Accumulating evidence suggests that subcutaneous and visceral adipose tissues are differentially associated with metabolic disorders. In obesity, subcutaneous adipose tissue is beneficial for metabolic homeostasis because of repressed inflammation. However, the underlying mechanism remains unclear. Here, we demonstrate that γ-aminobutyric acid (GABA) sensitivity is crucial in determining fat depot-selective adipose tissue macrophage (ATM) infiltration in obesity. In diet-induced obesity, GABA reduced monocyte migration in subcutaneous inguinal adipose tissue (IAT), but not in visceral epididymal adipose tissue (EAT). Pharmacological modulation of the GABAB receptor affected the levels of ATM infiltration and adipose tissue inflammation in IAT, but not in EAT, and GABA administration ameliorated systemic insulin resistance and enhanced insulin-dependent glucose uptake in IAT, accompanied by lower inflammatory responses. Intriguingly, compared with adipose-derived stem cells (ADSCs) from EAT, IAT-ADSCs played key roles in mediating GABA responses that repressed ATM infiltration in high-fat diet-fed mice. These data suggest that selective GABA responses in IAT contribute to fat depot-selective suppression of inflammatory responses and protection from insulin resistance in obesity.

Adipocytes have unique morphological traits in insulin sensitivity control. However, how the appearance of adipocytes can determine insulin sensitivity has not been understood. Here, we demonstrate that actin cytoskeleton reorganization upon lipid droplet (LD) configurations in adipocytes plays important roles in insulin-dependent glucose uptake by regulating GLUT4 trafficking. Compared to white adipocytes, brown/beige adipocytes with multilocular LDs exhibited well-developed filamentous actin (F-actin) structure and potentiated GLUT4 translocation to the plasma membrane in the presence of insulin. In contrast, LD enlargement and unilocularization in adipocytes downregulated cortical F-actin formation, eventually leading to decreased F-actin-to-globular actin (G-actin) ratio and suppression of insulin-dependent GLUT4 trafficking. Pharmacological inhibition of actin polymerization accompanied with impaired F/G-actin dynamics reduced glucose uptake in adipose tissue and conferred systemic insulin resistance in mice. Thus, our study reveals that adipocyte remodeling with different LD configurations could be an important factor to determine insulin sensitivity by modulating F/G-actin dynamics.

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Supplementary data are available at Bioinformatics online.

Genomic profiles of cancer patients such as gene expression have become a major source to predict responses to drugs in the era of personalized medicine. As large-scale drug screening data with cancer cell lines are available, a number of computational methods have been developed for drug response prediction. However, few methods incorporate both gene expression data and the biological network, which can harbor essential information about the underlying process of the drug response. We proposed an analysis framework called DrugGCN for prediction of Drug response using a Graph Convolutional Network (GCN). DrugGCN first generates a gene graph by combining a Protein-Protein Interaction (PPI) network and gene expression data with feature selection of drug-related genes, and the GCN model detects the local features such as subnetworks of genes that contribute to the drug response by localized filtering. We demonstrated the effectiveness of DrugGCN using biological data showing its high prediction accuracy among the competing methods.