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Absolute quantification of intracellular metabolite pools is a prerequisite for modeling and in-depth biological interpretation of metabolomics data. It is the final step of an elaborate metabolomics workflow, with challenges associated with all steps—from sampling to quantifying the physicochemically diverse metabolite pool. Chromatographic separation combined with mass spectrometric (MS) detection is the superior platform for high coverage, selective, and sensitive detection of metabolites. Herein, we apply our quantitative MS-metabolomics workflow to measure and present the central carbon metabolome of a panel of commonly applied biological model systems. The workflow includes three chromatographic methods combined with isotope dilution tandem mass spectrometry to allow for absolute quantification of 68 metabolites of glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, and the amino acid and (deoxy) nucleoside pools. The biological model systems; Bacillus subtilis, Saccharomyces cerevisiae, two microalgal species, and four human cell lines were all cultured in commonly applied culture media and sampled in exponential growth phase. Both literature and databases are scarce with comprehensive metabolite datasets, and existing entries range over several orders of magnitude. The workflow and metabolite panel presented herein can be employed to expand the list of reference metabolomes, as encouraged by the metabolomics community, in a continued effort to develop and refine high-quality quantitative metabolomics workflows.

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Background Saccharomyces cerevisiae is a well-known popular model system for basic biological studies and serves as a host organism for the heterologous production of commercially interesting small molecules and proteins. The central metabolism is at the core to provide building blocks and energy to support growth and survival in normal situations as well as during exogenous stresses and forced heterologous protein production. Here, we present a comprehensive study of intracellular central metabolite pool profiling when growing S. cerevisiae on different carbon sources in batch cultivations and at different growth rates in nutrient-limited glucose chemostats. The latest versions of absolute quantitative mass spectrometry-based metabolite profiling methodology were applied to cover glycolytic and pentose phosphate pathway metabolites, tricarboxylic acid cycle (TCA), complete amino acid, and deoxy-/nucleoside phosphate pools. Results Glutamate, glutamine, alanine, and citrate were the four most abundant metabolites for most conditions tested. The amino acid is the dominant metabolite class even though a marked relative reduction compared to the other metabolite classes was observed for nitrogen and phosphate limited chemostats. Interestingly, glycolytic and pentose phosphate pathway (PPP) metabolites display the largest variation among the cultivation conditions while the nucleoside phosphate pools are more stable and vary within a closer concentration window. The overall trends for glucose and nitrogen-limited chemostats were increased metabolite pools with the increasing growth rate. Next, comparing the chosen chemostat reference growth rate (0.12 h−1, approximate one-fourth of maximal unlimited growth rate) illuminates an interesting pattern: almost all pools are lower in nitrogen and phosphate limited conditions compared to glucose limitation, except for the TCA metabolites citrate, isocitrate and α-ketoglutarate. Conclusions This study provides new knowledge-how the central metabolism is adapting to various cultivations conditions and growth rates which is essential for expanding our understanding of cellular metabolism and the development of improved phenotypes in metabolic engineering.