RNA-protein interactions: disorder, moonlighting and junk contribute to eukaryotic complexity

Comprehensive identification of ripening-related RNA-binding proteins in tomatoes using improved plant phase extraction

RNA-binding proteins (RBPs) have emerged as key players in posttranscriptional gene regulation, yet their full scale role in fruit ripening remains to be fully elucidated. However, due to the complex structure and composition of fruit tissue, exploring RBPs in fruits still faces many challenges. Here, we optimized the plant phase extraction method and successfully applied it to tomato fruits for the unbiased excavation of RBPs in fruits, this method were named as "plant phase extraction in tomato fruit" (termed tfPPE). We yielded a comprehensive candidate RNA-binding proteome (RBPome) composed of 230 proteins and disclosed that approximately 66% of them were unconventional RBPs. Validation of the RNA-binding activities of six candidate RBPs unveiled that metabolic enzymes function as moonlighting RBPs. Furthermore, combined with transcriptome analysis, we identified 41 candidate RBPs associated with fruit ripening. Remarkably, we proposed that SlER21 and SlFER1 play significant roles in fruit coloring and ripening process. Taken together, these results demonstrate that tfPPE was an impactful approach for unbiased excavation RBPs in fruits and pave the way for investigating RBP functions in fruit-ripening regulatory network.

A Csde1-Strap complex regulates plasma cell differentiation by coupling mRNA translation and decay

Upon encountering antigens, B cells may undergo multiple differentiation paths, including becoming plasma cells and memory B cells. Although it is well-known that transcription factors govern gene expression programs underpinning these fate decisions in transcriptional level, the role of post-transcriptional regulators, with a focus on RNA-binding proteins, in the fate determination are lesser known. Here we find by RNA interactome capture-coupled CRISPR/Cas9 functional screening that the Csde1-Strap complex plays an important role in plasma cell differentiation. Mechanistically, the Csde1-Strap complex establishes the expression kinetics of Bach2, a key regulator of plasma cell differentiation. Bach2 expression is rapidly induced to promote B cell expansion and then decreased to initiate plasma cell differentiation. The Csde1-Strap interaction is critical for their binding to Bach2 mRNA to couple its decay with translation to restrain the magnitude and duration of Bach2 protein expression. In the absence of Csde1 or Strap, Bach2 translation is de-coupled from mRNA decay, leading to elevated and prolonged expression of Bach2 protein and impaired plasma cell differentiation. This study thus establishes the functional RBP landscape in B cells and illustrates the fundamental importance of controlling protein expression kinetics in cell fate determination.

A nuclear protein quality control system for elimination of nucleolus-related inclusions

The identification of pathways that control elimination of protein inclusions is essential to understand the cellular response to proteotoxicity, particularly in the nuclear compartment, for which our knowledge is limited. We report that stress-induced nuclear inclusions related to the nucleolus are eliminated upon stress alleviation during the recovery period. This process is independent of autophagy/lysosome and CRM1-mediated nuclear export pathways, but strictly depends on the ubiquitin-activating E1 enzyme, UBA1, and on nuclear proteasomes that are recruited into the formed inclusions. UBA1 activity is essential only for the recovery process but dispensable for nuclear inclusion formation. Furthermore, the E3 ligase HUWE1 and HSP70 are components of the ubiquitin/chaperone systems that promote inclusion elimination. The recovery process also requires RNA Pol I-dependent production of the lncRNA IGS42 during stress. IGS42 localises within the formed inclusions and promotes their elimination by preserving the mobility of resident proteins. These findings reveal a protein quality control system that operates within the nucleus for the elimination of stress-induced nucleolus-related inclusions.

Discrimination between Purine and Pyrimidine-Rich RNA in Liquid-Liquid Phase-Separated Condensates with Cationic Peptides and the Effect of Artificial Crowding Agents

Membraneless organelles, often referred to as condensates or coacervates, are liquid-liquid phase-separated systems formed between noncoding RNAs and intrinsically disordered proteins. While the importance of different amino acid residues in short peptide-based condensates has been investigated, the role of the individual nucleobases or the type of heterocyclic structures, the purine vs pyrimidine nucleobases, is less researched. The cell's crowded environment has been mimicked in vitro to demonstrate its ability to induce the formation of condensates, but more research in this area is required, especially with respect to RNA-facilitated phase separation and the properties of the crowding agent, poly(ethylene glycol) (PEG). Herein, we have shown that the nucleotide base sequence of RNA can greatly influence its propensity to undergo phase separation with cationic peptides, with the purine-only RNA decamer (AG)5 readily doing so while the pyrimidine-only (CU)5 does not. Furthermore, we show that the presence and size of a PEG macromolecular crowder affects both the ability to phase separate and the stability of coacervates formed, possibly due to co-condensation of PEG with the RNA and peptides. This work sheds light on the presence of low-complexity long purine- or pyrimidine-rich noncomplementary repeat (AG or CU) sequences in various noncoding RNAs found in biology.

Cellular RNA interacts with MAVS to promote antiviral signaling

Antiviral signaling downstream of RIG-I-like receptors (RLRs) proceeds through a multi-protein complex organized around the adaptor protein mitochondrial antiviral signaling protein (MAVS). Protein complex function can be modulated by RNA molecules that provide allosteric regulation or act as molecular guides or scaffolds. We hypothesized that RNA plays a role in organizing MAVS signaling platforms. We found that MAVS, through its central intrinsically disordered domain, directly interacted with the 3' untranslated regions of cellular messenger RNAs. Elimination of RNA by ribonuclease treatment disrupted the MAVS signalosome, including RNA-modulated MAVS interactors that regulate RLR signaling and viral restriction, and inhibited phosphorylation of transcription factors that induce interferons. This work uncovered a function for cellular RNA in promoting signaling through MAVS and highlights generalizable principles of RNA regulatory control of immune signaling complexes.

Pathogenic TDP-43 accelerates the generation of toxic exon1 HTT in Huntington's disease knock-in mice

Huntington's disease (HD) is caused by a CAG repeat expansion in exon1 of the HTT gene that encodes a polyglutamine tract in huntingtin protein. The formation of HTT exon1 fragments with an expanded polyglutamine repeat has been implicated as a key step in the pathogenesis of HD. It was reported that the CAG repeat length-dependent aberrant splicing of exon1 HTT results in a short polyadenylated mRNA that is translated into an exon1 HTT protein. Under normal conditions, TDP-43 is predominantly found in the nucleus, where it regulates gene expression. However, in various pathological conditions, TDP-43 is mislocalized in the cytoplasm. By investigating HD knock-in mice, we explore whether the pathogenic TDP-43 in the cytoplasm contributes to HD pathogenesis, through expressing the cytoplasmic TDP-43 without nuclear localization signal. We found that the cytoplasmic TDP-43 is increased in the HD mouse brain and that its mislocalization could deteriorate the motor and gait behavior. Importantly, the cytoplasmic TDP-43, via its binding to the intron1 sequence (GU/UG)n of the mouse Htt pre-mRNA, promotes the transport of exon1-intron1 Htt onto ribosome, resulting in the aberrant generation of exon1 Htt. Our findings suggest that cytoplasmic TDP-43 contributes to HD pathogenesis via its binding to and transport of nuclear un-spliced mRNA to the ribosome for the generation of a toxic protein product.

