RNA and disease

A computational workflow to determine drug candidates alternative to aminoglycosides targeting the decoding center of E. coli ribosome

The global antibiotic resistance problem necessitates fast and effective approaches to finding novel inhibitors to treat bacterial infections. In this study, we propose a computational workflow to identify plausible high-affinity compounds from FDA-approved, investigational, and experimental libraries for the decoding center on the small subunit 30S of the E. coli ribosome. The workflow basically consists of two molecular docking calculations on the intact 30S, followed by molecular dynamics (MD) simulations coupled with MM-GBSA calculations on a truncated ribosome structure. The parameters used in the molecular docking suits, Glide and AutoDock Vina, as well as in the MD simulations with Desmond were carefully adjusted to obtain expected interactions for the ligand-rRNA complexes. A filtering procedure was followed, considering a fingerprint based on aminoglycoside's binding site on the 30S to obtain seven hit compounds either with different clinical usages or aminoglycoside derivatives under investigation, suggested for in vitro studies. The detailed workflow developed in this study promises an effective and fast approach for the estimation of binding free energies of large protein-RNA and ligand complexes.

mRNA-CLA: An interpretable deep learning approach for predicting mRNA subcellular localization

Messenger RNA (mRNA) is vital for post-transcriptional gene regulation, acting as the direct template for protein synthesis. However, the methods available for predicting mRNA subcellular localization need to be improved and enhanced. Notably, few existing algorithms can annotate mRNA sequences with multiple localizations. In this work, we propose the mRNA-CLA, an innovative multi-label subcellular localization prediction framework for mRNA, leveraging a deep learning approach with a multi-head self-attention mechanism. The framework employs a multi-scale convolutional layer to extract sequence features across different regions and uses a self-attention mechanism explicitly designed for each sequence. Paired with Position Weight Matrices (PWMs) derived from the convolutional neural network layers, our model offers interpretability in the analysis. In particular, we perform a base-level analysis of mRNA sequences from diverse subcellular localizations to determine the nucleotide specificity corresponding to each site. Our evaluations demonstrate that the mRNA-CLA model substantially outperforms existing methods and tools.

Transcriptome-wide mapping of small-molecule RNA-binding sites in live cells

Small molecules targeting RNA can be valuable chemical probes and potential therapeutics. The interactions between small molecules, particularly fragments, and RNA, however, can be difficult to detect due to their modest affinities and short residence times. Here, we describe the procedures for mapping the molecular fingerprints of small molecules in vitro and throughout the human transcriptome in live cells, identifying both the targets bound by the small molecule and the sites of binding therein. For complete details on the use and execution of this protocol, please refer to 1.

Complete characterization of the yak testicular development using accurate full-length transcriptome sequencing

Alternative splicing is a prevalent phenomenon in testicular tissues. Due to the low assembly accuracy of short-read RNA sequencing technology in analyzing post-transcriptional regulatory events, full-length (FL) transcript sequencing is highly demanded to accurately determine FL splicing variants. In this study, we performed FL transcriptome sequencing of testicular tissues from 0.5, 1.5, 2.5, and 4-year-old yaks and 4-year-old cattle-yaks using Oxford Nanopore Technologies. The obtained sequencing data were predicted to have 47,185 open reading frames (ORFs), including 26,630 complete ORFs, detected 7645 fusion transcripts, 15,355 alternative splicing events, 25,798 simple sequence repeats, 7628 transcription factors, and 35,503 long non-coding RNAs. A total of 40,038 novel transcripts were obtained from the sequencing data, and the proportion was almost close to the number of known transcripts identified. Structural analysis and functional annotation of these novel transcripts resulted in the successful annotation of 9568 transcripts, with the highest and lowest annotation numbers in the Nr and KOG databases, respectively. Weighted gene co-expression network analysis revealed the key regulatory pathways and hub genes at various stages of yak testicular development. Our findings enhance our comprehension of transcriptome complexity, contribute to genome annotation refinement, and provide foundational data for further investigations into male sterility in cattle-yaks.

CRISPR-dCas13d-based deep screening of proximal and distal splicing-regulatory elements

Pre-mRNA splicing, a key process in gene expression, can be therapeutically modulated using various drug modalities, including antisense oligonucleotides (ASOs). However, determining promising targets is hampered by the challenge of systematically mapping splicing-regulatory elements (SREs) in their native sequence context. Here, we use the catalytically inactive CRISPR-RfxCas13d RNA-targeting system (dCas13d/gRNA) as a programmable platform to bind SREs and modulate splicing by competing against endogenous splicing factors. SpliceRUSH, a high-throughput screening method, was developed to map SREs in any gene of interest using a lentivirus gRNA library that tiles the genetic region, including distal intronic sequences. When applied to SMN2, a therapeutic target for spinal muscular atrophy, SpliceRUSH robustly identifies not only known SREs but also a previously unknown distal intronic SRE, which can be targeted to alter exon 7 splicing using either dCas13d/gRNA or ASOs. This technology enables a deeper understanding of splicing regulation with applications for RNA-based drug discovery.

Interaction of 3,9-disubstituted acridine with single stranded poly(rA), double stranded poly(rAU) and triple stranded poly(rUAU): molecular docking - A spectroscopic tandem study

RNA plays an important role in many biological processes which are crucial for cell survival, and it has been suggested that it may be possible to inhibit individual processes involved in many diseases by targeting specific sequences of RNA. The aim of this work is to determine the affinity of novel 3,9-disubstited acridine derivative 1 with three different RNA molecules, namely single stranded poly(rA), double stranded homopolymer poly(rAU) and triple stranded poly(rUAU). The results of the absorption titration assays show that the binding constant of the novel derivative to the RNA molecules was in the range of 1.7-6.2 × 104 mol dm-3. The fluorescence and circular dichroism titration assays revealed considerable changes. The most significant results in terms of interpreting the nature of the interactions were the melting temperatures of the RNA samples in complexes with the 1. In the case of poly(rA), denaturation resulted in a self-structure formation; increased stabilization was observed for poly(rAU), while the melting points of the ligand-poly(rUAU) complex showed significant destabilization as a result of the interaction. The principles of molecular mechanics were applied to propose the non-bonded interactions within the binding complex, pentariboadenylic acid and acridine ligand as the study model. Initial molecular docking provided the input structure for advanced simulation techniques. Molecular dynamics simulation and cluster analysis reveal π - π stacking and the hydrogen bonds formation as the main forces that can stabilize the binding complex. Subsequent MM-GBSA calculations showed negative binding enthalpy accompanied the complex formation and proposed the most preferred conformation of the interaction complex.

An Orthogonal CRISPR/dCas12a System for RNA Imaging in Live Cells

CRISPR/Cas technology has made great progress in the field of live-cell imaging beyond genome editing. However, effective and easy-to-use CRISPR systems for labeling multiple RNAs of interest are still needed. Here, we engineered a CRISPR/dCas12a system that enables the specific recognition of the target RNA under the guidance of a PAM-presenting oligonucleotide (PAMmer) to mimic the PAM recognition mechanism for DNA substrates. We demonstrated the feasibility and specificity of this system for specifically visualizing endogenous mRNA. By leveraging dCas12a-mediated precursor CRISPR RNA (pre-crRNA) processing and the orthogonality of dCas12a from different bacteria, we further demonstrated the proposed system as a simple and versatile molecular toolkit for multiplexed imaging of different types of RNA transcripts in live cells with high specificity. This programmable dCas12a system not only broadens the RNA imaging toolbox but also facilitates diverse applications for RNA manipulation.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms

Most human Transcription factors (TFs) genes encode multiple protein isoforms differing in DNA binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators", both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

Reference-informed prediction of alternative splicing and splicing-altering mutations from sequences

Alternative splicing plays a crucial role in protein diversity and gene expression regulation in higher eukaryotes and mutations causing dysregulated splicing underlie a range of genetic diseases. Computational prediction of alternative splicing from genomic sequences not only provides insight into gene-regulatory mechanisms but also helps identify disease-causing mutations and drug targets. However, the current methods for the quantitative prediction of splice site usage still have limited accuracy. Here, we present DeltaSplice, a deep neural network model optimized to learn the impact of mutations on quantitative changes in alternative splicing from the comparative analysis of homologous genes. The model architecture enables DeltaSplice to perform "reference-informed prediction" by incorporating the known splice site usage of a reference gene sequence to improve its prediction on splicing-altering mutations. We benchmarked DeltaSplice and several other state-of-the-art methods on various prediction tasks, including evolutionary sequence divergence on lineage-specific splicing and splicing-altering mutations in human populations and neurodevelopmental disorders, and demonstrated that DeltaSplice outperformed consistently. DeltaSplice predicted ~15% of splicing quantitative trait loci (sQTLs) in the human brain as causal splicing-altering variants. It also predicted splicing-altering de novo mutations outside the splice sites in a subset of patients affected by autism and other neurodevelopmental disorders, including 19 genes with recurrent splicing-altering mutations. Among the new candidate disease risk genes, MFN1 is involved in mitochondria fusion, which is frequently disrupted in autism patients. Our work expanded the capacity of in silico splicing models with potential applications in genetic diagnosis and the development of splicing-based precision medicine.

