Cite as: Cold Spring Harb. Protoc.; 2009; doi:10.1101/pdb.prot5222

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protocolProtocol

Metabolic Footprinting for the Study of Microbial Biodiversity

Georgina A. Pope1, Donald A. MacKenzie1, Marianne Defernez2, and Ian N. Roberts1,3

1 National Collection of Yeast Cultures, Institute of Food Research, Norwich Research Park, Colney, Norwich NR4 7UA, UK
2 Bioinformatics and Statistics Partnership, Institute of Food Research, Norwich Research Park, Colney, Norwich NR4 7UA, UK

3Corresponding author (ian.roberts{at}bbsrc.ac.uk)


INTRODUCTION

Mass spectrometric analysis of the metabolome (the complete set of small-molecule metabolites such as metabolic intermediates, hormones, and other signaling molecules, and secondary metabolites to be found within a biological sample, such as a single organism) has become a key component of modern systems biology. Within this broad definition, a number of technical refinements have enabled high-throughput profiling to be performed of the exometabolome (the metabolites that a cell or system excretes under controlled conditions). This technique has become known as metabolic footprinting and was first developed for analysis of yeast single- gene deletion mutants. More recently, it has proved valuable in metabolic profiling and comparative analysis of brewing and medically important yeast biodiversity. Direct injection mass spectrometry (DIMS) enables the direct injection or infusion of a sample, typically into an electrospray ionization mass spectrometer (ESI-MS). This article describes a detailed DIMS methodology in which samples of spent media from yeast cultures are introduced into an ESI-MS by direct injection into a flowing solvent (flow injection). DIMS resolves complex mixtures into components differing in ion mass using electrospray ionization, which avoids the need for derivatization and time-consuming chromatographic separation that is found with gas chromatography-mass spectrometry (GC-MS). The method is rapid and discriminatory. Populations of extremely closely related yeast strains can be identified and assigned to clusters of comparable phenotypes, even when standard genetic fingerprinting techniques fail to discriminate among such variants.


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