Methods to study RNA-protein interactions

Progress of CRISPR-Cas13 Mediated Live-Cell RNA Imaging and Detection of RNA-Protein Interactions

Ribonucleic acid (RNA) and proteins play critical roles in gene expression and regulation. The relevant study increases the understanding of various life processes and contributes to the diagnosis and treatment of different diseases. RNA imaging and mapping RNA-protein interactions expand the understanding of RNA biology. However, the existing methods have some limitations. Recently, precise RNA targeting of CRISPR-Cas13 in cells has been reported, which is considered a new promising platform for RNA imaging in living cells and recognition of RNA-protein interactions. In this review, we first described the current findings on Cas13. Furthermore, we introduced current tools of RNA real-time imaging and mapping RNA-protein interactions and highlighted the latest advances in Cas13-mediated tools. Finally, we discussed the advantages and disadvantages of Cas13-based methods, providing a set of new ideas for the optimization of Cas13-mediated methods.

SMC1A regulated by KIAA1429 in m6A-independent manner promotes EMT progress in breast cancer

As a component of N6-methyladenosine (m6A) “writers,” KIAA1429 was reported to promote breast cancer proliferation and growth in m6A-independent manners. However, the related mechanism of KIAA1429 in breast cancer metastasis has not been reported. In the present study, we found KIAA1429 could significantly promote the migration and invasion of breast cancer cells. Then we demonstrated that knockdown of KIAA1429 could impede breast cancer metastasis in nude mice in vivo. The level of SNAIL expression and epithelial-mesenchymal transition (EMT) progress was positively related with KIAA1429. Furthermore, we confirmed that the suppression of cell migration, invasion, and EMT progress by knockdown of KIAA1429 could be reversed by the upregulation of SNAIL. However, structural maintenance of chromosomes 1A (SMC1A), not KIAA1429, bound with the SNAIL promoter region directly and promoted the transcription of SNAIL. Then we confirmed that KIAA1429 could bind to the motif in the 3′ UTR of SMC1A mRNA directly and enhance SMC1A mRNA stability. In conclusion, our study revealed a novel mechanism of the KIAA1429/SMC1A/SNAIL axis in the regulation of metastasis of breast cancer. Moreover, it first provided detailed investigation of how KIAA1429 regulated the targeted gene expression at posttranscriptional levels as an RNA binding protein unrelated to its m6A modification.

Overexpression of cytosolic long noncoding RNA cytb protects against pressure-overload-induced heart failure via sponging microRNA-103-3p

Long noncoding RNAs (lncRNAs) play crucial roles in cardiovascular diseases. To date, only limited studies have reported the role of mitochondria-derived lncRNAs in heart failure (HF). In the current study, recombinant adeno-associated virus 9 was used to manipulate lncRNA cytb (lnccytb) expression in vivo. Fluorescence in situ hybridization (FISH) assay was used to determine the location of lnccytb, while microRNA (miRNA) sequencing and bioinformatics analyses were applied to identify the downstream targets. The competitive endogenous RNA (ceRNA) function of lnccytb was evaluated by biotin-coupled miRNA pull-down assays and luciferase reporter assays. Results showed that lnccytb expression was decreased in the heart of mice with transverse aortic constriction (TAC), as well as in the heart and plasma of patients with HF. FISH assay and absolute RNA quantification via real-time reverse transcription PCR suggested that the reduction of the lnccytb transcripts mainly occurred in the cytosol. Upregulation of cytosolic lnccytb attenuated cardiac dysfunction in TAC mice. Moreover, overexpression of cytosolic lnccytb in cardiomyocytes alleviated isoprenaline-induced reactive oxidative species (ROS) production and hypertrophy. Mechanistically, lnccytb acted as a ceRNA via sponging miR-103-3p, ultimately mitigating the suppression of PTEN by miR-103-3p. In summary, we demonstrated that the overexpression of cytosolic lnccytb could ameliorate HF.

A bacterial three-hybrid assay for forward and reverse genetic analysis of RNA-protein interactions

This protocol describes a bacterial three-hybrid (B3H) assay, an in vivo system that reports on RNA-protein interactions and can be implemented in both forward and reverse genetic experiments. The B3H assay connects the strength of an RNA-protein interaction inside of living Escherichia coli cells to the transcription of a reporter gene (here, lacZ). We present protocols to (1) insert RNA and protein sequences into appropriate vectors for B3H experiments, (2) detect putative RNA-protein interactions with both qualitative and quantitative readouts and (3) carry out forward genetic mutagenesis screens. The B3H assay builds on a well-established bacterial two-hybrid system for genetic analyses. As a result, protein-protein interactions can be assessed in tandem with RNA interactions with a bacterial two-hybrid assay to ensure that protein variants maintain their functionality. The B3H system is a powerful complement to traditional biochemical methods for dissecting RNA-protein interaction mechanisms: RNAs and proteins of interest do not need to be purified, and their interactions can be assessed under native conditions inside of a living bacterial cell. Once cloning has been completed, an assay can be completed in under a week and a screen in 1-2 weeks.

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.

Modulation of miRISC-Mediated Gene Silencing in Eukaryotes

Gene expression is regulated at multiple levels in eukaryotic cells. Regulation at the post-transcriptional level is modulated by various trans-acting factors that bind to specific sequences in the messenger RNA (mRNA). The binding of different trans factors influences various aspects of the mRNA such as degradation rate, translation efficiency, splicing, localization, etc. MicroRNAs (miRNAs) are short endogenous ncRNAs that combine with the Argonaute to form the microRNA-induced silencing complex (miRISC), which uses base-pair complementation to silence the target transcript. RNA-binding proteins (RBPs) contribute to post-transcriptional control by influencing the mRNA stability and translation upon binding to cis-elements within the mRNA transcript. RBPs have been shown to impact gene expression through influencing the miRISC biogenesis, composition, or miRISC-mRNA target interaction. While there is clear evidence that those interactions between RBPs, miRNAs, miRISC and target mRNAs influence the efficiency of miRISC-mediated gene silencing, the exact mechanism for most of them remains unclear. This review summarizes our current knowledge on gene expression regulation through interactions of miRNAs and RBPs.

6-Iodopurine as a Versatile Building Block for RNA Purine Architecture Modifications

Natural modified bases in RNA were found to be indispensable for basic biological processes. In addition, artificial RNA modifications have been a versatile toolbox for the study of RNA interference, structure, and dynamics. Here, we present a chemical method for the facile synthesis of RNA containing C⁶-modified purine. 6-Iodopurine, as a postsynthetic building block with high reactivity, was used for metal-free construction of C-N, C-O, and C-S bonds under mild conditions and C-C bond formation by Suzuki-Miyaura cross-coupling. Our strategy provides a convenient approach for the synthesis of various RNA modifications, especially for oligonucleotides containing specific structures.