Integrative Analysis of Germline Rare Variants in Clear and Non-clear Cell Renal Cell Carcinoma

Background and objective

Previous germline studies on renal cell carcinoma (RCC) have usually pooled clear and non-clear cell RCCs and have not adequately accounted for population stratification, which might have led to an inaccurate estimation of genetic risk. Here, we aim to analyze the major germline drivers of RCC risk and clinically relevant but underexplored germline variant types.

Methods

We first characterized germline pathogenic variants (PVs), cryptic splice variants, and copy number variants (CNVs) in 1436 unselected RCC patients. To evaluate the enrichment of PVs in RCC, we conducted a case-control study of 1356 RCC patients ancestry matched with 16 512 cancer-free controls using approaches accounting for population stratification and histological subtypes, followed by characterization of secondary somatic events.

Key findings and limitations

Clear cell RCC patients (n = 976) exhibited a significant burden of PVs in VHL compared with controls (odds ratio [OR]: 39.1, p = 4.95e-05). Non-clear cell RCC patients (n = 380) carried enrichment of PVs in FH (OR: 77.9, p = 1.55e-08) and MET (OR: 1.98e11, p = 2.07e-05). In a CHEK2-focused analysis with European participants, clear cell RCC (n = 906) harbored nominal enrichment of low-penetrance CHEK2 variants-p.Ile157Thr (OR: 1.84, p = 0.049) and p.Ser428Phe (OR: 5.20, p = 0.045), while non-clear cell RCC (n = 295) exhibited nominal enrichment of CHEK2 loss of function PVs (OR: 3.51, p = 0.033). Patients with germline PVs in FH, MET, and VHL exhibited significantly earlier age of cancer onset than patients without germline PVs (mean: 46.0 vs 60.2 yr, p < 0.0001), and more than half had secondary somatic events affecting the same gene (n = 10/15, 66.7%). Conversely, CHEK2 PV carriers exhibited a similar age of onset to patients without germline PVs (mean: 60.1 vs 60.2 yr, p = 0.99), and only 30.4% carried somatic events in CHEK2 (n = 7/23). Finally, pathogenic germline cryptic splice variants were identified in SDHA and TSC1, and pathogenic germline CNVs were found in 18 patients, including CNVs in FH, SDHA, and VHL.

Conclusions and clinical implications

This analysis supports the existing link between several RCC risk genes and RCC risk manifesting in earlier age of onset. It calls for caution when assessing the role of CHEK2 due to the burden of founder variants with varying population frequency. It also broadens the definition of the RCC germline landscape of pathogenicity to incorporate previously understudied types of germline variants.

Patient summary

In this study, we carefully compared the frequency of rare inherited mutations with a focus on patients' genetic ancestry. We discovered that subtle variations in genetic background may confound a case-control analysis, especially in evaluating the cancer risk associated with specific genes, such as CHEK2. We also identified previously less explored forms of rare inherited mutations, which could potentially increase the risk of kidney cancer.

On a kneading theory for gene-splicing

Two well-known facets in protein synthesis in eukaryotic cells are transcription of DNA to pre-RNA in the nucleus and the translation of messenger-RNA (mRNA) to proteins in the cytoplasm. A critical intermediate step is the removal of segments (introns) containing ∼97% of the nucleic-acid sites in pre-RNA and sequential alignment of the retained segments (exons) to form mRNA through a process referred to as splicing. Alternative forms of splicing enrich the proteome while abnormal splicing can enhance the likelihood of a cell developing cancer or other diseases. Mechanisms for splicing and origins of splicing errors are only partially deciphered. Our goal is to determine if rules on splicing can be inferred from data analytics on nucleic-acid sequences. Toward that end, we represent a nucleic-acid site as a point in a plane defined in terms of the anterior and posterior sub-sequences of the site. The "point-set" representation expands analytical approaches, including the use of statistical tools, to characterize genome sequences. It is found that point-sets for exons and introns are visually different, and that the differences can be quantified using a family of generalized moments. We design a machine-learning algorithm that can recognize individual exons or introns with 91% accuracy. Point-set distributions and generalized moments are found to differ between organisms.

Lanthanide Complex for Single-Molecule Fluorescent in Situ Hybridization and Background-Free Imaging

Traditional single-molecule fluorescence in situ hybridization (smFISH) methods for RNA detection often face sensitivity challenges due to the low fluorescence intensity of the probe. Also, short-lived autofluorescence complicates obtaining clear signals from tissue sections. In response, we have developed an smFISH probe using highly grafted lanthanide complexes to address both concentration quenching and autofluorescence background. Our approach involves an oligo PCR incorporating azide-dUTP, enabling conjugation with lanthanide complexes. This method has proven to be stable, convenient, and cost-effective. Notably, for the mRNA detection in SKBR3 cells, the lanthanide probe group exhibited 2.5 times higher luminescence intensity and detected 3 times more signal points in cells compared with the Cy3 group. Furthermore, we successfully applied the probe to image HER2 mRNA molecules in breast cancer FFPE tissue sections, achieving a 2.7-fold improvement in sensitivity compared to Cy3-based probes. These results emphasize the potential of time-resolved smFISH as a highly sensitive method for nucleic acid detection, free of background fluorescence interference.

Biosurfer for systematic tracking of regulatory mechanisms leading to protein isoform diversity

Long-read RNA sequencing has shed light on transcriptomic complexity, but questions remain about the functionality of downstream protein products. We introduce Biosurfer, a computational approach for comparing protein isoforms, while systematically tracking the transcriptional, splicing, and translational variations that underlie differences in the sequences of the protein products. Using Biosurfer, we analyzed the differences in 32,799 pairs of GENCODE annotated protein isoforms, finding a majority (70%) of variable N-termini are due to the alternative transcription start sites, while only 9% arise from 5' UTR alternative splicing. Biosurfer's detailed tracking of nucleotide-to-residue relationships helped reveal an uncommonly tracked source of single amino acid residue changes arising from the codon splits at junctions. For 17% of internal sequence changes, such split codon patterns lead to single residue differences, termed "ragged codons". Of variable C-termini, 72% involve splice- or intron retention-induced reading frameshifts. We found an unusual pattern of reading frame changes, in which the first frameshift is closely followed by a distinct second frameshift that restores the original frame, which we term a "snapback" frameshift. We analyzed long read RNA-seq-predicted proteome of a human cell line and found similar trends as compared to our GENCODE analysis, with the exception of a higher proportion of isoforms predicted to undergo nonsense-mediated decay. Biosurfer's comprehensive characterization of long-read RNA-seq datasets should accelerate insights of the functional role of protein isoforms, providing mechanistic explanation of the origins of the proteomic diversity driven by the alternative splicing. Biosurfer is available as a Python package at https://github.com/sheynkman-lab/biosurfer.

