The role of the M-band myomesin proteins in muscle integrity and cardiac disease

Characterization of the skeletal muscle arginine methylome in health and disease reveals remodeling in amyotrophic lateral sclerosis

Arginine methylation is a protein posttranslational modification important for the development of skeletal muscle mass and function. Despite this, our understanding of the regulation of arginine methylation under settings of health and disease remains largely undefined. Here, we investigated the regulation of arginine methylation in skeletal muscles in response to exercise and hypertrophic growth, and in diseases involving metabolic dysfunction and atrophy. We report a limited regulation of arginine methylation under physiological settings that promote muscle health, such as during growth and acute exercise, nor in disease models of insulin resistance. In contrast, we saw a significant remodeling of asymmetric dimethylation in models of atrophy characterized by the loss of innervation, including in muscle biopsies from patients with myotrophic lateral sclerosis (ALS). Mass spectrometry-based quantification of the proteome and asymmetric arginine dimethylome of skeletal muscle from individuals with ALS revealed the largest compendium of protein changes with the identification of 793 regulated proteins, and novel site-specific changes in asymmetric dimethyl arginine (aDMA) of key sarcomeric and cytoskeletal proteins. Finally, we show that in vivo overexpression of PRMT1 and aDMA resulted in increased fatigue resistance and functional recovery in mice. Our study provides evidence for asymmetric dimethylation as a regulator of muscle pathophysiology and presents a valuable proteomics resource and rationale for numerous methylated and nonmethylated proteins, including PRMT1, to be pursued for therapeutic development in ALS.

Proteomic analysis of the serum in dogs with pulmonary hypertension secondary to myxomatous mitral valve disease: the preliminary study

Background

Pulmonary hypertension (PH) is a common complication in dogs with myxomatous mitral valve disease (MMVD), characterized by elevated blood pressure in pulmonary artery. Echocardiography is a reliable technique for PH diagnosis in veterinary medicine. However, it is limited to use as an early detection method. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has found extensive application in the discovery of serum protein biomarkers for various diseases. The objective of this study was to identify serum proteins in healthy control dogs and MMVD dogs both with and without PH using LC-MS/MS.

Materials and methods

In this research, a total of 81 small-breed dogs participated, and they were categorized into three groups: the control (n = 28), MMVD (n = 24) and MMVD+PH (n = 29) groups. Serum samples were collected and analyzed by LC-MS/MS.

Results

Differentially expressed proteins were identified, and the upregulated and downregulated proteins in MMVD+PH group including Myomesin 1 (MYOM1) and Histone deacetylase 7 (HDAC7), Pleckstrin homology domain containing M3 (PLEKHM3), Diacylglycerol lipase alpha (DAGLA) and Tubulin tyrosine ligase like 6 (TTLL6) were selected as proteins of interest in MMVD dogs with PH.

Conclusion

Different types of proteins have been identified in healthy dogs and MMVD dogs with and without PH. Additional studies are needed to investigate the potential of these proteins as biomarkers for PH in dogs with MMVD.

Detection of PatIent-Level distances from single cell genomics and pathomics data with Optimal Transport (PILOT)

Although clinical applications represent the next challenge in single-cell genomics and digital pathology, we still lack computational methods to analyze single-cell or pathomics data to find sample-level trajectories or clusters associated with diseases. This remains challenging as single-cell/pathomics data are multi-scale, i.e., a sample is represented by clusters of cells/structures, and samples cannot be easily compared with each other. Here we propose PatIent Level analysis with Optimal Transport (PILOT). PILOT uses optimal transport to compute the Wasserstein distance between two individual single-cell samples. This allows us to perform unsupervised analysis at the sample level and uncover trajectories or cellular clusters associated with disease progression. We evaluate PILOT and competing approaches in single-cell genomics or pathomics studies involving various human diseases with up to 600 samples/patients and millions of cells or tissue structures. Our results demonstrate that PILOT detects disease-associated samples from large and complex single-cell or pathomics data. Moreover, PILOT provides a statistical approach to find changes in cell populations, gene expression, and tissue structures related to the trajectories or clusters supporting interpretation of predictions.

Loss of Cardiac Splicing Regulator RBM20 Is Associated With Early-Onset Atrial Fibrillation

We showed an association between atrial fibrillation and rare loss-of-function (LOF) variants in the cardiac splicing regulator RBM20 in 2 independent cohorts. In a rat model with loss of RBM20, we demonstrated altered splicing of sarcomere genes (NEXN, TTN, TPM1, MYOM1, and LDB3), and differential expression in key cardiac genes. We identified altered sarcomere and mitochondrial structure on electron microscopy imaging and found compromised mitochondrial function. Finally, we demonstrated that 3 novel LOF variants in RBM20, identified in patients with atrial fibrillation, lead to significantly reduced splicing activity. Our results implicate alternative splicing as a novel proarrhythmic mechanism in the atria.

