Search Results (27)

N6-methyladenosine (m6A) represents the most common and thoroughly investigated RNA modification and exerts essential functions in regulating gene expression through influencing the RNA stability, the translation efficiency, alternative splicing, and nuclear export processes. The rapid development of high-throughput sequencing approaches, including miCLIP and MeRIP-seq, has profoundly transformed epitranscriptomics research. These techniques facilitate the detailed transcriptome-wide profiling of m6A modifications, shedding light on their crucial roles in diverse biological pathways. This review comprehensively examines the identification, mechanisms of regulation, and functional consequences of m6A modifications. It emphasizes their critical roles in physiological contexts, encompassing immune function, neuronal development, and the differentiation of stem cells. Additionally, the review discusses the contributions of m6A dysregulation to pathological conditions, including cancer, neurodegenerative diseases, and disorders of metabolism. We also discuss the development and application of machine-learning algorithms for m6A site prediction, emphasizing the integration of sequence-based, structural, and evolutionary conservation features to enhance the predictive accuracy. Furthermore, the potential of applying the findings from m6A research in precision medicine and drug development is examined. By synthesizing the current knowledge and emerging trends, this review aims to provide a comprehensive understanding of m6A biology and its translational potential, offering new perspectives for future research and therapeutic innovation. Full article

The primary function of microglia is to maintain brain homeostasis. In neurodegenerative diseases like Alzheimer’s, microglia contribute to neurotoxicity and inflammation. In this study, we exposed neonatal murine primary microglial cultures to stimuli mimicking pathogens, injury, or toxins. Treatment with benzoyl ATP (bzATP) and lipopolysaccharide (LPS) triggered a coordinated increase in interleukin and chemokine expression. We analyzed statistically significant differentially expressed microRNAs (DEMs) at 3 and 8 h post-activation, identifying 33 and 57 DEMs, respectively. Notably, miR-155, miR-132, miR-3473e, miR-222, and miR-146b showed strong temporal regulation, while miR-3963 was sharply downregulated by bzATP. These DEMs regulate inflammatory pathways, including TNFα and NFκB signaling. We also examined the effect of ladostigil, a neuroprotective agent known to reduce oxidative stress and inflammation. At 8 h post-activation, ladostigil induced upregulation of anti-inflammatory miRNAs, such as miR-27a, miR-27b, and miR-23b. Our findings suggest that miRNA profiles reflect microglial responses to inflammatory cues and that ladostigil modulates these responses. This model of controlled microglial activation offers a powerful tool with which to study inflammation in the aging brain and the progression of neurodegenerative diseases. Full article

Background: Alternative Splicing (AS) is a post-transcriptional process that allows a single RNA to produce different mRNA variants and, in some cases, multiple proteins. Various processes, many yet to be discovered, regulate AS. This study focuses on regulation by RNA-binding proteins (RBPs), which are not only crucial for splicing regulation but also linked to cancer prognosis and are emerging as therapeutic targets for cancer treatment. CLIP-seq experiments help identify where RBPs bind on nascent transcripts, potentially revealing changes in splicing status that suggest causal relationships. Selecting specific RBPs for CLIP-seq experiments is often driven by a priori hypotheses. Results: We developed an algorithm to detect RBPs likely related to splicing changes between conditions by integrating several CLIP-seq databases and a differential splicing detection algorithm. This work refines a previous study by improving splicing event prediction, testing different enrichment statistics, and performing additional validation experiments. The new method provides more accurate predictions and is included in the Bioconductor package EventPointer 3.14. We tested the algorithm in four experiments involving knockdowns of seven different RBPs. The algorithm accurately assessed the statistical significance of these RBPs using only splicing alterations. Additionally, we applied the algorithm to study sixteen cancer types from The Cancer Genome Atlas (TCGA) and three from TARGET. We identified relationships between RBPs and various cancer types, including alterations in CREBBP and MBNL2 in adenocarcinomas of the lung, liver, prostate, rectum, stomach, and colon. Some of these findings are validated in the literature, while others are novel. Conclusions: The developed algorithm enhances the ability to predict and understand RBP-related splicing changes, offering more accurate predictions and novel insights into cancer-related splicing alterations. This work highlights the potential of RBPs as therapeutic targets and contributes to the broader understanding of their roles in cancer biology. Full article