Studying relative RNA localization From nucleus to the cytosol

The precise coordination of important biological processes, such as differentiation and development, is highly dependent on the regulation of expression of the genetic information. The flow of the genetic information is tightly regulated on multiple levels. Among them, RNA export to cytosol is an essential step for the production of proteins in eukaryotic cells. Hence, estimating the relative concentration of RNA molecules of a given transcript species in the nucleus and in the cytosol is of major significance as it contributes to the understanding of the dynamics of RNA trafficking between the nucleus and the cytosol. The most efficient way to estimate the levels of RNA species genome-wide is through RNA sequencing (RNAseq). While RNAseq can be performed separately in the nucleus and in the cytosol, because measured transcript levels are relative to the total volume of RNA in these compartments, and because this volume is usually unknown, the transcript levels in the nucleus and in the cytosol cannot be directly compared. Here we show theoretically that if, in addition to nuclear and cytosolic RNA-seq, whole cell RNA-seq is also performed, then accurate estimations of the localization of transcripts can be obtained. Based on this, we designed a method that estimates, first the fraction of the total RNA volume in the cytosol (nucleus), and then, this fraction for every transcript. We evaluate our methodology on simulated data and nuclear and cytosolic single cell data available. Finally, we use our method to investigate the cellular localization of transcripts using bulk RNAseq data from the ENCODE project.

Single-Atom Site SERS Chip for Rapid, Ultrasensitive, and Reproducible Direct-Monitoring of RNA Binding

Ribonucleic acids (RNA) play active roles within cells or viruses by catalyzing biological reactions, controlling gene expression, and communicating responses to cellular signals. Rapid monitoring RNA variation has become extremely important for appropriate clinical decisions and frontier biological research. However, the most widely used method for RNA detection, nucleic acid amplification, is restricted by a mandatory temperature cycling period of ≈1 h required to reach target detection criteria. Herein, a direct detection approach via single-atom site integrated surface-enhanced Raman scattering (SERS) monitoring nucleic acid pairing reaction, can be completed within 3 min and reaches high sensitivity and extreme reproducibility for COVID-19 and two other influenza viruses' detection. The mechanism is that a single-atom site on SERS chip, enabled by positioning a single-atom oxide coordinated with a specific complementary RNA probe on chip nanostructure hotspots, can effectively bind target RNA analytes to enrich them at designed sites so that the binding reaction can be detected through Raman signal variation. This ultrafast, sensitive, and reproducible single-atom site SERS chip approach paves the route for an alternative technique of immediate RNA detection. Moreover, single-atom site SERS is a novel surface enrichment strategy for SERS active sites for other analytes at ultralow concentrations.

The effect of emulsifier type and oil inclusion on stress-related gene expression of Salmonella typhimurium in oil-in-water emulsion

Salmonella has been associated with numerous outbreaks from contaminated food products, including emulsions. Emulsions are influenced by emulsifier type and oil presence, which can have varying degrees of stress or protection on bacteria. Although our previous research has shown that emulsifier solutions, rather than emulsions, provide a protective effect on Salmonella typhimurium after thermal treatment, the underlying mechanism remains unclear. This study selected S. typhimurium as the model microorganism and utilized the same emulsifiers (Tween 20, Tween 80, Triton X-100) to create emulsifier solutions and emulsions with the same oil fraction (60% (v/v)) to examine their effect on the expression of nine selected genes (rpoE, rpoH, otsB, proV, fadA, fabA, dnaK, ibpA, ompC) associated with stress response. Specifically, the study observed variations in gene expression under normal and thermal stress at 55°C. After 20-h incubation, Triton X-100 emulsion caused an upregulation of stress-related genes, rpoE, otsB, and fabA, suggesting stressful environment. After thermal treatment, S. typhimurium in Triton X-100 solution showed a longer 5-log reduction time with increased proV and decreased fabA and ompC expression, suggesting enhanced thermal protection compared to its emulsion. Conversely, Tween 80 solution increased fabA and ompC expression, indicating greater membrane fluidity and passive diffusion, potentially reducing thermal resistance. However, according to the upregulation of ibpA, this effect was likely mitigated by the overproduction of heat shock proteins. Notably, Triton X-100 environments exhibited the most significant gene expression changes after heat treatment, whereas Tween 80 without oil was the most inhospitable for bacterial survival. These findings inform bacterial responses under various conditions, aiding food safety strategies.

General and Specific Cytotoxicity of Chimeric Antisense Oligonucleotides in Bacterial Cells and Human Cell Lines

In the last two decades, antisense oligonucleotide technology has emerged as a promising approach to tackling various healthcare issues and diseases, such as antimicrobial resistance, cancer, and neurodegenerative diseases. Despite the numerous improvements in the structure and modifications of the antisense oligonucleotides (ASOs), there are still specific problems with their clinical efficacy and preclinical cytotoxicity results. To better understand the effects of the ASOs in this paper, we conducted many MTT assays to assess the general and specific cytotoxicity of four new chimeric ASOs in bacterial cells and human cell lines. We demonstrate the absence of inhibitory activity in the human pathogenic bacteria Staphylococcus aureus by non-specific ASOs. The pVEC-ASO1 and pVEC-ASO2 are designed to have no specific targets in S. aureus. They have only partial hybridization to the guanylate kinase mRNA. The pVEC-ASO3 targets UBA2 mRNA, a hallmark cancer pathology in MYC-driven cancer, while pVEC-ASO4 has no complementary sequences. We discovered some cytotoxicity of the non-specific ASOs in healthy and cancer human cell lines. The results are compared with two other ASOs, targeting specific mRNA in cancer cells. All ASOs are delivered into the cell via the cell-penetrating oligopeptide pVEC, which is attached to them. We draw a good correlation between the thermodynamic stability of ASO/target RNA and the toxicity effect in human cell lines. The data obtained signify the importance of thorough bioinformatic analysis and high specificity in designing and developing novel ASOs for safer therapeutic agents in clinical practice.

RNA-binding protein RBM5 plays an essential role in acute myeloid leukemia by activating the oncogenic protein HOXA9

BACKGROUND

The oncogenic protein HOXA9 plays a critical role in leukemia transformation and maintenance, and its aberrant expression is a hallmark of most aggressive acute leukemia. Although inhibiting the upstream regulators of HOXA9 has been proven as a significant therapeutic intervention, the comprehensive regulation network controlling HOXA9 expression in leukemia has not been systematically investigated.

RESULTS

Here, we perform genome-wide CRISPR/Cas9 screening in the HOXA9-driven reporter acute leukemia cells. We identify a poorly characterized RNA-binding protein, RBM5, as the top candidate gene required to maintain leukemia cell fitness. RBM5 is highly overexpressed in acute myeloid leukemia (AML) patients compared to healthy individuals. RBM5 loss triggered by CRISPR knockout and shRNA knockdown significantly impairs leukemia maintenance in vitro and in vivo. Through domain CRISPR screening, we reveal that RBM5 functions through a noncanonical transcriptional regulation circuitry rather than RNA splicing, such an effect depending on DNA-binding domains. By integrative analysis and functional assays, we identify HOXA9 as the downstream target of RBM5. Ectopic expression of HOXA9 rescues impaired leukemia cell proliferation upon RBM5 loss. Importantly, acute protein degradation of RBM5 through auxin-inducible degron system immediately reduces HOXA9 transcription.

CONCLUSIONS

We identify RBM5 as a new upstream regulator of HOXA9 and reveal its essential role in controlling the survival of AML. These functional and molecular mechanisms further support RBM5 as a promising therapeutic target for myeloid leukemia treatment.

Conserved Residues at the Mtr4 C-Terminus Coordinate Helicase Activity and Exosome Interactions

Mtr4 is an essential RNA helicase involved in nuclear RNA processing and degradation and is a member of the Ski2-like helicase family. Ski2-like helicases share a common core architecture that includes two RecA-like domains, a winged helix, and a helical bundle (HB) domain. In Mtr4, a short C-terminal tail immediately follows the HB domain and is positioned at the interface of the RecA-like domains. The tail ends with a SLYΦ sequence motif that is highly conserved in a subset of Ski2-like helicases. Here, we show that this sequence is critical for Mtr4 function. Mutations in the C-terminus result in decreased RNA unwinding activity. Mtr4 is a key activator of the RNA exosome complex, and mutations in the SLYΦ motif produce a slow growth phenotype when combined with a partial exosome defect in S. cerevisiae, suggesting an important role of the C-terminus of Mtr4 and the RNA exosome. We further demonstrate that C-terminal mutations impair RNA degradation activity by the major RNA exosome nuclease Rrp44 in vitro. These data demonstrate a role for the Mtr4 C-terminus in regulating helicase activity and coordinating Mtr4-exosome interactions.

