On-line stoichiometry and identification of metabolic state under dynamic process conditions

Optimization of dilution rate and mixed carbon feed for continuous production of recombinant plant sucrose:sucrose 1-fructosyltransferase in Komagataella phaffii

The trisaccharide 1-kestose, a major constituent of commercial fructooligosaccharide (FOS) formulations, shows a superior prebiotic effect compared to higher-chain FOS. The plant sucrose:sucrose 1-fructosyltransferases (1-SST) are extensively used for selective synthesis of lower chain FOS. In this study, enhanced recombinant (r) 1-SST production was achieved in Komagataella phaffii (formerly Pichia pastoris) containing three copies of a codon-optimized Festuca arundinacea 1-SST gene. R1-SST production reached 47 U/mL at the shake-flask level after a 96-h methanol induction phase. A chemostat-based strain characterization methodology was adopted to assess the influence of specific growth rate (µ) on cell-specific r1-SST productivity (Qp) and cell-specific oxygen uptake rate (Qo) under two different feeding strategies across dilution rates from 0.02 to 0.05 h-1. The methanol-sorbitol co-feeding strategy significantly reduced Qo by 46 ± 2.4% compared to methanol-only feeding without compromising r1-SST productivity. Based on the data, a dilution rate of 0.025 h-1 was applied for continuous cultivation of recombinant cells to achieve a sustained r1-SST productivity of 5000 ± 64.4 U/L/h for 15 days.

Accelerated Adaptive Laboratory Evolution by Automated Repeated Batch Processes in Parallelized Bioreactors

Adaptive laboratory evolution (ALE) is a valuable complementary tool for modern strain development. Insights from ALE experiments enable the improvement of microbial cell factories regarding the growth rate and substrate utilization, among others. Most ALE experiments are conducted by serial passaging, a method that involves large amounts of repetitive manual labor and comes with inherent experimental design flaws. The acquisition of meaningful and reliable process data is a burdensome task and is often undervalued and neglected, but also unfeasible in shake flask experiments due to technical limitations. Some of these limitations are alleviated by emerging automated ALE methods on the μL and mL scale. A novel approach to conducting ALE experiments is described that is faster and more efficient than previously used methods. The conventional shake flask approach was translated to a parallelized, L scale stirred-tank bioreactor system that runs controlled, automated, repeated batch processes. The method was validated with a growth optimization experiment of E. coli K-12 MG1655 grown with glycerol minimal media as a benchmark. Off-gas analysis enables the continuous estimation of the biomass concentration and growth rate using a black-box model based on first principles (soft sensor). The proposed method led to the same stable growth rates of E. coli with the non-native carbon source glycerol 9.4 times faster than the traditional manual approach with serial passaging in uncontrolled shake flasks and 3.6 times faster than an automated approach on the mL scale. Furthermore, it is shown that the cumulative number of cell divisions (CCD) alone is not a suitable timescale for measuring and comparing evolutionary progress.

Microbial technologies for biotherapeutics production: Key tools for advanced biopharmaceutical process development and control

Current trends in the biopharmaceutical market such as the diversification of therapies as well as the increasing time-to-market pressure will trigger the rethinking of bioprocess development and production approaches. Thereby, the importance of development time and manufacturing costs will increase, especially for microbial production. In the present review, we investigate three technological approaches which, to our opinion, will play a key role in the future of biopharmaceutical production. The first cornerstone of process development is the generation and effective utilization of platform knowledge. Building processes on well understood microbial and technological platforms allows to accelerate early-stage bioprocess development and to better condense this knowledge into multi-purpose technologies and applicable mathematical models. Second, the application of verified scale down systems and in silico models for process design and characterization will reduce the required number of large scale batches before dossier submission. Third, the broader availability of mathematical process models and the improvement of process analytical technologies will increase the applicability and acceptance of advanced control and process automation in the manufacturing scale. This will reduce process failure rates and subsequently cost of goods. Along these three aspects we give an overview of recently developed key tools and their potential integration into bioprocess development strategies.