A primer for junior trainees: Recognition of RNA modifications by RNA-binding proteins

The complexity of RNA cannot be fully expressed with the canonical A, C, G, and U alphabet. To date, over 170 distinct chemical modifications to RNA have been discovered in living systems. RNA modifications can profoundly impact the cellular outcomes of messenger RNAs (mRNAs), transfer and ribosomal RNAs, and noncoding RNAs. Additionally, aberrant RNA modifications are associated with human disease. RNA modifications are a rising topic within the fields of biochemistry and molecular biology. The role of RNA modifications in gene regulation, disease pathogenesis, and therapeutic applications increasingly captures the attention of the scientific community. This review aims to provide undergraduates, junior trainees, and educators with an appreciation for the significance of RNA modifications in eukaryotic organisms, alongside the skills required to identify and analyze fundamental RNA-protein interactions. The pumilio RNA-binding protein and YT521-B homology (YTH) family of modified RNA-binding proteins serve as examples to highlight the fundamental biochemical interactions that underlie the specific recognition of both unmodified and modified ribonucleotides, respectively. By instilling these foundational, textbook concepts through practical examples, this review contributes an analytical toolkit that facilitates engagement with RNA modifications research at large.

Challenges in Therapeutically Targeting the RNA-Recognition Motif

The RNA recognition motif (RRM) is the most common RNA binding domain found in the human proteome. RRM domains provide RNA-binding proteins with sequence specific RNA recognition allowing them to participate in RNA-centric processes such as mRNA maturation, translation initiation, splicing, and RNA degradation. They are drivers of various diseases through overexpression or mutation, making them attractive therapeutic targets and addressing these proteins through their RRM domains with chemical compounds is gaining ever more attention. However, it is still very challenging to find selective and potent RNA-competitors due to the small size of the domain and high structural conservation of its RNA binding interface. Despite these challenges, a selection of compounds has been reported for several RRM containing proteins, but often with limited biophysical evidence and low selectivity. A solution to selectively targeting RRM domains might be through avoiding the RNA-binding surface altogether, but rather look for composite pockets formed with other proteins or for protein-protein interaction sites that regulate the target's activity but are less conserved. Alternative modalities, such as oligonucleotides, peptides, and molecular glues, are exciting new approaches to address these challenging targets and achieve the goal of therapeutic intervention at the RNA regulatory level.

N-terminal domain of polypyrimidine-tract binding protein is a dynamic folding platform for adaptive RNA recognition

The N-terminal RNA recognition motif domain (RRM1) of polypyrimidine tract binding protein (PTB) forms an additional C-terminal helix α3, which docks to one edge of the β-sheet upon binding to a stem-loop RNA containing a UCUUU pentaloop. Importantly, α3 does not contact the RNA. The α3 helix therefore represents an allosteric means to regulate the conformation of adjacent domains in PTB upon binding structured RNAs. Here we investigate the process of dynamic adaptation by stem-loop RNA and RRM1 using NMR and MD in order to obtain mechanistic insights on how this allostery is achieved. Relaxation data and NMR structure determination of the free protein show that α3 is partially ordered and interacts with the domain transiently. Stem-loop RNA binding quenches fast time scale dynamics and α3 becomes ordered, however microsecond dynamics at the protein-RNA interface is observed. MD shows how RRM1 binding to the stem-loop RNA is coupled to the stabilization of the C-terminal helix and helps to transduce differences in RNA loop sequence into changes in α3 length and order. IRES assays of full length PTB and a mutant with altered dynamics in the α3 region show that this dynamic allostery influences PTB function in cultured HEK293T cells.

Regulation of DNA damage response by RNA/DNA-binding proteins: Implications for neurological disorders and aging

RNA-binding proteins (RBPs) are evolutionarily conserved across most forms of life, with an estimated 1500 RBPs in humans. Traditionally associated with post-transcriptional gene regulation, RBPs contribute to nearly every known aspect of RNA biology, including RNA splicing, transport, and decay. In recent years, an increasing subset of RBPs have been recognized for their DNA binding properties and involvement in DNA transactions. We refer to these RBPs with well-characterized DNA binding activity as RNA/DNA binding proteins (RDBPs), many of which are linked to neurological diseases. RDBPs are associated with both nuclear and mitochondrial DNA repair. Furthermore, the presence of intrinsically disordered domains in RDBPs appears to be critical for regulating their diverse interactions and plays a key role in controlling protein aggregation, which is implicated in neurodegeneration. In this review, we discuss the emerging roles of common RDBPs from the heterogeneous nuclear ribonucleoprotein (hnRNP) family, such as TAR DNA binding protein-43 (TDP43) and fused in sarcoma (FUS) in controlling DNA damage response (DDR). We also explore the implications of RDBP pathology in aging and neurodegenerative diseases and provide a prospective on the therapeutic potential of targeting RDBP pathology mediated DDR defects for motor neuron diseases and aging.

Refining the pool of RNA-binding domains advances the classification and prediction of RNA-binding proteins

From transcription to decay, RNA-binding proteins (RBPs) influence RNA metabolism. Using the RBP2GO database that combines proteome-wide RBP screens from 13 species, we investigated the RNA-binding features of 176 896 proteins. By compiling published lists of RNA-binding domains (RBDs) and RNA-related protein family (Rfam) IDs with lists from the InterPro database, we analyzed the distribution of the RBDs and Rfam IDs in RBPs and non-RBPs to select RBDs and Rfam IDs that were enriched in RBPs. We also explored proteins for their content in intrinsically disordered regions (IDRs) and low complexity regions (LCRs). We found a strong positive correlation between IDRs and RBDs and a co-occurrence of specific LCRs. Our bioinformatic analysis indicated that RBDs/Rfam IDs were strong indicators of the RNA-binding potential of proteins and helped predicting new RBP candidates, especially in less investigated species. By further analyzing RBPs without RBD, we predicted new RBDs that were validated by RNA-bound peptides. Finally, we created the RBP2GO composite score by combining the RBP2GO score with new quality factors linked to RBDs and Rfam IDs. Based on the RBP2GO composite score, we compiled a list of 2018 high-confidence human RBPs. The knowledge collected here was integrated into the RBP2GO database at https://RBP2GO-2-Beta.dkfz.de.

High-throughput quantitation of protein-RNA UV-crosslinking efficiencies as a predictive tool for high-confidence identification of RNA-binding proteins

UV-crosslinking has proven to be an invaluable tool for the identification of RNA-protein interactomes. The paucity of methods for distinguishing background from bona fide RNA-protein interactions, however, makes attribution of RNA-binding function on UV-crosslinking alone challenging. To address this need, we previously reported an RNA-binding protein (RBP) confidence scoring metric (RCS), incorporating both signal-to-noise (S:N) and protein abundance determinations to distinguish high- and low-confidence candidate RBPs. Although RCS has utility, we sought a direct metric for quantification and comparative evaluation of protein-RNA interactions. Here we propose the use of protein-specific UV-crosslinking efficiency (%CL), representing the molar fraction of a protein that is crosslinked to RNA, for functional evaluation of candidate RBPs. Application to the HeLa RNA interactome yielded %CL values for 1097 proteins. Remarkably, %CL values span over five orders of magnitude. For the HeLa RNA interactome, %CL values comprise a range from high efficiency, high specificity interactions, e.g., the Elav protein HuR and the Pumilio homolog Pum2, with %CL values of 45.9 and 24.2, respectively, to very low efficiency and specificity interactions, for example, the metabolic enzymes glyceraldehyde-3-phosphate dehydrogenase, fructose-bisphosphate aldolase, and alpha-enolase, with %CL values of 0.0016, 0.006, and 0.008, respectively. We further extend the utility of %CL through prediction of protein domains and classes with known RNA-binding functions, thus establishing it as a useful metric for RNA interactome analysis. We anticipate that this approach will benefit efforts to establish functional RNA interactomes and support the development of more predictive computational approaches for RBP identification.

