Graduation Year
2016
Document Type
Dissertation
Degree
Ph.D.
Degree Name
Doctor of Philosophy (Ph.D.)
Degree Granting Department
Biology (Cell Biology, Microbiology, Molecular Biology)
Major Professor
Brant R. Burkhardt, Ph.D.
Committee Member
Stanley M. Stevens, Jr, Ph.D.
Committee Member
Meera Nanjundan, Ph.D.
Committee Member
Patrick Bradshaw, Ph.D.
Keywords
PANDER, proteomics, phosphoproteomics, stable-isotope labeling
Abstract
PANcreatic DERived factor (PANDER, FAM3B) is a member of a superfamily of FAM3 proteins that are uniquely structured and strongly expressed from the endocrine pancreas and co-secreted with insulin. Unique animal models available to our lab have indicated that PANDER can induce a selective hepatic insulin resistant (SHIR) phenotype whereby insulin signaling is blunted yet lipogenesis is increased. The complexity of the biological networks involved with this process warranted the logical approach of employing quantitative mass spectrometry based proteomic analysis using stable isotope labeling of amino acids in cell culture (SILAC) to identify the global proteome differences between the PANDER transgenic (TG) overexpressing murine model to matched wild-type mice under three metabolic states (fasted, fed and insulin stimulated). Additionally, this technique was used to compare the hepatic proteome of mice on a high fat diet to elucidate early and late mechanisms of disease progression. The “spike-in” process was employed by equal addition of lysate obtained from livers of heavy L-Lysine (13C6, 97%) fed mice to the mice liver protein lysate (PANTG and WT) for relative quantitative analysis. Upon acquisition of the dataset by use of liquid chromatography tandem mass spectrometry (LC-MS/MS, LTQ Orbitrap), geometric means and Uniprot Protein identification numbers were uploaded to Ingenuity Pathway Analysis (IPA) to reveal the effect of PANDER on hepatic signaling. IPA identified lipid metabolism and fatty acid synthesis as top cellular functions differentially altered in all metabolic states. Several molecules with a role in lipid metabolism were identified and include FASN, ApoA1, ApoA4, SCD1, CD36, CYP7A1 and ACC. Furthermore, central to the differentially expressed proteins was the revealed activation of the liver X receptor (LXR) pathway. In summary, our SILAC proteomic approach has elucidated numerous previously unidentified PANDER induced molecules and pathways resulting in increased hepatic lipogenesis. In addition, we have demonstrated strong utility of this approach in comprehensively phenotyping animal models of hepatic insulin resistance. PANDER may potentially propagate pro-hepatic lipogenic effects by LXR activation in contrast to increased LXRα expression. This can be evaluated through the use of LXR agonists (T0901317) antagonists (GSK 2033). LXR activity can be measured by luciferase assays using an LXRE response plasmid. Our central hypothesis is that PANDER induces activation of LXR and is measured and predicted in our line of experiments. In general, PANDER induced LXR activation will be enhanced by T0901317 and diminish effects of GSK 2033 along with direct correlation of downstream metabolic effects such as increased hepatic lipogenesis and fatty acid metabolism. Taken together, PANDER strongly impacts hepatic lipid metabolism and may induce a SHIR phenotype via the LXR pathway. Additionally, phosphoproteomic analysis uncovered large-scale differences in protein phosphorylation states as PANDER impacts insulin signaling. A notable finding was the increased phosphorylation of glycogen synthase (GSK), possibly responsible for the decreased hepatic glycogen content in the PANTG mouse. In an effort to map out critical molecules involved in non-alcoholic fatty liver disease (NAFLD) pathogenesis, the same proteomic approach was carried out, providing a unique dataset of differentially expressed hepatic proteins due to a high at diet.
Scholar Commons Citation
Athanason, Mark Gabriel, "Quantitative Proteomic Investigation of Disease Models of Type 2 Diabetes" (2016). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/6460