Network model integrated with multi-omic data predicts MBNL1 signals that drive myofibroblast activation

Functions of the Muscleblind-like protein family and their role in disease

Conserved proteins are characterized by their functions remaining nearly constant throughout evolutionary history, both vertically through time and horizontally across species. In this review, we focus on a class of conserved proteins known as the Muscleblind-like (MBNL) family. As RNA-binding proteins, MBNL family members interact with pre-mRNAs through evolutionarily conserved tandem zinc finger domains and play critical roles in various RNA metabolic processes, including alternative splicing, mRNA stability, trafficking, regulation of subcellular localization, and alternative polyadenylation. Dysregulation of MBNL proteins can lead to severe consequences. Initially, research primarily associated MBNL proteins with myotonic dystrophy. However, recent studies have revealed their involvement in a broad spectrum of physiological and pathological processes, such as embryonic tissue differentiation and circulatory disorders. Furthermore, the emerging role of MBNL proteins in cancer sheds light on a novel aspect of these evolutionarily ancient proteins. This review provides a comprehensive overview of the MBNL family, emphasizing its structure, the mechanisms underlying its biological functions, and its roles in various diseases.Subject terms: Muscleblind-like-like protein, RNA-binding proteins, Alternative splicing, Tumor, Myotonic dystrophy.

Multiscale computational model predicts how environmental changes and treatments affect microvascular remodeling in fibrotic disease

Investigating the molecular, cellular, and tissue-level changes caused by disease, and the effects of pharmacological treatments across these biological scales, necessitates the use of multiscale computational modeling in combination with experimentation. Many diseases dynamically alter the tissue microenvironment in ways that trigger microvascular network remodeling, which leads to the expansion or regression of microvessel networks. When microvessels undergo remodeling in idiopathic pulmonary fibrosis (IPF), functional gas exchange is impaired and lung function declines. We integrated a multiscale computational model with independent experiments to investigate how combinations of biomechanical and biochemical cues in IPF alter cell fate decisions leading to microvascular remodeling. Our computational model predicted that extracellular matrix (ECM) stiffening reduced microvessel area, which was accompanied by physical uncoupling of endothelial cell (EC) and pericytes, the cells that comprise microvessels. Nintedanib, an Food and Drug Administration-approved drug for treating IPF, was predicted to further potentiate microvessel regression by decreasing the percentage of quiescent pericytes while increasing the percentage of pericytes undergoing pericyte-myofibroblast transition in high ECM stiffnesses. Importantly, the model suggested that YAP/TAZ inhibition may overcome the deleterious effects of nintedanib by promoting EC-pericyte coupling and maintaining microvessel homeostasis. Overall, our combination of computational and experimental modeling can predict and explain how cell decisions affect tissue changes during disease and in response to treatments.

Multiscale computational model predicts how environmental changes and drug treatments affect microvascular remodeling in fibrotic disease

Investigating the molecular, cellular, and tissue-level changes caused by disease, and the effects of pharmacological treatments across these biological scales, necessitates the use of multiscale computational modeling in combination with experimentation. Many diseases dynamically alter the tissue microenvironment in ways that trigger microvascular network remodeling, which leads to the expansion or regression of microvessel networks. When microvessels undergo remodeling in idiopathic pulmonary fibrosis (IPF), functional gas exchange is impaired due to loss of alveolar structures and lung function declines. Here, we integrated a multiscale computational model with independent experiments to investigate how combinations of biomechanical and biochemical cues in IPF alter cell fate decisions leading to microvascular remodeling. Our computational model predicted that extracellular matrix (ECM) stiffening reduced microvessel area, which was accompanied by physical uncoupling of endothelial cell (ECs) and pericytes, the cells that comprise microvessels. Nintedanib, an FDA-approved drug for treating IPF, was predicted to further potentiate microvessel regression by decreasing the percentage of quiescent pericytes while increasing the percentage of pericytes undergoing pericyte-myofibroblast transition (PMT) in high ECM stiffnesses. Importantly, the model suggested that YAP/TAZ inhibition may overcome the deleterious effects of nintedanib by promoting EC-pericyte coupling and maintaining microvessel homeostasis. Overall, our combination of computational and experimental modeling can explain how cell decisions affect tissue changes during disease and in response to treatments.

