining complex integrity and recognizing special RNA substrates. Currently, the roles of m6A modification in cancers are being extensively reviewed. The critical functions of METTL14 in the occurrence and development of a variety of cancers as well as the potential targeting of METTL14 as a cancer treatment have not yet been highlighted. Therefore, in this review, we summarize the m6A modification and focus on the structure and functions of METTL14 as well as its roles in oncogenesis, metastasis progression, treatment and prognosis in cancer.
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3.
DExD/H-box helicases: multifunctional regulators in antiviral innate immunity.
Su, C, Tang, YD, Zheng, C
Cellular and molecular life sciences : CMLS. 2021;(1):2
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Abstract
DExD/H-box helicases play critical roles in multiple cellular processes, including transcription, cellular RNA metabolism, translation, and infections. Several seminal studies over the past decades have delineated the distinct functions of DExD/H-box helicases in regulating antiviral innate immune signaling pathways, including Toll-like receptors, retinoic acid-inducible gene I-like receptors, cyclic GMP-AMP synthase-the stimulator of interferon gene, and NOD-like receptors signaling pathways. Besides the prominent regulatory roles, there is increasing attention on their functions as nucleic acid sensors involved in antiviral innate immunity. Here we summarize the complex regulatory roles of DExD/H-box helicases in antiviral innate immunity. A better understanding of the underlying molecular mechanisms of DExD/H-box helicases' regulatory roles is vital for developing new therapeutics targeting DExD/H-box helicases and their mediated signaling transduction in viral infectious diseases.
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Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning.
Sirinukunwattana, K, Domingo, E, Richman, SD, Redmond, KL, Blake, A, Verrill, C, Leedham, SJ, Chatzipli, A, Hardy, C, Whalley, CM, et al
Gut. 2021;(3):544-554
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Abstract
OBJECTIVE Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning. DESIGN Training and evaluation of a neural network were performed using a total of n=1206 tissue sections with comprehensive multi-omic data from three independent datasets (training on FOCUS trial, n=278 patients; test on rectal cancer biopsies, GRAMPIAN cohort, n=144 patients; and The Cancer Genome Atlas (TCGA), n=430 patients). Ground truth CMS calls were ascertained by matching random forest and single sample predictions from CMS classifier. RESULTS Image-based CMS (imCMS) accurately classified slides in unseen datasets from TCGA (n=431 slides, AUC)=0.84) and rectal cancer biopsies (n=265 slides, AUC=0.85). imCMS spatially resolved intratumoural heterogeneity and provided secondary calls correlating with bioinformatic prediction from molecular data. imCMS classified samples previously unclassifiable by RNA expression profiling, reproduced the expected correlations with genomic and epigenetic alterations and showed similar prognostic associations as transcriptomic CMS. CONCLUSION This study shows that a prediction of RNA expression classifiers can be made from H&E images, opening the door to simple, cheap and reliable biological stratification within routine workflows.
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5.
RNA Proximity Labeling: A New Detection Tool for RNA-Protein Interactions.
Weissinger, R, Heinold, L, Akram, S, Jansen, RP, Hermesh, O
Molecules (Basel, Switzerland). 2021;(8)
Abstract
Multiple cellular functions are controlled by the interaction of RNAs and proteins. Together with the RNAs they control, RNA interacting proteins form RNA protein complexes, which are considered to serve as the true regulatory units for post-transcriptional gene expression. To understand how RNAs are modified, transported, and regulated therefore requires specific knowledge of their interaction partners. To this end, multiple techniques have been developed to characterize the interaction between RNAs and proteins. In this review, we briefly summarize the common methods to study RNA-protein interaction including crosslinking and immunoprecipitation (CLIP), and aptamer- or antisense oligonucleotide-based RNA affinity purification. Following this, we focus on in vivo proximity labeling to study RNA-protein interactions. In proximity labeling, a labeling enzyme like ascorbate peroxidase or biotin ligase is targeted to specific RNAs, RNA-binding proteins, or even cellular compartments and uses biotin to label the proteins and RNAs in its vicinity. The tagged molecules are then enriched and analyzed by mass spectrometry or RNA-Seq. We highlight the latest studies that exemplify the strength of this approach for the characterization of RNA protein complexes and distribution of RNAs in vivo.
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6.
Structure and folding of four putative kink turns identified in structured RNA species in a test of structural prediction rules.
Huang, L, Liao, X, Li, M, Wang, J, Peng, X, Wilson, TJ, Lilley, DMJ
Nucleic acids research. 2021;(10):5916-5924
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Abstract
k-Turns are widespread key architectural elements that occur in many classes of RNA molecules. We have shown previously that their folding properties (whether or not they fold into their tightly kinked structure on addition of metal ions) and conformation depend on their local sequence, and we have elucidated a series of rules for prediction of these properties from sequence. In this work, we have expanded the rules for prediction of folding properties, and then applied the full set to predict the folding and conformation of four probable k-turns we have identified amongst 224 structured RNA species found in bacterial intergenenic regions by the Breaker lab (1). We have analyzed the ion-dependence of folding of the four k-turns using fluorescence resonance energy transfer, and determined the conformation of two of them using X-ray crystallography. We find that the experimental data fully conform to both the predicted folding and conformational properties. We conclude that our folding rules are robust, and can be applied to new k-turns of unknown characteristics with confidence.
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Characterization of RNA Sensing Pathways in Hepatoma Cell Lines and Primary Human Hepatocytes.