Human action recognition has become crucial in computer vision, with growing applications in surveillance, human–computer interaction, and healthcare. Traditional approaches often use broad feature representations, which may miss subtle variations in timing and movement within action sequences. Our proposed One-to-Many Hierarchical Contrastive Learning (OTM-HC) framework maps the input into multi-layered feature vectors, creating a hierarchical contrast representation that captures various granularities within a human skeleton sequence temporal and spatial domains. Using sequence-to-sequence (Seq2Seq) transformer encoders and downsampling modules, OTM-HC can distinguish between multiple levels of action representations, such as instance, domain, clip, and part levels. Each level contributes significantly to a comprehensive understanding of action representations. The OTM-HC model design is adaptable, ensuring smooth integration with advanced Seq2Seq encoders. We tested the OTM-HC framework across four datasets, demonstrating improved performance over state-of-the-art models. Specifically, OTM-HC achieved improvements of 0.9% and 0.6% on NTU60, 0.4% and 0.7% on NTU120, and 0.7% and 0.3% on PKU-MMD I and II, respectively, surpassing previous leading approaches across these datasets. These results showcase the robustness and adaptability of our model for various skeleton-based action recognition tasks. Full article

Influenza virus infection poses a great threat to human health globally each year. Non-coding RNAs (ncRNAs) in the human genome have been reported to participate in the replication process of the influenza virus, among which there are still many unknowns about Long Intergenic Non-Coding RNAs (LincRNAs) in the cell cycle of viral infections. Here, we observed an increased expression of Linc01615 in A549 cells upon influenza virus PR8 infection, accompanied by the successful activation of the intracellular immune system. The knockdown of Linc01615 using the shRNAs promoted the proliferation of the influenza A virus, and the intracellular immune system was inhibited, in which the expressions of IFN-β, IL-28A, IL-29, ISG-15, MX1, and MX2 were decreased. Predictions from the catRAPID website suggested a potential interaction between Linc01615 and DHX9. Also, knocking down Linc01615 promoted influenza virus proliferation. The subsequent transcriptome sequencing results indicated a decrease in Linc01615 expression after influenza virus infection when DHX9 was knocked down. Further analysis through cross-linking immunoprecipitation and high-throughput sequencing (CLIP-seq) in HEK293 cells stably expressing DHX9 confirmed the interaction between DHX9 and Linc01615. We speculate that DHX9 may interact with Linc01615 to partake in influenza virus replication and that Linc01615 helps to activate the intracellular immune system. These findings suggest a deeper connection between DHX9 and Linc01615, which highlights the significant role of Linc01615 in the influenza virus replication process. This research provides valuable insights into understanding influenza virus replication and offers new targets for preventing influenza virus infections. Full article

RNA-binding proteins (RBPs) play an important role in regulating biological processes, such as gene regulation. Understanding their behaviors, for example, their binding site, can be helpful in understanding RBP-related diseases. Studies have focused on predicting RNA binding by means of machine learning algorithms including deep convolutional neural network models. One of the integral parts of modeling deep learning is achieving optimal hyperparameter tuning and minimizing a loss function using optimization algorithms. In this paper, we investigate the role of optimization in the RBP classification problem using the CLIP-Seq 21 dataset. Three optimization methods are employed on the RNA–protein binding CNN prediction model; namely, grid search, random search, and Bayesian optimizer. The empirical results show an AUC of 94.42%, 93.78%, 93.23% and 92.68% on the ELAVL1C, ELAVL1B, ELAVL1A, and HNRNPC datasets, respectively, and a mean AUC of 85.30 on 24 datasets. This paper’s findings provide evidence on the role of optimizers in improving the performance of RNA–protein binding prediction. Full article

Y-box-binding proteins (YB proteins) are multifunctional DNA- and RNA-binding proteins that play an important role in the regulation of gene expression. The high homology of their cold shock domains and the similarity between their long, unstructured C-terminal domains suggest that Y-box-binding proteins may have similar functions in a cell. Here, we consider the functional interchangeability of the somatic YB proteins YB-1 and YB-3. RNA-seq and Ribo-seq are used to track changes in the mRNA abundance or mRNA translation in HEK293T cells solely expressing YB-1, YB-3, or neither of them. We show that YB proteins have a dual effect on translation. Although the expression of YB proteins stimulates global translation, YB-1 and YB-3 inhibit the translation of their direct CLIP-identified mRNA targets. The impact of YB-1 and YB-3 on the translation of their mRNA targets is similar, which suggests that they can substitute each other in inhibiting the translation of their mRNA targets in HEK293T cells. Full article