Challenges for machine learning in RNA-protein interaction prediction

RNA-protein interactions have long being recognised as crucial regulators of gene expression. Recently, the development of scalable experimental techniques to measure these interactions has revolutionised the field, leading to the production of large-scale datasets which offer both opportunities and challenges for machine learning techniques. In this brief note, we will discuss some of the major stumbling blocks towards the use of machine learning in computational RNA biology, focusing specifically on the problem of predicting RNA-protein interactions from next-generation sequencing data.

Protein-RNA interaction prediction with deep learning: structure matters

Protein-RNA interactions are of vital importance to a variety of cellular activities. Both experimental and computational techniques have been developed to study the interactions. Because of the limitation of the previous database, especially the lack of protein structure data, most of the existing computational methods rely heavily on the sequence data, with only a small portion of the methods utilizing the structural information. Recently, AlphaFold has revolutionized the entire protein and biology field. Foreseeably, the protein-RNA interaction prediction will also be promoted significantly in the upcoming years. In this work, we give a thorough review of this field, surveying both the binding site and binding preference prediction problems and covering the commonly used datasets, features and models. We also point out the potential challenges and opportunities in this field. This survey summarizes the development of the RNA-binding protein-RNA interaction field in the past and foresees its future development in the post-AlphaFold era.

Towards an Ideal In Cell Hybridization-Based Strategy to Discover Protein Interactomes of Selected RNA Molecules

RNA-binding proteins are crucial to the function of coding and non-coding RNAs. The disruption of RNA–protein interactions is involved in many different pathological states. Several computational and experimental strategies have been developed to identify protein binders of selected RNA molecules. Amongst these, ‘in cell’ hybridization methods represent the gold standard in the field because they are designed to reveal the proteins bound to specific RNAs in a cellular context. Here, we compare the technical features of different ‘in cell’ hybridization approaches with a focus on their advantages, limitations, and current and potential future applications.

Shaping the Innate Immune Response Through Post-Transcriptional Regulation of Gene Expression Mediated by RNA-Binding Proteins

Innate immunity is the frontline of defense against infections and tissue damage. It is a fast and semi-specific response involving a myriad of processes essential for protecting the organism. These reactions promote the clearance of danger by activating, among others, an inflammatory response, the complement cascade and by recruiting the adaptive immunity. Any disequilibrium in this functional balance can lead to either inflammation-mediated tissue damage or defense inefficiency. A dynamic and coordinated gene expression program lies at the heart of the innate immune response. This expression program varies depending on the cell-type and the specific danger signal encountered by the cell and involves multiple layers of regulation. While these are achieved mainly via transcriptional control of gene expression, numerous post-transcriptional regulatory pathways involving RNA-binding proteins (RBPs) and other effectors play a critical role in its fine-tuning. Alternative splicing, translational control and mRNA stability have been shown to be tightly regulated during the innate immune response and participate in modulating gene expression in a global or gene specific manner. More recently, microRNAs assisting RBPs and post-transcriptional modification of RNA bases are also emerging as essential players of the innate immune process. In this review, we highlight the numerous roles played by specific RNA-binding effectors in mediating post-transcriptional control of gene expression to shape innate immunity.

Identification of Protein-RNA Interactions in Mouse Testis Tissue Using fRIP

During development, cells must quickly switch from one cell state to the next to execute precise and timely differentiation. One method to ensure fast transitions in cell states is by controlling gene expression at the post-transcriptional level through action of RNA-binding proteins on mRNAs. The ability to accurately identify the RNA targets of RNA-binding proteins at specific stages is key to understanding the functional role of RNA-binding proteins during development. Here we describe an adapted formaldehyde RNA immunoprecipitation (fRIP) protocol to identify the in vivo RNA targets of a cytoplasmic RNA-binding protein, YTHDC2, from testis, during the first wave of spermatogenesis, at the stage when germ cells are shutting off the proliferative program and initiating terminal differentiation ( Bailey et al., 2017 ). This protocol enables quick and efficient identification of endogenous RNAs bound to an RNA-binding protein, and facilitates the monitoring of stage-specific changes during development.

Identifying Protein Interactomes of Target RNAs Using HyPR-MS

RNA-protein interactions are integral to maintaining proper cellular function and homeostasis, and the disruption of key RNA-protein interactions is central to many disease states. HyPR-MS (hybridization purification of RNA-protein complexes followed by mass spectrometry) is a highly versatile and efficient technology which enables multiplexed discovery of specific RNA-protein interactomes. This chapter provides extensive guidance for successful application of HyPR-MS to the system and target RNA(s) of interest, as well as a detailed description of the fundamental HyPR-MS procedure, including: (1) experimental design of controls, capture oligonucleotides, and qPCR assays; (2) formaldehyde cross-linking of cell culture; (3) cell lysis and RNA solubilization; (4) isolation of target RNA(s); (5) RNA purification and RT-qPCR analysis; (6) protein preparation and mass spectrometric analysis; and (7) mass spectrometric data analysis.

S-adenosylmethionine-dependent methyltransferase inhibitor DZNep blocks transcription and translation of SARS-CoV-2 genome with a low tendency to select for drug-resistant viral variants

We report the in vitro antiviral activity of DZNep (3-Deazaneplanocin A; an inhibitor of S-adenosylmethionine-dependent methyltransferase) against SARS-CoV-2, besides demonstrating its protective efficacy against lethal infection of infectious bronchitis virus (IBV, a member of the Coronaviridae family). DZNep treatment resulted in reduced synthesis of SARS-CoV-2 RNA and proteins without affecting other steps of viral life cycle. We demonstrated that deposition of N6-methyl adenosine (m6A) in SARS-CoV-2 RNA in the infected cells recruits heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1), an RNA binding protein which serves as a m6A reader. DZNep inhibited the recruitment of hnRNPA1 at m6A-modified SARS-CoV-2 RNA which eventually suppressed the synthesis of the viral genome. In addition, m6A-marked RNA and hnRNPA1 interaction was also shown to regulate early translation to replication switch of SARS-CoV-2 genome. Furthermore, abrogation of methylation by DZNep also resulted in defective synthesis of the 5’ cap of viral RNA, thereby resulting in its failure to interact with eIF4E (a cap-binding protein), eventually leading to a decreased synthesis of viral proteins. Most importantly, DZNep-resistant mutants could not be observed upon long-term sequential passage of SARS-CoV-2 in cell culture. In summary, we report the novel role of methylation in the life cycle of SARS-CoV-2 and propose that targeting the methylome using DZNep could be of significant therapeutic value against SARS-CoV-2 infection.

