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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Extracting time-dependent obese-diabetic specific networks in hepatic proteome analysis
Mukul K Midha1, Kamiya Tikoo, Neeraj Sinha
1Immunology Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi 110067, India.
Journal of Proteome Research
|October 12, 2012
Summary
This study reveals key protein changes in the liver during diet-induced obesity and type 2 diabetes (T2D). Understanding these molecular mechanisms offers new targets for preventing and treating metabolic diseases.
Area of Science:
- Proteomics
- Metabolic disease research
- Molecular mechanisms of obesity and diabetes
Background:
- The molecular underpinnings of dietary obesity and type 2 diabetes (T2D) remain largely elusive.
- Understanding these processes is crucial for developing effective interventions.
Purpose of the Study:
- To investigate liver proteome alterations in a mouse model of diet-induced obesity and diabetes.
- To identify key proteins and pathways involved in disease progression.
Main Methods:
- Utilized iTRAQ, 2D LC (SCX and RP), and MALDI-TOF/TOF MS for quantitative proteomic analysis.
- Analyzed protein expression changes over 3-15 weeks in a high-fat, high-sucrose diet (HFHSD) mouse model.
- Incorporated statistical and network analyses to capture pronounced proteome changes.
Main Results:
- Quantified 1639 proteins, revealing significant proteome changes correlating with disease progression.
- Identified key proteins in carbohydrate metabolism (e.g., Pklr, Suclg1), lipid metabolism (e.g., Fasn, Acat1), and ROS metabolism (e.g., Gpx1, Sod2).
- Observed down-regulation of glucose catabolism and lipogenesis proteins, and up-regulation of lipid peroxidation and oxidative phosphorylation proteins.
Conclusions:
- Proteomic profiles in the liver are dynamically altered during obesity and T2D development.
- Specific protein modules identified provide insights into the physiological state of metabolic disease.
- This study offers potential molecular targets for future mechanistic and therapeutic investigations into obesity and T2D.
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