Exosome Liberation by Human Neutrophils under L-Amino Acid Oxidase of Calloselasma rhodostoma Venom Action

L-Amino acid oxidase (LAAO) is an enzyme found in snake venom that has multifaceted effects, including the generation of hydrogen peroxide (H2O2) during oxidative reactions, leading to various biological and pharmacological outcomes such as apoptosis, cytotoxicity, modulation of platelet aggregation, hemorrhage, and neutrophil activation. Human neutrophils respond to LAAO by enhancing chemotaxis, and phagocytosis, and releasing reactive oxygen species (ROS) and pro-inflammatory mediators. Exosomes cellular nanovesicles play vital roles in intercellular communication, including immune responses. This study investigates the impact of Calloselasma rhodostoma snake venom-derived LAAO (Cr-LAAO) on human neutrophil exosome release, including activation patterns, exosome formation, and content. Neutrophils isolated from healthy donors were stimulated with Cr-LAAO (100 μg/mL) for 3 h, followed by exosome isolation and analysis. Results show that Cr-LAAO induces the release of exosomes with distinct protein content compared to the negative control. Proteomic analysis reveals proteins related to the regulation of immune responses and blood coagulation. This study uncovers Cr-LAAO's ability to activate human neutrophils, leading to exosome release and facilitating intercellular communication, offering insights into potential therapeutic approaches for inflammatory and immunological disorders.

A knowledge graph approach to predict and interpret disease-causing gene interactions

BACKGROUND

Understanding the impact of gene interactions on disease phenotypes is increasingly recognised as a crucial aspect of genetic disease research. This trend is reflected by the growing amount of clinical research on oligogenic diseases, where disease manifestations are influenced by combinations of variants on a few specific genes. Although statistical machine-learning methods have been developed to identify relevant genetic variant or gene combinations associated with oligogenic diseases, they rely on abstract features and black-box models, posing challenges to interpretability for medical experts and impeding their ability to comprehend and validate predictions. In this work, we present a novel, interpretable predictive approach based on a knowledge graph that not only provides accurate predictions of disease-causing gene interactions but also offers explanations for these results.

RESULTS

We introduce BOCK, a knowledge graph constructed to explore disease-causing genetic interactions, integrating curated information on oligogenic diseases from clinical cases with relevant biomedical networks and ontologies. Using this graph, we developed a novel predictive framework based on heterogenous paths connecting gene pairs. This method trains an interpretable decision set model that not only accurately predicts pathogenic gene interactions, but also unveils the patterns associated with these diseases. A unique aspect of our approach is its ability to offer, along with each positive prediction, explanations in the form of subgraphs, revealing the specific entities and relationships that led to each pathogenic prediction.

CONCLUSION

Our method, built with interpretability in mind, leverages heterogenous path information in knowledge graphs to predict pathogenic gene interactions and generate meaningful explanations. This not only broadens our understanding of the molecular mechanisms underlying oligogenic diseases, but also presents a novel application of knowledge graphs in creating more transparent and insightful predictors for genetic research.

Effect of 11-Deoxycorticosterone in the Transcriptomic Response to Stress in Rainbow Trout Skeletal Muscle

In aquaculture, many stressors can negatively affect growth in teleosts. It is believed that cortisol performs glucocorticoid and mineralocorticoid functions because teleosts do not synthesize aldosterone. However, recent data suggest that 11-deoxycorticosterone (DOC) released during stress events may be relevant to modulate the compensatory response. To understand how DOC modifies the skeletal muscle molecular response, we carried out a transcriptomic analysis. Rainbow trout (Oncorhynchus mykiss) were intraperitoneally treated with physiological doses of DOC in individuals pretreated with mifepristone (glucocorticoid receptor antagonist) or eplerenone (mineralocorticoid receptor antagonist). RNA was extracted from the skeletal muscles, and cDNA libraries were constructed from vehicle, DOC, mifepristone, mifepristone plus DOC, eplerenone, and eplerenone plus DOC groups. The RNA-seq analysis revealed 131 differentially expressed transcripts (DETs) induced by DOC with respect to the vehicle group, mainly associated with muscle contraction, sarcomere organization, and cell adhesion. In addition, a DOC versus mifepristone plus DOC analysis revealed 122 DETs related to muscle contraction, sarcomere organization, and skeletal muscle cell differentiation. In a DOC versus eplerenone plus DOC analysis, 133 DETs were associated with autophagosome assembly, circadian regulation of gene expression, and regulation of transcription from RNA pol II promoter. These analyses indicate that DOC has a relevant function in the stress response of skeletal muscles, whose action is differentially modulated by GR and MR and is complementary to cortisol.

Myofilament-associated proteins with intrinsic disorder (MAPIDs) and their resolution by computational modeling

The cardiac sarcomere is a cellular structure in the heart that enables muscle cells to contract. Dozens of proteins belong to the cardiac sarcomere, which work in tandem to generate force and adapt to demands on cardiac output. Intriguingly, the majority of these proteins have significant intrinsic disorder that contributes to their functions, yet the biophysics of these intrinsically disordered regions (IDRs) have been characterized in limited detail. In this review, we first enumerate these myofilament-associated proteins with intrinsic disorder (MAPIDs) and recent biophysical studies to characterize their IDRs. We secondly summarize the biophysics governing IDR properties and the state-of-the-art in computational tools toward MAPID identification and characterization of their conformation ensembles. We conclude with an overview of future computational approaches toward broadening the understanding of intrinsic disorder in the cardiac sarcomere.