SummaryWhereas intracellular carbon metabolism has emerged as an attractive drug target, the carbon sources of intracellularly replicating pathogens, such as the tuberculosis bacillus Mycobacterium tuberculosis, which causes long-term infections in one-third of the world’s population, remain mostly unknown. We used a systems-based approach—13C-flux spectral analysis (FSA) complemented with manual analysis—to measure the metabolic interaction between M. tuberculosis and its macrophage host cell. 13C-FSA analysis of experimental data showed that M. tuberculosis obtains a mixture of amino acids, C1 and C2 substrates from its host cell. We experimentally confirmed that the C1 substrate was derived from CO2. 13C labeling experiments performed on a phosphoenolpyruvate carboxykinase mutant revealed that intracellular M. tuberculosis has access to glycolytic C3 substrates. These findings provide constraints for developing novel chemotherapeutics.

Summary: 13C-based metabolic flux analysis (13C-MFA) is the state-of-the-art method to quantitatively determine in vivo metabolic reaction rates in microorganisms. 13CFLUX2 contains all tools for composing flexible computational 13C-MFA workflows to design and evaluate carbon labeling experiments. A specially developed XML language, FluxML, highly efficient data structures and simulation algorithms achieve a maximum of performance and effectiveness. Support of multicore CPUs, as well as compute clusters, enables scalable investigations. 13CFLUX2 outperforms existing tools in terms of universality, flexibility and built-in features. Therewith, 13CFLUX2 paves the way for next-generation high-resolution 13C-MFA applications on the large scale.Availability and implementation: 13CFLUX2 is implemented in C++ (ISO/IEC 14882 standard) with Java and Python add-ons to run under Linux/Unix. A demo version and binaries are available at www.13cflux.net.Contact: info@13cflux.net or k.noeh@fz-juelich.deSupplementary information: Supplementary data are available at Bioinformatics online.

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Methanol is already an important carbon feedstock in the chemical industry, but it has found only limited application in biotechnological production processes. This can be mostly attributed to the inability of most microbial platform organisms to utilize methanol as a carbon and energy source. With the aim to turn methanol into a suitable feedstock for microbial production processes, we engineered the industrially important but nonmethylotrophic bacterium Corynebacterium glutamicum toward the utilization of methanol as an auxiliary carbon source in a sugar-based medium. Initial oxidation of methanol to formaldehyde was achieved by heterologous expression of a methanol dehydrogenase from Bacillus methanolicus, whereas assimilation of formaldehyde was realized by implementing the two key enzymes of the ribulose monophosphate pathway of Bacillus subtilis: 3-hexulose-6-phosphate synthase and 6-phospho-3-hexuloisomerase. The recombinant C. glutamicum strain showed an average methanol consumption rate of 1.7 ؎ 0.3 mM/h (mean ؎ standard deviation) in a glucose-methanol medium, and the culture grew to a higher cell density than in medium without methanol. In addition, [13 C]methanol-labeling experiments revealed labeling fractions of 3 to 10% in the m ؉ 1 mass isotopomers of various intracellular metabolites. In the background of a C. glutamicum ⌬ald ⌬adhE mutant being strongly impaired in its ability to oxidize formaldehyde to CO 2 , the m ؉ 1 labeling of these intermediates was increased (8 to 25%), pointing toward higher formaldehyde assimilation capabilities of this strain. The engineered C. glutamicum strains represent a promising starting point for the development of sugar-based biotechnological production processes using methanol as an auxiliary substrate.