DeePNAP: A Deep Learning Method to Predict Protein-Nucleic Acid Binding Affinity from Their Sequences

Predicting the protein-nucleic acid (PNA) binding affinity solely from their sequences is of paramount importance for the experimental design and analysis of PNA interactions (PNAIs). A large number of currently developed models for binding affinity prediction are limited to specific PNAIs while also relying on the sequence and structural information of the PNA complexes for both training and testing, and also as inputs. As the PNA complex structures available are scarce, this significantly limits the diversity and generalizability due to the small training data set. Additionally, a majority of the tools predict a single parameter, such as binding affinity or free energy changes upon mutations, rendering a model less versatile for usage. Hence, we propose DeePNAP, a machine learning-based model built from a vast and heterogeneous data set with 14,401 entries (from both eukaryotes and prokaryotes) from the ProNAB database, consisting of wild-type and mutant PNA complex binding parameters. Our model precisely predicts the binding affinity and free energy changes due to the mutation(s) of PNAIs exclusively from their sequences. While other similar tools extract features from both sequence and structure information, DeePNAP employs sequence-based features to yield high correlation coefficients between the predicted and experimental values with low root mean squared errors for PNA complexes in predicting KD and ΔΔG, implying the generalizability of DeePNAP. Additionally, we have also developed a web interface hosting DeePNAP that can serve as a powerful tool to rapidly predict binding affinities for a myriad of PNAIs with high precision toward developing a deeper understanding of their implications in various biological systems. Web interface: http://14.139.174.41:8080/.

TcZC3HTTP, a regulatory element that contributes to Trypanosoma cruzi cell proliferation

Post-transcriptional regulation of gene expression is a critical process for adapting to and surviving Trypanosoma cruzi, a parasite with a complex life cycle. RNA-binding proteins (RBPs) are key players in this regulation, forming ribonucleoprotein complexes (messenger ribonucleoproteins) and RNA granules that control transcript stability, localization, degradation, and translation modulation. Understanding the specific roles of individual RBPs is crucial for unraveling the details of this regulatory network. In this study, we generated null mutants of the TcZC3HTTP gene, a specific RBP in the Trypanosoma family characterized by a C3H zinc finger and a DNAJ domain associated with RNA and protein binding, respectively. Through cell growth assays, we demonstrated that the absence of TcZC3HTTP or the expression of an additional tagged version impacted epimastigote growth, indicating its contribution to cell proliferation. TcZC3HTTP was found to associate with mRNAs involved in cell cycle and division in epimastigotes, while in nutritionally stressed parasites it exhibited associations with mRNAs coding for other RBPs and rRNA. Furthermore, our analysis identified that TcZC3HTTP protein partners were different during normal growth conditions compared to starvation conditions, with the latter showing enrichment of ribosomal proteins and other RBPs. Therefore, this study provides insights into TcZC3HTTP's role in the post-transcriptional regulation of gene expression during normal growth and nutritional stress in T. cruzi, uncovering its versatile functions in different cellular contexts.IMPORTANCEUnderstanding how Trypanosoma cruzi, the causative agent of Chagas disease, regulates gene expression is crucial for developing targeted interventions. In this study, we investigated the role of TcZC3HTTP, an RNA-binding protein, in post-transcriptional regulation. Our findings demonstrate that TcZC3HTTP is relevant for the growth and proliferation of epimastigotes, a stage of the parasite's life cycle. We identified its associations with specific mRNAs involved in cell cycle and division and its interactions with enzymes and other RNA-binding proteins (RBPs) under normal and starvation conditions. These insights shed light on the regulatory network underlying gene expression in T. cruzi and reveal the multifaceted functions of RBPs in this parasite. Such knowledge enhances our understanding of the parasite's biology and opens avenues for developing novel therapeutic strategies targeting post-transcriptional gene regulation in T. cruzi.

CoMemMoRFPred: Sequence-based Prediction of MemMoRFs by Combining Predictors of Intrinsic Disorder, MoRFs and Disordered Lipid-binding Regions

Molecular recognition features (MoRFs) are a commonly occurring type of intrinsically disordered regions (IDRs) that undergo disorder-to-order transition upon binding to partner molecules. We focus on recently characterized and functionally important membrane-binding MoRFs (MemMoRFs). Motivated by the lack of computational tools that predict MemMoRFs, we use a dataset of experimentally annotated MemMoRFs to conceptualize, design, evaluate and release an accurate sequence-based predictor. We rely on state-of-the-art tools that predict residues that possess key characteristics of MemMoRFs, such as intrinsic disorder, disorder-to-order transition and lipid-binding. We identify and combine results from three tools that include flDPnn for the disorder prediction, DisoLipPred for the prediction of disordered lipid-binding regions, and MoRFCHiBiLight for the prediction of disorder-to-order transitioning protein binding regions. Our empirical analysis demonstrates that combining results produced by these three methods generates accurate predictions of MemMoRFs. We also show that use of a smoothing operator produces predictions that closely mimic the number and sizes of the native MemMoRF regions. The resulting CoMemMoRFPred method is available as an easy-to-use webserver at http://biomine.cs.vcu.edu/servers/CoMemMoRFPred. This tool will aid future studies of MemMoRFs in the context of exploring their abundance, cellular functions, and roles in pathologic phenomena.

Twist-stretch relations in nucleic acids

Nucleic acids are highly deformable helical molecules constantly stretched, twisted and bent in their biological functioning. Single molecule experiments have shown that double stranded (ds)-RNA and standard ds-DNA have opposite twist-stretch patterns and stretching properties when overwound under a constant applied load. The key structural features of the A-form RNA and B-form DNA helices are here incorporated in a three-dimensional mesoscopic Hamiltonian model which accounts for the radial, bending and twisting fluctuations of the base pairs. Using path integral techniques which sum over the ensemble of the base pair fluctuations, I compute the average helical repeat of the molecules as a function of the load. The obtained twist-stretch relations and stretching properties, for short A- and B-helical fragments, are consistent with the opposite behaviors observed in kilo-base long molecules.