Usage of Digital Twins Along a Typical Process Development Cycle

Digital methods for process design, monitoring, and control can convert classical trial-and-error bioprocess development to a quantitative engineering approach. By interconnecting hardware, software, data, and humans currently untapped process optimization potential can be accessed. The key component within such a framework is a digital twin interacting with its physical process counterpart. In this chapter, we show how digital twin guided process development can be applied on an exemplary microbial cultivation process. The usage of digital twins is described along a typical process development cycle, ranging from early strain characterization to real-time control applications. Along an illustrative case study on microbial upstream bioprocessing, we emphasize that digital twins can integrate entire process development cycles if the digital twin itself and the underlying models are continuously adapted to newly available data. Therefore, the digital twin can be regarded as a powerful knowledge management tool and a decision support system for efficient process development. Its full potential can be deployed in a real-time environment where targeted control actions can further improve process performance.

The shortcomings of accurate rate estimations in cultivation processes and a solution for precise and robust process modeling

The accurate estimation of cell growth or the substrate consumption rate is crucial for the understanding of the current state of a bioprocess. Rates unveil the actual cell status, making them valuable for quality-by-design concepts. However, in bioprocesses, the real rates are commonly not accessible due to analytical errors. We simulated Escherichia coli fed-batch fermentations, sampled at four different intervals and added five levels of noise to mimic analytical inaccuracy. We computed stepwise integral estimations with and without using moving average estimations, and smoothing spline interpolations to compare the accuracy and precision of each method to calculate the rates. We demonstrate that stepwise integration results in low accuracy and precision, especially at higher sampling frequencies. Contrary, a simple smoothing spline function displayed both the highest accuracy and precision regardless of the chosen sampling interval. Based on this, we tested three different options for substrate uptake rate estimations.

Estimation of time-varying growth, uptake and excretion rates from dynamic metabolomics data

Motivation

Technological advances in metabolomics have made it possible to monitor the concentration of extracellular metabolites over time. From these data, it is possible to compute the rates of uptake and excretion of the metabolites by a growing cell population, providing precious information on the functioning of intracellular metabolism. The computation of the rate of these exchange reactions, however, is difficult to achieve in practice for a number of reasons, notably noisy measurements, correlations between the concentration profiles of the different extracellular metabolites, and discontinuties in the profiles due to sudden changes in metabolic regime.

Results

We present a method for precisely estimating time-varying uptake and excretion rates from time-series measurements of extracellular metabolite concentrations, specifically addressing all of the above issues. The estimation problem is formulated in a regularized Bayesian framework and solved by a combination of extended Kalman filtering and smoothing. The method is shown to improve upon methods based on spline smoothing of the data. Moreover, when applied to two actual datasets, the method recovers known features of overflow metabolism in Escherichia coli and Lactococcus lactis, and provides evidence for acetate uptake by L. lactis after glucose exhaustion. The results raise interesting perspectives for further work on rate estimation from measurements of intracellular metabolites.

Availability and implementation

The Matlab code for the estimation method is available for download at https://team.inria.fr/ibis/rate-estimation-software/, together with the datasets.

Supplementary information

Supplementary data are available at Bioinformatics online.

Synthesis and analysis of separation networks for the recovery of intracellular chemicals generated from microbial-based conversions

BACKGROUND

Bioseparations can contribute to more than 70% in the total production cost of a bio-based chemical, and if the desired chemical is localized intracellularly, there can be additional challenges associated with its recovery. Based on the properties of the desired chemical and other components in the stream, there can be multiple feasible options for product recovery. These options are composed of several alternative technologies, performing similar tasks. The suitability of a technology for a particular chemical depends on (1) its performance parameters, such as separation efficiency; (2) cost or amount of added separating agent; (3) properties of the bioreactor effluent (e.g., biomass titer, product content); and (4) final product specifications. Our goal is to first synthesize alternative separation options and then analyze how technology selection affects the overall process economics. To achieve this, we propose an optimization-based framework that helps in identifying the critical technologies and parameters.

