Analyzing the effect of using axial impellers in large-scale bioreactors.

In high-performance industrial fermentation processes, stirring and aeration may account for significant production costs. Compared to the widely applied Rushton impellers, axial-pumping impellers are known to yield a lower power draw and at the same time improve mixing. However, their lower gas dispersion capability requires stronger agitation, compromising these benefits. Diverse advanced impeller forms have been developed to cope with this challenge. We apply alternating radial and axial impellers and demonstrate strong gas dispersion and energy-efficient mixing for the first time in a large-scale (160 m3 ) bioreactor, based on experimental and computational fluid dynamics simulation data. For equal operating conditions (stirrer speed, aeration rate), this setup yielded similar gas hold-ups and better mixing times (35%) compared to a classical Rushton-only configuration. Hence, applying a radial impeller on an upper level for improving gas dispersion maintains the benefits of axial impellers in terms of reducing energy demand (up to 50%). We conclude that this effect is significant only at large-scale, when bubbles substantially expand due to the release of the hydrostatic pressure and have time to coalesce. The work thus extends current knowledge on mixing and aeration of large-scale reactors using classical impeller types.

Characterization of the gas dispersion behavior of multiple impeller stages by flow regime analysis and CFD simulations.

Multiple impeller reactors are widely used due to their advanced gas utilization and an increased volumetric mass transfer coefficient. However, with the application of Rushton impellers, gas dispersion efficiency varies between the bottom and the upper impeller levels. The present study analyzes the individual flow regime, power input, and gas hold-up in each compartment of a reactor equipped with four Rushton impellers. The results indicate that the pre-dispersion of the air introduced by the bottom impeller (up to 80%) plays a key role in a better gas retention efficiency of the upper impellers (>300%) and leads to a shift of the cavity and flooding lines in the flow map (Fr- vs Fl-Number) of the upper impellers. A novel analysis of the bubble flow in the dispersed state via a two-phase LES-based CFD model reveals that a more homogenous distribution of air bubbles in the upper compartments leads to high compartment gas hold-up values, but fewer bubbles in the vicinity of the impellers. The measured and simulated data of this study indicate that the upper impellers' efficiency mostly depends on the flow regime of and the pre-dispersion by the bottom impeller rather than on the upper impellers' flow regimes. These results contribute to the understanding of essential mixing processes and scaling of aerated bioreactors.

Real-time monitoring of fungal growth and morphogenesis at single-cell resolution.

Development times for efficient large-scale production, utilizing fungal species, are still very long. This is mainly due to the poor knowledge of many important variables related to fungal growth and morphogenesis. We specifically addressed this knowledge gap by combining a microfluidic cultivation device with time-lapse live cell imaging. This combination facilitates (i) studying population heterogeneity at single-cell resolution, (ii) monitoring of fungal morphogenesis in a high spatiotemporal manner under defined environmental conditions, and (iii) parallelization of experiments for statistical data analysis. Our analysis of Penicillium chrysogenum, the workhorse for antibiotic production worldwide, revealed significant heterogeneity in size, vitality and differentiation times between spore, mycelium and pellets when cultivated under industrially relevant conditions. For example, the swelling rate of single spores in complex medium ( µ = 0.077 ± 0.036 h - 1 ) and the formation rate of higher branched mycelia in defined glucose medium ( µ = 0.046 ± 0.031 h - 1 ) were estimated from broad time-dependent cell size distributions, which in turn were derived from computational image analysis of 257 and 49 time-lapse series, respectively. In order to speed up the development of new fungal production processes, a deeper understanding of these heterogeneities is required and the presented microfluidic single-cell approach provides a solid technical foundation for such quantitative studies.

MEMOSys 2.0: an update of the bioinformatics database for genome-scale models and genomic data.

The MEtabolic MOdel research and development System (MEMOSys) is a versatile database for the management, storage and development of genome-scale models (GEMs). Since its initial release, the database has undergone major improvements, and the new version introduces several new features. First, the novel concept of derived models allows users to create model hierarchies that automatically propagate modifications along their order. Second, all stored components can now be easily enhanced with additional annotations that can be directly extracted from a supplied Systems Biology Markup Language (SBML) file. Third, the web application has been substantially revised and now features new query mechanisms, an easy search system for reactions and new link-out services to publicly available databases. Fourth, the updated database now contains 20 publicly available models, which can be easily exported into standardized formats for further analysis. Fifth, MEMOSys 2.0 is now also available as a fully configured virtual image and can be found online at http://www.icbi.at/memosys and http://memoys.i-med.ac.at. Database URL: http://memosys.i-med.ac.at.

