rG4detector, a novel RNA G-quadruplex predictor, uncovers their impact on stress granule formation

RNA G-quadruplexes and stress: emerging mechanisms and functions

RNA G-quadruplexes (rG4s) are noncanonical secondary structures formed by guanine-rich sequences that are found in different regions of RNA molecules. These structures have been implicated in diverse biological processes, including translation, splicing, and RNA stability. Recent studies have suggested that rG4s play a role in the cellular response to stress. This review summarizes the current knowledge on rG4s under stress, focusing on their formation, regulation, and potential functions in stress response pathways. We discuss the molecular mechanisms that regulate the formation of rG4 under different stress conditions and the impact of these structures on RNA metabolism, gene expression, and cell survival. Finally, we highlight the potential therapeutic implications of targeting rG4s for the treatment of stress-related diseases through modulating cell survival.

The shaping of mRNA translation plasticity by RNA G-quadruplexes in cancer progression and therapy resistance

Translational reprogramming in response to oncogenic signaling or microenvironmental stress factors shapes the proteome of cancer cells, enabling adaptation and phenotypic changes underlying cell plasticity, tumor progression and response to cancer therapy. Among the mechanisms regulating translation are RNA G-quadruplexes (RG4s), non-canonical four-stranded structures whose conformational modulation by small molecule ligands and RNA-binding proteins affects the expression of cancer proteins. Here, we discuss the role of RG4s in the regulation of mRNA translation by focusing on paradigmatic examples showing their contribution to adaptive mechanisms of mRNA translation in cancer.

Stress granule and P-body clearance: Seeking coherence in acts of disappearance

Stress granules and P-bodies are conserved cytoplasmic biomolecular condensates whose assembly and composition are well documented, but whose clearance mechanisms remain controversial or poorly described. Such understanding could provide new insight into how cells regulate biomolecular condensate formation and function, and identify therapeutic strategies in disease states where aberrant persistence of stress granules in particular is implicated. Here, I review and compare the contributions of chaperones, the cytoskeleton, post-translational modifications, RNA helicases, granulophagy and the proteasome to stress granule and P-body clearance. Additionally, I highlight the potentially vital role of RNA regulation, cellular energy, and changes in the interaction networks of stress granules and P-bodies as means of eliciting clearance. Finally, I discuss evidence for interplay of distinct clearance mechanisms, suggest future experimental directions, and suggest a simple working model of stress granule clearance.

RNA G-quadruplex in functional regulation of noncoding RNA: Challenges and emerging opportunities

G-quadruplexes (G4s) are stable, noncanonical structures formed in guanine (G)-rich sequences of DNA/RNA. G4 structures are reported to play a regulatory role in various cellular processes and, recently, a considerable number of studies have attributed new biological functions to these structures, especially in RNA. Noncoding RNA (ncRNA), which does not translate into a functional protein, is widely expressed and has been shown to play a key role in shaping cellular activity. There has been growing evidence of G4 formation in several ncRNA classes, and it has been identified as a key part for diverse biological functions and physio-pathological contexts in neurodegenerative diseases and cancer. This review discusses RNA G4s (rG4s) in ncRNA, focusing on the molecular mechanism underlying its function. This review also aims to highlight potential and emerging opportunities to identify and target the rG4s in ncRNA to understand its function and, ultimately, treat many diseases.

Cellular Visualization of G-Quadruplex RNA via Fluorescence- Lifetime Imaging Microscopy

Over the past decade, appreciation of the roles of G-quadruplex (G4) structures in cellular regulation and maintenance has rapidly grown, making the establishment of robust methods to visualize G4s increasingly important. Fluorescent probes are commonly used for G4 detection in vitro; however, achieving sufficient selectivity to detect G4s in a dense and structurally diverse cellular environment is challenging. The use of fluorescent probes for G4 detection is further complicated by variations of probe uptake into cells, which may affect fluorescence intensity independently of G4 abundance. In this work, we report an alternative small-molecule approach to visualize G4s that does not rely on fluorescence intensity switch-on and, thus, does not require the use of molecules with exclusive G4 binding selectivity. Specifically, we have developed a novel thiazole orange derivative, TOR-G4, that exhibits a unique fluorescence lifetime when bound to G4s compared to other structures, allowing G4 binding to be sensitively distinguished from non-G4 binding, independent of the local probe concentration. Furthermore, TOR-G4 primarily colocalizes with RNA in the cytoplasm and nucleoli of cells, making it the first lifetime-based probe validated for exploring the emerging roles of RNA G4s in cellulo.