RESULTS

We study the separation networks for two representative classes of chemicals based on their properties. The separation network is divided into three stages: cell and product isolation (stage I), product concentration (II), and product purification and refining (III). Each stage exploits differences in specific product properties for achieving the desired product quality. The cost contribution analysis for the two cases (intracellular insoluble and intracellular soluble) reveals that stage I is the key cost contributor (>70% of the overall cost). Further analysis suggests that changes in input conditions and technology performance parameters lead to new designs primarily in stage I.

CONCLUSIONS

The proposed framework provides significant insights for technology selection and assists in making informed decisions regarding technologies that should be used in combination for a given set of stream/product properties and final output specifications. Additionally, the parametric sensitivity provides an opportunity to make crucial design and selection decisions in a comprehensive and rational manner. This will prove valuable in the selection of chemicals to be produced using bioconversions (bioproducts) as well as in creating better bioseparation flow sheets for detailed economic assessment and process implementation on the commercial scale.

Observability analysis of biochemical process models as a valuable tool for the development of mechanistic soft sensors

By enabling the estimation of difficult-to-measure target variables using available indirect measurements, mechanistic soft sensors have become important tools for various bioprocess monitoring and control scenarios. Despite promising higher process efficiencies and increased process understanding, widespread application of soft sensors has been stalled by uncertainty about the feasibility and reliability of their estimations given present process analytical constraints. Observability analysis can provide an indication of the possibility and reliability of soft sensor estimations by analyzing the structural properties of first-principle (mechanistic) models. In addition, it can provide a criteria for selection of suitable measurement methods with respect to their information content; thereby leading to successful implementation of soft sensors in bioprocess development and manufacturing environments. We demonstrate the utility of observability analysis for two classes of upstream bioprocesses: the processes involving growth and ethanol formation by Saccharomyces cerevisiae and the process of penicillin production by Penicillium chrysogenum. Results obtained from laboratory-scale cultivations in addition to in-silico experiments enable a comparison of theoretical aspects of observability analysis and the real-life performance of soft sensors. By taking the expected error of measurements provided to the soft sensor into account, an innovative scaling approach facilitates a higher degree of comparability of observability results among various measurement configurations and process conditions.

Selection of non-Saccharomyces yeast strains for reducing alcohol levels in wine by sugar respiration

Respiration of sugars by non-Saccharomyces yeasts has been recently proposed for lowering alcohol levels in wine. Development of industrial fermentation processes based on such an approach requires, amongst other steps, the identification of yeast strains which are able to grow and respire under the relatively harsh conditions found in grape must. This work describes the characterization of a collection of non-Saccharomyces yeast strains in order to identify candidate yeast strains for this specific application. It involved the estimation of respiratory quotient (RQ) values under aerated conditions, at low pH and high sugar concentrations, calculation of yields of ethanol and other relevant metabolites, and characterization of growth responses to the main stress factors found during the first stages of alcoholic fermentation. Physiological features of some strains of Metschnikowia pulcherrima or two species of Kluyveromyces, suggest they are suitable for lowering ethanol yields by respiration. The unsuitability of Saccharomyces cerevisiae strains for this purpose was not due to ethanol yields (under aerated conditions they are low enough for a significant reduction in final ethanol content), but to the high acetic acid yields under these growth conditions. According to results from controlled aeration fermentations with one strain of M. pulcherrima, design of an aeration regime allowing for lowering ethanol yields though preserving grape must components from excessive oxidation, would be conceivable.

A dynamic method for the investigation of induced state metabolic capacities as a function of temperature

Background

Science-based recombinant bioprocess designs as well as the design of statistical experimental plans for process optimization (Design of Experiments, DoE) demand information on physiological bioprocess boundaries, such as the onset of acetate production, adaptation times, mixed feed metabolic capabilities or induced state maximum metabolic rates as at the desired cultivation temperature. Dynamic methods provide experimental alternatives to determine this information in a fast and efficient way. Information on maximum metabolic capabilities as a function of temperature is needed in case a reduced cultivation temperature is desirable (e.g. to avoid inclusion body formation) and an appropriate feeding profile is to be designed.