RBPome identification in egg-cell like callus of Arabidopsis

RNA binding proteins (RBPs) have multiple and essential roles in transcriptional and posttranscriptional regulation of gene expression in all living organisms. Their biochemical identification in the proteome of a given cell or tissue requires significant protein amounts, which limits studies in rare and highly specialized cells. As a consequence, we know almost nothing about the role(s) of RBPs in reproductive processes such as egg cell development, fertilization and early embryogenesis in flowering plants. To systematically identify the RBPome of egg cells in the model plant Arabidopsis, we performed RNA interactome capture (RIC) experiments using the egg cell-like RKD2-callus and were able to identify 728 proteins associated with poly(A+)-RNA. Transcripts for 97 % of identified proteins could be verified in the egg cell transcriptome. 46 % of identified proteins can be associated with the RNA life cycle. Proteins involved in mRNA binding, RNA processing and metabolism are highly enriched. Compared with the few available RBPome datasets of vegetative plant tissues, we identified 475 egg cell-enriched RBPs, which will now serve as a resource to study RBP function(s) during egg cell development, fertilization and early embryogenesis. First candidates were already identified showing an egg cell-specific expression pattern in ovules.

CELLULAR RNA INTERACTS WITH MAVS TO PROMOTE ANTIVIRAL SIGNALING

Immune signaling needs to be well-regulated to promote clearance of pathogens, while preventing aberrant inflammation. Interferons (IFNs) and antiviral genes are activated by the detection of viral RNA by RIG-I-like receptors (RLRs). Signal transduction downstream of RLRs proceeds through a multi-protein complex organized around the central adaptor protein MAVS. Recent work has shown that protein complex function can be modulated by RNA molecules providing allosteric regulation or acting as molecular guides or scaffolds. Thus, we hypothesized that RNA plays a role in organizing MAVS signaling platforms. Here, we show that MAVS, through its central intrinsically disordered domain, directly interacts with the 3' untranslated regions of cellular mRNAs. Importantly, elimination of RNA by RNase treatment disrupts the MAVS signalosome, including newly identified regulators of RLR signaling, and inhibits phosphorylation of the transcription factor IRF3. This supports the hypothesis that RNA molecules scaffold proteins in the MAVS signalosome to induce IFNs. Together, this work uncovers a function for cellular RNA in promoting signaling through MAVS and highlights a generalizable principle of RNA regulatory control of cytoplasmic immune signaling complexes.

Signal-noise metrics for RNA binding protein identification reveal broad spectrum protein-RNA interaction frequencies and dynamics

Recent efforts towards the comprehensive identification of RNA-bound proteomes have revealed a large, surprisingly diverse family of candidate RNA-binding proteins (RBPs). Quantitative metrics for characterization and validation of protein-RNA interactions and their dynamic interactions have, however, proven analytically challenging and prone to error. Here we report a method termed LEAP-RBP (Liquid-Emulsion-Assisted-Purification of RNA-Bound Protein) for the selective, quantitative recovery of UV-crosslinked RNA-protein complexes. By virtue of its high specificity and yield, LEAP-RBP distinguishes RNA-bound and RNA-free protein levels and reveals common sources of experimental noise in RNA-centric RBP enrichment methods. We introduce strategies for accurate RBP identification and signal-based metrics for quantifying protein-RNA complex enrichment, relative RNA occupancy, and method specificity. In this work, the utility of our approach is validated by comprehensive identification of RBPs whose association with mRNA is modulated in response to global mRNA translation state changes and through in-depth benchmark comparisons with current methodologies.

The DNA binding high mobility group box protein family functionally binds RNA

Nucleic acid binding proteins regulate transcription, splicing, RNA stability, RNA localization, and translation, together tailoring gene expression in response to stimuli. Upon discovery, these proteins are typically classified as either DNA or RNA binding as defined by their in vivo functions; however, recent evidence suggests dual DNA and RNA binding by many of these proteins. High mobility group box (HMGB) proteins have a DNA binding HMGB domain, act as transcription factors and chromatin remodeling proteins, and are increasingly understood to interact with RNA as means to regulate gene expression. Herein, multiple layers of evidence that the HMGB family are dual DNA and RNA binding proteins is comprehensively reviewed. For example, HMGB proteins directly interact with RNA in vitro and in vivo, are localized to RNP granules involved in RNA processing, and their protein interactors are enriched in RNA binding proteins involved in RNA metabolism. Importantly, in cell-based systems, HMGB-RNA interactions facilitate protein-protein interactions, impact splicing outcomes, and modify HMGB protein genomic or cellular localization. Misregulation of these HMGB-RNA interactions are also likely involved in human disease. This review brings to light that as a family, HMGB proteins are likely to bind RNA which is essential to HMGB protein biology. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.

A Kuhnian revolution in molecular biology: Most genes in complex organisms express regulatory RNAs

Thomas Kuhn described the progress of science as comprising occasional paradigm shifts separated by interludes of 'normal science'. The paradigm that has held sway since the inception of molecular biology is that genes (mainly) encode proteins. In parallel, theoreticians posited that mutation is random, inferred that most of the genome in complex organisms is non-functional, and asserted that somatic information is not communicated to the germline. However, many anomalies appeared, particularly in plants and animals: the strange genetic phenomena of paramutation and transvection; introns; repetitive sequences; a complex epigenome; lack of scaling of (protein-coding) genes and increase in 'noncoding' sequences with developmental complexity; genetic loci termed 'enhancers' that control spatiotemporal gene expression patterns during development; and a plethora of 'intergenic', overlapping, antisense and intronic transcripts. These observations suggest that the original conception of genetic information was deficient and that most genes in complex organisms specify regulatory RNAs, some of which convey intergenerational information. Also see the video abstract here: https://youtu.be/qxeGwahBANw.

Surveying the global landscape of post-transcriptional regulators

Numerous proteins regulate gene expression by modulating mRNA translation and decay. To uncover the full scope of these post-transcriptional regulators, we conducted an unbiased survey that quantifies regulatory activity across the budding yeast proteome and delineates the protein domains responsible for these effects. Our approach couples a tethered function assay with quantitative single-cell fluorescence measurements to analyze ~50,000 protein fragments and determine their effects on a tethered mRNA. We characterize hundreds of strong regulators, which are enriched for canonical and unconventional mRNA-binding proteins. Regulatory activity typically maps outside the RNA-binding domains themselves, highlighting a modular architecture that separates mRNA targeting from post-transcriptional regulation. Activity often aligns with intrinsically disordered regions that can interact with other proteins, even in core mRNA translation and degradation factors. Our results thus reveal networks of interacting proteins that control mRNA fate and illuminate the molecular basis for post-transcriptional gene regulation.

Long non-coding RNAs: definitions, functions, challenges and recommendations

Genes specifying long non-coding RNAs (lncRNAs) occupy a large fraction of the genomes of complex organisms. The term 'lncRNAs' encompasses RNA polymerase I (Pol I), Pol II and Pol III transcribed RNAs, and RNAs from processed introns. The various functions of lncRNAs and their many isoforms and interleaved relationships with other genes make lncRNA classification and annotation difficult. Most lncRNAs evolve more rapidly than protein-coding sequences, are cell type specific and regulate many aspects of cell differentiation and development and other physiological processes. Many lncRNAs associate with chromatin-modifying complexes, are transcribed from enhancers and nucleate phase separation of nuclear condensates and domains, indicating an intimate link between lncRNA expression and the spatial control of gene expression during development. lncRNAs also have important roles in the cytoplasm and beyond, including in the regulation of translation, metabolism and signalling. lncRNAs often have a modular structure and are rich in repeats, which are increasingly being shown to be relevant to their function. In this Consensus Statement, we address the definition and nomenclature of lncRNAs and their conservation, expression, phenotypic visibility, structure and functions. We also discuss research challenges and provide recommendations to advance the understanding of the roles of lncRNAs in development, cell biology and disease.