Roles of Emerging RNA-Binding Activity of cGAS in Innate Antiviral Response

cGAS, a DNA sensor in mammalian cells, catalyzes the generation of 2'-3'-cyclic AMP-GMP (cGAMP) once activated by the binding of free DNA. cGAMP can bind to STING, activating downstream TBK1-IRF-3 signaling to initiate the expression of type I interferons. Although cGAS has been considered a traditional DNA-binding protein, several lines of evidence suggest that cGAS is a potential RNA-binding protein (RBP), which is mainly supported by its interactions with RNAs, RBP partners, RNA/cGAS-phase-separations as well as its structural similarity with the dsRNA recognition receptor 2'-5' oligoadenylate synthase. Moreover, two influential studies reported that the cGAS-like receptors (cGLRs) of fly Drosophila melanogaster sense RNA and control 3'-2'-cGAMP signaling. In this review, we summarize and discuss in depth recent studies that identified or implied cGAS as an RBP. We also comprehensively summarized current experimental methods and computational tools that can identify or predict RNAs that bind to cGAS. Based on these discussions, we appeal that the RNA-binding activity of cGAS cannot be ignored in the cGAS-mediated innate antiviral response. It will be important to identify RNAs that can bind and regulate the activity of cGAS in cells with or without virus infection. Our review provides novel insight into the regulation of cGAS by its RNA-binding activity and extends beyond its DNA-binding activity. Our review would be significant for understanding the precise modulation of cGAS activity, providing the foundation for the future development of drugs against cGAS-triggering autoimmune diseases such as Aicardi-Gourtières syndrome.

sRNA23, a novel small RNA, regulates to the pathogenesis of Streptococcus suis serotype 2

ABBREVIATION

sRNA: small noncoding RNA; FBA: fructose diphosphate aldolase; rplB: 50S ribosomal protein L2; RACE: rapid amplification of cDNA ends; EMSA: electrophoretic mobility shift assay; THB: Todd-Hewitt broth; FBS: fetal bovine serum; BIP: 2,2'-Bipyridine.

Phospho-RNA sequencing with circAID-p-seq

Most RNA footprinting approaches that require ribonuclease cleavage generate RNA fragments bearing a phosphate or cyclic phosphate group at their 3′ end. Unfortunately, current library preparation protocols rely only on a 3′ hydroxyl group for adaptor ligation or poly-A tailing. Here, we developed circAID-p-seq, a PCR-free library preparation for selective 3′ phospho-RNA sequencing. As a proof of concept, we applied circAID-p-seq to ribosome profiling, which is based on sequencing of RNA fragments protected by ribosomes after endonuclease digestion. CircAID-p-seq, combined with the dedicated computational pipeline circAidMe, facilitates accurate, fast and highly efficient sequencing of phospho-RNA fragments from eukaryotic cells and tissues. We used circAID-p-seq to portray ribosome occupancy in transcripts, providing a versatile and PCR-free strategy to possibly unravel any endogenous 3′-phospho RNA molecules.

LPI-HyADBS: a hybrid framework for lncRNA-protein interaction prediction integrating feature selection and classification

Background

Long noncoding RNAs (lncRNAs) have dense linkages with a plethora of important cellular activities. lncRNAs exert functions by linking with corresponding RNA-binding proteins. Since experimental techniques to detect lncRNA-protein interactions (LPIs) are laborious and time-consuming, a few computational methods have been reported for LPI prediction. However, computation-based LPI identification methods have the following limitations: (1) Most methods were evaluated on a single dataset, and researchers may thus fail to measure their generalization ability. (2) The majority of methods were validated under cross validation on lncRNA-protein pairs, did not investigate the performance under other cross validations, especially for cross validation on independent lncRNAs and independent proteins. (3) lncRNAs and proteins have abundant biological information, how to select informative features need to further investigate.

Results

Under a hybrid framework (LPI-HyADBS) integrating feature selection based on AdaBoost, and classification models including deep neural network (DNN), extreme gradient Boost (XGBoost), and SVM with a penalty Coefficient of misclassification (C-SVM), this work focuses on finding new LPIs. First, five datasets are arranged. Each dataset contains lncRNA sequences, protein sequences, and an LPI network. Second, biological features of lncRNAs and proteins are acquired based on Pyfeat. Third, the obtained features of lncRNAs and proteins are selected based on AdaBoost and concatenated to depict each LPI sample. Fourth, DNN, XGBoost, and C-SVM are used to classify lncRNA-protein pairs based on the concatenated features. Finally, a hybrid framework is developed to integrate the classification results from the above three classifiers. LPI-HyADBS is compared to six classical LPI prediction approaches (LPI-SKF, LPI-NRLMF, Capsule-LPI, LPI-CNNCP, LPLNP, and LPBNI) on five datasets under 5-fold cross validations on lncRNAs, proteins, lncRNA-protein pairs, and independent lncRNAs and independent proteins. The results show LPI-HyADBS has the best LPI prediction performance under four different cross validations. In particular, LPI-HyADBS obtains better classification ability than other six approaches under the constructed independent dataset. Case analyses suggest that there is relevance between ZNF667-AS1 and Q15717.

Conclusions

Integrating feature selection approach based on AdaBoost, three classification techniques including DNN, XGBoost, and C-SVM, this work develops a hybrid framework to identify new linkages between lncRNAs and proteins.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04485-x.

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.

CBRPP: a new RNA-centric method to study RNA-protein interactions

RNA and protein are interconnected biomolecules that can influence each other's life cycles and functions through physical interactions. Abnormal RNA-protein interactions lead to cell dysfunctions and human diseases. Therefore, mapping networks of RNA-protein interactions is crucial for understanding cellular processes and pathogenesis of related diseases. Different practical protein-centric methods for studying RNA-protein interactions have been reported, but few robust RNA-centric methods exist. Here, we developed CRISPR-based RNA proximity proteomics (CBRPP), a new RNA-centric method to identify proteins associated with an endogenous RNA of interest in native cellular context without pre-editing of the target RNA, cross-linking or RNA-protein complexes manipulation in vitro. CBRPP is based on a fusion of dCas13 and proximity-based labelling (PBL) enzyme. dCas13 can deliver PBL enzyme to the target RNA with high specificity, while PBL enzyme labels the surrounding proteins of the target RNA, which are then identified by mass spectrometry.

RNA Binding Proteins as Pioneer Determinants of Infection: Protective, Proviral, or Both?

As the first intracellular host factors that directly interact with the genomes of RNA viruses, RNA binding proteins (RBPs) have a profound impact on the outcome of an infection. Recent discoveries brought about by new methodologies have led to an unprecedented ability to peer into the earliest events between viral RNA and the RBPs that act upon them. These discoveries have sparked a re-evaluation of current paradigms surrounding RBPs and post-transcriptional gene regulation. Here, we highlight questions that have bloomed from the implementation of these novel approaches. Canonical RBPs can impact the fates of both cellular and viral RNA during infection, sometimes in conflicting ways. Noncanonical RBPs, some of which were first characterized via interactions with viral RNA, may encompass physiological roles beyond viral pathogenesis. We discuss how these RBPs might discriminate between an RNA of either cellular or viral origin and thus exert either pro- or antiviral effects—which is a particular challenge as viruses contain mechanisms to mimic molecular features of cellular RNA.

