Quantification of Microbial Phenotypes

Martínez, Verónica; Krömer, Jens O.

doi:10.3390/metabo6040045

Cited by 3 publications

(2 citation statements)

References 89 publications

(127 reference statements)

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“…Further, the discrepancy between reported concentrations, both in original literature and databases, is large. Reliable and reproducible absolute quantitative data is a prerequisite for successful application of kinetic and metabolite network modeling, but is to a large extent still lacking [15][16][17][18]. The fact that concentration entries in metabolite databases may vary over several orders of magnitude [19][20][21] is to be expected, as the database entries are recorded by different analytical methods, and from organisms cultivated at various conditions.…”

Section: Introductionmentioning

confidence: 99%

Absolute Quantification of the Central Carbon Metabolome in Eight Commonly Applied Prokaryotic and Eukaryotic Model Systems

et al. 2020

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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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Section: Introductionmentioning

confidence: 99%

Absolute Quantification of the Central Carbon Metabolome in Eight Commonly Applied Prokaryotic and Eukaryotic Model Systems

et al. 2020

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“…mutant vs. wild-type/ reference strains, but the ultimate goal is to report absolute intracellular concentrations 7 . Such information is essential to testing and validating kinetic models 8 , to increase of understanding in genotype-phenotype interactions and cellular engineering [9][10][11] . These data will be important for further emphasis to integrate different level omics-data with mathematical models, especially genome-scale metabolic models, of biological systems.…”

Section: Introductionmentioning

confidence: 99%

Adaptation of Central Metabolite Pools to Variations in Growth Rate and Cultivation Conditions in Saccharomyces Cerevisiae

Kumar

Venkatraman

Bruheim³

2020

Preprint

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Background: Saccharomyces cerevisiae is a well-known popular model system for basic biological studies and to serve as host organism for 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 exogeneous 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. Latest versions of absolute quantitative mass spectrometry-based metabolite profiling methodology were applied to cover glycolytic and pentose phosphate pathway metabolites, TCA, complete amino acid and deoxy-/nucleoside phosphate pools. We have attempted to correlate the total metabolite pool composition with growth rates and nutrient limitation in both batch and chemostat cultivations. We have also tried to dissect the Crabtree-effect, i.e. ethanol-producing cultivation conditions, based on metabolite pool composition. Results: Glutamate, glutamine, alanine and citrate were the four most abundant metabolites for most conditions tested. 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 PPP metabolites display 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 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 a-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 development of improved phenotypes in metabolic engineering.

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Adaptation of central metabolite pools to variations in growth rate and cultivation conditions in Saccharomyces cerevisiae

2021

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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.

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Quantification of Microbial Phenotypes

Cited by 3 publications

References 89 publications

Absolute Quantification of the Central Carbon Metabolome in Eight Commonly Applied Prokaryotic and Eukaryotic Model Systems

Absolute Quantification of the Central Carbon Metabolome in Eight Commonly Applied Prokaryotic and Eukaryotic Model Systems

Adaptation of Central Metabolite Pools to Variations in Growth Rate and Cultivation Conditions in Saccharomyces Cerevisiae

Adaptation of central metabolite pools to variations in growth rate and cultivation conditions in Saccharomyces cerevisiae

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