Development of a highly optimized procedure for the discovery of RNA G-quadruplexes by combining several strategies

RNA G-quadruplexes (rG4s) are non-canonical secondary structures that are formed by the self-association of guanine quartets and that are stabilized by monovalent cations (e.g. potassium). rG4s are key elements in several post-transcriptional regulation mechanisms, including both messenger RNA (mRNA) and microRNA processing, mRNA transport and translation, to name but a few examples. Over the past few years, multiple high-throughput approaches have been developed in order to identify rG4s, including bioinformatic prediction, in vitro assays and affinity capture experiments coupled to RNA sequencing. Each individual approach had its limits, and thus yielded only a fraction of the potential rG4 that are further confirmed (i.e., there is a significant level of false positive). This report aims to benefit from the strengths of several existing approaches to identify rG4s with a high potential of being folded in cells. Briefly, rG4s were pulled-down from cell lysates using the biotinylated biomimetic G4 ligand BioTASQ and the sequences thus isolated were then identified by RNA sequencing. Then, a novel bioinformatic pipeline that included DESeq2 to identify rG4 enriched transcripts, MACS2 to identify rG4 peaks, rG4-seq to increase rG4 formation probability and G4RNA Screener to detect putative rG4s was performed. This workflow uncovers new rG4 candidates whose rG4-folding was then confirmed in vitro using an array of established biophysical methods. Clearly, this workflow led to the identification of novel rG4s in a highly specific and reliable manner.

BLM helicase protein negatively regulates stress granule formation through unwinding RNA G-quadruplex structures

Bloom's syndrome (BLM) protein is a known nuclear helicase that is able to unwind DNA secondary structures such as G-quadruplexes (G4s). However, its role in the regulation of cytoplasmic processes that involve RNA G-quadruplexes (rG4s) has not been previously studied. Here, we demonstrate that BLM is recruited to stress granules (SGs), which are cytoplasmic biomolecular condensates composed of RNAs and RNA-binding proteins. BLM is enriched in SGs upon different stress conditions and in an rG4-dependent manner. Also, we show that BLM unwinds rG4s and acts as a negative regulator of SG formation. Altogether, our data expand the cellular activity of BLM and shed light on the function that helicases play in the dynamics of biomolecular condensates.

RNA 3D Structure Prediction: Progress and Perspective

Ribonucleic acid (RNA) molecules play vital roles in numerous important biological functions such as catalysis and gene regulation. The functions of RNAs are strongly coupled to their structures or proper structure changes, and RNA structure prediction has been paid much attention in the last two decades. Some computational models have been developed to predict RNA three-dimensional (3D) structures in silico, and these models are generally composed of predicting RNA 3D structure ensemble, evaluating near-native RNAs from the structure ensemble, and refining the identified RNAs. In this review, we will make a comprehensive overview of the recent advances in RNA 3D structure modeling, including structure ensemble prediction, evaluation, and refinement. Finally, we will emphasize some insights and perspectives in modeling RNA 3D structures.

An overview on nucleic-acid G-quadruplex prediction: from rule-based methods to deep neural networks

Nucleic-acid G-quadruplexes (G4s) play vital roles in many cellular processes. Due to their importance, researchers have developed experimental assays to measure nucleic-acid G4s in high throughput. The generated high-throughput datasets gave rise to unique opportunities to develop machine-learning-based methods, and in particular deep neural networks, to predict G4s in any given nucleic-acid sequence and any species. In this paper, we review the success stories of deep-neural-network applications for G4 prediction. We first cover the experimental technologies that generated the most comprehensive nucleic-acid G4 high-throughput datasets in recent years. We then review classic rule-based methods for G4 prediction. We proceed by reviewing the major machine-learning and deep-neural-network applications to nucleic-acid G4 datasets and report a novel comparison between them. Next, we present the interpretability techniques used on the trained neural networks to learn key molecular principles underlying nucleic-acid G4 folding. As a new result, we calculate the overlap between measured DNA and RNA G4s and compare the performance of DNA- and RNA-G4 predictors on RNA- and DNA-G4 datasets, respectively, to demonstrate the potential of transfer learning from DNA G4s to RNA G4s. Last, we conclude with open questions in the field of nucleic-acid G4 prediction and computational modeling.

G-quadruplexes from non-coding RNAs

Non-coding RNAs (ncRNAs) are significant regulators of gene expression in a wide range of biological processes, such as transcription, RNA maturation, or translation. ncRNAs interplay with proteins or other RNAs through not only classical sequence-based mechanisms but also unique higher-order structures such as RNA G-quadruplexes (rG4s). rG4s are predictably formed in guanine-rich sequences and are closely related to various human diseases, such as tumors, neurodegenerative diseases, and infections. This review focuses on the vital role of rG4s in ncRNAs, particularly lncRNAs and miRNAs. We outline the dynamic balance between rG4s and RNA stem-loop/hairpin structures and the interplay between ncRNAs and interactors, thereby modulating gene expression and disease progression. A complete understanding of the biological regulatory role and mechanism of rG4s in ncRNAs affirms the critical importance of folding into the appropriate three-dimensional structure in maintaining or modulating the functions of ncRNAs. It makes them novel therapeutic targets for adjusting potential-G4-containing-ncRNAs-associated diseases.