Loss of p300/CBP-associated factor aggravates cardiac remodeling via regulation of CAMKK2 acetylation

Experimental & Molecular Medicine · 2026-04-20

Here we aim to elucidate the role of the p300/CBP-associated factor (PCAF) in pathological cardiac remodeling. Specifically, we explore how PCAF-mediated acetylation of calcium/calmodulin-dependent protein kinase kinase 2 (CAMKK2) influences AMPK signaling, thereby regulating cardiac hypertrophy and dysfunction under pathological stress. A genetically engineered PCAF-knockout (KO) mouse model was generated using the CRISPR-Cas9 system to evaluate the effect of PCAF deficiency on cardiac remodeling induced by isoproterenol infusion and transverse aortic constriction (TAC). PCAF deficiency significantly aggravated cardiac enlargement with features of eccentric hypertrophy, as demonstrated by histological analysis and echocardiography. To determine these phenotypes were cardiomyocyte specific, we generated a cardiomyocyte-specific conditional KO model, which also showed a dilated cardiomyopathy-like phenotype similar to that of the global-KO mice. Transcriptomic analysis of TAC-operated hearts from wild-type and KO mice revealed enrichment of pathways related to mitochondrial function and energy homeostasis. Mechanistically, PCAF directly acetylated CAMKK2, promoting its activation and the subsequent phosphorylation of AMP-activated protein kinase α (AMPKα) at Thr172, a critical step in maintaining metabolic balance under stresses. These signaling alterations were also observed in the hearts of PCAF-KO hearts subjected to isoproterenol administration or TAC. Pharmacological activation of PCAF with SPV106 effectively attenuated TAC-induced cardiac remodeling, preserving cardiac structure and function. Collectively, these findings identify PCAF as a pivotal regulator of pathological cardiac remodeling through modulation of the CAMKK2-AMPK signaling axis. Loss of PCAF exacerbates stress-induced cardiac hypertrophy and dysfunction, highlighting its potential as a therapeutic target to preserve cardiac function and counteract stress-induced remodeling.

EpGAT: integrating epigenetics and 3D genome structure to predict alternative splicing and polyadenylation

Briefings in Bioinformatics · 2026-02-11

Understanding how the 3D structure of the genome influences gene regulation is a growing area of interest, particularly in the context of alternative post-transcriptional regulatory events such as alternative splicing (AS) and alternative polyadenylation (APA). These processes are essential for generating transcript and protein diversity, and they are tightly coordinated with transcription. However, despite their biological importance, the relationship between chromatin interactions and alternative pre-messenger RNA regulation remains poorly understood. This gap largely stems from a lack of computational tools capable of integrating structural genomic data with RNA processing dynamics. Exploring how chromatin interactions and epigenetic landscapes shape these events is essential for uncovering the multilayered regulation of gene expression. To bridge this gap, we present EpGAT, a graph attention network-based model that integrates epigenetic read coverage and chromatin interaction data to predict and quantify AS and APA events. By explicitly modeling the spatial organization of the genome, EpGAT captures the regulatory influence of chromatin looping and long-range genomic interactions on RNA processing. The model's predictions are validated through rigorous cross-cell line and cross-chromosome evaluations, affirming its generalizability and reliability. Beyond prediction, EpGAT offers interpretability by tracing learned parameters back to genomic features, enabling the identification of active enhancers, mapping promoter-enhancer connectivity, and pinpointing the epigenetic factors most critical to specific RNA processing events. These capabilities make EpGAT a powerful tool for dissecting the complex interplay between genome architecture and transcriptomic regulation. More broadly, it provides a generalizable framework for multiple tasks to study the link between 3D genome organization, epigenetic signals, and RNA processing.

Cytoplasmic RBMX coordinates selective mRNA translation to suppress senescence in cancer

Research Square · 2026-02-24

PolyA-GLM: A comprehensive framework for <i>De novo</i> polyadenylation site prediction using genome language models