Elucidating the RNA-Protein Interactomes of Target RNAs in Tissue

RNA-protein interactions are key to many aspects of cellular homeostasis and their identification is important to understanding cellular function. Multiple strategies have been developed for the RNA-centric characterization of RNA-protein complexes. However, these studies have all been done in immortalized cell lines that do not capture the complexity of heterogeneous tissue samples. Here, we develop hybridization purification of RNA-protein complexes followed by mass spectrometry (HyPR-MS) for use in tissue samples. We isolated both polyadenylated RNA and the specific long noncoding RNA MALAT1 and characterized their protein interactomes. These results demonstrate the feasibility of HyPR-MS in tissue for the multiplexed characterization of specific RNA-protein complexes.

Moonlighting enzymes: when cellular context defines specificity

It is not often realized that the absolute protein specificity is an exception rather than a rule. Two major kinds of protein multi-specificities are promiscuity and moonlighting. This review discusses the idea of enzyme specificity and then focusses on moonlighting. Some important examples of protein moonlighting, such as crystallins, ceruloplasmin, metallothioniens, macrophage migration inhibitory factor, and enzymes of carbohydrate metabolism are discussed. How protein plasticity and intrinsic disorder enable the removing the distinction between enzymes and other biologically active proteins are outlined. Finally, information on important roles of moonlighting in human diseases is updated.

Protein-RNA interactions: from mass spectrometry to drug discovery

Proteins and RNAs are fundamental parts of biological systems, and their interactions affect many essential cellular processes. Therefore, it is crucial to understand at a molecular and at a systems level how proteins and RNAs form complexes and mutually affect their functions. In the present mini-review, we will first provide an overview of different mass spectrometry (MS)-based methods to study the RNA-binding proteome (RBPome), most of which are based on photochemical cross-linking. As we will show, some of these methods are also able to provide higher-resolution information about binding sites, which are important for the structural characterisation of protein-RNA interactions. In addition, classical structural biology techniques such as nuclear magnetic resonance (NMR) spectroscopy and biophysical methods such as electron paramagnetic resonance (EPR) spectroscopy and fluorescence-based methods contribute to a detailed understanding of the interactions between these two classes of biomolecules. We will discuss the relevance of such interactions in the context of the formation of membrane-less organelles (MLOs) by liquid-liquid phase separation (LLPS) processes and their emerging importance as targets for drug discovery.

HybridRNAbind: prediction of RNA interacting residues across structure-annotated and disorder-annotated proteins

The sequence-based predictors of RNA-binding residues (RBRs) are trained on either structure-annotated or disorder-annotated binding regions. A recent study of predictors of protein-binding residues shows that they are plagued by high levels of cross-predictions (protein binding residues are predicted as nucleic acid binding) and that structure-trained predictors perform poorly for the disorder-annotated regions and vice versa. Consequently, we analyze a representative set of the structure and disorder trained predictors of RBRs to comprehensively assess quality of their predictions. Our empirical analysis that relies on a new and low-similarity benchmark dataset reveals that the structure-trained predictors of RBRs perform well for the structure-annotated proteins while the disorder-trained predictors provide accurate results for the disorder-annotated proteins. However, these methods work only modestly well on the opposite types of annotations, motivating the need for new solutions. Using an empirical approach, we design HybridRNAbind meta-model that generates accurate predictions and low amounts of cross-predictions when tested on data that combines structure and disorder-annotated RBRs. We release this meta-model as a convenient webserver which is available at https://www.csuligroup.com/hybridRNAbind/.

Unravelling the tripartite interactions among Hepatitis E virus RNA, miR-140 and hnRNP K: Running title: Interactions between HEV-RNA, miR-140 and hnRNP K

In the present investigation, we have identified the functional significance of the highly conserved miR-140 binding site on the Hepatitis E Virus (HEV) genome. Multiple sequence alignment of the viral genome sequences along with RNA folding prediction indicated that the putative miR-140 binding site has significant conservation for sequence and secondary RNA structure among HEV genotypes. Site-directed mutagenesis and reporter assays indicated that an intact sequence of the miR-140 binding site is essential for HEV translation. Provision of mutant miR-140 oligos carrying same mutation as on mutant HEV successfully rescued mutant HEV replication. In vitro cell-based assays with modified oligos proved that host factor-miR-140 is a critical requirement for HEV replication. Biotinylated RNA pulldown and RNA immunoprecipitation assays proved that the predicted secondary RNA structure of the miR-140 binding site allows the recruitment of hnRNP K, which is a key protein of the HEV replication complex. We predicted the model from the obtained results that the miR-140 binding site can serve as a platform for recruitment of hnRNP K and other proteins of HEV replication complex only in the presence of miR-140.

Upstream of N-Ras C-terminal cold shock domains mediate poly(A) specificity in a novel RNA recognition mode and bind poly(A) binding protein

RNA binding proteins (RBPs) often engage multiple RNA binding domains (RBDs) to increase target specificity and affinity. However, the complexity of target recognition of multiple RBDs remains largely unexplored. Here we use Upstream of N-Ras (Unr), a multidomain RBP, to demonstrate how multiple RBDs orchestrate target specificity. A crystal structure of the three C-terminal RNA binding cold-shock domains (CSD) of Unr bound to a poly(A) sequence exemplifies how recognition goes beyond the classical ππ-stacking in CSDs. Further structural studies reveal several interaction surfaces between the N-terminal and C-terminal part of Unr with the poly(A)-binding protein (pAbp). All interactions are validated by mutational analyses and the high-resolution structures presented here will guide further studies to understand how both proteins act together in cellular processes.

Computational Prediction of Protein Intrinsically Disordered Region Related Interactions and Functions

Intrinsically Disordered Proteins (IDPs) and Regions (IDRs) exist widely. Although without well-defined structures, they participate in many important biological processes. In addition, they are also widely related to human diseases and have become potential targets in drug discovery. However, there is a big gap between the experimental annotations related to IDPs/IDRs and their actual number. In recent decades, the computational methods related to IDPs/IDRs have been developed vigorously, including predicting IDPs/IDRs, the binding modes of IDPs/IDRs, the binding sites of IDPs/IDRs, and the molecular functions of IDPs/IDRs according to different tasks. In view of the correlation between these predictors, we have reviewed these prediction methods uniformly for the first time, summarized their computational methods and predictive performance, and discussed some problems and perspectives.

