S. Aljoscha Wahl

Thermodynamics-based design of microbial cell factories for anaerobic product formation.

The field of metabolic engineering has delivered new microbial cell factories and processes for the production of different compounds including biofuels, (di)carboxylic acids, alcohols, and amino acids. Most of these processes are aerobic, with few exceptions (e.g., alcoholic fermentation), and attention is focused on assembling a high-flux product pathway with a production limit usually set by the oxygen transfer rate. By contrast, anaerobic product synthesis offers significant benefits compared to aerobic systems: higher yields, less heat generation, reduced biomass production, and lower mechanical energy input, which can significantly reduce production costs. Using simple thermodynamic calculations, we demonstrate that many products can theoretically be produced under anaerobic conditions using several conventional and non-conventional substrates.

Flux response of glycolysis and storage metabolism during rapid feast/famine conditions in Penicillium chrysogenum using dynamic 13C labeling

The scale-up of fermentation processes frequently leads to a reduced productivity compared to small-scale screening experiments. Large-scale mixing limitations that lead to gradients in substrate and oxygen availability could influence the microorganism performance. Here, the impact of substrate gradients on a penicillin G producing Penicillium chrysogenum cultivation was analyzed using an intermittent glucose feeding regime. The intermittent feeding led to fluctuations in the extracellular glucose concentration between 400 μM down to 6.5 μM at the end of the cycle. The intracellular metabolite concentrations responded strongly and showed up to 100-fold changes. The intracellular flux changes were estimated on the basis of dynamic (13) C mass isotopomer measurements during three cycles of feast and famine using a novel hybrid modeling approach. The flux estimations indicated a high turnover of internal and external storage metabolites in P. chrysogenum under feast/famine conditions. The synthesis and degradation of storage requires cellular energy (ATP and UTP) in competition with other cellular functions including product formation. Especially, 38% of the incoming glucose was recycled once in storage metabolism. This result indicated that storage turnover is increased under dynamic cultivation conditions and contributes to the observed decrease in productivity compared to reference steady-state conditions.

Determination of the Cytosolic NADPH/NADP Ratio in Saccharomyces cerevisiae using Shikimate Dehydrogenase as Sensor Reaction

Eukaryotic metabolism is organised in complex networks of enzyme catalysed reactions which are distributed over different organelles. To quantify the compartmentalised reactions, quantitative measurements of relevant physiological variables in different compartments are needed, especially of cofactors. NADP(H) are critical components in cellular redox metabolism. Currently, available metabolite measurement methods allow whole cell measurements. Here a metabolite sensor based on a fast equilibrium reaction is introduced to monitor the cytosolic NADPH/NADP ratio in Saccharomyces cerevisiae: . The cytosolic NADPH/NADP ratio was determined by measuring the shikimate and dehydroshikimate concentrations (by GC-MS/MS). The cytosolic NADPH/NADP ratio was determined under batch and chemostat (aerobic, glucose-limited, D = 0.1 h−1) conditions, to be 22.0 ± 2.6 and 15.6 ± 0.6, respectively. These ratios were much higher than the whole cell NADPH/NADP ratio (1.05 ± 0.08). In response to a glucose pulse, the cytosolic NADPH/NADP ratio first increased very rapidly and restored the steady state ratio after 3 minutes. In contrast to this dynamic observation, the whole cell NADPH/NADP ratio remained nearly constant. The novel cytosol NADPH/NADP measurements provide new insights into the thermodynamic driving forces for NADP(H)-dependent reactions, like amino acid synthesis, product pathways like fatty acid production or the mevalonate pathway.

MetDFBA: incorporating time-resolved metabolomics measurements into dynamic flux balance analysis.

Understanding cellular adaptation to environmental changes is one of the major challenges in systems biology. To understand how cellular systems react towards perturbations of their steady state, the metabolic dynamics have to be described. Dynamic properties can be studied with kinetic models but development of such models is hampered by limited in vivo information, especially kinetic parameters. Therefore, there is a need for mathematical frameworks that use a minimal amount of kinetic information. One of these frameworks is dynamic flux balance analysis (DFBA), a method based on the assumption that cellular metabolism has evolved towards optimal changes to perturbations. However, DFBA has some limitations. It is less suitable for larger systems because of the high number of parameters to estimate and the computational complexity. In this paper, we propose MetDFBA, a modification of DFBA, that incorporates measured time series of both intracellular and extracellular metabolite concentrations, in order to reduce both the number of parameters to estimate and the computational complexity. MetDFBA can be used to estimate dynamic flux profiles and, in addition, test hypotheses about metabolic regulation. In a first case study, we demonstrate the validity of our method by comparing our results to flux estimations based on dynamic 13C MFA measurements, which we considered as experimental reference. For these estimations time-resolved metabolomics data from a feast-famine experiment with Penicillium chrysogenum was used. In a second case study, we used time-resolved metabolomics data from glucose pulse experiments during aerobic growth of Saccharomyces cerevisiae to test various metabolic objectives.

Natural isotope correction of MS/MS measurements for metabolomics and 13C fluxomics

Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of 13C 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 useof 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; 13C 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. Biotechnol. Bioeng. 2016;113: 1137–1147.