Comparative Assessment of Pose Prediction Accuracy in RNA-Ligand Docking

Structure-based virtual high-throughput screening is used in early-stage drug discovery. Over the years, docking protocols and scoring functions for protein-ligand complexes have evolved to improve the accuracy in the computation of binding strengths and poses. In the past decade, RNA has also emerged as a target class for new small-molecule drugs. However, most ligand docking programs have been validated and tested for proteins and not RNA. Here, we test the docking power (pose prediction accuracy) of three state-of-the-art docking protocols on 173 RNA-small molecule crystal structures. The programs are AutoDock4 (AD4) and AutoDock Vina (Vina), which were designed for protein targets, and rDock, which was designed for both protein and nucleic acid targets. AD4 performed relatively poorly. For RNA targets for which a crystal structure of a bound ligand used to limit the docking search space is available and for which the goal is to identify new molecules for the same pocket, rDock performs slightly better than Vina, with success rates of 48% and 63%, respectively. However, in the more common type of early-stage drug discovery setting, in which no structure of a ligand-target complex is known and for which a larger search space is defined, rDock performed similarly to Vina, with a low success rate of ∼27%. Vina was found to have bias for ligands with certain physicochemical properties, whereas rDock performs similarly for all ligand properties. Thus, for projects where no ligand-protein structure already exists, Vina and rDock are both applicable. However, the relatively poor performance of all methods relative to protein-target docking illustrates a need for further methods refinement.

Alternative Transcripts Diversify Genome Function for Phenome Relevance to Health and Diseases

Manipulation using alternative exon splicing (AES), alternative transcription start (ATS), and alternative polyadenylation (APA) sites are key to transcript diversity underlying health and disease. All three are pervasive in organisms, present in at least 50% of human protein-coding genes. In fact, ATS and APA site use has the highest impact on protein identity, with their ability to alter which first and last exons are utilized as well as impacting stability and translation efficiency. These RNA variants have been shown to be highly specific, both in tissue type and stage, with demonstrated importance to cell proliferation, differentiation and the transition from fetal to adult cells. While alternative exon splicing has a limited effect on protein identity, its ubiquity highlights the importance of these minor alterations, which can alter other features such as localization. The three processes are also highly interwoven, with overlapping, complementary, and competing factors, RNA polymerase II and its CTD (C-terminal domain) chief among them. Their role in development means dysregulation leads to a wide variety of disorders and cancers, with some forms of disease disproportionately affected by specific mechanisms (AES, ATS, or APA). Challenges associated with the genome-wide profiling of RNA variants and their potential solutions are also discussed in this review.

Comparing RNA extraction methods to face the variations in RNA quality using two human biological matrices

BACKGROUND

Nucleic acids, RNA among them, are widely used in biomedicine and Biotechnology. Because of their susceptibility to degradation by RNases, the handling and extraction process of RNA from cells and tissues require specialized personnel and standardized methods to guarantee high purity and integrity. Due to the diversity of techniques found in the market, a comparative study between different RNA extraction methods is useful to facilitate the best choice for the researcher or in research service platforms such as biobanks to see the traceability of the samples.

METHODS AND RESULTS

In this study, we have compared seven different RNA extraction methods: manual (TRIzol™), semiautomated (QIAGEN™, Bio-Rad, Monarch®, and Canvax™), and fully automated (QIAcube™ and Maxwell®) processes, from two biological matrices: human Jurkat T cells and peripheral blood mononuclear cells (PBMC). Results showed marked differences in the RNA quality and functionality according to the method employed for RNA extraction and the matrix used.

DISCUSSION

QIAcube™ and semi-automated extraction methods were perceived as the best options because of their lower variability, good functionality, and lower cost (P < 0.001). These data contribute to facilitating researchers or research service platforms (Biobanks) in decision-making practices and emphasize the relevance of the selection of the RNA extraction method in each experimental procedure or traceability study to guarantee both quality standards and its reproducibility.

Evaluating the Effect of Gestational Exposure to Perfluorohexane Sulfonate on Placental Development in Mice Combining Alternative Splicing and Gene Expression Analyses

BACKGROUND

Perfluorohexane sulfonate (PFHxS) is a frequently detected per- and polyfluoroalkyl substance in most populations, including in individuals who are pregnant, a period critical for early life development. Despite epidemiological evidence of exposure, developmental toxicity, particularly at realistic human exposures, remains understudied.

OBJECTIVES

We evaluated the effect of gestational exposure to human-relevant body burden of PFHxS on fetal and placental development and explored mechanisms of action combining alternative splicing (AS) and gene expression (GE) analyses.

METHODS

Pregnant ICR mice were exposed to 0, 0.03, and 0.3 μ g / kg / day  from gestational day 7 to day 17 via oral gavage. Upon euthanasia, PFHxS distribution was measured using liquid chromatography-tandem mass spectrometry. Maternal and fetal phenotypes were recorded, and histopathology was examined for placenta impairment. Multiomics was adopted by combining AS and GE analyses to unveil disruptions in mRNA quality and quantity. The key metabolite transporters were validated by quantitative real-time PCR (qRT-PCR) for quantification and three-dimensional (3D) structural simulation by AlphaFold2. Targeted metabolomics based on liquid chromatography-tandem mass spectrometry was used to detect amino acid and amides levels in the placenta.

RESULTS

Pups developmentally exposed to PFHxS exhibited signs of intrauterine growth restriction (IUGR), characterized by smaller fetal weight and body length (p < 0.01 ) compared to control mice. PFHxS concentration in maternal plasma was 5.01 ± 0.54  ng / mL . PFHxS trans-placenta distribution suggested dose-dependent transfer through placental barrier. Histopathology of placenta of exposed dams showed placental dysplasia, manifested with an attenuated labyrinthine layer area and deescalated blood sinus counts and placental vascular development index marker CD34. Combined GE and AS analyses pinpointed differences in genes associated with key biological processes of placental development, proliferation, metabolism, and transport in placenta of exposed dams compared to that of control dams. Further detection of placental key transporter gene expression, protein structure simulation, and amino acid and amide metabolites levels suggested that PFHxS exposure during pregnancy led to impairment of placental amino acid transportation.

DISCUSSION

The findings from this study suggest that exposure to human-relevant very-low-dose PFHxS during pregnancy in mice caused IUGR, likely via downregulating of placental amino acid transporters, thereby impairing placental amino acid transportation, resulting in impairment of placental development. Our findings confirm epidemiological findings and call for future attention on the health risk of this persistent yet ubiquitous chemical in the early developmental stage and provide a new approach for understanding gene expression from both quantitative and qualitative omics approaches in toxicological studies. https://doi.org/10.1289/EHP13217.

Investigation of a Fused in Sarcoma Splicing Mutation in a Chinese Amyotrophic Lateral Sclerosis Patient

OBJECTIVE

Genetic mutations of fused in sarcoma (FUS) causing amyotrophic lateral sclerosis (ALS) may disrupt mRNA splicing events. For example, the FUS c.1394-2delA variant was reported in two western ALS patients, but its molecular mechanism is unclear. In this study, we aim to investigate FUS splice site mutations in Chinese ALS patients.

METHODS

Sanger sequencing was used to identify FUS splicing mutations in Chinese ALS patients. We combined a deep learning tool (SpliceAI), RNA sequencing, and RT-PCR/RT-qPCR to analyze the effect of FUS c.1394-2delA mutation on RNA splicing and expression. AlphaFold was used to predict the protein structure of mutant FUS. In transfected cell lines, we used immunofluorescence to assess cytoplasmic mislocalization of mutant FUS protein.

RESULTS

We identified a de novo FUS splice acceptor site mutation (c.1394-2delA, p. Gly466Valfs*14) in one Chinese sporadic ALS patient, which is linked to exon 14 skipping, and upregulated total FUS mRNA expression. The FUS splice site mutation was predicted to be translated into a truncated protein product at C-terminal. In vitro studies revealed that the FUS mutation increased cytoplasmic mislocalization in both HEK293T and SH-SY5Y cells.

CONCLUSIONS

We identified a de novo FUS splicing mutation (c.1394-2delA, p. Gly466Valfs*14) in 1 out of 233 Chinese ALS patients. It caused abnormal RNA splicing, upregulated gene expression, truncated FUS translation, and cytosolic mislocalization. Our findings suggested that FUS splice site mutation is rare in Chinese ALS patients and extended our knowledge of molecular mechanisms of the FUS c.1394-2delA mutation.

