Aerobic growth physiology of Saccharomyces cerevisiae on sucrose is strain-dependent.

Present knowledge on the quantitative aerobic physiology of the yeast Saccharomyces cerevisiae during growth on sucrose as sole carbon and energy source is limited to either adapted cells or to the model laboratory strain CEN.PK113-7D. To broaden our understanding of this matter and open novel opportunities for sucrose-based biotechnological processes, we characterized three strains, with distinct backgrounds, during aerobic batch bioreactor cultivations. Our results reveal that sucrose metabolism in S. cerevisiae is a strain-specific trait. Each strain displayed distinct extracellular hexose concentrations and invertase activity profiles. Especially, the inferior maximum specific growth rate (0.21 h-1) of the CEN.PK113-7D strain, with respect to that of strains UFMG-CM-Y259 (0.37 h-1) and JP1 (0.32 h-1), could be associated to its low invertase activity (0.04-0.09 U/mgDM). Moreover, comparative experiments with glucose or fructose alone, or in combination, suggest mixed mechanisms of sucrose utilization by the industrial strain JP1, and points out the remarkable ability of the wild isolate UFMG-CM-259 to grow faster on sucrose than on glucose in a well-controlled cultivation system. This work hints to a series of metabolic traits that can be exploited to increase sucrose catabolic rates and bioprocess efficiency.

Modelling cell-free RNA and protein synthesis with minimal systems.

DNA-guided cell-free protein synthesis using a minimal set of purified components has emerged as a versatile platform in constructive biology. The E. coli-based PURE (protein synthesis using recombinant elements) system offers the basic protein synthesis factory in a prospective minimal cell relying on extant molecules. However, there is an urgent need to improve the system's performance and to build a mechanistic computational model that can help interpret and predict gene expression dynamics. Herein, we utilized all three commercially available PURE system variants: PURExpress, PUREfrex and PUREfrex2.0. We monitored apparent kinetics of mRNA and protein synthesis by fluorescence spectroscopy at different concentrations of DNA template. Analysis of polysome distributions by atomic force microscopy, combined with a stochastic model of translation, revealed inefficient usage of ribosomes, consistent with the idea that translation initiation is a limiting step. This preliminary dataset was used to formulate hypotheses regarding possible mechanisms impeding robust gene expression. Next, we challenged these hypotheses by devising targeted experiments aimed to alleviate the current limitations of PUREfrex. We identified depletion of key initiation factors (IFs) by translationally inactive mRNA as a possible inhibitory mechanism. This adverse process could partly be remedied by targeted mRNA degradation, whereas addition of more IFs and of the hrpA RNA helicase had no substantial effects. Moreover, the depletion of tRNAs as peptidyl-tRNAs can become limiting in PUREfrex (but not in PURExpress), which can be alleviated by addition of peptidyl-tRNA-hydrolase (PTH). We attempted to build a new model for PURE system dynamics integrating all experimental observations. Although a satisfying global fit can be obtained in specific conditions (with PTH), a unifying system's level model is still missing.

Accurate Measurement of the in vivo Ammonium Concentration in Saccharomyces cerevisiae.

Ammonium (NH4⁺) is the most common N-source for yeast fermentations, and N-limitation is frequently applied to reduce growth and increase product yields. While there is significant molecular knowledge on NH4⁺ transport and assimilation, there have been few attempts to measure the in vivo concentration of this metabolite. In this article, we present a sensitive and accurate analytical method to quantify the in vivo intracellular ammonium concentration in Saccharomyces cerevisiae based on standard rapid sampling and metabolomics techniques. The method validation experiments required the development of a proper sample processing protocol to minimize ammonium production/consumption during biomass extraction by assessing the impact of amino acid degradation-an element that is often overlooked. The resulting cold chloroform metabolite extraction method, together with quantification using ultra high performance liquid chromatography-isotope dilution mass spectrometry (UHPLC-IDMS), was not only more sensitive than most of the existing methods but also more accurate than methods that use electrodes, enzymatic reactions, or boiling water or boiling ethanol biomass extraction because it minimized ammonium consumption/production during sampling processing and interference from other metabolites in the quantification of intracellular ammonium. Finally, our validation experiments showed that other metabolites such as pyruvate or 2-oxoglutarate (αKG) need to be extracted with cold chloroform to avoid measurements being biased by the degradation of other metabolites (e.g., amino acids).