RNA-binding proteins are vital regulators in numerous biological processes. Their disfunction can result in diverse diseases, such as cancer or neurodegenerative disorders, making the prediction of their binding sites of high importance. Deep learning (DL) has brought about a revolution in various biological domains, including the field of protein–RNA interactions. Nonetheless, several challenges persist, such as the limited availability of experimentally validated binding sites to train well-performing DL models for the majority of proteins. Here, we present a novel training approach based on transfer learning (TL) to address the issue of limited data. Employing a sophisticated and interpretable architecture, we compare the performance of our method trained using two distinct approaches: training from scratch (SCR) and utilizing TL. Additionally, we benchmark our results against the current state-of-the-art methods. Furthermore, we tackle the challenges associated with selecting appropriate input features and determining optimal interval sizes. Our results show that TL enhances model performance, particularly in datasets with minimal training data, where satisfactory results can be achieved with just a few hundred RNA binding sites. Moreover, we demonstrate that integrating both sequence and evolutionary conservation information leads to superior performance. Additionally, we showcase how incorporating an attention layer into the model facilitates the interpretation of predictions within a biologically relevant context. Full article

As a master regulator in cells, RNA-binding protein (RBP) plays critical roles in organismal development, metabolism and various diseases. It regulates gene expression at various levels mostly by specific recognition of target RNA. The traditional CLIP-seq method to detect transcriptome-wide RNA targets of RBP is less efficient in yeast due to the low UV transmissivity of their cell walls. Here, we established an efficient HyperTRIBE (Targets of RNA-binding proteins Identified By Editing) in yeast, by fusing an RBP to the hyper-active catalytic domain of human RNA editing enzyme ADAR2 and expressing the fusion protein in yeast cells. The target transcripts of RBP were marked with new RNA editing events and identified by high-throughput sequencing. We successfully applied HyperTRIBE to identifying the RNA targets of two yeast RBPs, KHD1 and BFR1. The antibody-free HyperTRIBE has competitive advantages including a low background, high sensitivity and reproducibility, as well as a simple library preparation procedure, providing a reliable strategy for RBP target identification in Saccharomyces cerevisiae. Full article

Heart failure is the final stage of various cardiovascular diseases and seriously threatens human health. Increasing mediators have been found to be involved in the pathogenesis of heart failure, including the RNA binding protein RBFox2. It participates in multiple aspects of the regulation of cardiac function and plays a critical role in the process of heart failure. However, how RBFox2 itself is regulated remains unclear. Here, we dissected transcriptomic signatures, including mRNAs and miRNAs, in a mouse model of heart failure after TAC surgery. A global analysis showed that an asymmetric alternation in gene expression and a large-scale upregulation of miRNAs occurred in heart failure. An association analysis revealed that the latter not only contributed to the degradation of numerous mRNA transcripts, but also suppressed the translation of key proteins such as RBFox2. With the aid of Ago2 CLIP-seq data, luciferase assays verified that RBFox2 was targeted by multiple miRNAs, including Let-7, miR-16, and miR-200b, which were significantly upregulated in heart failure. The overexpression of these miRNAs suppressed the RBFox2 protein and its downstream effects in cardiomyocytes, which was evidenced by the suppressed alternative splicing of the Enah gene and impaired E–C coupling via the repression of the Jph2 protein. The inhibition of Let-7, the most abundant miRNA family targeting RBFox2, could restore the RBFox2 protein as well as its downstream effects in dysfunctional cardiomyocytes induced by ISO treatment. In all, these findings revealed the molecular mechanism leading to RBFox2 depression in heart failure, and provided an approach to rescue RBFox2 through miRNA inhibition for the treatment of heart failure. Full article

Background: The gonads of Chrysemys picta, a turtle with temperature-dependent sex determination (TSD), exhibit differential DNA methylation between males and females, but whether the same is true in somatic tissues remains unknown. Such differential DNA methylation in the soma would provide a non-lethal sex diagnostic for TSD turtle hatchings who lack visually detectable sexual dimorphism when young. Methods: Here, we tested multiple approaches to study DNA methylation in tail clips of Chrysemys picta hatchlings, to identify differentially methylated candidate regions/sites that could serve as molecular sex markers To detect global differential methylation in the tails we used methylation-sensitive ELISA, and to test for differential local methylation we developed a novel hybrid method by sequencing immunoprecipitated and bisulfite converted DNA (MeDIP-BS-seq) followed by PCR validation of candidate regions/sites after digestion with a methylation-sensitive restriction enzyme. Results: We detected no global differences in methylation between males and females via ELISA. While we detected inter-individual variation in DNA methylation in the tails, this variation was not sexually dimorphic, in contrast with hatchling gonads. Conclusions: Results highlight that differential DNA methylation is tissue-specific and plays a key role in gonadal formation (primary sexual development) and maintenance post-hatching, but not in the somatic tail tissue. Full article