Results

Here, we present a novel dynamic method for the determination of the specific growth rate as a function of temperature for induced recombinant bacterial bioprocesses. The method is based on the control of the residual substrate concentration at non-limiting conditions with dynamic changes in cultivation temperature. The presented method was automated in respect to information extraction and closed loop control by means of in-line Fourier Transformation Infrared Spectroscopy (FTIR) residual substrate measurements and on-line first principle rate-based soft-sensors. Maximum induced state metabolic capabilities as a function of temperature were successfully extracted for a recombinant E. coli C41 fed-batch bioprocess without the need for sampling in a time frame of 20 hours.

Conclusions

The presented method was concluded to allow the fast and automated extraction of maximum metabolic capabilities (specific growth rate) as a function of temperature. This complements the dynamic toolset necessary for science-based recombinant bacterial bioprocess design and DoE design.

Substrate oscillations boost recombinant protein release from Escherichia coli

Intracellular production of recombinant proteins in prokaryotes necessitates subsequent disruption of cells for protein recovery. Since the cell disruption and subsequent purification steps largely contribute to the total production cost, scalable tools for protein release into the extracellular space is of utmost importance. Although there are several ways for enhancing protein release, changing culture conditions is rather a simple and scalable approach compared to, for example, molecular cell design. This contribution aimed at quantitatively studying process technological means to boost protein release of a periplasmatic recombinant protein (alkaline phosphatase) from E. coli. Quantitative analysis of protein in independent bioreactor runs could demonstrate that a defined oscillatory feeding profile was found to improve protein release, about 60 %, compared to the conventional constant feeding rate. The process technology included an oscillatory post-induction feed profile with the frequency of 4 min. The feed rate was oscillated triangularly between a maximum (1.3-fold of the maximum feed rate achieved at the end of the fed-batch phase) and a minimum (45 % of the maximum). The significant improvement indicates the potential to maximize the production rate, while this oscillatory feed profile can be easily scaled to industrial processes. Moreover, quantitative analysis of the primary metabolism revealed that the carbon dioxide yield can be used to identify the preferred feeding profile. This approach is therefore in line with the initiative of process analytical technology for science-based process understanding in process development and process control strategies.

Effects of temperature shifts and oscillations on recombinant protein production expressed in Escherichia coli

Escherichia coli is widely used host for the intracellular expression of many proteins. However, in some cases also secretion of protein from periplasm was observed. Improvement of both intracellular and extracellular production of recombinant protein in E. coli is an attractive goal in order to reduce production cost and increase process efficiency and economics. Since heat shock proteins in E. coli were reported to be helpful for protein refolding and hindering aggregation, in this work different types of single and periodic heat shocks were tested on lab scale to enhance intracellular and extracellular protein production. A single heat shock prior to induction and different oscillatory temperature variations during the induction phase were executed. The results showed that these variations influence protein production negatively. In other words, 45 and 50 % reduction in extracellular protein production were observed for the single heat shock and oscillated temperature between 35 and 40 °C, respectively. However, the oscillatory temperature approach introduced in this study is recommended as a tool to quantitatively analyze the effects of inhomogeneous temperature on cell physiology and productivity in large-scale bioreactors.

Model-based analysis on the extractability of information from data in dynamic fed-batch experiments

Dynamic changes of physiological bioprocess parameters, e.g. a change in the specific growth rate μ, are frequently observed during industrial manufacturing as well as bioprocess development. A quantitative description of these variations is of great interest, since it can bring elucidation to the physiological state of the culture. The goal of this contribution was to show limitations and issues for the calculation of rates with regard to temporal resolution for dynamic fed-batch experiments. The impact of measurement errors, temporal resolution and the physiological activity on the signal to noise ratio (SNR) of the calculated rates was evaluated using an in-silico approach. To make use of that in practice, a generally applicable rule of thumb equation for the estimation of the SNR of specific rates was presented. The SNR calculated by this rule of thumb equation helps with definition of sampling intervals and making a decision whether an observed change is statistically significant or should be attributed to random error. Furthermore, a generic reconciliation approach to remove random as well as systematic error from data was presented. This reconciliation technique requires only little prior knowledge. The validity of the proposed tools was checked with real data from a fed-batch culture of E. coli with dynamic variations due to feed profile. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 2013