Quantitative Metabolomics and Instationary 13C-Metabolic Flux Analysis Reveals Impact of Recombinant Protein Production on Trehalose and Energy Metabolism in Pichia pastoris.

Pichia pastoris has been recognized as an effective host for recombinant protein production. In this work, we combine metabolomics and instationary 13C metabolic flux analysis (INST 13C-MFA) using GC-MS and LC-MS/MS to evaluate the potential impact of the production of a Rhizopus oryzae lipase (Rol) on P. pastoris central carbon metabolism. Higher oxygen uptake and CO2 production rates and slightly reduced biomass yield suggest an increased energy demand for the producing strain. This observation is further confirmed by 13C-based metabolic flux analysis. In particular, the flux through the methanol oxidation pathway and the TCA cycle was increased in the Rol-producing strain compared to the reference strain. Next to changes in the flux distribution, significant variations in intracellular metabolite concentrations were observed. Most notably, the pools of trehalose, which is related to cellular stress response, and xylose, which is linked to methanol assimilation, were significantly increased in the recombinant strain.

Fast "Feast/Famine" Cycles for Studying Microbial Physiology Under Dynamic Conditions: A Case Study with Saccharomyces cerevisiae.

Microorganisms are constantly exposed to rapidly changing conditions, under natural as well as industrial production scale environments, especially due to large-scale substrate mixing limitations. In this work, we present an experimental approach based on a dynamic feast/famine regime (400 s) that leads to repetitive cycles with moderate changes in substrate availability in an aerobic glucose cultivation of Saccharomyces cerevisiae. After a few cycles, the feast/famine produced a stable and repetitive pattern with a reproducible metabolic response in time, thus providing a robust platform for studying the microorganism's physiology under dynamic conditions. We found that the biomass yield was slightly reduced (-5%) under the feast/famine regime, while the averaged substrate and oxygen consumption as well as the carbon dioxide production rates were comparable. The dynamic response of the intracellular metabolites showed specific differences in comparison to other dynamic experiments (especially stimulus-response experiments, SRE). Remarkably, the frequently reported ATP paradox observed in single pulse experiments was not present during the repetitive perturbations applied here. We found that intracellular dynamic accumulations led to an uncoupling of the substrate uptake rate (up to 9-fold change at 20 s.) Moreover, the dynamic profiles of the intracellular metabolites obtained with the feast/famine suggest the presence of regulatory mechanisms that resulted in a delayed response. With the feast famine setup many cellular states can be measured at high frequency given the feature of reproducible cycles. The feast/famine regime is thus a versatile platform for systems biology approaches, which can help us to identify and investigate metabolite regulations under realistic conditions (e.g., large-scale bioreactors or natural environments).

Glucose-methanol co-utilization in Pichia pastoris studied by metabolomics and instationary ¹³C flux analysis.