Evolving Landscape of Long Non-coding RNAs in Cerebrospinal Fluid: A Key Role From Diagnosis to Therapy in Brain Tumors

Long non-coding RNAs (lncRNAs) are a type of non-coding RNAs that act as molecular fingerprints and modulators of many pathophysiological processes, particularly in cancer. Specifically, lncRNAs can be involved in the pathogenesis and progression of brain tumors, affecting stemness/differentiation, replication, invasion, survival, DNA damage response, and chromatin dynamics. Furthermore, the aberrations in the expressions of these transcripts can promote treatment resistance, leading to tumor recurrence. The development of next-generation sequencing technologies and the creation of lncRNA-specific microarrays have boosted the study of lncRNA etiology. Cerebrospinal fluid (CSF) directly mirrors the biological fluid of biochemical processes in the brain. It can be enriched for small molecules, peptides, or proteins released by the neurons of the central nervous system (CNS) or immune cells. Therefore, strategies that identify and target CSF lncRNAs may be attractive as early diagnostic and therapeutic options. In this review, we have reviewed the studies on CSF lncRNAs in the context of brain tumor pathogenesis and progression and discuss their potential as biomarkers and therapeutic targets.

Interactions between long non‑coding RNAs and RNA‑binding proteins in cancer (Review)

Long non-coding RNAs (lncRNAs) fulfill important roles in the majority of cellular processes. Previous studies have demonstrated that lncRNAs are involved in the pathogenesis of various diseases, including cancer. However, to date, the functions of only a small number of the known lncRNAs have been well-documented. lncRNAs comprise a class of multifunctional non-coding transcripts that are able to interact with different types of biomolecules. Interactions between lncRNAs and RNA-binding proteins (RBPs) provide an important mechanism through which lncRNAs exert their regulatory functions, mainly through findings on ‘generalized RBPs’. Regulatory effects on lncRNAs mediated by RBPs have also been explored. Taking account of the research that has been completed to date, the continued and in-depth study of the bidirectional interactions between lncRNAs and RBPs will prove to be of major importance for understanding the pathogenesis of cancer and for developing effective therapies. The present review aims to explore the interactions between lncRNAs and RBPs that have been investigated in cancer, taking into consideration several different aspects, including the regulation of expression, subcellular localization and the mediation of diverse functions.

Glioblastoma Cell-Derived lncRNA-Containing Exosomes Induce Microglia to Produce Complement C5, Promoting Chemotherapy Resistance

Glioblastoma (GBM), the most common malignant primary brain cancer in adults, nearly always becomes resistant to current treatments, including the chemotherapeutic temozolomide (TMZ). The long noncoding RNA (lncRNA) TMZ-associated lncRNA in GBM recurrence (lnc-TALC) promotes GBM resistance to TMZ. Exosomes can release biochemical cargo into the tumor microenvironment (TME) or transfer their contents, including lncRNAs, to other cells as a form of intercellular communication. In this study, we found that lnc-TALC could be incorporated into exosomes and transmitted to tumor-associated macrophages (TAM) and could promote M2 polarization of the microglia. This M2 polarization correlated with secretion of the complement components C5/C5a, which occurred downstream of lnc-TALC binding to ENO1 to promote the phosphorylation of p38 MAPK. In addition, C5 promoted the repair of TMZ-induced DNA damage, leading to chemotherapy resistance, and C5a-targeted immunotherapy showed improved efficacy that limited lnc-TALC-mediated TMZ resistance. Our results reveal that exosome-transmitted lnc-TALC could remodel the GBM microenvironment and reduce tumor sensitivity to TMZ chemotherapy, indicating that the lnc-TALC-mediated cross-talk between GBM cells and microglia could attenuate chemotherapy efficacy and pointing to potential combination therapy strategies to overcome TMZ resistance in GBM.See related Spotlight by Zhao and Xie, p. 1372.

Mass Spectrometry of Nucleic Acid Noncovalent Complexes

Nucleic acids have been among the first targets for antitumor drugs and antibiotics. With the unveiling of new biological roles in regulation of gene expression, specific DNA and RNA structures have become very attractive targets, especially when the corresponding proteins are undruggable. Biophysical assays to assess target structure as well as ligand binding stoichiometry, affinity, specificity, and binding modes are part of the drug development process. Mass spectrometry offers unique advantages as a biophysical method owing to its ability to distinguish each stoichiometry present in a mixture. In addition, advanced mass spectrometry approaches (reactive probing, fragmentation techniques, ion mobility spectrometry, ion spectroscopy) provide more detailed information on the complexes. Here, we review the fundamentals of mass spectrometry and all its particularities when studying noncovalent nucleic acid structures, and then review what has been learned thanks to mass spectrometry on nucleic acid structures, self-assemblies (e.g., duplexes or G-quadruplexes), and their complexes with ligands.

Systematic Analysis of the Impact of R-Methylation on RBPs-RNA Interactions: A Proteomic Approach

RNA binding proteins (RBPs) bind RNAs through specific RNA-binding domains, generating multi-molecular complexes known as ribonucleoproteins (RNPs). Various post-translational modifications (PTMs) have been described to regulate RBP structure, subcellular localization, and interactions with other proteins or RNAs. Recent proteome-wide experiments showed that RBPs are the most representative group within the class of arginine (R)-methylated proteins. Moreover, emerging evidence suggests that this modification plays a role in the regulation of RBP-RNA interactions. Nevertheless, a systematic analysis of how changes in protein-R-methylation can affect globally RBPs-RNA interactions is still missing. We describe here a quantitative proteomics approach to profile global changes of RBP-RNA interactions upon the modulation of type I and II protein arginine methyltransferases (PRMTs). By coupling the recently described Orthogonal Organic Phase Separation (OOPS) strategy with the Stable Isotope Labelling with Amino acids in Cell culture (SILAC) and pharmacological modulation of PRMTs, we profiled RNA-protein interaction dynamics in dependence of protein-R-methylation. Data are available via ProteomeXchange with identifier PXD024601.

