Microbial metabolomics: Toward a platform with full metabolome coverage Marie¨t J. van der Werf * , Karin M. Overkamp, Bas Muilwijk, Leon Coulier, Thomas Hankemeier 1 TNO Quality of Life, 3700 AJ Zeist, The Netherlands Received 23 February 2007 Available online 1 August 2007 Abstract Achieving metabolome data with satisfactory coverage is a formidable challenge in metabolomics because metabolites are a chemi- cally highly diverse group of compounds. Here we present a strategy for the development of an advanced analytical platform that allows the comprehensive analysis of microbial metabolomes. Our approach started with in silico metabolome information from three micro- organisms—Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae—and resulted in a list of 905 different metabolites. Subse- quently, these metabolites were classified based on their physicochemical properties, followed by the development of complementary gas chromatography–mass spectrometry and liquid chromatography–mass spectrometry methods, each of which analyzes different metabolite classes. This metabolomics platform, consisting of six different analytical methods, was applied for the analysis of the metab- olites for which commercial standards could be purchased (399 compounds). Of these 399 metabolites, 380 could be analyzed with the platform. To demonstrate the potential of this metabolomics platform, we report on its application to the analysis of the metabolome composition of mid-logarithmic E. coli cells grown on a mineral salts medium using glucose as the carbon source. Of the 431 peaks detected, 235 (=176 unique metabolites) could be identified. These include 61 metabolites that were not previously identified or anno- tated in existing E. coli databases. Ó 2007 Elsevier Inc. All rights reserved. Keywords: Metabolomics; Metabolome analysis; Microbial systems biology; Coverage Metabolomics is a functional genomics technology of vital importance for understanding cellular functioning because the metabolome is a direct reflection of the physi- ological status of a cell [1,2]. Another key feature of this technology is that it analyzes all metabolites, in this way allowing an open, and thus unbiased, approach toward identifying those biomolecules that are important for a spe- cific biological question [3]. Despite the fundamental advantages of metabolomics, so far no metabolomics platform that allows the reliable analysis of full (microbial) metabolomes has been described. Actually, it is still commonly believed that the analysis of the full metabolomes is an ‘‘impossible task’’ [4,5] due to the chemical diversity of cellular metabolites [6]. Estimates for the number of metabolites present in microbial metabolomes based on genome information range from 241 for a ‘‘simple’’ bacterium such as Myco- plasma pneumoniae to 794 for the well-studied Escherichia coli [7]. However, in view of the many genes of unknown function present in the genomes and the broad substrate specificity of many enzymes, this number is likely to be a factor two to three times higher [3]. Notwithstanding the fact that during the past 5 years advances have been made in the comprehensive analysis of 100 to 500 metabolites in a single run [8–14], it is not clear what the coverage of these methods is in relation to the full metabolome composition of the organisms studied. 0003-2697/$ - see front matter Ó 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.ab.2007.07.022 * Corresponding author. Fax: +31 30 6944466. E-mail address: mariet.vanderwerf@tno.nl (M.J. van der Werf). 1 Current address: Division of Analytical Biosciences, Leiden/Amster- dam Center for Drug Research, 2300 RA Leiden, The Netherlands. www.elsevier.com/locate/yabio ANALYTICAL BIOCHEMISTRY Analytical Biochemistry 370 (2007) 17–25