Simultaneous utilization of glucose and gluconate in Penicillium chrysogenum during overflow metabolism.

The filamentous fungus Penicillium chrysogenum is one of the most important production organism for ß-lactam antibiotics, especially penicillin. A specific feature of P. chrysogenum is the formation of gluconate as the primary overflow metabolite under non-limiting growth on glucose. Gluconate can be formed extracellularly by the enzyme glucose oxidase (GOD) that shows high activities under glucose excess conditions. Currently, it is assumed that under these conditions glucose is the preferred carbon substrate for P. chrysogenum and gluconate consumption first starts after glucose becomes limiting. Here, we specifically address this hypothesis by combining batch cultivation experiments on defined glucose media, time-dependent GOD activity measurements, and (13)C-tracer studies. Our data prove that both substrates are metabolized simultaneously independent from the actual glucose concentration and therefore suggest that no distinct mechanism of carbon catabolite repression exists for gluconate in P. chrysogenum. Moreover, gluconate consumption does not interfere with penicillin V production by repression of the penicillin genes. Finally, by following a model-driven approach the specific uptake rates for glucose and gluconate were quantified and found to be significantly higher for gluconate. In summary, our results show that P. chrysogenum metabolizes gluconate directly and at high rates making it an interesting alternative carbon source for production purposes.

Quantitative quenching evaluation and direct intracellular metabolite analysis in Penicillium chrysogenum.

Sustained progress in metabolic engineering methodologies has stimulated new efforts toward optimizing fungal production strains such as through metabolite analysis of Penicillium chrysogenum industrial-scale processes. Accurate intracellular metabolite quantification requires sampling procedures that rapidly stop metabolism (quenching) and avoid metabolite loss via the cell membrane (leakage). When sampling protocols are validated, the quenching efficiency is generally not quantitatively assessed. For fungal metabolomics, quantitative biomass separation using centrifugation is a further challenge. In this study, P. chrysogenum intracellular metabolites were quantified directly from biomass extracts using automated sampling and fast filtration. A master/slave bioreactor concept was applied to provide industrial production conditions. Metabolic activity during sampling was monitored by 13C tracing. Enzyme activities were efficiently stopped and metabolite leakage was absent. This work provides a reliable method for P. chrysogenum metabolomics and will be an essential base for metabolic engineering of industrial processes.

Prediction of kinetic parameters from DNA-binding site sequences for modeling global transcription dynamics in Escherichia coli.

The majority of dynamic gene regulatory network (GRN) models are comprised of only a few genes and do not take multiple transcription regulation into account. The models are conceived in this way in order to minimize the number of kinetic parameters. In this paper, we propose a new approach for predicting kinetic parameters from DNA-binding site sequences by correlating the protein-DNA-binding affinities with nucleotide sequence conservation. We present the dynamic modeling of the cra modulon transcription in Escherichia coli during glucose-limited fed-batch cultivation. The concentration of the Cra regulator protein inhibitor, fructose 1,6-bis(phosphate), decreases sharply, eventually leading to the repression of transcription. Total RNA concentration data indicate a strong regulation of transcription through the availability of RNA polymerase. A critical assessment of the results of the model simulations supports this finding. This new approach for the prediction of transcription dynamics may improve the metabolic engineering of gene regulation processes.

Quantifying cytosolic messenger RNA concentrations in Escherichia coli using real-time polymerase chain reaction for a systems biology approach.