BACKGROUND: Several studies have shown that the utilization of mixed carbon feeds instead of methanol as sole carbon source is beneficial for protein production with the methylotrophic yeast Pichia pastoris. In particular, growth under mixed feed conditions appears to alleviate the metabolic burden related to stress responses triggered by protein overproduction and secretion. Yet, detailed analysis of the metabolome and fluxome under mixed carbon source metabolizing conditions are missing. To obtain a detailed flux distribution of central carbon metabolism, including the pentose phosphate pathway under methanol-glucose conditions, we have applied metabolomics and instationary ¹³C flux analysis in chemostat cultivations. RESULTS: Instationary ¹³C-based metabolic flux analysis using GC-MS and LC-MS measurements in time allowed for an accurate mapping of metabolic fluxes of glycolysis, pentose phosphate and methanol assimilation pathways. Compared to previous results from NMR-derived stationary state labelling data (proteinogenic amino acids, METAFoR) more fluxes could be determined with higher accuracy. Furthermore, using a thermodynamic metabolic network analysis the metabolite measurements and metabolic flux directions were validated. Notably, the concentration of several metabolites of the upper glycolysis and pentose phosphate pathway increased under glucose-methanol feeding compared to the reference glucose conditions, indicating a shift in the thermodynamic driving forces. Conversely, the extracellular concentrations of all measured metabolites were lower compared with the corresponding exometabolome of glucose-grown P. pastoris cells.The instationary ¹³C flux analysis resulted in fluxes comparable to previously obtained from NMR datasets of proteinogenic amino acids, but allowed several additional insights. Specifically, i) in vivo metabolic flux estimations were expanded to a larger metabolic network e.g. by including trehalose recycling, which accounted for about 1.5% of the glucose uptake rate; ii) the reversibility of glycolytic/gluconeogenesis, TCA cycle and pentose phosphate pathways reactions was estimated, revealing a significant gluconeogenic flux from the dihydroxyacetone phosphate/glyceraldehydes phosphate pool to glucose-6P. The origin of this finding could be carbon recycling from the methanol assimilatory pathway to the pentose phosphate pool. Additionally, high exchange fluxes of oxaloacetate with aspartate as well as malate indicated amino acid pool buffering and the activity of the malate/Asp shuttle; iii) the ratio of methanol oxidation vs utilization appeared to be lower (54 vs 79% assimilated methanol directly oxidized to CO2). CONCLUSIONS: In summary, the application of instationary ¹³C-based metabolic flux analysis to P. pastoris provides an experimental framework with improved capabilities to explore the regulation of the carbon and energy metabolism of this yeast, particularly for the case of methanol and multicarbon source metabolism.

Resolving phenylalanine metabolism sheds light on natural synthesis of penicillin G in Penicillium chrysogenum.

The industrial production of penicillin G by Penicillium chrysogenum requires the supplementation of the growth medium with the side chain precursor phenylacetate. The growth of P. chrysogenum with phenylalanine as the sole nitrogen source resulted in the extracellular production of phenylacetate and penicillin G. To analyze this natural pathway for penicillin G production, chemostat cultures were switched to [U-(13)C]phenylalanine as the nitrogen source. The quantification and modeling of the dynamics of labeled metabolites indicated that phenylalanine was (i) incorporated in nascent protein, (ii) transaminated to phenylpyruvate and further converted by oxidation or by decarboxylation, and (iii) hydroxylated to tyrosine and subsequently metabolized via the homogentisate pathway. The involvement of the homogentisate pathway was supported by the comparative transcriptome analysis of P. chrysogenum cultures grown with phenylalanine and with (NH(4))(2)SO(4) as the nitrogen source. This transcriptome analysis also enabled the identification of two putative 2-oxo acid decarboxylase genes (Pc13g9300 and Pc18g01490). cDNAs of both genes were cloned and expressed in the 2-oxo-acid-decarboxylase-free Saccharomyces cerevisiae strain CEN.PK711-7C (pdc1 pdc5 pdc6Δ aro10Δ thi3Δ). The introduction of Pc13g09300 restored the growth of this S. cerevisiae mutant on glucose and phenylalanine, thereby demonstrating that Pc13g09300 encodes a dual-substrate pyruvate and phenylpyruvate decarboxylase, which plays a key role in an Ehrlich-type pathway for the production of phenylacetate in P. chrysogenum. These results provide a basis for the metabolic engineering of P. chrysogenum for the production of the penicillin G side chain precursor phenylacetate.

Metabolic effects of influenza virus infection in cultured animal cells: Intra- and extracellular metabolite profiling.