Cisplatin (CP), which is a conventional cancer chemotherapeutic drug, induces apoptosis by modulating a diverse array of gene regulatory mechanisms. However, cisplatin-mediated changes in the m⁶A methylome are unknown. We employed an m⁶A miCLIP-seq approach to investigate the effect of m⁶A methylation marks under cisplatin-mediated apoptotic conditions on HeLa cells. Our high-resolution approach revealed numerous m⁶A marks on 972 target mRNAs with an enrichment on 132 apoptotic mRNAs. We tracked the fate of differentially methylated candidate mRNAs under METTL3 knockdown and cisplatin treatment conditions. Polysome profile analyses revealed perturbations in the translational efficiency of PMAIP1 and PHLDA1 transcripts. Congruently, PMAIP1 amounts were dependent on METTL3. Additionally, cisplatin-mediated apoptosis was sensitized by METTL3 knockdown. These results suggest that apoptotic pathways are modulated by m⁶A methylation events and that the METTL3–PMAIP1 axis modulates cisplatin-mediated apoptosis in HeLa cells. Full article

Transcriptome-wide analysis of RNA-binding partners is commonly achieved using UV crosslinking and immunoprecipitation (CLIP). Individual-nucleotide-resolution CLIP (iCLIP)enables identification of the specific position of the protein–RNA interaction. In addition to RNA-binding proteins (RBPs), microRNA (miRNA)–mRNA interactions also play a crucial role in the regulation of gene expression. Argonaute-2 (Ago2) mediates miRNA binding to a multitude of mRNA target sites, enabling the identification of miRNA–mRNA interactions by employing modified Ago2-CLIP protocols. Here, we describe an Ago2-specific CLIP protocol optimized for the use of small quantities of cell material, targeting endogenous Ago2 while avoiding possible methodological biases such as metabolic labeling or Ago2 overexpression and applying the latest advances in CLIP library preparation, the iCLIP2 protocol. In particular, we focus on the optimization of lysis conditions and improved radioactive labeling of the 5′ end of the miRNA. Full article

The RNA cytosine C5 methyltransferase NSUN2 has a variety of RNA substrates and plays an important role in mRNA metabolism. NSUN2 binds to specific sequences enriched in exosomal mRNAs, suggesting its possible involvement in the sorting of mRNAs into exosomes. We applied the photoactivatable.4-thiouridine-enhanced cross-linking and immunoprecipitation assay involving high-throughput RNA sequencing (RNA-seq) to HEK293T cells to determine NSUN2 mRNA targets. NSUN2 cross-linking sites were found in more than one hundred relatively abundant mRNAs with a high GC content and a pronounced secondary structure. Then, utilizing RNA-seq for the total and polysome-associated mRNA from HEK293T cells with and without the knockdown of NSUN2, we identified differentially expressed genes, as well as genes with altered translational efficiency (GATEs). It turned out that the up-regulated GATE mRNAs were much shorter on average than the down-regulated ones, and their GC content was higher; moreover, they contained motifs with C residues located in GC-rich environments. Our findings reveal the specific features of mRNAs that make them potential targets for NSUN2 and expand our understanding of the role of NSUN2 in controlling translation and, possibly, in mRNA sorting into exosomes implemented through the methylation of cytosine residues. Full article

Rift Valley fever virus (RVFV) is a negative-sense, tripartite RNA virus that is endemic to Africa and the Arabian Peninsula. It can cause severe disease and mortality in humans and domestic livestock and is a concern for its potential to spread more globally. RVFV’s nucleocapsid protein (N) is an RNA-binding protein that is necessary for viral transcription, replication, and the production of nascent viral particles. We have conducted crosslinking, immunoprecipitation, and sequencing (CLIP-seq) to characterize N interactions with host and viral RNAs during infection. In parallel, to precisely measure intracellular N levels, we employed multiple reaction monitoring mass spectrometry (MRM-MS). Our results show that N binds mostly to host RNAs at early stages of infection, yielding nascent virus particles of reduced infectivity. The expression of N plateaus 10 h post-infection, whereas the intracellular viral RNA concentration continues to increase. Moreover, the virions produced later in infection have higher infectivity. Taken together, the detailed examination of these N–RNA interactions provides insight into how the regulated expression of N and viral RNA produces both infectious and incomplete, noninfectious particles. Full article