Nicolay, W, Moeller, R, Kahl, S, Vondran, FWR, Pietschmann, T, Kunz, S, Gerold, G
Cells. 2021;(11)
Abstract
The liver is targeted by several human pathogenic RNA viruses for viral replication and dissemination; despite this, the extent of innate immune sensing of RNA viruses by human hepatocytes is insufficiently understood to date. In particular, for highly human tropic viruses such as hepatitis C virus, cell culture models are needed to study immune sensing. However, several human hepatoma cell lines have impaired RNA sensing pathways and fail to mimic innate immune responses in the human liver. Here we compare the RNA sensing properties of six human hepatoma cell lines, namely Huh-6, Huh-7, HepG2, HepG2-HFL, Hep3B, and HepaRG, with primary human hepatocytes. We show that primary liver cells sense RNA through retinoic acid-inducible gene I (RIG-I) like receptor (RLR) and Toll-like receptor 3 (TLR3) pathways. Of the tested cell lines, Hep3B cells most closely mimicked the RLR and TLR3 mediated sensing in primary hepatocytes. This was shown by the expression of RLRs and TLR3 as well as the expression and release of bioactive interferon in primary hepatocytes and Hep3B cells. Our work shows that Hep3B cells partially mimic RNA sensing in primary hepatocytes and thus can serve as in vitro model to study innate immunity to RNA viruses in hepatocytes.
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The mutual interactions of RNA, counterions and water - quantifying the electrostatics at the phosphate-water interface.
Fingerhut, BP
Chemical communications (Cambridge, England). 2021;(96):12880-12897
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Abstract
The structure and dynamics of polyanionic biomolecules, like RNA, are decisively determined by their electric interactions with the water molecules and the counterions in the environment. The solvation dynamics of the biomolecules involves a subtle balance of non-covalent and many-body interactions with structural fluctuations due to thermal motion occurring in a femto- to subnanosecond time range. This complex fluctuating many particle scenario is crucial in defining the properties of biological interfaces with far reaching significance for the folding of RNA structures and for facilitating RNA-protein interactions. Given the inherent complexity, suited model systems, carefully calibrated and benchmarked by experiments, are required to quantify the relevant interactions of RNA with the aqueous environment. In this feature article we summarize our recent progress in the understanding of the electrostatics at the biological interface of double stranded RNA (dsRNA) and transfer RNA (tRNA). Dimethyl phosphate (DMP) is introduced as a viable and rigorously accessible model system allowing the interaction strength with water molecules and counterions, their relevant fluctuation timescales and the spatial reach of interactions to be established. We find strong (up to ≈90 MV cm-1) interfacial electric fields with fluctuations extending up to ≈20 THz and demonstrate how the asymmetric stretching vibration νAS(PO2)- of the polarizable phosphate group can serve as the most sensitive probe for interfacial interactions, establishing a rigorous link between simulations and experiment. The approach allows for the direct interfacial observation of interactions of biologically relevant Mg2+ counterions with phosphate groups in contact pair geometries via the rise of a new absorption band imposed by exchange repulsion interactions at short interatomic distances. The systematic extension to RNA provides microscopic insights into the changes of the hydration structure that accompany the temperature induced melting of the dsRNA double helix and quantify the ionic interactions in the folded tRNA. The results show that pairs of negatively charged phosphate groups and Mg2+ ions represent a key structural feature of RNA embedded in water. They highlight the importance of binding motifs made of contact pairs in the electrostatic stabilization of RNA structures that have a strong impact on the surface potential and enable the fine tuning of the local electrostatic properties which are expected to be relevant for mediating the interactions between biomolecules.
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9.
RSVdb: a comprehensive database of transcriptome RNA structure.
Yu, H, Zhang, Y, Sun, Q, Gao, H, Tao, S
Briefings in bioinformatics. 2021;(3)
Abstract
RNA fulfills a crucial regulatory role in cells by folding into a complex RNA structure. To date, a chemical compound, dimethyl sulfate (DMS), has been developed to probe the RNA structure at the transcriptome level effectively. We proposed a database, RSVdb (https://taolab.nwafu.edu.cn/rsvdb/), for the browsing and visualization of transcriptome RNA structures. RSVdb, including 626 225 RNAs with validated DMS reactivity from 178 samples in eight species, supports four main functions: information retrieval, research overview, structure prediction and resource download. Users can search for species, studies, transcripts and genes of interest; browse the quality control of sequencing data and statistical charts of RNA structure information; preview and perform online prediction of RNA structures in silico and under DMS restraint of different experimental treatments and download RNA structure data for species and studies. Together, RSVdb provides a reference for RNA structure and will support future research on the function of RNA structure at the transcriptome level.
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10.
Salt dependent mesoscopic model for RNA at multiple strand concentrations.
Ferreira, I, Amarante, TD, Weber, G
Biophysical chemistry. 2021;:106551
Abstract
Mesoscopic models can be used for the description of the thermodynamic properties of RNA duplexes. With the use of experimental melting temperatures, its parametrization can provide important insights into its hydrogen bonds and stacking interactions as has been done for high sodium concentrations. However, the RNA parametrization for lower salt concentrations is still missing due to the limited amount of published melting temperature data. While the Peyrard-Bishop (PB) parametrization was found to be largely independent of strand concentrations, it requires that all temperatures are provided at the same strand concentrations. Here we adapted the PB model to handle multiple strand concentrations and in this way we were able to make use of an experimental set of temperatures to model the hydrogen bond and stacking interactions at low and intermediate sodium concentrations. For the parametrizations we make a distinction between terminal and internal base pairs, and the resulting potentials were qualitatively similar as we obtained previously for DNA. The main difference from DNA parameters, was the Morse potentials at low sodium concentrations for terminal r(AU) which is stronger than d(AT), suggesting higher hydrogen bond strength.