BACKGROUND: Many details in cell culture-derived influenza vaccine production are still poorly understood and approaches for process optimization mainly remain empirical. More insights on mammalian cell metabolism after a viral infection could give hints on limitations and cell-specific virus production capacities. A detailed metabolic characterization of an influenza infected adherent cell line (MDCK) was carried out based on extracellular and intracellular measurements of metabolite concentrations. RESULTS: For most metabolites the comparison of infected (human influenza A/PR/8/34) and mock-infected cells showed a very similar behavior during the first 10-12 h post infection (pi). Significant changes were observed after about 12 h pi: (1) uptake of extracellular glucose and lactate release into the cell culture supernatant were clearly increased in infected cells compared to mock-infected cells. At the same time (12 h pi) intracellular metabolite concentrations of the upper part of glycolysis were significantly increased. On the contrary, nucleoside triphosphate concentrations of infected cells dropped clearly after 12 h pi. This behaviour was observed for two different human influenza A/PR/8/34 strains at slightly different time points. CONCLUSIONS: Comparing these results with literature values for the time course of infection with same influenza strains, underline the hypothesis that influenza infection only represents a minor additional burden for host cell metabolism. The metabolic changes observed after 12 h pi are most probably caused by the onset of apoptosis in infected cells. The comparison of experimental data from two variants of the A/PR/8/34 virus strain (RKI versus NIBSC) with different productivities and infection dynamics showed comparable metabolic patterns but a clearly different timely behavior. Thus, infection dynamics are obviously reflected in host cell metabolism.

Metabolic flux model for an anchorage-dependent MDCK cell line: characteristic growth phases and minimum substrate consumption flux distribution.

Up to now cell-culture based vaccine production processes only reach low productivities. The reasons are: (i) slow cell growth and (ii) low cell concentrations. To address these shortcomings, a quantitative analysis of the process conditions, especially the cell growth and the metabolic capabilities of the host cell line is required. For this purpose a MDCK cell based influenza vaccine production process was investigated. With a segregated growth model four distinct cell growth phases are distinguished in the batch process. In the first phase the cells attach to the surface of the microcarriers and show low metabolic activity. The second phase is characterized by exponential cell growth. In the third phase, preceded by a change in oxygen consumption, contact inhibition leads to a decrease in cell growth. Finally, the last phase before infection shows no further increase in cell numbers. To gain insight into the metabolic activity during these phases, a detailed metabolic model of MDCK cell was developed based on genome information and experimental analysis. The MDCK model was also used to calculate a theoretical flux distribution representing an optimized cell that only consumes a minimum of carbon sources. Comparing this minimum substrate consumption flux distribution to the fluxes estimated from experiments unveiled high overflow metabolism under the applied process conditions.

Comparison of metabolic flux distributions for MDCK cell growth in glutamine- and pyruvate-containing media.

In mammalian cell cultures, ammonia that is released into the medium as a result of glutamine metabolism and lactate that is excreted due to incomplete glucose oxidation are both known to essentially inhibit the growth of cells. For some cell lines, for example, hybridoma cells, excreted ammonia also has an effect on product formation. Although glutamine has been generally considered as the major energy source for mammalian cells, it was recently found that various adherent cell lines (MDCK, CHO-K1, and BHK21) can grow as well in glutamine-free medium, provided glutamine is substituted with pyruvate. In such a medium the level of both ammonia and lactate released was significantly reduced. In this study, metabolic flux analysis (MFA) was applied to Madin Darby Canine Kidney (MDCK) cells cultivated in glutamine-containing and glutamine-free medium. The results of the MFA allowed further investigation of the influence of glutamine substitution with pyruvate on the metabolism of MDCK cells during different growth stages of adherent cells, e.g., early exponential and late contact-inhibited phase. Pyruvate seemed to directly enter the TCA cycle, whereas most of the glucose consumed was excreted as lactate. Although the exact mechanisms are not clear so far, this resulted in a reduction of the glucose uptake necessary for cellular metabolism in glutamine-free medium. Furthermore, consumption of ATP by futile cycles seemed to be significantly reduced when substituting glutamine with pyruvate. These findings imply that glutamine-free medium favors a more efficient use of nutrients by cells. However, a number of metabolic fluxes were similar in the two cultivations considered, e.g., most of the amino acid uptake and degradation rates or fluxes through the branch of the TCA cycle converting alpha-ketoglutarate to malate, which is responsible for the mitochondrial ATP synthesis. Besides, the specific rate of cell growth was approximately the same in both cultivations. Thus, the switch from glutamine-containing to glutamine-free medium with pyruvate provided a series of benefits without dramatic changes of cellular metabolism.