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Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of (13)C isotopes allows comprehensive insights into the functional operation of cellular metabolism. Compared to single MS, tandem mass spectrometry (MS/MS) provides more detailed and accurate measurements of the metabolite enrichment patterns (tandem mass isotopomers), increasing the accuracy of metabolite concentration measurements and metabolic flux estimation. MS-type data from isotope labeling experiments is biased by naturally occurring stable isotopes (C, H, N, O, etc.). In particular, GC-MS(/MS) requires derivatization for the usually non-volatile intracellular metabolites introducing additional natural isotopes leading to measurements that do not directly represent the carbon labeling distribution. To make full use of LC- and GC-MS/MS mass isotopomer measurements, the influence of natural isotopes has to be eliminated (corrected). Our correction approach is analyzed for the two most common applications; (13)C fluxomics and isotope dilution mass spectrometry (IDMS) based metabolomics. Natural isotopes can have an impact on the calculated flux distribution which strongly depends on the substrate labeling and the actual flux distribution. Second, we show that in IDMS based metabolomics natural isotopes lead to underestimated concentrations that can and should be corrected with a nonlinear calibration. Our simulations indicate that the correction for natural abundance in isotope based fluxomics and quantitative metabolomics is essential for correct data interpretation.

Developmental neurotoxicity (DNT) may be induced when chemicals disturb a key neurodevelopmental process, and many tests focus on this type of toxicity. Alternatively, DNT may occur when chemicals are cytotoxic only during a specific neurodevelopmental stage. The toxicant sensitivity is affected by the expression of toxicant targets and by resilience factors. Although cellular metabolism plays an important role, little is known how it changes during human neurogenesis, and how potential alterations affect toxicant sensitivity of mature vs. immature neurons. We used immature (d0) and mature (d6) LUHMES cells (dopaminergic human neurons) to provide initial answers to these questions. Transcriptome profiling and characterization of energy metabolism suggested a switch from predominantly glycolytic energy generation to a more pronounced contribution of the tricarboxylic acid cycle (TCA) during neuronal maturation. Therefore, we used pulsed stable isotope-resolved metabolomics (pSIRM) to determine intracellular metabolite pool sizes (concentrations), and isotopically non-stationary C-metabolic flux analysis (INSTC-MFA) to calculate metabolic fluxes. We found that d0 cells mainly use glutamine to fuel the TCA. Furthermore, they rely on extracellular pyruvate to allow continuous growth. This metabolic situation does not allow for mitochondrial or glycolytic spare capacity, i.e. the ability to adapt energy generation to altered needs. Accordingly, neuronal precursor cells displayed a higher sensitivity to several mitochondrial toxicants than mature neurons differentiated from them. In summary, this study shows that precursor cells lose their glutamine dependency during differentiation while they gain flexibility of energy generation and thereby increase their resistance to low concentrations of mitochondrial toxicants.

BackgroundThe bacterium Pseudomonas fluorescens switches to an alginate-producing phenotype when the pleiotropic anti-sigma factor MucA is inactivated. The inactivation is accompanied by an increased biomass yield on carbon sources when grown under nitrogen-limited chemostat conditions. A previous metabolome study showed significant changes in the intracellular metabolite concentrations, especially of the nucleotides, in mucA deletion mutants compared to the wild-type. In this study, the P. fluorescens SBW25 wild-type and an alginate non-producing mucA- ΔalgC double-knockout mutant are investigated through model-based 13C-metabolic flux analysis (13C-MFA) to explore the physiological consequences of MucA inactivation at the metabolic flux level. Intracellular metabolite extracts from three carbon labelling experiments using fructose as the sole carbon source are analysed for 13C-label incorporation in primary metabolites by gas and liquid chromatography tandem mass spectrometry.ResultsFrom mass isotopomer distribution datasets, absolute intracellular metabolic reaction rates for the wild type and the mutant are determined, revealing extensive reorganisation of carbon flux through central metabolic pathways in response to MucA inactivation. The carbon flux through the Entner-Doudoroff pathway was reduced in the mucA- ΔalgC mutant, while flux through the pentose phosphate pathway was increased. Our findings also indicated flexibility of the anaplerotic reactions through down-regulation of the pyruvate shunt in the mucA- ΔalgC mutant and up-regulation of the glyoxylate shunt.ConclusionsAbsolute metabolic fluxes and metabolite levels give detailed, integrated insight into the physiology of this industrially, medically and agriculturally important bacterial species and suggest that the most efficient way of using a mucA- mutant as a cell factory for alginate production would be to use non-growing conditions and nitrogen deprivation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-015-0148-0) contains supplementary material, which is available to authorized users.