Regulation of Flowering Time and Other Developmental Plasticities by 3' Splicing Factor-Mediated Alternative Splicing in Arabidopsis thaliana

Plants, as sessile organisms, show a high degree of plasticity in their growth and development and have various strategies to cope with these alterations under continuously changing environments and unfavorable stress conditions. In particular, the floral transition from the vegetative and reproductive phases in the shoot apical meristem (SAM) is one of the most important developmental changes in plants. In addition, meristem regions, such as the SAM and root apical meristem (RAM), which continually generate new lateral organs throughout the plant life cycle, are important sites for developmental plasticity. Recent findings have shown that the prevailing type of alternative splicing (AS) in plants is intron retention (IR) unlike in animals; thus, AS is an important regulatory mechanism conferring plasticity for plant growth and development under various environmental conditions. Although eukaryotes exhibit some similarities in the composition and dynamics of their splicing machinery, plants have differences in the 3' splicing characteristics governing AS. Here, we summarize recent findings on the roles of 3' splicing factors and their interacting partners in regulating the flowering time and other developmental plasticities in Arabidopsis thaliana.

RNA trafficking and subcellular localization-a review of mechanisms, experimental and predictive methodologies

RNA localization is essential for regulating spatial translation, where RNAs are trafficked to their target locations via various biological mechanisms. In this review, we discuss RNA localization in the context of molecular mechanisms, experimental techniques and machine learning-based prediction tools. Three main types of molecular mechanisms that control the localization of RNA to distinct cellular compartments are reviewed, including directed transport, protection from mRNA degradation, as well as diffusion and local entrapment. Advances in experimental methods, both image and sequence based, provide substantial data resources, which allow for the design of powerful machine learning models to predict RNA localizations. We review the publicly available predictive tools to serve as a guide for users and inspire developers to build more effective prediction models. Finally, we provide an overview of multimodal learning, which may provide a new avenue for the prediction of RNA localization.

[Tau Protein Induces Aberrant Alternative Splicing Changes in PS19 Transgenic Mice]

Objective

To explore through big data analysis whether aberrant alternative splicing (AS) events precede tau P301S-induced neurodegenerative phenotype in 6-month-old PS19 mice.

Methods

The original sequencing files of the GSE182170 dataset was downloaded from the European Nucleotide Archive (ENA) database with axel, aligned to the reference genome of the ENSEMBL database by using STAR software, and common AS event analysis and visualization were performed with rMATS and rmats2sashimiplot R packages. RSEM software was utilized for gene transcript quantification, Deseq2, edgeR, and limma R packages were used for differential expression analysis, and clusterProfiler R package was applied for GO enrichment analysis. String and Cytoscape were used for protein-protein interaction (PPI) analysis. Gene expression correlation analysis was performed with ggcorrplot R package. AS events were validated using PCR followed by agarose electrophoresis.

Results

A total of 8 079 AS events were identified with rMATS and 117 significant AS events (ΔPSI>0.1, sequencing coverage >1) were selected eventually. The most frequent type of AS event was skipped exon (SE) (50.43%), followed by alternative 3' splice site (A3SS) and mutually exclusive exons (MXE). GO enrichment analysis revealed that synapse organization genes were aberrantly spliced in SE events and spliceosome genes were spliced in A3SS events. PPI and correlation analyses showed that the splicing factor Snrpn was significantly associated with the largest number of transcripts. Agarose electrophoresis confirmed the aberrant AS event of the Lrp8 gene in PS19 mice.

Conclusion

Dysregulated splicing factors may contribute to tau P301S-induced aberrant AS changes. The study also increases the understanding of the cycling of tau protein and splicing factors in tauopathies.

RNA-RNA competitive interactions: a molecular civil war ruling cell physiology and diseases

The idea that proteins are the main determining factors in the functioning of cells and organisms, and their dysfunctions are the first cause of pathologies, has been predominant in biology and biomedicine until recently. This protein-centered view was too simplistic and failed to explain the physiological and pathological complexity of the cell. About 80% of the human genome is dynamically and pervasively transcribed, mostly as non-protein-coding RNAs (ncRNAs), which competitively interact with each other and with coding RNAs generating a complex RNA network regulating RNA processing, stability, and translation and, accordingly, fine-tuning the gene expression of the cells. Qualitative and quantitative dysregulations of RNA-RNA interaction networks are strongly involved in the onset and progression of many pathologies, including cancers and degenerative diseases. This review will summarize the RNA species involved in the competitive endogenous RNA network, their mechanisms of action, and involvement in pathological phenotypes. Moreover, it will give an overview of the most advanced experimental and computational methods to dissect and rebuild RNA networks.

Deep screening of proximal and distal splicing-regulatory elements in a native sequence context

Pre-mRNA splicing, a key process in gene expression, can be therapeutically modulated using various drug modalities, including antisense oligonucleotides (ASOs). However, determining promising targets is impeded by the challenge of systematically mapping splicing-regulatory elements (SREs) in their native sequence context. Here, we use the catalytically dead CRISPR-RfxCas13d RNA-targeting system (dCas13d/gRNA) as a programmable platform to bind SREs and modulate splicing by competing against endogenous splicing factors. SpliceRUSH, a high-throughput screening method, was developed to map SREs in any gene of interest using a lentivirus gRNA library that tiles the genetic region, including distal intronic sequences. When applied to SMN2, a therapeutic target for spinal muscular atrophy, SpliceRUSH robustly identified not only known SREs, but also a novel distal intronic splicing enhancer, which can be targeted to alter exon 7 splicing using either dCas13d/gRNA or ASOs. This technology enables a deeper understanding of splicing regulation with applications for RNA-based drug discovery.

Advances in chaperone-assisted RNA crystallography using synthetic antibodies

RNA molecules play essential roles in many biological functions, from gene expression regulation, cellular growth, and metabolism to catalysis. They frequently fold into three-dimensional structures to perform their functions. Therefore, determining RNA structure represents a key step for understanding the structure-function relationships and developing RNA-targeted therapeutics. X-ray crystallography remains a method of choice for determining high-resolution RNA structures, but it has been challenging due to difficulties associated with RNA crystallization and phasing. Several natural and synthetic RNA binding proteins have been used to facilitate RNA crystallography. Having unique properties to help crystal packing and phasing, synthetic antibody fragments, specifically the Fabs, have emerged as promising RNA crystallization chaperones, and so far, over a dozen of RNA structures have been solved using this strategy. Nevertheless, multiple steps in this approach need to be improved, including the recombinant expression of these anti-RNA Fabs, to warrant the full potential of these synthetic Fabs as RNA crystallization chaperones. This review highlights the nuts and bolts and recent advances in the chaperone-assisted RNA crystallography approach, specifically emphasizing the Fab antibody fragments as RNA crystallization chaperones.

SaBrcada: Survival Intervals Prediction for Breast Cancer Patients by Dimension Raising and Age Stratification

(1) Background: Breast cancer is the second leading cause of cancer death among women. The accurate prediction of survival intervals will help physicians make informed decisions about treatment strategies or the use of palliative care. (2) Methods: Gene expression is predictive and correlates to patient prognosis. To establish a reliable prediction tool, we collected a total of 1187 RNA-seq data points from breast cancer patients (median age 58 years) in Fragments Per Kilobase Million (FPKM) format from the TCGA database. Among them, we selected 144 patients with date of death information to establish the SaBrcada-AD dataset. We first normalized the SaBrcada-AD dataset to TPM to build the survival prediction model SaBrcada. After normalization and dimension raising, we used the differential gene expression data to test eight different deep learning architectures. Considering the effect of age on prognosis, we also performed a stratified random sampling test on all ages between the lower and upper quartiles of patient age, 48 and 69 years; (3) Results: Stratifying by age 61, the performance of SaBrcada built by GoogLeNet was improved to a highest accuracy of 0.798. We also built a free website tool to provide five predicted survival periods: within six months, six months to one year, one to three years, three to five years, or over five years, for clinician reference. (4) Conclusions: We built the prediction model, SaBrcada, and the website tool of the same name for breast cancer survival analysis. Through these models and tools, clinicians will be provided with survival interval information as a basis for formulating precision medicine.