Structure of a bacterial ribonucleoprotein complex central to the control of cell envelope biogenesis

Biogenesis of the essential precursor of the bacterial cell envelope, glucosamine-6-phosphate (GlcN6P), is controlled by intricate post-transcriptional networks mediated by GlmZ, a small regulatory RNA (sRNA). GlmZ stimulates translation of the mRNA encoding GlcN6P synthtase in Escherichia coli, but when bound by RapZ protein, the sRNA becomes inactivated through cleavage by the endoribonuclease RNase E. Here, we report the cryoEM structure of the RapZ:GlmZ complex, revealing a complementary match of the RapZ tetrameric quaternary structure to structural repeats in the sRNA. The nucleic acid is contacted by RapZ mostly through a highly conserved domain that shares an evolutionary relationship with phosphofructokinase and suggests links between metabolism and riboregulation. We also present the structure of a precleavage intermediate formed between the binary RapZ:GlmZ complex and RNase E that reveals how GlmZ is presented and recognised by the enzyme. The structures provide a framework for understanding how other encounter complexes might guide recognition and action of endoribonucleases on target transcripts, and how structured substrates in polycistronic precursors may be recognised for processing by RNase E.

Conformational Heterogeneity of RNA Stem-Loop Hairpins Bound to FUS-RNA Recognition Motif with Disordered RGG Tail Revealed by Unbiased Molecular Dynamics Simulations

RNA-protein complexes use diverse binding strategies, ranging from structurally well-defined interfaces to completely disordered regions. Experimental characterization of flexible segments is challenging and can be aided by atomistic molecular dynamics (MD) simulations. Here, we used an extended set of microsecond-scale MD trajectories (400 μs in total) to study two FUS-RNA constructs previously characterized by nuclear magnetic resonance (NMR) spectroscopy. The FUS protein contains a well-structured RNA recognition motif domain followed by a presumably disordered RGG tail that binds RNA stem-loop hairpins. Our simulations not only provide several suggestions complementing the experiments but also reveal major methodological difficulties in studies of such complex RNA-protein interfaces. Despite efforts to stabilize the binding via system-specific force-field adjustments, we have observed progressive distortions of the RNA-protein interface inconsistent with experimental data. We propose that the dynamics is so rich that its converged description is not achievable even upon stabilizing the system. Still, after careful analysis of the trajectories, we have made several suggestions regarding the binding. We identify substates in the RNA loops, which can explain the NMR data. The RGG tail localized in the minor groove remains disordered, sampling countless transient interactions with the RNA. There are long-range couplings among the different elements contributing to the recognition, which can lead to allosteric communication throughout the system. Overall, the RNA-FUS systems form dynamical ensembles that cannot be fully represented by single static structures. Thus, albeit imperfect, MD simulations represent a viable tool to investigate dynamic RNA-protein complexes.

Intrinsically Disordered Proteins: An Overview

Many proteins and protein segments cannot attain a single stable three-dimensional structure under physiological conditions; instead, they adopt multiple interconverting conformational states. Such intrinsically disordered proteins or protein segments are highly abundant across proteomes, and are involved in various effector functions. This review focuses on different aspects of disordered proteins and disordered protein regions, which form the basis of the so-called "Disorder-function paradigm" of proteins. Additionally, various experimental approaches and computational tools used for characterizing disordered regions in proteins are discussed. Finally, the role of disordered proteins in diseases and their utility as potential drug targets are explored.

Long non-coding RNA and RNA-binding protein interactions in cancer: Experimental and machine learning approaches

Understanding the complex and specific roles played by non-coding RNAs (ncRNAs), which comprise the bulk of the genome, is important for understanding virtually every hallmark of cancer. This large group of molecules plays pivotal roles in key regulatory mechanisms in various cellular processes. Regulatory mechanisms, mediated by long non-coding RNA (lncRNA) and RNA-binding protein (RBP) interactions, are well documented in several types of cancer. Their effects are enabled through networks affecting lncRNA and RBP stability, RNA metabolism including N⁶-methyladenosine (m⁶A) and alternative splicing, subcellular localization, and numerous other mechanisms involved in cancer. In this review, we discuss the reciprocal interplay between lncRNAs and RBPs and their involvement in epigenetic regulation via histone modifications, as well as their key role in resistance to cancer therapy. Other aspects of RBPs including their structural domains, provide a deeper knowledge on how lncRNAs and RBPs interact and exert their biological functions. In addition, current state-of-the-art knowledge, facilitated by machine and deep learning approaches, unravels such interactions in better details to further enhance our understanding of the field, and the potential to harness RNA-based therapeutics as an alternative treatment modality for cancer are discussed.

Positional motif analysis reveals the extent of specificity of protein-RNA interactions observed by CLIP

BACKGROUND

Crosslinking and immunoprecipitation (CLIP) is a method used to identify in vivo RNA-protein binding sites on a transcriptome-wide scale. With the increasing amounts of available data for RNA-binding proteins (RBPs), it is important to understand to what degree the enriched motifs specify the RNA-binding profiles of RBPs in cells.

RESULTS

We develop positionally enriched k-mer analysis (PEKA), a computational tool for efficient analysis of enriched motifs from individual CLIP datasets, which minimizes the impact of technical and regional genomic biases by internal data normalization. We cross-validate PEKA with mCross and show that the use of input control for background correction is not required to yield high specificity of enriched motifs. We identify motif classes with common enrichment patterns across eCLIP datasets and across RNA regions, while also observing variations in the specificity and the extent of motif enrichment across eCLIP datasets, between variant CLIP protocols, and between CLIP and in vitro binding data. Thereby, we gain insights into the contributions of technical and regional genomic biases to the enriched motifs, and find how motif enrichment features relate to the domain composition and low-complexity regions of the studied proteins.

CONCLUSIONS

Our study provides insights into the overall contributions of regional binding preferences, protein domains, and low-complexity regions to the specificity of protein-RNA interactions, and shows the value of cross-motif and cross-RBP comparison for data interpretation. Our results are presented for exploratory analysis via an online platform in an RBP-centric and motif-centric manner ( https://imaps.goodwright.com/apps/peka/ ).

The Disordered EZH2 Loop: Atomic Level Characterization by 1HN- and 1Hα-Detected NMR Approaches, Interaction with the Long Noncoding HOTAIR RNA

The 96-residue-long loop of EZH2 is proposed to play a role in the interaction with long non-coding RNAs (lncRNAs) and to contribute to EZH2 recruitment to the chromatin. However, molecular details of RNA recognition have not been described so far. Cellular studies have suggested that phosphorylation of the Thr345 residue localized in this loop influences RNA binding; however, no mechanistic explanation has been offered. To address these issues, a systematic NMR study was performed. As the ¹H^N-detected NMR approach presents many challenges under physiological conditions, our earlier developed, as well as improved, ¹H^α-detected experiments were used. As a result of the successful resonance assignment, the obtained chemical shift values indicate the highly disordered nature of the EZH2 loop, with some nascent helical tendency in the Ser407–Ser412 region. Further investigations conducted on the phosphomimetic mutant EZH2^T345D showed that the mutation has only a local effect, and that the loop remains disordered. On the other hand, the mutation influences the cis/trans Pro346 equilibrium. Interactions of both the wild-type and the phosphomimetic mutant with the lncRNA HOTAIR₁₄₀ (1–140 nt) highlight that the Thr367–Ser375 region is affected. This segment does not resemble any of the previously reported RNA-binding motifs, therefore the identified binding region is unique. As no structural changes occur in the EZH2 loop upon RNA binding, we can consider the protein–RNA interaction as a “fuzzy” complex.