Long Non-Coding RNA Regulation of Epigenetics in Vascular Cells

The vascular endothelium comprises the interface between the circulation and the vessel wall and, as such, is under the dynamic regulation of vascular signalling, nutrients, and hypoxia. Understanding the molecular drivers behind endothelial cell (EC) and vascular smooth muscle cell (VSMC) function and dysfunction remains a pivotal task for further clinical progress in tackling vascular disease. A newly emerging era in vascular biology with landmark deep sequencing approaches has provided us with the means to profile diverse layers of transcriptional regulation at a single cell, chromatin, and epigenetic level. This review describes the roles of major vascular long non-coding RNA (lncRNAs) in the epigenetic regulation of EC and VSMC function and discusses the recent progress in their discovery, detection, and functional characterisation. We summarise new findings regarding lncRNA-mediated epigenetic mechanisms—often regulated by hypoxia—within the vascular endothelium and smooth muscle to control vascular homeostasis in health and disease. Furthermore, we outline novel molecular techniques being used in the field to delineate the lncRNA subcellular localisation and interaction with proteins to unravel their biological roles in the epigenetic regulation of vascular genes.

Identification of Key Functional Modules and Immunomodulatory Regulators of Hepatocellular Carcinoma

Despite the advances in the treatment of hepatocellular carcinoma (HCC), the prognosis of HCC patients remains unsatisfactory due to postsurgical recurrence and treatment resistance. Therefore, it is important to reveal the mechanisms underlying HCC and identify potential therapeutic targets against HCC, which could facilitate the development of novel therapies. Based on 12 HCC samples and 12 paired paracancerous normal tissues, we identified differentially expressed mRNAs and lncRNAs using the "limma" package in R software. Moreover, we used the weighted gene coexpression network analysis (WGCNA) to analyze the expression data and screened hub genes. Furthermore, we performed pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. In addition, the relative abundance of a given gene set was estimated by single-sample Gene Set Enrichment Analysis. We identified 687 differentially expressed mRNAs and 260 differentially expressed lncRNAs. A total of 6 modules were revealed by WGCNA, and MT1M and MT1E genes from the red module were identified as hub genes. Moreover, pathway analysis revealed the top 10 enriched KEGG pathways of upregulated or downregulated genes. Additionally, we also found that CD58 might act as an immune checkpoint gene in HCC via PD1/CTLA4 pathways and regulate the levels of tumor-infiltrating immune cells in HCC tissues, which might be an immunotherapeutic target in HCC. Our research identified key functional modules and immunomodulatory regulators for HCC, which might offer novel diagnostic biomarkers and/or therapeutic targets for cancer immunotherapy.

Biomolecule and Bioentity Interaction Databases in Systems Biology: A Comprehensive Review

Technological advances in high-throughput techniques have resulted in tremendous growth of complex biological datasets providing evidence regarding various biomolecular interactions. To cope with this data flood, computational approaches, web services, and databases have been implemented to deal with issues such as data integration, visualization, exploration, organization, scalability, and complexity. Nevertheless, as the number of such sets increases, it is becoming more and more difficult for an end user to know what the scope and focus of each repository is and how redundant the information between them is. Several repositories have a more general scope, while others focus on specialized aspects, such as specific organisms or biological systems. Unfortunately, many of these databases are self-contained or poorly documented and maintained. For a clearer view, in this article we provide a comprehensive categorization, comparison and evaluation of such repositories for different bioentity interaction types. We discuss most of the publicly available services based on their content, sources of information, data representation methods, user-friendliness, scope and interconnectivity, and we comment on their strengths and weaknesses. We aim for this review to reach a broad readership varying from biomedical beginners to experts and serve as a reference article in the field of Network Biology.

The Immune Heterogeneity Between Pulmonary Adenocarcinoma and Squamous Cell Carcinoma: A Comprehensive Analysis Based on lncRNA Model

Adenocarcinoma (AD) and squamous cell carcinoma (SCC) are both classified as major forms of non-small cell lung cancer, but differences in clinical prognoses and molecular mechanisms are remarkable. Recent studies have supported the importance of understanding immune status in that it influences clinical outcomes of cancer, and immunotherapies based on the theory of “immune editing” have had notable clinical success. Our study aimed to identify specific long non-coding (lnc) RNAs that control key immune-related genes and to use them to construct risk models for AD and SCC. Risk scores were used to separate patients into high- and low-risk groups, and we validated the prognostic significance of both risk scores with our own cohorts. A Gene Set Enrichment Analysis suggested that the immune responses of patients in the AD high-risk group and the SCC low-risk group tended to be weakened. Evaluation of immune infiltration revealed that the degree of infiltration of dendritic cells is of particular importance in AD. In addition, prediction of responses to immune checkpoint inhibitor (ICI) treatments, based on the T Cell Immune Dysfunction and Exclusion and immunophenoscore models, indicated that deterioration of the immune microenvironment is due mainly to T cell exclusion in AD patients and T cell dysfunction in SCC patients and that high-risk patients with SCC might benefit from ICI treatment. The prediction of downstream targets via The Cancer Proteome Atlas and RNA-seq analyses of a transfected lung cancer cell line indicated that the lncRNA LINC00996 is a potential therapeutic target in AD.

NANOS2 is a sequence-specific mRNA-binding protein that promotes transcript degradation in spermatogonial stem cells

Spermatogonial stem cells (SSCs) sustain spermatogenesis and fertility throughout adult male life. The conserved RNA-binding protein NANOS2 is essential for the maintenance of SSCs, but its targets and mechanisms of function are not fully understood. Here, we generated a fully functional epitope-tagged Nanos2 mouse allele and applied the highly stringent cross-linking and analysis of cDNAs to define NANOS2 RNA occupancy in SSC lines. NANOS2 recognizes the AUKAAWU consensus motif, mostly found in the 3' untranslated region of defined messenger RNAs (mRNAs). We find that NANOS2 is a regulator of key signaling and metabolic pathways whose dosage or activity are known to be critical for SSC maintenance. NANOS2 interacts with components of CCR4-NOT deadenylase complex in SSC lines, and consequently, NANOS2 binding reduces the half-lives of target transcripts. In summary, NANOS2 contributes to SSC maintenance through the regulation of target mRNA stability and key self-renewal pathways.

An RNA tagging approach for system-wide RNA-binding proteome profiling and dynamics investigation upon transcription inhibition

RNA-protein interactions play key roles in epigenetic, transcriptional and posttranscriptional regulation. To reveal the regulatory mechanisms of these interactions, global investigation of RNA-binding proteins (RBPs) and monitor their changes under various physiological conditions are needed. Herein, we developed a psoralen probe (PP)-based method for RNA tagging and ribonucleic-protein complex (RNP) enrichment. Isolation of both coding and noncoding RNAs and mapping of 2986 RBPs including 782 unknown candidate RBPs from HeLa cells was achieved by PP enrichment, RNA-sequencing and mass spectrometry analysis. The dynamics study of RNPs by PP enrichment after the inhibition of RNA synthesis provides the first large-scale distribution profile of RBPs bound to RNAs with different decay rates. Furthermore, the remarkably greater decreases in the abundance of the RBPs obtained by PP-enrichment than by global proteome profiling suggest that PP enrichment after transcription inhibition offers a valuable way for large-scale evaluation of the candidate RBPs.