Structural basis for specific RNA recognition by the alternative splicing factor RBM5

The RNA-binding motif protein RBM5 belongs to a family of multi-domain RNA binding proteins that regulate alternative splicing of genes important for apoptosis and cell proliferation and have been implicated in cancer. RBM5 harbors structural modules for RNA recognition, such as RRM domains and a Zn finger, and protein-protein interactions such as an OCRE domain. Here, we characterize binding of the RBM5 RRM1-ZnF1-RRM2 domains to cis-regulatory RNA elements. A structure of the RRM1-ZnF1 region in complex with RNA shows how the tandem domains cooperate to sandwich target RNA and specifically recognize a GG dinucleotide in a non-canonical fashion. While the RRM1-ZnF1 domains act as a single structural module, RRM2 is connected by a flexible linker and tumbles independently. However, all three domains participate in RNA binding and adopt a closed architecture upon RNA binding. Our data highlight how cooperativity and conformational modularity of multiple RNA binding domains enable the recognition of distinct RNA motifs, thereby contributing to the regulation of alternative splicing. Remarkably, we observe surprising differences in coupling of the RNA binding domains between the closely related homologs RBM5 and RBM10.

Analysis and application of RNA binding protein gene pairs to predict the prognosis of gastric cancer

Background

RNA-binding proteins (RBPs) are closely related to tumors, but little is known about the mechanism of RBPs in tumorigenesis and progression of gastric cancer (GC). As genes do not usually act alone in the pathway deregulation, gene pair combinations are more likely to become stable and accurate biomarkers. The purpose of our research is to establish a novel signature based on RBP gene pairs to predict the prognosis of gastric cancer patients.

Methods

We downloaded genetic and clinical information from the TCGA and GEO database. TCGA and GSE13911 were used for screening differentially expressed genes (DEGs). The RBP genes were gathered from previous studies and employed to screen out DE-RBP genes after intersecting with DEGs. Samples were classified according to the relative expression of each pair of DE-RBP genes. The univariate Cox regression analysis and random forest were used to identify hub gene pairs to construct signature for predicting the prognosis of gastric cancer. Time-dependent ROC curves and KM survival curves were performed to evaluate the signature. GSEA was performed in TCGA training cohort and GSE62254 testing cohort to analyze enrichment pathways. Finally, the influence of these gene pairs on the prognosis of GC patients was further elucidated respectively through the combination of high and low expression of the two genes in each hub gene pair.

Results

We screened out 6 hub RBP gene pairs (COL5A2/FEN1, POP1/GFRA1, EXO1/PLEKHS1, SLC39A10/CHI3L1, MMP7/PPP1R1 B and SLC5A6/BYSL) to predict the prognosis of patients with gastric cancer. Using the optimal cut-off value to divide patients into high-risk and low-risk groups in the training and testing cohort, we found that the overall survival (OS) of the low-risk group was higher than that of the high-risk group (P < 0.05). The area under the ROC curves for 1, 3, and 5 years were (0.659, 0.744, 0.758) and (0.624, 0.650, 0.653) in two cohorts. Univariate and multivariate Cox regression analysis showed that 6 RBP gene pairs signature were independent prognostic factors for gastric cancer (P < 0.05). In addition, the prognostic survival analysis showed that COL5A2-high/FEN1-low, POP1-low/GFRA1-high, EXO1-low/PLEKHS1-low,SLC39A10-high/CHI3L1-low, MMP7-high/PPP1R1 B-low, SLC5A6-low/BYSL-low had worse OS (P < 0.05). And the gene correlation analysis showed that there was no obvious correlation between the genes in each gene pairs except SLC5A6/BYSL and POP1/GFRA1. Finally, GSEA analysis showed that the high-risk group was enriched in tumor migration, invasion and growth-related pathways.

Conclusion

Our study identified a novel 6 RBP gene pairs signature to predict the prognosis of gastric cancer patients and provide potential targets for clinical gene therapy.

Counting pseudoalignments to novel splicing events

MOTIVATION

Alternative splicing (AS) of introns from pre-mRNA produces diverse sets of transcripts across cell types and tissues, but is also dysregulated in many diseases. Alignment-free computational methods have greatly accelerated the quantification of mRNA transcripts from short RNA-seq reads, but they inherently rely on a catalog of known transcripts and might miss novel, disease-specific splicing events. By contrast, alignment of reads to the genome can effectively identify novel exonic segments and introns. Event-based methods then count how many reads align to predefined features. However, an alignment is more expensive to compute and constitutes a bottleneck in many AS analysis methods.

RESULTS

Here, we propose fortuna, a method that guesses novel combinations of annotated splice sites to create transcript fragments. It then pseudoaligns reads to fragments using kallisto and efficiently derives counts of the most elementary splicing units from kallisto's equivalence classes. These counts can be directly used for AS analysis or summarized to larger units as used by other widely applied methods. In experiments on synthetic and real data, fortuna was around 7× faster than traditional align and count approaches, and was able to analyze almost 300 million reads in just 15 min when using four threads. It mapped reads containing mismatches more accurately across novel junctions and found more reads supporting aberrant splicing events in patients with autism spectrum disorder than existing methods. We further used fortuna to identify novel, tissue-specific splicing events in Drosophila.

AVAILABILITY AND IMPLEMENTATION

fortuna source code is available at https://github.com/canzarlab/fortuna.

RBM33 is a unique m6A RNA-binding protein that regulates ALKBH5 demethylase activity and substrate selectivity

Regulation of RNA substrate selectivity of m6A demethylase ALKBH5 remains elusive. Here, we identify RNA-binding motif protein 33 (RBM33) as a previously unrecognized m6A-binding protein that plays a critical role in ALKBH5-mediated mRNA m6A demethylation of a subset of mRNA transcripts by forming a complex with ALKBH5. RBM33 recruits ALKBH5 to its m6A-marked substrate and activates ALKBH5 demethylase activity through the removal of its SUMOylation. We further demonstrate that RBM33 is critical for the tumorigenesis of head-neck squamous cell carcinoma (HNSCC). RBM33 promotes autophagy by recruiting ALKBH5 to demethylate and stabilize DDIT4 mRNA, which is responsible for the oncogenic function of RBM33 in HNSCC cells. Altogether, our study uncovers the mechanism of selectively demethylate m6A methylation of a subset of transcripts during tumorigenesis that may explain demethylation selectivity in other cellular processes, and we showed its importance in the maintenance of tumorigenesis of HNSCC.

A review from biological mapping to computation-based subcellular localization

Subcellular localization is crucial to the study of virus and diseases. Specifically, research on protein subcellular localization can help identify clues between virus and host cells that can aid in the design of targeted drugs. Research on RNA subcellular localization is significant for human diseases (such as Alzheimer's disease, colon cancer, etc.). To date, only reviews addressing subcellular localization of proteins have been published, which are outdated for reference, and reviews of RNA subcellular localization are not comprehensive. Therefore, we collated (the most up-to-date) literature on protein and RNA subcellular localization to help researchers understand changes in the field of protein and RNA subcellular localization. Extensive and complete methods for constructing subcellular localization models have also been summarized, which can help readers understand the changes in application of biotechnology and computer science in subcellular localization research and explore how to use biological data to construct improved subcellular localization models. This paper is the first review to cover both protein subcellular localization and RNA subcellular localization. We urge researchers from biology and computational biology to jointly pay attention to transformation patterns, interrelationships, differences, and causality of protein subcellular localization and RNA subcellular localization.

RNA Overwriting of Cellular mRNA by Cas13b-Directed RNA-Dependent RNA Polymerase of Influenza A Virus

Dysregulation of mRNA processing results in diseases such as cancer. Although RNA editing technologies attract attention as gene therapy for repairing aberrant mRNA, substantial sequence defects arising from mis-splicing cannot be corrected by existing techniques using adenosine deaminase acting on RNA (ADAR) due to the limitation of adenosine-to-inosine point conversion. Here, we report an RNA editing technology called "RNA overwriting" that overwrites the sequence downstream of a designated site on the target RNA by utilizing the RNA-dependent RNA polymerase (RdRp) of the influenza A virus. To enable RNA overwriting within living cells, we developed a modified RdRp by introducing H357A and E361A mutations in the polymerase basic 2 of RdRp and fusing the C-terminus with catalytically inactive Cas13b (dCas13b). The modified RdRp knocked down 46% of the target mRNA and further overwrote 21% of the mRNA. RNA overwriting is a versatile editing technique that can perform various modifications, including addition, deletion, and mutation introduction, and thus allow for repair of the aberrant mRNA produced by dysregulation of mRNA processing, such as mis-splicing.