A comprehensive and quantitative review of dark fermentative biohydrogen production

Biohydrogen production (BHP) can be achieved by direct or indirect biophotolysis, photo-fermentation and dark fermentation, whereof only the latter does not require the input of light energy. Our motivation to compile this review was to quantify and comprehensively report strains and process performance of dark fermentative BHP. This review summarizes the work done on pure and defined co-culture dark fermentative BHP since the year 1901. Qualitative growth characteristics and quantitative normalized results of H2 production for more than 2000 conditions are presented in a normalized and therefore comparable format to the scientific community.Statistically based evidence shows that thermophilic strains comprise high substrate conversion efficiency, but mesophilic strains achieve high volumetric productivity. Moreover, microbes of Thermoanaerobacterales (Family III) have to be preferred when aiming to achieve high substrate conversion efficiency in comparison to the families Clostridiaceae and Enterobacteriaceae. The limited number of results available on dark fermentative BHP from fed-batch cultivations indicates the yet underestimated potential of this bioprocessing application. A Design of Experiments strategy should be preferred for efficient bioprocess development and optimization of BHP aiming at improving medium, cultivation conditions and revealing inhibitory effects. This will enable comparing and optimizing strains and processes independent of initial conditions and scale.

Efficient feeding profile optimization for recombinant protein production using physiological information

A multivariate study was performed aiming at the optimization of a recombinant rhamnose inducible E. coli induction system with alkaline phosphatase as target product. The effects of typical factors with impact on post- as well as pre-induction feeding rates were investigated with respect to the space–time yield of the target product. The goal was increased understanding as well as quantitative characterization of these factors with respect to their physiological impact on the model system. The optical density (OD) at which the culture was induced had a strong positive effect on the space–time yield. Pre-induction growth rate (k) had a second-order effect, while induction feed rate drop (J), a factor defining the linear post-induction feed rate, was interacting with (k). However, explanation of the observed effects to acquire more understanding regarding their effect on cell metabolism was not straight forward. Hence, the original process parameters were transformed into physiological more meaningful parameters and served as the basis for a multivariate data analysis. The observed variance with respect to observed volumetric activity was fully explained by the specific substrate uptake rate (q_s) and induction OD, merging the process parameters pre-induction growth rate (k) and feed rate drop (J) into the physiological parameter specific substrate uptake rate (q_s). After transformation of the response volumetric activity (U/ml) into the biomass specific activity (U/g_biomass), the observed variance was fully explained solely by the specific substrate uptake rate (q_s). Due to physiological multivariate data analysis, the interpretation of the results was facilitated and factors were reduced. On the basis of the obtained results, it was concluded that the physiological parameter q_s rather than process parameters (k, J, induction OD) should be used for process optimization with respect to the feeding profile.

Switching industrial production processes from complex to defined media: method development and case study using the example of Penicillium chrysogenum

BACKGROUND

Filamentous fungi are versatile cell factories and widely used for the production of antibiotics, organic acids, enzymes and other industrially relevant compounds at large scale. As a fact, industrial production processes employing filamentous fungi are commonly based on complex raw materials. However, considerable lot-to-lot variability of complex media ingredients not only demands for exhaustive incoming components inspection and quality control, but unavoidably affects process stability and performance. Thus, switching bioprocesses from complex to defined media is highly desirable.

RESULTS

This study presents a strategy for strain characterization of filamentous fungi on partly complex media using redundant mass balancing techniques. Applying the suggested method, interdependencies between specific biomass and side-product formation rates, production of fructooligosaccharides, specific complex media component uptake rates and fungal strains were revealed. A 2-fold increase of the overall penicillin space time yield and a 3-fold increase in the maximum specific penicillin formation rate were reached in defined media compared to complex media.