Long noncoding RNA IL6-AS1 is highly expressed in chronic obstructive pulmonary disease and is associated with interleukin 6 by targeting miR-149-5p and early B-cell factor 1

Chronic obstructive pulmonary disease is a complex condition with multiple etiologies, including inflammation. We identified a novel long noncoding RNA (lncRNA), interleukin 6 antisense RNA 1 (IL6-AS1), which is upregulated in this disease and is associated with airway inflammation. We found that IL6-AS1 promotes the expression of inflammatory factors, especially interleukin (IL) 6. Mechanistically, cytoplasmic IL6-AS1 acts as an endogenous sponge by competitively binding to the microRNA miR-149-5p to stabilize IL-6 mRNA. Nuclear IL6-AS1 promotes IL-6 transcription by recruiting early B-cell factor 1 to the IL-6 promoter, which increases the methylation of the H3K4 histone and acetylation of the H3K27 histone. We propose a model of lncRNA expression in both the nucleus and cytoplasm that exerts similar effects through differing mechanisms, and IL6-AS1 probably increases inflammation via multiple pathways.

The SARS-CoV-2 RNA interactome

SARS-CoV-2 is an RNA virus whose success as a pathogen relies on its abilities to repurpose host RNA-binding proteins (RBPs) and to evade antiviral RBPs. To uncover the SARS-CoV-2 RNA interactome, we here develop a robust ribonucleoprotein (RNP) capture protocol and identify 109 host factors that directly bind to SARS-CoV-2 RNAs. Applying RNP capture on another coronavirus, HCoV-OC43, revealed evolutionarily conserved interactions between coronaviral RNAs and host proteins. Transcriptome analyses and knockdown experiments delineated 17 antiviral RBPs, including ZC3HAV1, TRIM25, PARP12, and SHFL, and 8 proviral RBPs, such as EIF3D and CSDE1, which are responsible for co-opting multiple steps of the mRNA life cycle. This also led to the identification of LARP1, a downstream target of the mTOR signaling pathway, as an antiviral host factor that interacts with the SARS-CoV-2 RNAs. Overall, this study provides a comprehensive list of RBPs regulating coronaviral replication and opens new avenues for therapeutic interventions.

Dissecting the plant chromatin interactome using mass spectrometry

The protein interactome mediates crucial functions in transcription, chromatin remodeling, and higher-order structural organization. Elucidating the proteins that interact with chromatin-associated RNA or proteins is key to understanding fundamental epigenetic regulatory pathways. We discuss the opportunities and challenges of mass spectrometry (MS)-based proteomics for characterizing the plant chromatin interactome.

A Survey of Current Resources to Study lncRNA-Protein Interactions

Phenotypes are driven by regulated gene expression, which in turn are mediated by complex interactions between diverse biological molecules. Protein-DNA interactions such as histone and transcription factor binding are well studied, along with RNA-RNA interactions in short RNA silencing of genes. In contrast, lncRNA-protein interaction (LPI) mechanisms are comparatively unknown, likely directed by the difficulties in studying LPI. However, LPI are emerging as key interactions in epigenetic mechanisms, playing a role in development and disease. Their importance is further highlighted by their conservation across kingdoms. Hence, interest in LPI research is increasing. We therefore review the current state of the art in lncRNA-protein interactions. We specifically surveyed recent computational methods and databases which researchers can exploit for LPI investigation. We discovered that algorithm development is heavily reliant on a few generic databases containing curated LPI information. Additionally, these databases house information at gene-level as opposed to transcript-level annotations. We show that early methods predict LPI using molecular docking, have limited scope and are slow, creating a data processing bottleneck. Recently, machine learning has become the strategy of choice in LPI prediction, likely due to the rapid growth in machine learning infrastructure and expertise. While many of these methods have notable limitations, machine learning is expected to be the basis of modern LPI prediction algorithms.

Computational methods for predicting hotspots at protein-RNA interfaces

Protein-RNA interactions play essential roles in many critical biological events. A comprehensive understanding of the mechanisms underlying these interactions is helpful when studying cellular activities and therapeutic applications. Hotspots are a small portion of residues contributing much toward protein-RNA binding affinity. In pharmaceutical research, the hotspot residues are seen as the best option for designing small molecules to target proteins of therapeutic interest. With the accumulation of experimental data about protein-RNA interactions, computational methods have been produced for hotspot prediction on a large scale. In this review, we first present an overview of the existing databases for protein-RNA binding data. Furthermore, we outline the most adopted computational methods for hotspots prediction in protein-RNA interactions. Finally, we discuss the applications of hotspot prediction. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA Methods > RNA Analyses In Vitro and In Silico.

SNHG3 cooperates with ELAVL2 to modulate cell apoptosis and extracellular matrix accumulation by stabilizing SNAI2 in human trabecular meshwork cells under oxidative stress

Glaucoma is the main reason for irreversible blindness, and pathological increased intraocular pressure is the leading risk factor for glaucoma. It is reported that trabecular meshwork cell injury is closely associated with the elevated intraocular pressure. The current study aimed to investigate the role of small nucleolar RNA host gene 3 (SNHG3) in human trabecular meshwork (HTM) cells under oxidative stress. A series of experiments including real-time quantitative polymerase chain reaction, subcellular fractionation assay, western blot analysis, cell counting kit-8 assay, RNA pull down, flow cytometry analysis, and RNA immunoprecipitation assay were used to explore the biological function and regulatory mechanism of SNHG3 in HTM cells under oxidative stress. First, we observed that H₂ O₂ induced SNHG3 upregulation in HTM cells. Then, we found that SNHG3 silencing alleviated H₂ O₂ -induced oxidative damage in HTM cells. Moreover, snail family transcriptional repressor 2 (SNAI2) knockdown alleviated the oxidative damage induced by H₂ O₂ in HTM cells. Mechanistically, SNHG3 bound with ELAV like RNA binding protein 2 (ELAVL2) to stabilize SNAI2. Finally, SNAI2 overexpression counteracted the effect of SNHG3 silencing on H₂ O₂ -treated HTM cells. In conclusion, our results demonstrated that SNHG3 cooperated with ELAVL2 to modulate cell apoptosis and extracellular matrix accumulation by stabilizing SNAI2 in HTM cells under oxidative stress.