PIE-seq: identifying RNA-binding protein targets by dual RNA-deaminase editing and sequencing

RNA-binding proteins (RBPs) are essential for gene regulation, but it remains a challenge to identify their RNA targets across cell types. Here we present PIE-Seq to investigate Protein-RNA Interaction with dual-deaminase Editing and Sequencing by conjugating C-to-U and A-to-I base editors to RBPs. We benchmark PIE-Seq and demonstrate its sensitivity in single cells, its application in the developing brain, and its scalability with 25 human RBPs. Bulk PIE-Seq identifies canonical binding features for RBPs such as PUM2 and NOVA1, and nominates additional target genes for most tested RBPs such as SRSF1 and TDP-43/TARDBP. Homologous RBPs frequently edit similar sequences and gene sets in PIE-Seq while different RBP families show distinct targets. Single-cell PIE-PUM2 uncovers comparable targets to bulk samples and applying PIE-PUM2 to the developing mouse neocortex identifies neural-progenitor- and neuron-specific target genes such as App. In summary, PIE-Seq provides an orthogonal approach and resource to uncover RBP targets in mice and human cells.

Reversible Control of RNA Splicing by Photoswitchable Small Molecules

Dynamics are intrinsic to both RNA function and structure. Yet, the available means to precisely provide RNA-based processes with spatiotemporal resolution are scarce. Here, our work pioneers a reversible approach to regulate RNA splicing within primary patient-derived cells by synthetic photoswitches. Our small molecule enables conditional real-time control at mRNA and protein levels. NMR experiments, together with theoretical calculations, photochemical characterization, fluorescence polarization measurements, and living cell-based assays, confirmed light-dependent exon inclusion as well as an increase in the target functional protein. Therefore, we first demonstrated the potential of photopharmacology modulation in splicing, tweaking the current optochemical toolkit. The timeliness on the consolidation of RNA research as the driving force toward therapeutical innovation holds the promise that our approach will contribute to redrawing the vision of RNA.

Programming inactive RNA-binding small molecules into bioactive degraders

Target occupancy is often insufficient to elicit biological activity, particularly for RNA, compounded by the longstanding challenges surrounding the molecular recognition of RNA structures by small molecules. Here we studied molecular recognition patterns between a natural-product-inspired small-molecule collection and three-dimensionally folded RNA structures. Mapping these interaction landscapes across the human transcriptome defined structure-activity relationships. Although RNA-binding compounds that bind to functional sites were expected to elicit a biological response, most identified interactions were predicted to be biologically inert as they bind elsewhere. We reasoned that, for such cases, an alternative strategy to modulate RNA biology is to cleave the target through a ribonuclease-targeting chimera, where an RNA-binding molecule is appended to a heterocycle that binds to and locally activates RNase L1. Overlay of the substrate specificity for RNase L with the binding landscape of small molecules revealed many favourable candidate binders that might be bioactive when converted into degraders. We provide a proof of concept, designing selective degraders for the precursor to the disease-associated microRNA-155 (pre-miR-155), JUN mRNA and MYC mRNA. Thus, small-molecule RNA-targeted degradation can be leveraged to convert strong, yet inactive, binding interactions into potent and specific modulators of RNA function.

FRET probe for detecting two mutations in one EGFR mRNA

Technologies for visualizing and tracking RNA are essential in molecular biology, including in disease-related fields. In this study, we propose a novel probe set (DAt-probe and T-probe) that simultaneously detects two mutations in the same RNA using fluorescence resonance energy transfer (FRET). The DAt-probe carrying the fluorophore Atto488 and the quencher Dabcyl were used to detect a cancer mutation (exon19del), and the T-probe carrying the fluorophore Tamra was used to detect drug resistance mutations (T790M) in epidermal growth factor receptor (EGFR) mRNA. These probes were designed to induce FRET when both mutations were present in the mRNA. Gel electrophoresis confirmed that the two probes could efficiently bind to the mutant mRNA. We measured the FRET ratios using wild-type and double-mutant RNAs and found a significant difference between them. Even in living cells, the FRET probe could visualize mutant RNA. As a result, we conclude that this probe set provides a method for detecting two mutations in the single EGFR mRNA via FRET.

Proteomics Methodologies: The Search of Protein Biomarkers Using Microfluidic Systems Coupled to Mass Spectrometry

Protein biomarkers have been the subject of intensive studies as a target for disease diagnostics and monitoring. Indeed, biomarkers have been extensively used for personalized medicine. In biological samples, these biomarkers are most often present in low concentrations masked by a biologically complex proteome (e.g., blood) making their detection difficult. This complexity is further increased by the needs to detect proteoforms and proteome complexity such as the dynamic range of compound concentrations. The development of techniques that simultaneously pre-concentrate and identify low-abundance biomarkers in these proteomes constitutes an avant-garde approach to the early detection of pathologies. Chromatographic-based methods are widely used for protein separation, but these methods are not adapted for biomarker discovery, as they require complex sample handling due to the low biomarker concentration. Therefore, microfluidics devices have emerged as a technology to overcome these shortcomings. In terms of detection, mass spectrometry (MS) is the standard analytical tool given its high sensitivity and specificity. However, for MS, the biomarker must be introduced as pure as possible in order to avoid chemical noise and improve sensitivity. As a result, microfluidics coupled with MS has become increasingly popular in the field of biomarker discovery. This review will show the different approaches to protein enrichment using miniaturized devices and the importance of their coupling with MS.

The nexus between RNA-binding proteins and their effectors

RNA-binding proteins (RBPs) regulate essentially every event in the lifetime of an RNA molecule, from its production to its destruction. Whereas much has been learned about RNA sequence specificity and general functions of individual RBPs, the ways in which numerous RBPs instruct a much smaller number of effector molecules, that is, the core engines of RNA processing, as to where, when and how to act remain largely speculative. Here, we survey the known modes of communication between RBPs and their effectors with a particular focus on converging RBP-effector interactions and their roles in reducing the complexity of RNA networks. We discern the emerging unifying principles and discuss their utility in our understanding of RBP function, regulation of biological processes and contribution to human disease.

The SARS-CoV-2 UTR’s Intrudes Host RBP’s and Modulates Cellular Splicing

SARS-CoV-2 is a novel coronavirus that causes a potentially fatal respiratory disease known as coronavirus disease (COVID-19) and is responsible for the ongoing pandemic with increasing mortality. Understanding the host-virus interaction involved in SARS-CoV-2 pathophysiology will enhance our understanding of the mechanistic basis of COVID-19 infection. The characterization of post-transcriptional gene regulatory networks, particularly pre-mRNA splicing, and the identification and characterization of host proteins interacting with the 5′ and 3′UTRs of SARS-CoV-2 will improve our understanding of post-transcriptional gene regulation during SARS-CoV-2 pathogenesis. Here, we demonstrate that either SARS-CoV-2 infection or exogenous overexpression of the 5′ and 3’UTRs of the viral genomic RNAs, results in reduced mRNA levels possibly due to modulation of host cell pre-mRNA splicing. Further, we have investigated the potential RNA-binding proteins interacting with the 5′ and 3′UTRs, using in-silico approaches. Our results suggest that 5′ and 3′UTRs indeed interact with many RNA-binding proteins. Our results provide a primer for further investigations into the UTR-mediated regulation of splicing and related molecular mechanisms in host cells.