Cavin-2 promotes fibroblast-to-myofibroblast trans-differentiation and aggravates cardiac fibrosis

AIMS

Transforming growth factor β (TGF-β) signalling is one of the critical pathways in fibroblast activation, and several drugs targeting the TGF-β/Smad signalling pathway in heart failure with cardiac fibrosis are being tested in clinical trials. Some caveolins and cavins, which are components of caveolae on the plasma membrane, are known for their association with the regulation of TGF-β signalling. Cavin-2 is particularly abundant in fibroblasts; however, the detailed association between Cavin-2 and cardiac fibrosis is still unclear. We tried to clarify the involvement and role of Cavin-2 in fibroblasts and cardiac fibrosis.

METHODS AND RESULTS

To clarify the role of Cavin-2 in cardiac fibrosis, we performed transverse aortic constriction (TAC) operations on four types of mice: wild-type (WT), Cavin-2 null (Cavin-2 KO), Cavin-2flox/flox , and activated fibroblast-specific Cavin-2 conditional knockout (Postn-Cre/Cavin-2flox/flox , Cavin-2 cKO) mice. We collected mouse embryonic fibroblasts (MEFs) from WT and Cavin-2 KO mice and investigated the effect of Cavin-2 in fibroblast trans-differentiation into myofibroblasts and associated TGF-β signalling. Four weeks after TAC, cardiac fibrotic areas in both the Cavin-2 KO and the Cavin-2 cKO mice were significantly decreased compared with each control group (WT 8.04 ± 1.58% vs. Cavin-2 KO 0.40 ± 0.03%, P < 0.01; Cavin-2flox/flox , 7.19 ± 0.50% vs. Cavin-2 cKO 0.88 ± 0.44%, P < 0.01). Fibrosis-associated mRNA expression (Col1a1, Ctgf, and Col3) was significantly attenuated in the Cavin-2 KO mice after TAC. α1 type I collagen deposition and non-vascular αSMA-positive cells (WT 43.5 ± 2.4% vs. Cavin-2 KO 25.4 ± 3.2%, P < 0.01) were reduced in the heart of the Cavin-2 cKO mice after TAC operation. The levels of αSMA protein (0.36-fold, P < 0.05) and fibrosis-associated mRNA expression (Col1a1, 0.69-fold, P < 0.01; Ctgf, 0.27-fold, P < 0.01; Col3, 0.60-fold, P < 0.01) were decreased in the Cavin-2 KO MEFs compared with the WT MEFs. On the other hand, αSMA protein levels were higher in the Cavin-2 overexpressed MEFs compared with the control MEFs (2.40-fold, P < 0.01). TGF-β1-induced Smad2 phosphorylation was attenuated in the Cavin-2 KO MEFs compared with WT MEFs (0.60-fold, P < 0.01). Heat shock protein 90 protein levels were significantly reduced in the Cavin-2 KO MEFs compared with the WT MEFs (0.69-fold, P < 0.01).

CONCLUSIONS

Cavin-2 loss suppressed fibroblast trans-differentiation into myofibroblasts through the TGF-β/Smad signalling. The loss of Cavin-2 in cardiac fibroblasts suppresses cardiac fibrosis and may maintain cardiac function.

Physiological Indirect Response Model to Omics-Powered Quantitative Systems Pharmacology Model

Over the past several decades, mathematical modeling has been applied to increasingly wider scopes of questions in drug development. Accordingly, the range of modeling tools has also been evolving, as showcased by contributions of Jusko and colleagues: from basic pharmacokinetics/pharmacodynamics (PK/PD) modeling to today's platform-based approach of quantitative systems pharmacology (QSP) modeling. Aimed at understanding the mechanism of action of investigational drugs, QSP models characterize systemic effects by incorporating information about cellular signaling networks, which is often represented by omics data. In this perspective, we share a few examples illustrating approaches for the integration of omics into mechanistic QSP modeling. We briefly overview how the evolution of PK/PD modeling into QSP has been accompanied by an increase in available data and the complexity of mathematical methods that integrate it. We discuss current gaps and challenges of integrating omics data into QSP models and propose several potential areas where integrated QSP and omics modeling may benefit drug development.