Decoding LncRNAs

Non-coding RNAs (ncRNAs) have been considered as unimportant additions to the transcriptome. Yet, in light of numerous studies, it has become clear that ncRNAs play important roles in development, health and disease. Long-ignored, long non-coding RNAs (lncRNAs), ncRNAs made of more than 200 nucleotides have gained attention due to their involvement as drivers or suppressors of a myriad of tumours. The detailed understanding of some of their functions, structures and interactomes has been the result of interdisciplinary efforts, as in many cases, new methods need to be created or adapted to characterise these molecules. Unlike most reviews on lncRNAs, we summarize the achievements on lncRNA studies by taking into consideration the approaches for identification of lncRNA functions, interactomes, and structural arrangements. We also provide information about the recent data on the involvement of lncRNAs in diseases and present applications of these molecules, especially in medicine.

Rapidly Growing Protein-Centric Technologies to Extensively Identify Protein-RNA Interactions: Application to the Analysis of Co-Transcriptional RNA Processing

During mRNA transcription, diverse RNA-binding proteins (RBPs) are recruited to RNA polymerase II (RNAP II) transcription machinery. These RBPs bind to distinct sites of nascent RNA to co-transcriptionally operate mRNA processing. Recent studies have revealed a close relationship between transcription and co-transcriptional RNA processing, where one affects the other’s activity, indicating an essential role of protein–RNA interactions for the fine-tuning of mRNA production. Owing to their limited amount in cells, the detection of protein–RNA interactions specifically assembled on the transcribing RNAP II machinery still remains challenging. Currently, cross-linking and immunoprecipitation (CLIP) has become a standard method to detect in vivo protein–RNA interactions, although it requires a large amount of input materials. Several improved methods, such as infrared-CLIP (irCLIP), enhanced CLIP (eCLIP), and target RNA immunoprecipitation (tRIP), have shown remarkable enhancements in the detection efficiency. Furthermore, the utilization of an RNA editing mechanism or proximity labeling strategy has achieved the detection of faint protein–RNA interactions in cells without depending on crosslinking. This review aims to explore various methods being developed to detect endogenous protein–RNA interaction sites and discusses how they may be applied to the analysis of co-transcriptional RNA processing.

New insights into the functional role of retrotransposon dynamics in mammalian somatic cells

Retrotransposons are genetic elements present across all eukaryotic genomes. While their role in evolution is considered as a potentially beneficial natural source of genetic variation, their activity is classically considered detrimental due to their potentially harmful effects on genome stability. However, studies are increasingly shedding light on the regulatory function and beneficial role of somatic retroelement reactivation in non-pathological contexts. Here, we review recent findings unveiling the regulatory potential of retrotransposons, including their role in noncoding RNA transcription, as modulators of mammalian transcriptional and epigenome landscapes. We also discuss technical challenges in deciphering the multifaceted activity of retrotransposable elements, highlighting an unforeseen central role of this neglected portion of the genome both in early development and in adult life.

Opportunities and Challenges in Global Quantification of RNA-Protein Interaction via UV Cross-Linking

RNA-binding proteins (RBPs) are key mediators of posttranscriptional gene expression control. However, the links between cell signaling on the one hand and RBP function on the other are understudied. While thousands of posttranslational modification (PTM) sites on RBPs have been identified, their functional roles are only poorly characterized. RNA-interactome capture (RIC) and cross-linking and immunoprecipitation (CLIP) are attractive methods that provide information about RBP-RNA interactions on a genome-wide scale. Both approaches rely on the in situ UV cross-linking of RBPs and RNAs, biochemical enrichment and analysis by RNA-sequencing (CLIP) or mass spectrometry (RIC). In principle, RIC- and CLIP-like methods could be used to globally quantify RBP-RNA interactions in response to perturbations. However, several biases have to be taken into account to avoid misinterpretation of the results obtained. Here, we focus on RIC-like methods and discuss four key aspects relevant for quantitative interpretation: (1) the RNA isolation efficiency, (2) the inefficient and highly variable UV cross-linking, (3) the baseline RNA occupancy of RBPs, and (4) indirect factors affecting RBP-RNA interaction. We highlight these points by presenting selected examples of PTMs that might induce differential quantification in RIC-like experiments without necessarily affecting RNA-binding. We conclude that quantifying RBP-RNA interactions via RIC or CLIP-like methods should not be regarded as an end in itself but rather as starting points for deeper analysis.

Mutations in cis that affect mRNA synthesis, processing and translation

Genetic mutations that cause hereditary diseases usually affect the composition of the transcribed mRNA and its encoded protein, leading to instability of the mRNA and/or the protein. Sometimes, however, such mutations affect the synthesis, the processing or the translation of the mRNA, with similar disastrous effects. We here present an overview of mRNA synthesis, its posttranscriptional modification and its translation into protein. We then indicate which elements in these processes are known to be affected by pathogenic mutations, but we restrict our review to mutations in cis, in the DNA of the gene that encodes the affected protein. These mutations can be in enhancer or promoter regions of the gene, which act as binding sites for transcription factors involved in pre-mRNA synthesis. We also describe mutations in polyadenylation sequences and in splice site regions, exonic and intronic, involved in intron removal. Finally, we include mutations in the Kozak sequence in mRNA, which is involved in protein synthesis. We provide examples of genetic diseases caused by mutations in these DNA regions and refer to databases to help identify these regions. The over-all knowledge of mRNA synthesis, processing and translation is essential for improvement of the diagnosis of patients with genetic diseases.

Characterization of RNA-binding proteins in the cell nucleus and cytoplasm

As critical players in the regulation of gene expression, RNA-binding proteins (RBPs) play fundamental roles in cellular functions and diseases. In this study, we established an analytical strategy to characterize RBPs from different subcellular regions by combining subcellular fractionation, acidic guanidinium-thiocyanate-phenol-chloroform biphasic extraction, and quantitative mass spectrometry. Using this method, we identified 1775 and 2245 RBPs from the cell nucleus and cytoplasm. The data confirmed a large spectrum of known RBPs, revealed 614 novel ones that have never been reported before, and cataloged their subcellular localizations. Intriguingly, 200 metabolic enzymes from diverse metabolic pathways were observed as RBPs, some of which were further validated through western blotting following UV-mediated crosslinking and biphasic extraction. Furthermore, we characterized 2157 RNA-binding interfaces, providing structural information regarding the complex nature of RNA-protein interactions. Taken together, our data greatly expand the current reservoir of known RBPs and highlight the potential role of RNA-binding in the regulation of cellular metabolism.

ELAVL1 primarily couples mRNA stability with the 3' UTRs of interferon-stimulated genes

Upon pathogen detection, the innate immune system triggers signaling events leading to upregulation of pro-inflammatory and anti-microbial mRNA transcripts. RNA-binding proteins (RBPs) interact with these critical mRNAs and regulate their fates at the post-transcriptional level. One such RBP is ELAVL1. Although significant progress has been made in understanding how embryonic lethal vision-like protein 1 (ELAVL1) regulates mRNAs, its target repertoire and binding distribution within an immunological context remain poorly understood. We overlap four high-throughput approaches to define its context-dependent targets and determine its regulatory impact during immune activation. ELAVL1 transitions from binding overwhelmingly intronic sites to 3′ UTR sites upon immune stimulation of cells, binding previously and newly expressed mRNAs. We find that ELAVL1 mediates the RNA stability of genes that regulate pathways essential to pathogen sensing and cytokine production. Our findings reveal the importance of examining RBP regulatory impact under dynamic transcriptomic events to understand their post-transcriptional regulatory roles within specific biological circuitries.

