Machine learning reveals distinct gene signature profiles in lesional and nonlesional regions of inflammatory skin diseases.

Analysis of gene expression from cutaneous lupus erythematosus, psoriasis, atopic dermatitis, and systemic sclerosis using gene set variation analysis (GSVA) revealed that lesional samples from each condition had unique features, but all four diseases displayed common enrichment in multiple inflammatory signatures. These findings were confirmed by both classification and regression tree analysis and machine learning (ML) models. Nonlesional samples from each disease also differed from normal samples and each other by ML. Notably, the features used in classification of nonlesional disease were more distinct than their lesional counterparts, and GSVA confirmed unique features of nonlesional disease. These data show that lesional and nonlesional skin samples from inflammatory skin diseases have unique profiles of gene expression abnormalities, especially in nonlesional skin, and suggest a model in which disease-specific abnormalities in "prelesional" skin may permit environmental stimuli to trigger inflammatory responses leading to both the unique and shared manifestations of each disease.

Innate immune signaling in Drosophila shifts anabolic lipid metabolism from triglyceride storage to phospholipid synthesis to support immune function.

During infection, cellular resources are allocated toward the metabolically-demanding processes of synthesizing and secreting effector proteins that neutralize and kill invading pathogens. In Drosophila, these effectors are antimicrobial peptides (AMPs) that are produced in the fat body, an organ that also serves as a major lipid storage depot. Here we asked how activation of Toll signaling in the larval fat body perturbs lipid homeostasis to understand how cells meet the metabolic demands of the immune response. We find that genetic or physiological activation of fat body Toll signaling leads to a tissue-autonomous reduction in triglyceride storage that is paralleled by decreased transcript levels of the DGAT homolog midway, which carries out the final step of triglyceride synthesis. In contrast, Kennedy pathway enzymes that synthesize membrane phospholipids are induced. Mass spectrometry analysis revealed elevated levels of major phosphatidylcholine and phosphatidylethanolamine species in fat bodies with active Toll signaling. The ER stress mediator Xbp1 contributed to the Toll-dependent induction of Kennedy pathway enzymes, which was blunted by deleting AMP genes, thereby reducing secretory demand elicited by Toll activation. Consistent with ER stress induction, ER volume is expanded in fat body cells with active Toll signaling, as determined by transmission electron microscopy. A major functional consequence of reduced Kennedy pathway induction is an impaired immune response to bacterial infection. Our results establish that Toll signaling induces a shift in anabolic lipid metabolism to favor phospholipid synthesis and ER expansion that may serve the immediate demand for AMP synthesis and secretion but with the long-term consequence of insufficient nutrient storage.

Adipocyte lipolysis drives acute stress-induced insulin resistance.

Stress hyperglycemia and insulin resistance are evolutionarily conserved metabolic adaptations to severe injury including major trauma, burns, or hemorrhagic shock (HS). In response to injury, the neuroendocrine system increases secretion of counterregulatory hormones that promote rapid mobilization of nutrient stores, impair insulin action, and ultimately cause hyperglycemia, a condition known to impair recovery from injury in the clinical setting. We investigated the contributions of adipocyte lipolysis to the metabolic response to acute stress. Both surgical injury with HS and counterregulatory hormone (epinephrine) infusion profoundly stimulated adipocyte lipolysis and simultaneously triggered insulin resistance and hyperglycemia. When lipolysis was inhibited, the stress-induced insulin resistance and hyperglycemia were largely abolished demonstrating an essential requirement for adipocyte lipolysis in promoting stress-induced insulin resistance. Interestingly, circulating non-esterified fatty acid levels did not increase with lipolysis or correlate with insulin resistance during acute stress. Instead, we show that impaired insulin sensitivity correlated with circulating levels of the adipokine resistin in a lipolysis-dependent manner. Our findings demonstrate the central importance of adipocyte lipolysis in the metabolic response to injury. This insight suggests new approaches to prevent insulin resistance and stress hyperglycemia in trauma and surgery patients and thereby improve outcomes.

Fibronectin fibrils regulate TGF-ß1-induced Epithelial-Mesenchymal Transition.

Epithelial-Mesenchymal Transition (EMT) is a dynamic process through which epithelial cells transdifferentiate from an epithelial phenotype into a mesenchymal phenotype. Previous studies have demonstrated that both mechanical signaling and soluble growth factor signaling facilitate this process. One possible point of integration for mechanical and growth factor signaling is the extracellular matrix. Here we investigate the role of the extracellular matrix (ECM) protein fibronectin (FN) in this process. We demonstrate that inhibition of FN fibrillogenesis blocks activation of the Transforming Growth Factor-Beta (TGF-ß) signaling pathway via Smad2 signaling, decreases cell migration and ultimately leads to inhibition of EMT. Results show that soluble FN, FN fibrils, or increased contractile forces are insufficient to independently induce EMT. We further demonstrate that inhibition of latent TGF-ß1 binding to FN fibrils via either a monoclonal blocking antibody against the growth factor binding domain of FN or through use of a FN deletion mutant that lacks the growth factor binding domains of FN blocks EMT progression, indicating a novel role for FN in EMT in which the assembly of FN fibrils serves to localize TGF-ß1 signaling to drive EMT.