Fuzzy RNA recognition by the Trypanosoma brucei editosome

The assembly of high molecular mass ribonucleoprotein complexes typically relies on the binary interaction of defined RNA sequences or precisely folded RNA motifs with dedicated RNA-binding domains on the protein side. Here we describe a new molecular recognition principle of RNA molecules by a high molecular mass protein complex. By chemically probing the solvent accessibility of mitochondrial pre-mRNAs when bound to the Trypanosoma brucei editosome, we identified multiple similar but non-identical RNA motifs as editosome contact sites. However, by treating the different motifs as mathematical graph objects we demonstrate that they fit a consensus 2D-graph consisting of 4 vertices (V) and 3 edges (E) with a Laplacian eigenvalue of 0.5477 (λ₂). We establish that synthetic 4V(3E)-RNAs are sufficient to compete for the editosomal pre-mRNA binding site and that they inhibit RNA editing in vitro. Furthermore, we demonstrate that only two topological indices are necessary to predict the binding of any RNA motif to the editosome with a high level of confidence. Our analysis corroborates that the editosome has adapted to the structural multiplicity of the mitochondrial mRNA folding space by recognizing a fuzzy continuum of RNA folds that fit a consensus graph descriptor.

Phase Separation Drives SARS-CoV-2 Replication: A Hypothesis

Identifying human proteins that interact with SARS-CoV-2 genome is important to understand its replication and to identify therapeutic strategies. Recent studies have unveiled protein interactions of SARS-COV-2 in different cell lines and through a number of high-throughput approaches. Here, we carried out a comparative analysis of four experimental and one computational studies to characterize the interactions of SARS-CoV-2 genomic RNA. Although hundreds of interactors have been identified, only twenty-one appear in all the experiments and show a strong propensity to bind. This set of interactors includes stress granule forming proteins, pre-mRNA regulators and elements involved in the replication process. Our calculations indicate that DDX3X and several editases bind the 5′ end of SARS-CoV-2, a regulatory region previously reported to attract a large number of proteins. The small overlap among experimental datasets suggests that SARS-CoV-2 genome establishes stable interactions only with few interactors, while many proteins bind less tightly. In analogy to what has been previously reported for Xist non-coding RNA, we propose a mechanism of phase separation through which SARS-CoV-2 progressively sequesters human proteins hijacking the host immune response.

F/YGG-motif is an intrinsically disordered nucleic-acid binding motif

Heterogeneous nuclear ribonucleoproteins (hnRNP) function in RNA processing, have RNA-recognition motifs (RRMs) and intrinsically disordered, low-complexity domains (LCDs). While RRMs are drivers of RNA binding, there is only limited knowledge about the RNA interaction by the LCD of some hnRNPs. Here, we show that the LCD of hnRNPA2 interacts with RNA via an embedded Tyr/Gly-rich region which is a disordered RNA-binding motif. RNA binding is maintained upon mutating tyrosine residues to phenylalanines, but abrogated by mutating to alanines, thus we term the RNA-binding region ‘F/YGG motif’. The F/YGG motif can bind a broad range of structured (e.g. tRNA) and disordered (e.g. polyA) RNAs, but not rRNA. As the F/YGG otif can also interact with DNA, we consider it a general nucleic acid-binding motif. hnRNPA2 LCD can form dense droplets, by liquid–liquid phase separation (LLPS). Their formation is inhibited by RNA binding, which is mitigated by salt and 1,6-hexanediol, suggesting that both electrostatic and hydrophobic interactions feature in the F/YGG motif. The D290V mutant also binds RNA, which interferes with both LLPS and aggregation thereof. We found homologous regions in a broad range of RNA- and DNA-binding proteins in the human proteome, suggesting that the F/YGG motif is a general nucleic acid-interaction motif.

OpenCell: Endogenous tagging for the cartography of human cellular organization

Elucidating the wiring diagram of the human cell is a central goal of the postgenomic era. We combined genome engineering, confocal live-cell imaging, mass spectrometry, and data science to systematically map the localization and interactions of human proteins. Our approach provides a data-driven description of the molecular and spatial networks that organize the proteome. Unsupervised clustering of these networks delineates functional communities that facilitate biological discovery. We found that remarkably precise functional information can be derived from protein localization patterns, which often contain enough information to identify molecular interactions, and that RNA binding proteins form a specific subgroup defined by unique interaction and localization properties. Paired with a fully interactive website (opencell.czbiohub.org), our work constitutes a resource for the quantitative cartography of human cellular organization.

Pull-down of Biotinylated RNA and Associated Proteins

Mapping networks of RNA-protein interactions in cells is essential for understanding the inner workings of many biological processes, including RNA processing, trafficking, and translation. Current in vivo methods for studying protein-RNA interactions rely mostly on purification of poly(A) transcripts, which represent only ~2-3% of total RNAs (Figure 1). Alternate robust methods for tagging RNA molecules with an RNA aptamer (e.g., MS2-, U1A- and biotin-RNA aptamer) and capturing the RNA-protein complex by the respective aptamer-specific partner are not extensively studied. Here, we describe a protocol (Figure 2) in which a biotin-RNA aptamer, referred to as the RNA mimic of biotin (RMB), was conjugated separately to two small RNA secondary structures that contribute to trafficking and translating HAC1 mRNA in the budding yeast Saccharomyces cerevisiae. The RMB-tagged RNA was expressed in yeast cells from a constitutive promoter. The biotinylated RNA bound to proteins was pulled down from the cell lysate by streptavidin agarose beads. RNA was detected by RT-PCR (Figure 3) and associated proteins by mass spectrometry (Figure 4). Our findings show that an RNA aptamer tag to RNA molecule is an effective method to explore the functional roles of RNA-protein networks in vivo.

The Role of DEAD-Box ATPases in Gene Expression and the Regulation of RNA-Protein Condensates

DEAD-box ATPases constitute a very large protein family present in all cells, often in great abundance. From bacteria to humans, they play critical roles in many aspects of RNA metabolism, and due to their widespread importance in RNA biology, they have been characterized in great detail at both the structural and biochemical levels. DEAD-box proteins function as RNA-dependent ATPases that can unwind short duplexes of RNA, remodel ribonucleoprotein (RNP) complexes, or act as clamps to promote RNP assembly. Yet, it often remains enigmatic how individual DEAD-box proteins mechanistically contribute to specific RNA-processing steps. Here, we review the role of DEAD-box ATPases in the regulation of gene expression and propose that one common function of these enzymes is in the regulation of liquid-liquid phase separation of RNP condensates. Expected final online publication date for the Annual Review of Biochemistry, Volume 91 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

In vitro evolution reveals non-cationic protein-RNA interaction mediated by metal ions

RNA–peptide/protein interactions have been of utmost importance to life since its earliest forms, reaching even before the last universal common ancestor (LUCA). However, the ancient molecular mechanisms behind this key biological interaction remain enigmatic because extant RNA–protein interactions rely heavily on positively charged and aromatic amino acids that were absent (or heavily under-represented) in the early pre-LUCA evolutionary period. Here, an RNA-binding variant of the ribosomal uL11 C-terminal domain was selected from an approximately 10¹⁰ library of partially randomized sequences, all composed of ten prebiotically plausible canonical amino acids. The selected variant binds to the cognate RNA with a similar overall affinity although it is less structured in the unbound form than the wild-type protein domain. The variant complex association and dissociation are both slower than for the wild-type, implying different mechanistic processes involved. The profile of the wild-type and mutant complex stabilities along with molecular dynamics simulations uncovers qualitative differences in the interaction modes. In the absence of positively charged and aromatic residues, the mutant uL11 domain uses ion bridging (K⁺/Mg²⁺) interactions between the RNA sugar-phosphate backbone and glutamic acid residues as an alternative source of stabilization. This study presents experimental support to provide a new perspective on how early protein–RNA interactions evolved, where the lack of aromatic/basic residues may have been compensated by acidic residues plus metal ions.