Visualizing regulatory interactions in metabolic networks.

BACKGROUND: Direct visualization of data sets in the context of biochemical network drawings is one of the most appealing approaches in the field of data evaluation within systems biology. One important type of information that is very helpful in interpreting and understanding metabolic networks has been overlooked so far. Here we focus on the representation of this type of information given by the strength of regulatory interactions between metabolite pools and reaction steps. RESULTS: The visualization of such interactions in a given metabolic network is based on a novel concept defining the regulatory strength (RS) of effectors regulating certain reaction steps. It is applicable to any mechanistic reaction kinetic formula. The RS values are measures for the strength of an up- or down-regulation of a reaction step compared with the completely non-inhibited or non-activated state, respectively. One numerical RS value is associated to any effector edge contained in the network. The RS is approximately interpretable on a percentage scale where 100% means the maximal possible inhibition or activation, respectively, and 0% means the absence of a regulatory interaction. If many effectors influence a certain reaction step, the respective percentages indicate the proportion in which the different effectors contribute to the total regulation of the reaction step. The benefits of the proposed method are demonstrated with a complex example system of a dynamic E. coli network. CONCLUSION: The presented visualization approach is suitable for an intuitive interpretation of simulation data of metabolic networks under dynamic as well as steady-state conditions. Huge amounts of simulation data can be analyzed in a quick and comprehensive way. An extended time-resolved graphical network presentation provides a series of information about regulatory interaction within the biological system under investigation.

Computational tools for isotopically instationary 13C labeling experiments under metabolic steady state conditions.

(13)C metabolic flux analysis (MFA) has become an important and powerful tool for the quantitative analysis of metabolic networks in the framework of metabolic engineering. Isotopically instationary (13)C MFA under metabolic stationary conditions is a promising refinement of classical stationary MFA. It accounts for the experimental requirements of non-steady-state cultures as well as for the shortening of the experimental duration. This contribution extends all computational methods developed for classical stationary (13)C MFA to the instationary situation by using high-performance computing methods. The developed tools allow for the simulation of instationary carbon labeling experiments (CLEs), sensitivity calculation with respect to unknown parameters, fitting of the model to the measured data, statistical identifiability analysis and an optimal experimental design facility. To explore the potential of the new approach all these tools are applied to the central metabolism of Escherichia coli. The achieved results are compared to the outcome of the stationary counterpart, especially focusing on statistical properties. This demonstrates the specific strengths of the instationary method. A new ranking method is proposed making both an a priori and an a posteriori design of the sampling times available. It will be shown that although still not all fluxes are identifiable, the quality of flux estimates can be strongly improved in the instationary case. Moreover, statements about the size of some immeasurable pool sizes can be made.

Serial 13C-based flux analysis of an L-phenylalanine-producing E. coli strain using the sensor reactor.

With the aid of the recently developed Sensor reactor system, a series of three subsequent (13)C labeling experiments was performed mirroring the l-phenylalanine (l-Phe) production phase of a recombinant E. coli strain that was cultivated under industry-like conditions in a 300 L bioreactor. On the basis of the data from NMR labeling analysis, three subsequent flux patterns were successfully derived monitoring the l-Phe formation during an observation window from 14 to 23.3 h process time. Linear programming was performed to identify optimal flux patterns for l-Phe formation. Additionally, flux sensitivity analysis was used to identify the most promising metabolic engineering target. As a result, high rates of phosphoenolpyruvate (PEP) to pyruvate (PYR) conversion were identified as the most important reason for deterioration of the l-Phe/glucose yield from 20 to finally 11 mol %. Considering the characteristics of the enzyme kinetics involved, the working hypothesis was formulated that phosphoenolpyruvate synthase activity was increasingly hampered by rising oxaloacetate and 2-oxoglutarate concentrations, while at the same time pyruvate kinase activity arose due to activation by fructose 1,6-diphosphate. Hence, pps overexpression should be performed to optimize the existing production strain.