Rothamel et al. show that upon immune activation, the RNA-binding protein ELAVL1 accumulates in the cytoplasm and redistributes from introns to mRNA 3′ UTRs. 3′ UTR binding confers enrichment and transcript stability. Many top-ranking transcripts are interferon-stimulated genes (ISGs), indicating that ELAVL1 is a positive regulator of an innate immune response.

Identification of host factors binding to dengue and Zika virus subgenomic RNA by efficient yeast three-hybrid screens of the human ORFeome

Flaviviruses such as the dengue (DENV) and the Zika virus (ZIKV) are important human pathogens causing around 100 million symptomatic infections each year. During infection, small subgenomic flavivirus RNAs (sfRNAs) are formed inside the infected host cell as a result of incomplete degradation of the viral RNA genome by cellular exoribonuclease XRN1. Although the full extent of sfRNA functions is to be revealed, these non-coding RNAs are key virulence factors and their detrimental effects on multiple cellular processes seem to consistently involve molecular interactions with RNA-binding proteins (RBPs). Discovery of such sfRNA-binding host-factors has followed established biochemical pull-down approaches skewed towards highly abundant proteins hampering proteome-wide coverage. Yeast three-hybrid (Y3H) systems represent an attractive alternative approach. To facilitate proteome-wide screens for RBP, we revisited and improved existing RNA-Y3H methodology by (1) implementing full-length ORF libraries in combination with (2) efficient yeast mating to increase screening depth and sensitivity, and (3) stringent negative controls to eliminate over-representation of non-specific RNA-binders. These improvements were validated employing the well-characterized interaction between DDX6 (DEAD-box helicase 6) and sfRNA of DENV as paradigm. Our advanced Y3H system was used to screen for human proteins binding to DENV and ZIKV sfRNA, resulting in a list of 69 putative sfRNA-binders, including several previously reported as well as numerous novel RBP host factors. Our methodology requiring no sophisticated infrastructure or analytic pipeline may be employed for the discovery of meaningful RNA-protein interactions at large scale in other fields.

Robust single-cell discovery of RNA targets of RNA-binding proteins and ribosomes

RNA-binding proteins (RBPs) are critical regulators of gene expression and RNA processing that are required for gene function. Yet the dynamics of RBP regulation in single cells is unknown. To address this gap in understanding, we developed STAMP (Surveying Targets by APOBEC-Mediated Profiling), which efficiently detects RBP-RNA interactions. STAMP does not rely on ultraviolet cross-linking or immunoprecipitation and, when coupled with single-cell capture, can identify RBP-specific and cell-type-specific RNA-protein interactions for multiple RBPs and cell types in single, pooled experiments. Pairing STAMP with long-read sequencing yields RBP target sites in an isoform-specific manner. Finally, Ribo-STAMP leverages small ribosomal subunits to measure transcriptome-wide ribosome association in single cells. STAMP enables the study of RBP-RNA interactomes and translational landscapes with unprecedented cellular resolution.

Methods to study circRNA-protein interactions

Circular RNAs (circRNAs) have been studied extensively in the last few years, uncovering functional roles in a diverse range of cell types and organisms. As shown for a few cases, these functions may be mediated by trans-acting factors, in particular RNA-binding proteins (RBPs). However, the specific interaction partners for most circRNAs remain unknown. This is mainly due to technical difficulties in their identification and in differentiating between interactors of circRNAs and their linear counterparts. Here we review the currently used methodology to systematically study circRNA-protein complexes (circRNPs), focusing either on a specific RNA or protein, both on the gene-specific or global level, and discuss advantages and challenges of the available approaches.

A KRAS-responsive long non-coding RNA controls microRNA processing

Wild-type KRAS (KRASWT) amplification has been shown to be a secondary means of KRAS activation in cancer and associated with poor survival. Nevertheless, the precise role of KRASWT overexpression in lung cancer progression is largely unexplored. Here, we identify and characterize a KRAS-responsive lncRNA, KIMAT1 (ENSG00000228709) and show that it correlates with KRAS levels both in cell lines and in lung cancer specimens. Mechanistically, KIMAT1 is a MYC target and drives lung tumorigenesis by promoting the processing of oncogenic microRNAs (miRNAs) through DHX9 and NPM1 stabilization while halting the biogenesis of miRNAs with tumor suppressor function via MYC-dependent silencing of p21, a component of the Microprocessor Complex. KIMAT1 knockdown suppresses not only KRAS expression but also KRAS downstream signaling, thereby arresting lung cancer growth in vitro and in vivo. Taken together, this study uncovers a role for KIMAT1 in maintaining a positive feedback loop that sustains KRAS signaling during lung cancer progression and provides a proof of principle that interfering with KIMAT1 could be a strategy to hamper KRAS-induced tumorigenesis.

Glycolysis reprogramming in cancer-associated fibroblasts promotes the growth of oral cancer through the lncRNA H19/miR-675-5p/PFKFB3 signaling pathway

As an important component of the tumor microenvironment, cancer-associated fibroblasts (CAFs) secrete energy metabolites to supply energy for tumor progression. Abnormal regulation of long noncoding RNAs (lncRNAs) is thought to contribute to glucose metabolism, but the role of lncRNAs in glycolysis in oral CAFs has not been systematically examined. In the present study, by using RNA sequencing and bioinformatics analysis, we analyzed the lncRNA/mRNA profiles of normal fibroblasts (NFs) derived from normal tissues and CAFs derived from patients with oral squamous cell carcinoma (OSCC). LncRNA H19 was identified as a key lncRNA in oral CAFs and was synchronously upregulated in both oral cancer cell lines and CAFs. Using small interfering RNA (siRNA) strategies, we determined that lncRNA H19 knockdown affected proliferation, migration, and glycolysis in oral CAFs. We found that knockdown of lncRNA H19 by siRNA suppressed the MAPK signaling pathway, 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) and miR-675-5p. Furthermore, the lncRNA H19/miR-675-5p/PFKFB3 axis was involved in promoting the glycolysis pathway in oral CAFs, as demonstrated by a luciferase reporter system assay and treatment with a miRNA-specific inhibitor. Our study presents a new way to understand glucose metabolism in oral CAFs, theoretically providing a novel biomarker for OSCC molecular diagnosis and a new target for antitumor therapy.