The versatile role of HuR in Glioblastoma and its potential as a therapeutic target for a multi-pronged attack

Glioblastoma (GBM) is a malignant and aggressive brain tumor with a median survival of ∼15 months. Resistance to treatment arises from the extensive cellular and molecular heterogeneity in the three major components: glioma tumor cells, glioma stem cells, and tumor-associated microglia and macrophages. Within this triad, there is a complex network of intrinsic and secreted factors that promote classic hallmarks of cancer, including angiogenesis, resistance to cell death, proliferation, and immune evasion. A regulatory node connecting these diverse pathways is at the posttranscriptional level as mRNAs encoding many of the key drivers contain adenine- and uridine rich elements (ARE) in the 3' untranslated region. Human antigen R (HuR) binds to ARE-bearing mRNAs and is a major positive regulator at this level. This review focuses on basic concepts of ARE-mediated RNA regulation and how targeting HuR with small molecule inhibitors represents a plausible strategy for a multi-pronged therapeutic attack on GBM.

Deep structural insights into RNA-binding disordered protein regions

Recent efforts to identify RNA binding proteins in various organisms and cellular contexts have yielded a large collection of proteins that are capable of RNA binding in the absence of conventional RNA recognition domains. Many of the recently identified RNA interaction motifs fall into intrinsically disordered protein regions (IDRs). While the recognition mode and specificity of globular RNA binding elements have been thoroughly investigated and described, much less is known about the way IDRs can recognize their RNA partners. Our aim was to summarize the current state of structural knowledge on the RNA binding modes of disordered protein regions and to propose a classification system based on their sequential and structural properties. Through a detailed structural analysis of the complexes that contain disordered protein regions binding to RNA, we found two major binding modes that represent different recognition strategies and, most likely, functions. We compared these examples with DNA binding disordered proteins and found key differences stemming from the nucleic acids as well as similar binding strategies, implying a broader substrate acceptance by these proteins. Due to the very limited number of known structures, we integrated molecular dynamics simulations in our study, whose results support the proposed structural preferences of specific RNA‐binding IDRs. To broaden the scope of our review, we included a brief analysis of RNA‐binding small molecules and compared their structural characteristics and RNA recognition strategies to the RNA‐binding IDRs.

This article is categorized under:

RNA Structure and Dynamics > RNA Structure, Dynamics, and Chemistry

RNA Interactions with Proteins and Other Molecules > Protein–RNA Recognition

RNA Interactions with Proteins and Other Molecules > Small Molecule–RNA Interactions

A global analysis on the differential regulation of RNA binding proteins (RBPs) by TNF–α as potential modulators of metabolic syndromes

Metabolic syndrome (MetS) is associated with a group of conditions, which enhances the risk of diabetes, heart diseases and stroke in the affected individuals. Earlier reports from our lab have shown that Tumor necrosis factor-α (TNF-α) significantly modulates the expression of 56 genes at the alternative splicing level which are involved in various signaling and metabolic pathways (MetS genes) connected to MetS. These MetS genes were predicted to interact with various RNA-binding proteins (RBPs) when exposed to TNF-α, resulting changes in their alternative splicing patterns. Here we are presenting data of an RNA-Seq analysis, which identified 1218 unique, and significantly regulated genes by TNF-α, 15% of which are RBPs . Among the 1218 genes, 204 genes have been identified as MetS genes by the ingenuity pathway analysis, and 10% of the MetS genes are found as RBPs. Our results also show that TNF-α changes the phosphorylation status of certain RBPs such as SR proteins, crucial players in alternative splicing, possibly via changing the activation status of certain upstream signaling molecules which also act as upstream kinases for these proteins. Taken together, these findings suggest that TNF-α influences the regulation of the RBPs at the various levels for their expression, which may lead to the alteration of the splicing pattern of the MetS genes. MetS genes acting as RBPs and are modulated by TNF-α, predict the existence of highly interconnected mechanisms which require further analysis to understand their dual roles on the onset of these diseases.

DisoLipPred: accurate prediction of disordered lipid-binding residues in protein sequences with deep recurrent networks and transfer learning

MOTIVATION

Intrinsically disordered protein regions interact with proteins, nucleic acids and lipids. Regions that bind lipids are implicated in a wide spectrum of cellular functions and several human diseases. Motivated by the growing amount of experimental data for these interactions and lack of tools that can predict them from the protein sequence, we develop DisoLipPred, the first predictor of the disordered lipid-binding residues (DLBRs).

RESULTS

DisoLipPred relies on a deep bidirectional recurrent network that implements three innovative features: transfer learning, bypass module that sidesteps predictions for putative structured residues, and expanded inputs that cover physiochemical properties associated with the protein-lipid interactions. Ablation analysis shows that these features drive predictive quality of DisoLipPred. Tests on an independent test dataset and the yeast proteome reveal that DisoLipPred generates accurate results and that none of the related existing tools can be used to indirectly identify DLBR. We also show that DisoLipPred's predictions complement the results generated by predictors of the transmembrane regions. Altogether, we conclude that DisoLipPred provides high-quality predictions of DLBRs that complement the currently available methods.

AVAILABILITY AND IMPLEMENTATION

DisoLipPred's webserver is available at http://biomine.cs.vcu.edu/servers/DisoLipPred/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Correlation in Domain Fluctuations Navigates Target Search of a Viral Peptide along RNA

Biological macromolecules often exhibit correlations in fluctuations involving distinct domains. This study decodes their functional implications in RNA-protein recognition and target-specific binding. The target search of a peptide along RNA in a viral TAR-Tat complex is closely monitored using atomistic simulations, steered molecular dynamics simulations, free energy calculations, and a machine-learning-based clustering technique. An anticorrelated domain fluctuation is identified between the tetraloop and the bulge region in the apo form of TAR RNA that sets a hierarchy in the domain-specific fluctuations at each binding event and that directs the succeeding binding footsteps. Thus, at each binding footstep, the dynamic partner selects an RNA location for binding where it senses a higher fluctuation, which is conventionally reduced upon binding. This event stimulates an alternate domain fluctuation, which then dictates sequential binding footstep/s and thus the search progresses. Our cross-correlation maps show that the fluctuations relay from one domain to another specific domain until the anticorrelation between those interdomain fluctuations sustains. Artificial attenuation of that hierarchical domain fluctuation inhibits specific RNA binding. The binding is completed with the arrival of a few long-lived water molecules that mediate slightly distant RNA-protein sites and finally stabilize the overall complex. The study underscores the functional importance of naturally designed fluctuating RNA motifs (bulge, tetraloop) and their interplay in dictating the directionality of the search in a highly dynamic environment.