Extracellular vesicles (EVs) are membranous structures containing bioactive molecules, secreted by most cells into the extracellular environment. EVs are classified by their biogenesis mechanisms into two major subtypes: ectosomes (enriched in large EVs; lEVs), budding directly from the plasma membrane, which is common in both prokaryotes and eukaryotes, and exosomes (enriched in small EVs; sEVs) generated through the multivesicular bodies via the endomembrane system, which is unique to eukaryotes. Even though recent proteomic analyses have identified key proteins associated with EV subtypes, there has been no systematic analysis, thus far, to support the general validity and utility of current EV subtype separation methods, still largely dependent on physical properties, such as vesicular size and sedimentation. Here, we classified human EV proteomic datasets into two main categories based on distinct centrifugation protocols commonly used for isolating sEV or lEV fractions. We found characteristic, evolutionarily conserved profiles of sEV and lEV proteins linked to their respective biogenetic origins. This may suggest that the evolutionary trajectory of vesicular proteins may result in a membership bias toward specific EV subtypes. Protein–protein interaction (PPI) network analysis showed that vesicular proteins formed distinct clusters with proteins in the same EV fraction, providing evidence for the existence of EV subtype-specific protein recruiters. Moreover, we identified functional modules enriched in each fraction, including multivesicular body sorting for sEV, and mitochondria cellular respiration for lEV proteins. Our analysis successfully captured novel features of EVs embedded in heterogeneous proteomics studies and suggests specific protein markers and signatures to be used as quality controllers in the isolation procedure for subtype-enriched EV fractions.

Recent systems biological studies of cardiac systems have greatly advanced our understanding of cardiac physiology with a particular focus on the excitation-contraction coupling. With these advancements, there is a growing interest in systems analysis of the cardiac signaling network because its dynamical property is closely associated with cardiac diseases. In this article, we review recent attempts at computational modeling of the cardiac signaling network and provide a system-level perspective on the analysis of the large-scale cardiac signaling network. We discuss why the systems biological approach is useful and what novel insights it can provide for the development of personalized therapeutic strategies for cardiac diseases in the post-genomic era.

Apoptosis and hypertrophy of cardiomyocytes are the primary causes of heart failure and are known to be regulated by complex interactions in the underlying intracellular signaling network. Previous experimental studies were successful in identifying some key signaling components, but most of the findings were confined to particular experimental conditions corresponding to specific cellular contexts. A question then arises as to whether there might be essential regulatory interactions that prevail across diverse cellular contexts. To address this question, we have constructed a large-scale cardiac signaling network by integrating previous experimental results and developed a mathematical model using normalized ordinary differential equations. Specific cellular contexts were reflected to different kinetic parameters sampled from random distributions. Through extensive computer simulations with various parameter distributions, we revealed the five most essential context-independent regulatory interactions (between: (1) αAR and Gαq, (2) IP3 and calcium, (3) epac and CaMK, (4) JNK and NFAT, and (5) p38 and NFAT) for hypertrophy and apoptosis that were consistently found over all our perturbation analyses. These essential interactions are expected to be the most promising therapeutic targets across a broad spectrum of individual conditions of heart failure patients.Heart failure is a typical complex disease that is often accompanied by apoptosis and hypertrophy of cardiomyocytes. Loss of cardiomyocytes owing to apoptosis causes a permanent reduction in myocardial function leading to the development of heart failure 1-4 . Hypertrophy of cardiomyocytes (i.e., increased length and width) impairs the coordination of myocardial contraction, predisposing individuals to heart failure and sudden death. Both apoptosis and hypertrophy are regulated by complex interactions in the intracellular signaling pathways (e.g., for apoptosis: β-adrenergic receptor (AR) pathway, mitogen associated protein kinase (MAPK) pathway, and phosphoinositide-3-kinase (PI3K)-Akt pathway; for hypertrophy: calcineurin-nuclear factor of activated T cells (CaN-NFAT) pathway, PI3K-Akt pathway, and MAPK pathways) 5 .Many experimental studies have sought to identify key signaling components involved in the development of apoptosis or hypertrophy by investigating the following three relationships between signaling components and the phenotypes: (i) a significant association that shows a substantial difference in expression or activity of signaling components between pathologic (apoptotic and/or hypertrophic) myocardium and normal myocardium 6 ; (ii) inducing a relationship where a signaling component is enhanced by treatment of a stimulant or a transfection experiment 7,8 ; and (iii) suppressing a relationship where a signaling component is inhibited by treatment of an inhibitor or a knock-out experiment 9, 10 . However, these relationships can vary depending on the experimental conditions, thus leading to their inapplicability to other cellular contexts. F...