Computational and Structural Biotechnology Journal · 2025-12-17 · 1 citations

Polyadenylation sites (poly(A) sites) play a key role in the post-transcriptional regulation of gene expression. Accurate prediction of poly(A) sites is essential for identifying RNA processing defects associated with cancer and developmental disorders. Traditional approaches based on sequence motifs and experimental validation often struggle to generalize across different cell types and species. To address this limitation, we investigate the use of genome language models (GLMs) for poly(A) site prediction, leveraging their ability to capture long-range dependencies within genomic sequences. Specifically, we evaluate three state-of-the-art GLMs, DNABERT-2, Nucleotide Transformer, and HyenaDNA, using both few-shot classification and fine-tuning strategies. These models effectively recognize canonical polyadenylation signals (PASs) (i.e., AATAAA or other variants) and their spatial relationship (10-30 bp) to cleavage sites, with HyenaDNA achieving an AUC of 0.751 in the few-shot setting and improved performance after fine-tuning. We further validate model interpretability through systematic signal perturbation experiments, confirming their capacity to detect canonical PASs. Additionally, we propose a token-level classification approach for precise position-wise poly(A) site identification across extended gene regions. Finally, we present PolyA-GLM, an end-to-end pipeline for discovering novel poly(A) sites, highlighting the potential of GLMs to reveal regulatory elements overlooked by conventional methods. Overall, this work demonstrates the promise of GLMs in advancing our understanding of RNA processing and regulatory element discovery.

IPScan: Detecting novel intronic PolyAdenylation events with RNA-seq data

PLoS Computational Biology · 2025-11-11 · 2 citations

Intronic PolyAdenylation (IPA) is an important post-transcriptional mechanism that can alter transcript coding potential by truncating translation regions, thereby increasing transcriptome and proteome diversity. This process generates novel protein isoforms with altered peptide sequences, some of which are implicated in disease progression, including cancer. Truncated proteins may lose tumor-suppressive functions, contributing to oncogenesis. Despite advancements in Alternative PolyAdenylation (APA) analysis using RNA-seq, detecting and quantifying novel IPA events remains challenging. To address this, we developed IPScan, a computational pipeline for precise IPA event identification, quantification, and visualization. IPScan has been benchmarked against existing methods using simulated data, different human and mouse cell lines, and TCGA (The Cancer Genome Atlas) breast cancer datasets. Differential IPA events under different biological conditions were quantified and validated via qPCR.

Regulation of transcriptome plasticity by mTOR signaling pathway

Experimental & Molecular Medicine · 2025-08-14 · 7 citations

The mechanistic target of rapamycin (mTOR) pathway, long recognized for its critical roles in cellular metabolism and growth, is increasingly appreciated for its regulatory impact on the transcriptome. Recent insights into mTOR's regulation of alternative splicing and polyadenylation reveal a sophisticated mechanism by which mTOR influences RNA processing to affect the proteome's diversity and functionality. Here, in this Review, we delve into the multifaceted roles of mTOR in modulating transcriptome plasticity, highlighting its influence beyond traditional functions such as protein synthesis and cell growth. By examining the latest findings, we explore how mTOR-mediated transcriptome plasticity plays a pivotal role in cellular adaptation and pathogenesis. Studies indicate that mTOR modulation of RNA processing pathways enables cells to respond dynamically to environmental and metabolic cues, thereby altering protein function and cellular behavior in a context-dependent manner. This capability is crucial for both normal physiological responses and the development of disease. The Review also discusses the implications of these findings for understanding complex biological systems and diseases, particularly cancer, where mTOR's regulation of transcript diversity could drive tumor heterogeneity and treatment resistance. As research continues to uncover the extensive influence of mTOR on RNA processing, it becomes clear that a comprehensive understanding of these mechanisms is essential for the development of targeted therapies and the prediction of their outcomes in clinical settings.

Exploring transcriptome plasticity at the intersection of cell signaling, metabolism and computational biology

Experimental & Molecular Medicine · 2025-08-14

Over the past decade, our understanding of the transcriptome has deepened notably, revealing unprecedented layers of complexity and regulation beyond the canonical view of gene expression.Far from being a static intermediary between DNA and proteins, the transcriptome is now recognized as a dynamic and responsive entity, shaped by posttranscriptional modifications, environmental cues, metabolic states and signaling networks.This special review section, 'Advances in transcriptomics: cell signaling, metabolism, RNA regulation and computational insights', brings together four timely and comprehensive articles that explore distinct yet interconnected dimensions of transcriptome plasticity. MTOR AS A MASTER REGULATOR OF RNA PROCESSINGThe review by Yong et al. explores a rapidly emerging frontier in transcriptome biology: how the mechanistic target of rapamycin (mTOR) pathway governs RNA processing events such as alternative splicing and polyadenylation.Long known for its role in regulating translation and cell growth 1 , mTOR is now understood to extend its influence deep into the transcriptome.The authors provide a detailed examination of how mTOR signaling modulates transcriptome plasticity, affecting the isoform output of the genome and potentially altering protein localization, stability and interaction networks.What distinguishes this review is its emphasis on contextdependent transcript remodeling.mTOR-mediated shifts in isoform expression are shown to contribute to adaptive responses and disease phenotypes-including tumor heterogeneity and treatment resistance 2-6 .This review also proposes that future work must move beyond transcript quantification to functional interrogation of isoform-specific roles, particularly in mTOR-driven disease contexts.

