The circular RNA circHelz enhances cardiac fibrosis by facilitating the nuclear translocation of YAP1

Circular RNA regulatory role in pathological cardiac remodelling

Cardiac remodelling involves structural, cellular and molecular alterations in the heart after injury, resulting in progressive loss of heart function and ultimately leading to heart failure. Circular RNAs (circRNAs) are a recently rediscovered class of non-coding RNAs that play regulatory roles in the pathogenesis of cardiovascular diseases, including heart failure. Thus, a more comprehensive understanding of the role of circRNAs in the processes governing cardiac remodelling may set the ground for the development of circRNA-based diagnostic and therapeutic strategies. In this review, the current knowledge about circRNA origin, conservation, characteristics and function is summarized. Bioinformatics and wet-lab methods used in circRNA research are discussed. The regulatory function of circRNAs in cardiac remodelling mechanisms such as cell death, cardiomyocyte hypertrophy, inflammation, fibrosis and metabolism is highlighted. Finally, key challenges and opportunities in circRNA research are discussed, and orientations for future work to address the pharmacological potential of circRNAs in heart failure are proposed.

Circular RNA: A new expectation for cardiovascular diseases

Circular RNA (circRNA) is a class of RNA with the 5' and 3' ends connected covalently to form a closed loop structure and characterized by high stability, conserved sequences and tissue specificity, which is caused by special reverse splicing methods. Currently, it has become a hot spot for research. With the discovery of its powerful regulatory functions and roles, the molecular mechanisms and future value of circRNA in participating in and regulating biological and pathological processes are becoming increasingly apparent. Among them is the increasing prevalence of cardiovascular diseases (CVDs). Many studies have elucidated that circRNA plays a crucial role in the development and progression of CVDs. Therefore, circRNA shows its advantages and brilliant expectations in the field of CVDs. In this review, we describe the biogenesis, bioinformatics detection and function of circRNA and discuss the role of circRNA and its effects on CVDs, including atherosclerosis, myocardial infarction, cardiac hypertrophy and heart failure, myocardial fibrosis, cardiac senescence, pulmonary hypertension, and diabetic cardiomyopathy by different mechanisms. That shows circRNA advantages and brilliant expectations in the field of CVDs.

Exploring the Multifaceted Biologically Relevant Roles of circRNAs: From Regulation, Translation to Biomarkers

CircRNAs are a category of regulatory RNAs that have garnered significant attention in the field of regulatory RNA research due to their structural stability and tissue-specific expression. Their circular configuration, formed via back-splicing, results in a covalently closed structure that exhibits greater resistance to exonucleases compared to linear RNAs. The distinctive regulation of circRNAs is closely associated with several physiological processes, as well as the advancement of pathophysiological processes in several human diseases. Despite a good understanding of the biogenesis of circular RNA, details of their biological roles are still being explored. With the steady rise in the number of investigations being carried out regarding the involvement of circRNAs in various regulatory pathways, understanding the biological and clinical relevance of circRNA-mediated regulation has become challenging. Given the vast landscape of circRNA research in the development of the heart and vasculature, we evaluated cardiovascular system research as a model to critically review the state-of-the-art understanding of the biologically relevant functions of circRNAs. We conclude the review with a discussion of the limitations of current functional studies and provide potential solutions by which these limitations can be addressed to identify and validate the meaningful and impactful functions of circRNAs in different physiological processes and diseases.

A Bayesian noisy logic model for inference of transcription factor activity from single cell and bulk transcriptomic data

The advent of high-throughput sequencing has made it possible to measure the expression of genes at relatively low cost. However, direct measurement of regulatory mechanisms, such as transcription factor (TF) activity is still not readily feasible in a high-throughput manner. Consequently, there is a need for computational approaches that can reliably estimate regulator activity from observable gene expression data. In this work, we present a noisy Boolean logic Bayesian model for TF activity inference from differential gene expression data and causal graphs. Our approach provides a flexible framework to incorporate biologically motivated TF-gene regulation logic models. Using simulations and controlled over-expression experiments in cell cultures, we demonstrate that our method can accurately identify TF activity. Moreover, we apply our method to bulk and single cell transcriptomics measurements to investigate transcriptional regulation of fibroblast phenotypic plasticity. Finally, to facilitate usage, we provide user-friendly software packages and a web-interface to query TF activity from user input differential gene expression data: https://umbibio.math.umb.edu/nlbayes/.

Bioactive Compounds and Cardiac Fibrosis: Current Insight and Future Prospect

Cardiac fibrosis is a pathological condition characterized by excessive deposition of collagen and other extracellular matrix components in the heart. It is recognized as a major contributor to the development and progression of heart failure. Despite significant research efforts in characterizing and identifying key molecular mechanisms associated with myocardial fibrosis, effective treatment for this condition is still out of sight. In this regard, bioactive compounds have emerged as potential therapeutic antifibrotic agents due to their anti-inflammatory and antioxidant properties. These compounds exhibit the ability to modulate fibrogenic processes by inhibiting the production of extracellular matrix proteins involved in fibroblast to myofibroblast differentiation, or by promoting their breakdown. Extensive investigation of these bioactive compounds offers new possibilities for preventing or reducing cardiac fibrosis and its detrimental consequences. This comprehensive review aims to provide a thorough overview of the mechanisms underlying cardiac fibrosis, address the limitations of current treatment strategies, and specifically explore the potential of bioactive compounds as therapeutic interventions for the treatment and/or prevention of cardiac fibrosis.

A Bayesian Noisy Logic Model for Inference of Transcription Factor Activity from Single Cell and Bulk Transcriptomic Data

The advent of high-throughput sequencing has made it possible to measure the expression of genes at relatively low cost. However, direct measurement of regulatory mechanisms, such as Transcription Factor (TF) activity is still not readily feasible in a high-throughput manner. Consequently, there is a need for computational approaches that can reliably estimate regulator activity from observable gene expression data. In this work, we present a noisy Boolean logic Bayesian model for TF activity inference from differential gene expression data and causal graphs. Our approach provides a flexible framework to incorporate biologically motivated TF-gene regulation logic models. Using simulations and controlled over-expression experiments in cell cultures, we demonstrate that our method can accurately identify TF activity. Moreover, we apply our method to bulk and single cell transcriptomics measurements to investigate transcriptional regulation of fibroblast phenotypic plasticity. Finally, to facilitate usage, we provide user-friendly software packages and a web-interface to query TF activity from user input differential gene expression data: https://umbibio.math.umb.edu/nlbayes/.