Klaus Mauch

Bio: Klaus Mauch is an academic researcher from University of Stuttgart. The author has contributed to research in topics: Metabolic network & Metabolic flux analysis. The author has an hindex of 19, co-authored 42 publications receiving 1739 citations. Previous affiliations of Klaus Mauch include DSM.

Dynamic modeling of the central carbon metabolism of Escherichia coli.

Abstract: Application of metabolic engineering principles to the rational design of microbial production processes crucially depends on the ability to describe quantitatively the systemic behavior of the central carbon metabolism to redirect carbon fluxes to the product-forming pathways. Despite the importance for several production processes, development of an essential dynamic model for central carbon metabolism of Escherichia coli has been severely hampered by the current lack of kinetic information on the dynamics of the metabolic reactions. Here we present the design and experimental validation of such a dynamic model, which, for the first time, links the sugar transport system (i.e., phosphotransferase system [PTS]) with the reactions of glycolysis and the pentose-phosphate pathway. Experimental observations of intracellular concentrations of metabolites and cometabolites at transient conditions are used to validate the structure of the model and to estimate the kinetic parameters. Further analysis of the detailed characteristics of the system offers the possibility of studying important questions regarding the stability and control of metabolic fluxes. © 2002 Wiley Periodicals, Inc. Biotechnol Bioeng 79: 53–73; 2002.

Metabolic flux analysis in Escherichia coli by integrating isotopic dynamic and isotopic stationary 13C labeling data

Abstract: The novel concept of isotopic dynamic 13C metabolic flux analysis (ID-13C MFA) enables integrated analysis of isotopomer data from isotopic transient and/or isotopic stationary phase of a 13C labeling experiment, short-time experiments, and an extended range of applications of 13C MFA. In the presented work, an experimental and computational framework consisting of short-time 13C labeling, an integrated rapid sampling procedure, a LC-MS analytical method, numerical integration of the system of isotopomer differential equations, and estimation of metabolic fluxes was developed and applied to determine intracellular fluxes in glycolysis, pentose phosphate pathway (PPP), and citric acid cycle (TCA) in Escherichia coli grown in aerobic, glucose-limited chemostat culture at a dilution rate of D = 0.10 h−1. Intracellular steady state concentrations were quantified for 12 metabolic intermediates. A total of 90 LC-MS mass isotopomers were quantified at sampling times t = 0, 91, 226, 346, 589 s and at isotopic stationary conditions. Isotopic stationarity was reached within 10 min in glycolytic and PPP metabolites. Consistent flux solutions were obtained by ID-13C MFA using isotopic dynamic and isotopic stationary 13C labeling data and by isotopic stationary 13C MFA (IS-13C MFA) using solely isotopic stationary data. It is demonstrated that integration of dynamic 13C labeling data increases the sensitivity of flux estimation, particularly at the glucose-6-phosphate branch point. The identified split ratio between glycolysis and PPP was 55%:44%. These results were confirmed by IS-13C MFA additionally using labeling data in proteinogenic amino acids (GC-MS) obtained after 5 h from sampled biomass. Biotechnol. Bioeng. 2008;99: 1170–1185. © 2007 Wiley Periodicals, Inc.

Identification of metabolic fluxes in hepatic cells from transient 13C-labeling experiments: Part II. Flux estimation.

Abstract: This contribution addresses the identification of metabolic fluxes and metabolite concentrations in mammalian cells from transient (13)C-labeling experiments. Whilst part I describes experimental set-up and acquisition of required metabolite and (13)C-labeling data, part II focuses on setting up network models and the estimation of intracellular fluxes. Metabolic fluxes were determined in glycolysis, pentose-phosphate pathway (PPP), and citric acid cycle (TCA) in a hepatoma cell line grown in aerobic batch cultures. In glycolytic and PPP metabolite pools isotopic stationarity was observed within 30 min, whereas in the TCA cycle the labeling redistribution did not reach isotopic steady state even within 180 min. In silico labeling dynamics were in accordance with in vivo (13)C-labeling data. Split ratio between glycolysis and PPP was 57%:43%; intracellular glucose concentration was estimated at 101.6 nmol per 10(6) cells. In contrast to isotopic stationary (13)C-flux analysis, transient (13)C-flux analysis can also be applied to industrially relevant mammalian cell fed-batch and batch cultures.

Bridging the layers: towards integration of signal transduction, regulation and metabolism into mathematical models.

Abstract: Mathematical modelling is increasingly becoming an indispensable tool for the study of cellular processes, allowing their analysis in a systematic and comprehensive manner. In the vast majority of the cases, models focus on specific subsystems, and in particular describe either metabolism, gene expression or signal transduction. Integrated models that are able to span and interconnect these layers are, by contrast, rare as their construction and analysis face multiple challenges. Such methods, however, would represent extremely useful tools to understand cell behaviour, with application in distinct fields of biological and medical research. In particular, they could be useful tools to study genotype–phenotype mappings, and the way they are affected by specific conditions or perturbations. Here, we review existing computational approaches that integrate signalling, gene regulation and/or metabolism. We describe existing challenges, available methods and point at potentially useful strategies.

