Protein Sets Define Disease States and Predict In Vivo Effects of Drug Treatment

David Meierhofer,Christopher Weidner,Ludger Hartmann,Johannes A Mayr,Chung-Ting Han,Frank C Schroeder,Sascha Sauer

doi:10.1074/mcp.m112.025031

Abstract

Gaining understanding of common complex diseases and their treatments are the main drivers for life sciences. As we show here, comprehensive protein set analyses offer new opportunities to decipher functional molecular networks of diseases and assess the efficacy and side-effects of treatments in vivo. Using mass spectrometry, we quantitatively detected several thousands of proteins and observed significant changes in protein pathways that were (dys-) regulated in diet-induced obesity mice. Analysis of the expression and post-translational modifications of proteins in various peripheral metabolic target tissues including adipose, heart, and liver tissue generated functional insights in the regulation of cell and tissue homeostasis during high-fat diet feeding and medication with two antidiabetic compounds. Protein set analyses singled out pathways for functional characterization, and indicated, for example, early-on potential cardiovascular complication of the diabetes drug rosiglitazone. In vivo protein set detection can provide new avenues for monitoring complex disease processes, and for evaluating preclinical drug candidates.

Highlights

The application of reductionism and experimental manipulation in the 20th century biological research has generated important insights into functional processes of life
We compared the effects of the drug rosiglitazone (RSG)1, which has been associated with a number of undesirable side effects [10], and the plant-derived amorfrutin A1 (A1) [11] in diet-induced obesity (DIO) mice
We treated our mice with RSG for 3 weeks only, which was already predictive for potential systemic cardiovascular complications

Summary

Introduction

The application of reductionism and experimental manipulation in the 20th century biological research has generated important insights into functional processes of life. Whereas analyses of single protein changes were mostly uninformative, quantitative protein set enrichment analysis was an efficient tool to monitor tissue-specific responses of anti-diabetic treatments This approach allows for investigation of interacting molecular and physiological processes that occur on the pathway level, and enables sensitive, unbiased and robust diagnostic detection of treatments in vivo. In this pilot study, we compared the effects of the drug rosiglitazone (RSG), which has been associated with a number of undesirable side effects [10], and the plant-derived amorfrutin A1 (A1) [11] in diet-induced obesity (DIO) mice.

Results

Discussion

Conclusion