Current state and challenges for dynamic metabolic modeling

While the stoichiometry of metabolism is probably the best studied cellular level, the dynamics in metabolism can still not be well described, predicted and, thus, engineered. Unknowns in the metabolic flux behavior arise from kinetic interactions, especially allosteric control mechanisms. While the stoichiometry of enzymes is preserved in vitro, their activity and kinetic behavior differs from the in vivo situation. Next to this challenge, it is infeasible to test the interaction of each enzyme with each intracellular metabolite in vitro exhaustively. As a consequence, the whole interacting metabolome has to be studied in vivo to identify the relevant enzymes properties. In this review we discuss current approaches for in vivo perturbation experiments, that is, stimulus response experiments using different setups and quantitative analytical approaches, including dynamic carbon tracing. Next to reliable and informative data, advanced modeling approaches and computational tools are required to identify kinetic mechanisms and their parameters.

Quantitative Metabolomics Using ID-MS

Quantitative intracellular metabolite measurements are essential for systems biology and modeling of cellular metabolism. The MS-based quantification is error prone because (1) several sampling processing steps have to be performed, (2) the sample contains a complex mixture of partly compounds with the same mass and similar retention time, and (3) especially salts influence the ionization efficiency. Therefore internal standards are required, best for each measured compound. The use of labeled biomass, (13)C extract, is a valuable tool, reducing the standard deviations of intracellular concentration measurements significantly (especially regarding technical reproducibility). Using different platforms, i.e., LC-MS and GC-MS, a large number of different metabolites can be quantified (currently about 110).

Membrane potential independent transport of NH3 in the absence of ammonium permeases in Saccharomyces cerevisiae

BackgroundMicrobial production of nitrogen containing compounds requires a high uptake flux and assimilation of the N-source (commonly ammonium), which is generally coupled with ATP consumption and negatively influences the product yield. In the industrial workhorse Saccharomyces cerevisiae, ammonium (NH4+) uptake is facilitated by ammonium permeases (Mep1, Mep2 and Mep3), which transport the NH4+ ion, resulting in ATP expenditure to maintain the intracellular charge balance and pH by proton export using the plasma membrane-bound H+-ATPase.ResultsTo decrease the ATP costs for nitrogen assimilation, the Mep genes were removed, resulting in a strain unable to uptake the NH4+ ion. Subsequent analysis revealed that growth of this ∆mep strain was dependent on the extracellular NH3 concentrations. Metabolomic analysis revealed a significantly higher intracellular NHX concentration (3.3-fold) in the ∆mep strain than in the reference strain. Further proteomic analysis revealed significant up-regulation of vacuolar proteases and genes involved in various stress responses.ConclusionsOur results suggest that the uncharged species, NH3, is able to diffuse into the cell. The measured intracellular/extracellular NHX ratios under aerobic nitrogen-limiting conditions were consistent with this hypothesis when NHx compartmentalization was considered. On the other hand, proteomic analysis indicated a more pronounced N-starvation stress response in the ∆mep strain than in the reference strain, which suggests that the lower biomass yield of the ∆mep strain was related to higher turnover rates of biomass components.

A Toolkit to Enable Hydrocarbon Conversion in Aqueous Environments

This work puts forward a toolkit that enables the conversion of alkanes by Escherichia coli and presents a proof of principle of its applicability. The toolkit consists of multiple standard interchangeable parts (BioBricks)(9) addressing the conversion of alkanes, regulation of gene expression and survival in toxic hydrocarbon-rich environments. A three-step pathway for alkane degradation was implemented in E. coli to enable the conversion of medium- and long-chain alkanes to their respective alkanols, alkanals and ultimately alkanoic-acids. The latter were metabolized via the native β-oxidation pathway. To facilitate the oxidation of medium-chain alkanes (C5-C13) and cycloalkanes (C5-C8), four genes (alkB2, rubA3, rubA4and rubB) of the alkane hydroxylase system from Gordonia sp. TF6(8,21) were transformed into E. coli. For the conversion of long-chain alkanes (C15-C36), theladA gene from Geobacillus thermodenitrificans was implemented. For the required further steps of the degradation process, ADH and ALDH (originating from G. thermodenitrificans) were introduced(10,11). The activity was measured by resting cell assays. For each oxidative step, enzyme activity was observed. To optimize the process efficiency, the expression was only induced under low glucose conditions: a substrate-regulated promoter, pCaiF, was used. pCaiF is present in E. coli K12 and regulates the expression of the genes involved in the degradation of non-glucose carbon sources. The last part of the toolkit - targeting survival - was implemented using solvent tolerance genes, PhPFDα and β, both from Pyrococcus horikoshii OT3. Organic solvents can induce cell stress and decreased survivability by negatively affecting protein folding. As chaperones, PhPFDα and β improve the protein folding process e.g. under the presence of alkanes. The expression of these genes led to an improved hydrocarbon tolerance shown by an increased growth rate (up to 50%) in the presences of 10% n-hexane in the culture medium were observed. Summarizing, the results indicate that the toolkit enables E. coli to convert and tolerate hydrocarbons in aqueous environments. As such, it represents an initial step towards a sustainable solution for oil-remediation using a synthetic biology approach.