Loss of Sugar Detection by GLUT2 Affects Glucose Homeostasis in Mice

International audienceBACKGROUND: Mammals must sense the amount of sugar available to them and respond appropriately. For many years attention has focused on intracellular glucose sensing derived from glucose metabolism. Here, we studied the detection of extracellular glucose concentrations in vivo by invalidating the transduction pathway downstream from the transporter-detector GLUT2 and measured the physiological impact of this pathway. METHODOLOGY/PRINCIPAL FINDINGS: We produced mice that ubiquitously express the largest cytoplasmic loop of GLUT2, blocking glucose-mediated gene expression in vitro without affecting glucose metabolism. Impairment of GLUT2-mediated sugar detection transiently protected transgenic mice against starvation and streptozotocin-induced diabetes, suggesting that both low- and high-glucose concentrations were not detected. Transgenic mice favored lipid oxidation, and oral glucose was slowly cleared from blood due to low insulin production, despite massive urinary glucose excretion. Kidney adaptation was characterized by a lower rate of glucose reabsorption, whereas pancreatic adaptation was associated with a larger number of small islets. CONCLUSIONS/SIGNIFICANCE: Molecular invalidation of sugar sensing in GLUT2-loop transgenic mice changed multiple aspects of glucose homeostasis, highlighting by a top-down approach, the role of membrane glucose receptors as potential therapeutic targets

Validation Study of Existing Gene Expression Signatures for Anti-TNF Treatment in Patients with Rheumatoid Arthritis

So far, there are no means of identifying rheumatoid arthritis (RA) patients who will fail to respond to tumour necrosis factor blocking agents (anti-TNF), prior to treatment. We set out to validate eight previously reported gene expression signatures predicting therapy outcome. Genome-wide expression profiling using Affymetrix GeneChip Exon 1.0 ST arrays was performed on RNA isolated from whole blood of 42 RA patients starting treatment with infliximab or adalimumab. Clinical response according to EULAR criteria was determined at week 14 of therapy. Genes that have been reported to be associated with anti-TNF treatment were extracted from our dataset. K-means partition clustering was performed to assess the predictive value of the gene-sets. We performed a hypothesis-driven analysis of the dataset using eight existing gene sets predictive of anti-TNF treatment outcome. The set that performed best reached a sensitivity of 71% and a specificity of 61%, for classifying the patients in the current study. We successfully validated one of eight previously reported predictive expression profile. This replicated expression signature is a good starting point for developing a prediction model for anti-TNF treatment outcome that can be used in a daily clinical setting. Our results confirm that gene expression profiling prior to treatment is a useful tool to predict anti-TNF (non) response

Extraction of relevant transcription modules using pattern discovery

National audienc

Extraction of relevant transcription modules using pattern discovery

National audienc

Age-dependent transcriptomic changes in the rat heart. Implications for cardiac arrhythmogenesis

International audienc

MicroRNAs from urinary extracellular vesicles are non-invasive early biomarkers of diabetic nephropathy in type 2 diabetes patients with the ‘Asian Indian phenotype’

International audienc

Concurrent BMP signaling maintenance and TGF-β signaling inhibition is a hallmark of natural resistance to muscle atrophy

International audienc

Concurrent BMP signaling maintenance and TGF-β signaling inhibition is a hallmark of natural resistance to muscle atrophy

International audienc

Concurrent BMP signaling maintenance and TGF-β signaling inhibition is a hallmark of natural resistance to muscle atrophy

National audienceMuscle atrophy arises from a multiplicity of physiological or pathological situations (e.g. diabetes, cancers, aging, physical inactivity…) and its consequences are very detrimental at whole-body level. Even though knowledge of the underlying mechanisms keeps growing, there is still no proven treatment to date. To address this major clinical challenge, we selected here an innovative approach that compares muscle adaptations between an original model of natural resistance to muscle atrophy, the hibernating brown bear, and a classical model of disuse-induced atrophy in mouse. Remarkably, the bear has the unique ability to withstand muscle loss during hibernation, being able to cope with main triggers of atrophy, physical inactivity and prolonged fasting. Using transcriptomic analysis by RNA sequencing, we identified 2693 differentially expressed genes between the active versus hibernating period in bear muscle. We focused on TGF-β and BMP signaling pathways that are respectively involved in muscle mass loss and maintenance. During hibernation, gene expression of the TGF-β and BMP pathways components was overall downregulated and upregulated, respectively. On the contrary, an increased expression of TGF-β signaling genes and a decreased expression of BMP signaling genes was observed in mice muscles during unloading. We have further substantiated this opposite regulation between atrophied muscles of the unloaded mouse and non-atrophied muscles of the hibernating bear at the protein level. Altogether, our data identified a balance between TGF-β and BMP signaling pathways as crucial for muscle mass maintenance during long-term physical inactivity. In addition to the TGF-β pathway, already targeted in a wide range of therapies, the BMP pathway therefore appears to be an additional potential therapeutic target to prevent muscle atrophy