Nonalcoholic fatty liver disease (NAFLD) is a serious metabolic disorder characterized by excess fat accumulation in the liver. Over the past decade, NAFLD prevalence and incidence have risen globally. There are currently no effective licensed drugs for its treatment. Thus, further study is required to identify new targets for NAFLD prevention and treatment. In this study, we fed C57BL6/J mice one of three diets, a standard chow diet, high-sucrose diet, or high-fat diet, and then characterized them. The mice fed a high-sucrose diet had more severely compacted macrovesicular and microvesicular lipid droplets than those in the other groups. Mouse liver transcriptome analysis identified lymphocyte antigen 6 family member D (Ly6d) as a key regulator of hepatic steatosis and the inflammatory response. Data from the Genotype-Tissue Expression project database showed that individuals with high liver Ly6d expression had more severe NAFLD histology than those with low liver Ly6d expression. In AML12 mouse hepatocytes, Ly6d overexpression increased lipid accumulation, while Ly6d knockdown decreased lipid accumulation. Inhibition of Ly6d ameliorated hepatic steatosis in a diet-induced NAFLD mouse model. Western blot analysis showed that Ly6d phosphorylated and activated ATP citrate lyase, which is a key enzyme in de novo lipogenesis. In addition, RNA- and ATAC-sequencing analyses revealed that Ly6d drives NAFLD progression by causing genetic and epigenetic changes. In conclusion, Ly6d is responsible for the regulation of lipid metabolism, and inhibiting Ly6d can prevent diet-induced steatosis in the liver. These findings highlight Ly6d as a novel therapeutic target for NAFLD.

Gastrointestinal malignancies such as colon adenocarcinoma (COAD) and liver hepatocellular carcinoma (LIHC) are the major causes of cancer-related deaths worldwide. Identifying the common genetic foundations and signaling pathways among these cancers can lead to improved understanding of their underlying mechanisms and potential therapeutic targets. Here, we tried to identify differentially expressed genes (DEGs) and enriched pathways associated with tumorigenesis using publicly accessible the Cancer Genome Atlas datasets of COAD and LIHC. Our analysis revealed that DEGs during early tumorigenesis were associated with various aspects of cell cycle regulation. Genes related to lipid metabolism were significantly enriched in COAD and LIHC, suggesting that dysregulated lipid metabolism may play a crucial role in the development and progression of COAD and LIHC. A subset of DEGs associated with mitochondrial function and structure was identified, among which genes involved in mitochondrial protein import and mitochondrial respiratory complex assembly were upregulated in both cancers. We identified mitochondrial 3-hydroxy-3-methylglutaryl-CoA synthase (HMGCS2) as a crucial regulator of cancer cell metabolism. Using a genome-scale metabolic model, we showed that HMGCS2 suppression increased glycolysis, lipid biosynthesis and elongation, and decreased fatty acid oxidation in colon cancer cells. Overall, the present study highlights the potential contribution of dysregulated lipid metabolism, including ketogenesis, to the development and progression of COAD and LIHC. These findings could prove vital for developing targeted therapies for these malignancies and pave the way for more effective treatments.