Alternatively-Spliced CAMKK2 isoforms drive differential metabolic stress response and the regulation of ferroptosis

bioRxiv (Cold Spring Harbor Laboratory) · 2025-05-15

Abstract Calcium/Calmodulin-dependent protein kinase kinase 2 (CAMKK2) is a multifunctional kinase that regulates metabolic processes by phosphorylating downstream targets. CAMKK2 is expressed as several highly similar protein isoforms, although the specific functions of these individual isoforms remain largely unexplored. These isoforms have been shown to display tissue-specific expression patterns, suggesting unique roles in distinct cellular contexts. In this study, we investigated the biochemical and functional relevance of CAMKK2 isoforms, LF and SF, in the context of glucose metabolism. Co-immunoprecipitation experiments revealed that the LF isoform preferentially binds the adaptor protein 14-3-3, while the SF isoform interacts with Calmodulin. Furthermore, the interaction between SF and Calmodulin was enhanced upon glucose starvation, whereas this interaction was not observed for LF. To assess their functional significance, we generated doxycycline-inducible, isoform-specific HeLa cell lines. Under low glucose conditions, cells expressing the LF isoform failed to activate AMPK, while cells expressing the SF isoform exhibited robust increase in AMPK phosphorylation. Moreover, LF-expressing cells accumulated higher levels of reactive oxygen species, upregulated ferroptosis-related genes via BACH1/NRF2, and displayed increased cell death compared to SF-expressing cells. Collectively, these findings demonstrate that CAMKK2 isoforms exhibit differential selectivity for protein partners and mediate distinct downstream signaling pathways, impacting metabolism in cancer.

Computational methods for alternative polyadenylation and splicing in post-transcriptional gene regulation

Experimental & Molecular Medicine · 2025-08-14 · 6 citations

Alternative polyadenylation (APA) and alternative splicing (AS) are essential post-transcriptional mechanisms that enhance transcriptome diversity and regulate gene expression across various biological contexts. APA modifies transcript stability, localization and translation efficiency by generating mRNA isoforms with distinct 3' untranslated regions or coding sequences, while AS alters protein diversity through exon inclusion or exclusion. The advent of high-throughput RNA sequencing has driven the development of computational methods to systematically identify, quantify and analyze APA and AS events, shedding light on their regulatory roles in normal physiology and disease. These methods can be broadly categorized based on their underlying methodologies and the data types they process, with specialized tools designed for both bulk and single-cell RNA sequencing. Here, in this Review, we provide a comprehensive overview of computational strategies for APA and AS detection and differential analysis, highlighting their advantages, limitations and applications. In addition, we explore techniques specifically tailored for single-cell RNA sequencing. We enhance our understanding of APA and AS regulation across diverse biological systems by summarizing recent advancements, offering new insights into gene regulation at both the population and single-cell levels.

The role of Ephexin1 in translation and mTOR-targeted cancer therapy

Experimental & Molecular Medicine · 2025-08-25 · 2 citations

Ephexin1, also known as neuronal guanine nucleotide exchange factor (NGEF), plays a key role in axon guidance and synaptic homeostasis. However, our recent studies have revealed a critical role for Ephexin1 in the pathogenesis of colon and lung cancers. Here we used multidisciplinary approaches to further explore the underlying mechanisms of Ephexin1 in cancer progression. We discovered that Ephexin1 is essential for promoting polysome formation by coordinating the assembly of translation initiation complexes. Our investigations into gene expression affected by Ephexin1 deficiency showed that Ephexin1 specifically promotes the translation of genes containing 5'-terminal oligopyrimidine (TOP) or 5'-TOP-like motifs, identifying Ephexin1 as a key mediator of mTOR-regulated translation. Importantly, we found that the efficacy of mTOR inhibitors in treating lung cancer was significantly enhanced in a mouse xenograft model when Ephexin1 was deficient. This suggests that Ephexin1 could serve as a synthetic lethality target for mTORC1-targeting therapeutics in cancer treatment. Our findings provide mechanistic insights into the role of Ephexin1 in cancer pathogenesis and highlight its potential as a therapeutic target for improving current cancer treatment strategies.