The uprise of RNA biology in neuroendocrine neoplasms: altered splicing and RNA species unveil translational opportunities

Neuroendocrine neoplasms (NENs) comprise a highly heterogeneous group of tumors arising from the diffuse neuroendocrine system. NENs mainly originate in gastrointestinal, pancreatic, and pulmonary tissues, and despite being rare, show rising incidence. The molecular mechanisms underlying NEN development are still poorly understood, although recent studies are unveiling their genomic, epigenomic and transcriptomic landscapes. RNA was originally considered as an intermediary between DNA and protein. Today, compelling evidence underscores the regulatory relevance of RNA processing, while new RNA molecules emerge with key functional roles in core cell processes. Indeed, correct functioning of the interrelated complementary processes comprising RNA biology, its processing, transport, and surveillance, is essential to ensure adequate cell homeostasis, and its misfunction is related to cancer at multiple levels. This review is focused on the dysregulation of RNA biology in NENs. In particular, we survey alterations in the splicing process and available information implicating the main RNA species and processes in NENs pathology, including their role as biomarkers, and their functionality and targetability. Understanding how NENs precisely (mis)behave requires a profound knowledge at every layer of their heterogeneity, to help improve NEN management. RNA biology provides a wide spectrum of previously unexplored processes and molecules that open new avenues for NEN detection, classification and treatment. The current molecular biology era is rapidly evolving to facilitate a detailed comprehension of cancer biology and is enabling the arrival of personalized, predictive and precision medicine to rare tumors like NENs.

Crosstalk between circRNAs and the PI3K/AKT and/or MEK/ERK signaling pathways in digestive tract malignancy progression

Evidence indicates that circular RNAs (circRNAs) may play an important role in regulating gene expression by binding to miRNAs through miRNA response elements. circRNAs are formed by back-splicing and have a covalently closed structure. The biogenesis of circRNAs also appears to be regulated by certain cell-specific and/or gene-specific mechanisms, and thus some circRNAs are tissue specific and tumor-expression specific. Furthermore, the high stability and tissue specificity of circRNAs may be of value for early diagnosis, survival prediction and precision medicine. This review summarizes current knowledge regarding the classification and functions of circRNAs and the role of circRNAs in regulating the PI3K/AKT and/or MEK/ERK signaling pathways in digestive tract malignancy tumors.

Mass Nanotags Mediate Parallel Amplifications on Nanointerfaces for Multiplexed Profiling of RNAs

Multiplexed profiling of RNAs aids in a comprehensive understanding of multiparameter-defined cellular processes and pathological states. We herein present a mass nanotags-enabled interfacial assembly system (MNTs-AS) with parallel amplification motors for simultaneous assaying of multiple RNAs in biosystems by matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS). Four kinds of MNTs encoding corresponding RNA can be cyclically assembled on magnetic beads by target-triggered catalytic hairpin assembly (CHA) machineries on nanointerfaces, generating multiplexed and amplified characteristic ion signals assigned to target RNAs upon MALDI MS interrogation. By virtue of high sensitivity and multiplexing capability, the MNTs-AS-based MS assay allows precision subtyping of diverse breast cancer cells and their exosomes by multiplexed profiling of miRNA-21, miRNA-373, miRNA-155, and manganese superoxide dismutase mRNA via a single MS inquiry. This method provides a promising tool for unraveling multiple RNA-involved biological events in fundamental research and distinguishing different cancer subtypes in clinical practice.

DeepmRNALoc: A Novel Predictor of Eukaryotic mRNA Subcellular Localization Based on Deep Learning

The subcellular localization of messenger RNA (mRNA) precisely controls where protein products are synthesized and where they function. However, obtaining an mRNA's subcellular localization through wet-lab experiments is time-consuming and expensive, and many existing mRNA subcellular localization prediction algorithms need to be improved. In this study, a deep neural network-based eukaryotic mRNA subcellular location prediction method, DeepmRNALoc, was proposed, utilizing a two-stage feature extraction strategy that featured bimodal information splitting and fusing for the first stage and a VGGNet-like CNN module for the second stage. The five-fold cross-validation accuracies of DeepmRNALoc in the cytoplasm, endoplasmic reticulum, extracellular region, mitochondria, and nucleus were 0.895, 0.594, 0.308, 0.944, and 0.865, respectively, demonstrating that it outperforms existing models and techniques.

RHAU Peptides Specific for Parallel G-Quadruplexes: Potential Applications in Chemical Biology

G-quadruplexes (G4s) are non-canonical nucleic acid structures formed by guanine (G)-rich sequences, which are ubiquitously found in the human genome and transcriptome. Targeting G4s by specific ligands provides a powerful tool to monitor and regulate G4s-associated biological processes. RHAU peptides, derived from the G4-binding motif of "RNA Helicase associated with AU-rich element" (RHAU), have emerged as extraordinary ligands for specific recognition of parallel G4s. This review highlights the significances of recent studies investigating potential applications of the engineered RHAU peptides incorporated to different functional moieties.

Integrative Analysis of Germline Rare Variants in Clear and Non-Clear Cell Renal Cell Carcinoma

IMPORTANCE

RCC encompasses a set of histologically distinct cancers with a high estimated genetic heritability, of which only a portion is currently explained. Previous rare germline variant studies in RCC have usually pooled clear and non-clear cell RCCs and have not adequately accounted for population stratification that may significantly impact the interpretation and discovery of certain candidate risk genes.

OBJECTIVE

To evaluate the enrichment of germline PVs in established cancer-predisposing genes (CPGs) in clear cell and non-clear cell RCC patients compared to cancer-free controls using approaches that account for population stratification and to identify unconventional types of germline RCC risk variants that confer an increased risk of developing RCC.

DESIGN SETTING AND PARTICIPANTS

In 1,436 unselected RCC patients with sufficient data quality, we systematically identified rare germline PVs, cryptic splice variants, and copy number variants (CNVs). From this unselected cohort, 1,356 patients were ancestry-matched with 16,512 cancer-free controls, and gene-level enrichment of rare germline PVs were assessed in 143 CPGs, followed by an investigation of somatic events in matching tumor samples.

MAIN OUTCOMES AND MEASURES

Gene-level burden of rare germline PVs, identification of secondary somatic events accompanying the germline PVs, and characterization of less-explored types of rare germline PVs in RCC patients.

RESULTS

In clear cell RCC (n = 976 patients), patients exhibited significantly higher prevalence of PVs in VHL compared to controls (OR: 39.1, 95% CI: 7.01-218.07, p-value:4.95e-05, q-value:0.00584). In non-clear cell RCC (n = 380 patients), patients carried enriched burden of PVs in FH (OR: 77.9, 95% CI: 18.68-324.97, p-value:1.55e-08, q-value: 1.83e-06) and MET (OR: 1.98e11, 95% CI: 0-inf, p-value: 2.07e-05, q-value: 3.50e-07). In a CHEK2-focused analysis with European cases and controls, clear cell RCC patients (n=906 European patients) harbored nominal enrichment of the previously reported low-penetrance CHEK2 variants, p.Ile157Thr (OR:1.84, 95% CI: 1.00-3.36, p-value:0.049) and p.Ser428Phe (OR:5.20, 95% CI: 1.00-26.40, p-value:0.045) while non-clear cell RCC patients (n=295 European patients) exhibited nominal enrichment of CHEK2 LOF germline PVs (OR: 3.51, 95% CI: 1.10-11.10, p-value: 0.033). RCC patients with germline PVs in FH, MET, and VHL exhibited significantly earlier age of cancer onset compared to patients without any germline PVs in CPGs (Mean: 46.0 vs 60.2 years old, Tukey adjusted p-value < 0.0001), and more than half had secondary somatic events affecting the same gene (n=10/15, 66.7%, 95% CI: 38.7-87.0%). Conversely, patients with rare germline PVs in CHEK2 exhibited a similar age of disease onset to patients without any identified germline PVs in CPGs (Mean: 60.1 vs 60.2 years old, Tukey adjusted p-value: 0.99), and only 30.4% of the patients carried secondary somatic events in CHEK2 (n=7/23, 95% CI: 14.1-53.0%). Finally, rare pathogenic germline cryptic splice variants underexplored in RCC were identified in SDHA and TSC1, and rare pathogenic germline CNVs were found in 18 patients, including CNVs in FH, SDHA, and VHL.

CONCLUSIONS AND RELEVANCE

This systematic analysis supports the existing link between several RCC risk genes and elevated RCC risk manifesting in earlier age of RCC onset. Our analysis calls for caution when assessing the role of germline PVs in CHEK2 due to the burden of founder variants with varying population frequency in different ancestry groups. It also broadens the definition of the RCC germline landscape of pathogenicity to incorporate previously understudied types of germline variants, such as cryptic splice variants and CNVs.