A Functional Analysis of Mouse Models of Cardiac Disease through Metabolic Profiling

Kieran Clarke,Julian L. Griffin,Catharine Goddard,Andrew A. Grace,Brian C. Sweatman,Gareth L.A.H. Jones,Russell J. Mortishire-Smith,Elizabeth Sang,Kay Davies,John N. Haselden

doi:10.1074/jbc.m410200200

Abstract

Since the completion of the human and mouse genomes, the focus in mammalian biology has been on assessing gene function. Tools are needed for assessing the phenotypes of the many mouse models that are now being generated, where genes have been "knocked out," "knocked in," or mutated, so that gene expression can be understood in its biological context. Metabolic profiling of cardiac tissue through high resolution NMR spectroscopy in conjunction with multivariate statistics has been used to classify mouse models of cardiac disease. The data sets included metabolic profiles from mouse models of Duchenne muscular dystrophy, two models of cardiac arrhythmia, and one of cardiac hypertrophy. The metabolic profiles demonstrate that the strain background is an important component of the global metabolic phenotype of a mouse, providing insight into how a given gene deletion may result in very different responses in diverse populations. Despite these differences associated with strain, multivariate statistics were capable of separating each mouse model from its control strain, demonstrating that metabolic profiles could be generated for each disease. Thus, this approach is a rapid method of phenotyping mouse models of disease.

Highlights

Since the completion of the human and mouse genomes, the focus in mammalian biology has been on assessing gene function
Despite these differences associated with strain, multivariate statistics were capable of separating each mouse model from its control strain, demonstrating that metabolic profiles could be generated for each disease
In this study we demonstrate that the Functional ANalysis by Co-responses in Yeast (FANCY) approach described for yeast can be extended to mammalian systems by using high resolution NMR spectroscopy to classify mouse models of cardiac disease

Summary

Introduction

Since the completion of the human and mouse genomes, the focus in mammalian biology has been on assessing gene function. To measure a phenotype in such “silent” strains, Raamsdonk and co-workers [6, 7] suggested an approach described as Functional ANalysis by Co-responses in Yeast (FANCY), which uses global analytical tools such as 1H NMR spectroscopy [7] or mass spectrometry [8] to study the metabolic changes induced in different yeast mutants. These profiles were used to classify samples, clustering mutants that arise from similar deletions together.

Methods

Results

Conclusion