Activation of incretin receptors by their cognate agonist augments sustained cAMP generation both from the plasma membrane as well as from the endosome. To address the functional outcome of this spati Show more
Activation of incretin receptors by their cognate agonist augments sustained cAMP generation both from the plasma membrane as well as from the endosome. To address the functional outcome of this spatiotemporal signaling, we developed a nonacylated glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) receptor dual agonist I-M-150847 that reduced receptor internalization following activation of the incretin receptors. The incretin receptor dual agonist I-M-150847 was developed by replacing the tryptophan cage of exendin-4 tyrosine substituted at the amino terminus with the C-terminal undecapeptide sequence of oxyntomodulin that placed lysine 30 of I-M-150847 in frame with the corresponding lysine residue of GIP. The peptide I-M-150847 is a partial agonist of GLP-1R and GIPR; however, the receptors, upon activation by I-M-150847, undergo reduced internalization that promotes agonist-mediated iterative cAMP signaling and augments glucose-stimulated insulin exocytosis in pancreatic β cells. Chronic administration of I-M-150847 improved glycemic control, enhanced insulin sensitivity, and provided profound weight loss in diet-induced obese (DIO) mice. Our results demonstrated that despite being a partial agonist, I-M-150847, by reducing the receptor internalization upon activation, enhanced the incretin effect and reversed obesity. Show less
RNA-seq is a promising technology to re-sequence protein coding genes for the identification of single nucleotide variants (SNV), while simultaneously obtaining information on structural variations an Show more
RNA-seq is a promising technology to re-sequence protein coding genes for the identification of single nucleotide variants (SNV), while simultaneously obtaining information on structural variations and gene expression perturbations. We asked whether RNA-seq is suitable for the detection of driver mutations in T-cell acute lymphoblastic leukemia (T-ALL). These leukemias are caused by a combination of gene fusions, over-expression of transcription factors and cooperative point mutations in oncogenes and tumor suppressor genes. We analyzed 31 T-ALL patient samples and 18 T-ALL cell lines by high-coverage paired-end RNA-seq. First, we optimized the detection of SNVs in RNA-seq data by comparing the results with exome re-sequencing data. We identified known driver genes with recurrent protein altering variations, as well as several new candidates including H3F3A, PTK2B, and STAT5B. Next, we determined accurate gene expression levels from the RNA-seq data through normalizations and batch effect removal, and used these to classify patients into T-ALL subtypes. Finally, we detected gene fusions, of which several can explain the over-expression of key driver genes such as TLX1, PLAG1, LMO1, or NKX2-1; and others result in novel fusion transcripts encoding activated kinases (SSBP2-FER and TPM3-JAK2) or involving MLLT10. In conclusion, we present novel analysis pipelines for variant calling, variant filtering, and expression normalization on RNA-seq data, and successfully applied these for the detection of translocations, point mutations, INDELs, exon-skipping events, and expression perturbations in T-ALL. Show less