Extracting Time-dependent Obese-diabetic Specific Networks in Hepatic Proteome Analysis

Molecular mechanism governing biological processes leading
to dietary
obesity and diabetes are largely unknown. Here we study the liver
proteome differentially expressed in a long-term high-fat and high-sucrose
diet (HFHSD)-induced obesity and diabetes mouse model. Changes in
mouse liver proteins were identified using iTRAQ, offline 2D LC (SCX
and RP) and MALDI-TOF/TOF MS. A total of 1639 proteins was quantified
during 3–15 weeks of disease progression and a pronounced proteome
change was captured by incorporating the statistical analysis and
network analysis. This underscores the importance of protein expression
profiles involved in different biological processes that correlate
well with the disease progression. The functionally important modules
with key hub proteins such as Egfr, Pklr, Suclg1, and Pcx (Carbohydrate
metabolism), Cyp2e1, Fasn, Acat1, and Hmgcs2 (Lipid metabolism and
ketogenesis), and Gpx1, Mgst1, and Sod2 (ROS metabolism) can be linked to a physiological state
of obesity and T2D. Multiple proteins involved in glucose catabolism
and lipogenesis were down-regulated, whereas proteins involved in
lipid peroxidation and oxidative phosphorylation were up-regulated.
In conclusion, this proteomic study provides targets for future mechanistic
and therapeutic studies in relation to development and prevention
of obesity and Type 2 Diabetes.