Molekulare Charakterisierung von Hunk, ein neuer Regulator der pankreatischen β-Zellfunktion
Zusammenfassung der Projektergebnisse
My initial research project was supposed to deal with the molecular characterization of the gene Hunk, which has been nominated as a driver gene for an insulin secretion quantitative trait locus (QTL) on Chr.16 in the Attie lab. To validate its role in insulin secretion, the Attie team isolated pancreatic islets from whole-body Hunk Knockout (HunkKO) mice to test their insulin secretory response. Indeed, islets from HUNKKO mice displayed increased insulin secretion compared to islets from HUNKWT mice, indicating that Hunk acts as an inhibitor of insulin secretion in pancreatic islet. To elucidate the mechanism that HUNK uses to regulate insulin secretion, my first task was to establish a cell model that would help to identify the direct substrates of Hunk, which are not known yet. However, despite of a high overexpression efficiency, HUNK overexpressing INS1 cells did not show altered insulin secretion compared to control cells. Also, overexpression of HUNK in isolated islets from HUNKKO mice failed to alter insulin secretion compared to controls. As a consequence, since all attempts to phenocopy HUNKKO islets failed, the project was put on hold and I continued working on other projects. In the second project I worked on Ptpn18, another gene that was identified in the genetic screen of the DO population as a candidate gene for an insulin secretion QTL on Chr.1. Transgenic mice carrying a knock-in mutation in the catalytic domain of Ptpn18 (Ptpn18D191A (abbr.: Ptpn18KI)) are more insulin-tolerant compared to Ptpn18WT controls. To investigate a potential role of the gene in insulin secretion, I overexpressed Ptpn18KI and Ptpn18WT in INS1 cells and tested their insulin secretory response to different secretagogues. However, a difference in insulin secretion could not be observed between the different genotypes. The third project was supposed to serve as a validation experiment for the islet protein QTL (pQTL) database from the Attie lab. For The generation of this database, the protein abundance of each protein from each DO mouse was quantified by mass spectrometry and genetically mapped to identify the genomic regulators of the protein expression. Protein interactions were further investigated by bioinformatic mediation analysis. For the publication of this database, I tried to validate the interaction between two proteins, SCG2 and SLC37A2, which appeared to have the strongest interaction in the database. SCG2 is known to be secreted from pancreatic βcells, whereas SLC37A2 functions as glucose-6-phosphat transporter in the endoplasmic reticulum (ER) membrane from macrophages, suggesting that the protein interaction involves the crosstalk of two different tissues. However, treatment of RAW macrophages with SCG2 recombinant protein as well as with conditioned media failed to alter SLC37A2 protein abundance and thus could not validate the hypothesized interaction of the two proteins. Project number four was about the identification of novel candidate genes for different liver triglyceride (TG) QTL recently detected in the DO population. By correlating the allelic effects of the e-and pQTL with the allele effects of the respective liver TG QTL, the number of candidates was narrowed down from 2556 protein coding genes annotated in the QTL regions, to 20 most likely candidates. These genes are currently further investigated in context with a potential role hepatic steatosis in the Attie lab.