Reductive glutamine metabolism by IDH1 mediates lipogenesis under hypoxia

Abstract: Acetyl coenzyme A (AcCoA) is the central biosynthetic precursor for fatty-acid synthesis and protein acetylation. In the conventional view of mammalian cell metabolism, AcCoA is primarily generated from glucose-derived pyruvate through the citrate shuttle and ATP citrate lyase in the cytosol. However, proliferating cells that exhibit aerobic glycolysis and those exposed to hypoxia convert glucose to lactate at near-stoichiometric levels, directing glucose carbon away from the tricarboxylic acid cycle and fatty-acid synthesis. Although glutamine is consumed at levels exceeding that required for nitrogen biosynthesis, the regulation and use of glutamine metabolism in hypoxic cells is not well understood. Here we show that human cells use reductive metabolism of α-ketoglutarate to synthesize AcCoA for lipid synthesis. This isocitrate dehydrogenase-1 (IDH1)-dependent pathway is active in most cell lines under normal culture conditions, but cells grown under hypoxia rely almost exclusively on the reductive carboxylation of glutamine-derived α-ketoglutarate for de novo lipogenesis. Furthermore, renal cell lines deficient in the von Hippel-Lindau tumour suppressor protein preferentially use reductive glutamine metabolism for lipid biosynthesis even at normal oxygen levels. These results identify a critical role for oxygen in regulating carbon use to produce AcCoA and support lipid synthesis in mammalian cells.

Carbon catabolite repression in bacteria: many ways to make the most out of nutrients

Abstract: Using the process of carbon catabolite repression (CCR), bacteria control gene expression and protein activity to preferentially metabolize the carbon sources that are most easily accessible and allow fastest growth. Recent findings have provided new insight into the mechanisms that different bacteria use to control CCR. Most bacteria can selectively use substrates from a mixture of different carbon sources. The presence of preferred carbon sources prevents the expression, and often also the activity, of catabolic systems that enable the use of secondary substrates. This regulation, called carbon catabolite repression (CCR), can be achieved by different regulatory mechanisms, including transcription activation and repression and control of translation by an RNA-binding protein, in different bacteria. Moreover, CCR regulates the expression of virulence factors in many pathogenic bacteria. In this Review, we discuss the most recent findings on the different mechanisms that have evolved to allow bacteria to use carbon sources in a hierarchical manner.

Universally sloppy parameter sensitivities in systems biology models.

Abstract: Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a ‘‘sloppy’’ spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME.

Abstract: This review encompasses the most important advances in liver functions and hepatotoxicity and analyzes which mechanisms can be studied in vitro. In a complex architecture of nested, zonated lobules, the liver consists of approximately 80 % hepatocytes and 20 % non-parenchymal cells, the latter being involved in a secondary phase that may dramatically aggravate the initial damage. Hepatotoxicity, as well as hepatic metabolism, is controlled by a set of nuclear receptors (including PXR, CAR, HNF-4α, FXR, LXR, SHP, VDR and PPAR) and signaling pathways. When isolating liver cells, some pathways are activated, e.g., the RAS/MEK/ERK pathway, whereas others are silenced (e.g. HNF-4α), resulting in up- and downregulation of hundreds of genes. An understanding of these changes is crucial for a correct interpretation of in vitro data. The possibilities and limitations of the most useful liver in vitro systems are summarized, including three-dimensional culture techniques, co-cultures with non-parenchymal cells, hepatospheres, precision cut liver slices and the isolated perfused liver. Also discussed is how closely hepatoma, stem cell and iPS cell-derived hepatocyte-like-cells resemble real hepatocytes. Finally, a summary is given of the state of the art of liver in vitro and mathematical modeling systems that are currently used in the pharmaceutical industry with an emphasis on drug metabolism, prediction of clearance, drug interaction, transporter studies and hepatotoxicity. One key message is that despite our enthusiasm for in vitro systems, we must never lose sight of the in vivo situation. Although hepatocytes have been isolated for decades, the hunt for relevant alternative systems has only just begun.

Dynamic modeling of the central carbon metabolism of Escherichia coli.

Abstract: Application of metabolic engineering principles to the rational design of microbial production processes crucially depends on the ability to describe quantitatively the systemic behavior of the central carbon metabolism to redirect carbon fluxes to the product-forming pathways. Despite the importance for several production processes, development of an essential dynamic model for central carbon metabolism of Escherichia coli has been severely hampered by the current lack of kinetic information on the dynamics of the metabolic reactions. Here we present the design and experimental validation of such a dynamic model, which, for the first time, links the sugar transport system (i.e., phosphotransferase system [PTS]) with the reactions of glycolysis and the pentose-phosphate pathway. Experimental observations of intracellular concentrations of metabolites and cometabolites at transient conditions are used to validate the structure of the model and to estimate the kinetic parameters. Further analysis of the detailed characteristics of the system offers the possibility of studying important questions regarding the stability and control of metabolic fluxes. © 2002 Wiley Periodicals, Inc. Biotechnol Bioeng 79: 53–73; 2002.