Current messenger RNA (mRNA) quantification methods are sophisticated tools for the analysis of gene regulation. However, these methods are not suitable for more complex quantitative approaches such as the mathematical modeling of the in vivo regulation of transcription where dynamic cytosolic mRNA concentrations need to be taken into consideration. In the current study, the "standard curve method" for quantitative reverse transcription real-time polymerase chain reaction (qRT-PCR) was extended by including an internal RNA standard. This standard enables transcript losses that occur during the process, as well as variations resulting from nonquantitative processes, to be accounted for. The use of an internal standard yielded transcript concentration estimates that were on average seven times higher than those in cases where an internal standard is omitted. Choosing the cra modulon in Escherichia coli as an example, the method applied shows that the regulation of the Cra protein, as well as the growth rate-dependent regulation, need to be taken into consideration. The new method, which enables the determination of cytosolic mRNA concentrations, allows the quantitative representation of transcriptional dynamics. This is an important aspect of the analysis of the complex interactions of metabolism and regulation and in the application of mathematical modeling for systems biology.

In vitro synthesis and characterization of guanosine 3',5'-bis(diphosphate).

The intracellular alarmone guanosine 3',5'-bis(diphosphate) (ppGpp) has been thoroughly investigated over the past 40 years and has become one of the best-known effectors in bacterial physiology. ppGpp is also of great importance for biotechnological applications. Systems biology research, involving experimental and mathematical approaches, has contributed a great deal to uncovering the alarmone's complex regulatory effects. HPLC analysis and UV detection are used to quantify intracellular ppGpp. The samples analyzed also contain other phosphorylated guanine nucleotides and, therefore, are spiked with a standard ppGpp solution. A rapidly growing number of laboratories are turning to synthesizing the nucleotide in vitro involving time-consuming protocols and yielding only low amounts of ppGpp. The current article provides a protocol for the preparation of large quantities of a ribosome extract that contains high ppGpp synthesis activity. The demonstrated upscaling from shaking flask to bioreactor cultivation involves the continuous and refrigerated harvest of the biomass. (13)C NMR analysis enabled the structural characterization of the synthesis product and was complemented by mass spectrometry and methods that are commonly used to identify ppGpp.

Quantification of rRNA in Escherichia coli using capillary gel electrophoresis with laser-induced fluorescence detection.

Over the past 10 years, sophisticated powerful techniques have been developed for the quantification of messenger RNA (mRNA) and ribosomal RNA (rRNA), enabling researchers in science, industry, and molecular medicine to explore gene expression. These techniques require the (reverse) transcription of analyte RNA, hybridization with synthetic oligonucleotides, and other additional steps that make them costly, time-consuming, and quantitatively difficult to perform. The current work demonstrates how 16S and 23S rRNA can be quantified precisely using capillary gel electrophoresis with laser-induced fluorescence detection (CGE-LIF) directly after the extraction of total RNA without requiring further reactions or calibration. CGE-LIF normally is used for the qualitative examination of RNA preparations. Its quantitative performance could be improved significantly using MS2 bacteriophage RNA as an internal standard. The entire analytical procedure was validated for linearity, repeatability, reproducibility, and recovery. This validation also included total RNA extraction from bacterial cells, an aspect examined for the first time in absolute RNA quantification. Recovery is close to 100%, and the analytical precision was increased 10-fold (CV<3%), as compared with similar approaches. The demonstrated method is simple and opens up new possibilities for the absolute quantification of not only rRNA but also individual mRNAs.

Topology of the global regulatory network of carbon limitation in Escherichia coli.

One fundamental shortcoming of biotechnological processes operating under carbon-limiting conditions is the high-energy demand (maintenance) of the cells. Although the function of the central carbon metabolism in supplying precursors and energy for biosynthesis has been thoroughly characterized, its regulation and dynamic behaviour during carbon-limited growth has not yet been revealed. The current work demonstrates a time series of metabolic flux distributions during fed-batch cultivation of Escherichia coli K-12 W3110 applying a constant feed rate. The fluxes in glycolysis, pentose phosphate pathway and biosynthesis fell significantly, whereas TCA cycle fluxes remained constant. The flux redistribution resulted in an enhanced energy generation in the TCA cycle and consequently, in a 20% lower biomass yield. The intracellular alarmones ppGpp and cAMP accumulated in large quantities after the onset of nutrient limitation, subsequently declining to basal levels. The network topology of the regulation of the central metabolic pathways was identified so that the observed metabolic and regulatory behaviour can be described. This provides novel aspects of global regulation of the metabolism by the cra, crp and relA/spoT modulons. The work constitutes an important step towards dynamic mathematical modelling of regulation and metabolism, which is needed for the rational optimization of biotechnological processes.