CONCLUSIONS

The newly developed methodology enabled fast characterization of two different industrial Penicillium chrysogenum candidate strains on complex media based on specific complex media component uptake kinetics and identification of the most promising strain for switching the process from complex to defined conditions. Characterization at different complex/defined media ratios using only a limited number of analytical methods allowed maximizing the overall industrial objectives of increasing both, method throughput and the generation of scientific process understanding.

A dynamic fed batch strategy for a Pichia pastoris mixed feed system to increase process understanding

Mixed substrate feeding strategies are frequently investigated to enhance the productivity of recombinant Pichia pastoris processes. For this purpose, numerous fed batch experiments or time-consuming continuous cultivations are required to optimize control parameters such as the substrate mixing ratio and the applied methanol concentration. In this study, we decoupled the feeding of methanol and glycerol in a mixed substrate fed batch environment to gain process understanding for a recombinant P. pastoris Muts strain producing the model enzyme horseradish peroxidase. Specific substrate uptake rates (qs) were controlled separately, and a stepwise increased qGly-control scheme was applied to investigate the effect of various substrate fluxes on the culture. The qs-controlled strategy allowed a parallel characterization of the metabolism and the recombinant protein expression in a fed batch environment. A critical-specific glycerol uptake rate was determined, where a decline of the specific productivity occurred, and a time-dependent acceleration of protein expression was characterized with the dynamic fed batch approach. Based on the observations on recombinant protein expression, propositions for an optimal feeding design to target maximal productivities were stated. Thus, the dynamic fed batch strategy was found to be a valuable tool for both process understanding and optimization of product formation for P. pastoris in a mixed substrate environment.

Model-based analysis on the relationship of signal quality to real-time extraction of information in bioprocesses

Quality by design (QbD) is a current structured approach to design processes yielding a quality product. Knowledge and process understanding cannot be achieved without proper experimental data; hence requirements for measurement error and frequency of measurement of bioprocess variables have to be defined. In this contribution, a model-based approach is used to investigate impact factors on calculated rates to predict the obtainable information from real-time measurements (= signal quality). Measurement error, biological activity, and averaging window (= period of observation) were identified as biggest impact factors on signal quality. Moreover, signal quality has been set in context with a quantifiable measure using statistical error testing, which can be used as a benchmark for process analytics and exploitation of data. Results have been validated with data from an E. coli batch process. This approach is useful to get an idea which process dynamics can be observed with a given bioprocess setup and sampling strategy beforehand.

Effect of post-induction substrate oscillation on recombinant alkaline phosphatase production expressed in Escherichia coli

Microorganisms are exposed to fast changes in microenvironment in large scale bioreactors. Because of their fast response to the changes, overall performance of biological system in small scale differs from large scale. Hence the variations in the environment that microorganisms are living in are mimicked in small scale. For this purpose one way is to feed substrate into the bioreactor in an oscillatory profile. In this work two different types of triangular oscillatory feeding profiles were applied as the post induction feeding strategy in intracellular recombinant alkaline phosphatase production expressed in Escherichia coli to find out if this biological system behaves in inhomogeneous environment differently. On line and offline measurements provide evaluation of product quality and quantity. Then the results of the experiments were compared with those of the control run at which constant feeding rate was executed. The results showed that oscillatory feeding at which cells were not starved led to higher yield of protein per substrate (0.027C-mol/C-mol) and higher activity per protein (0.79U/mg) when compared to a constant feeding rate (0.011C-mol/C-mol and 0.11U/mg).

The energy spilling reactions of bacteria and other organisms

For many years it was assumed that living organisms always utilized ATP in a highly efficient manner, but simple growth studies with bacteria indicated that the efficiency of biomass production was often at least 3-fold lower than the amount that would be predicted from standard biosynthetic pathways. The utilization of energy for maintenance could only explain a small portion of this discrepancy particularly when the growth rate was high. These ideas and thermodynamic arguments indicated that cells might have another avenue of energy utilization. This phenomenon has also been called 'uncoupling', 'spillage' and 'overflow metabolism', but 'energy spilling' is probably the most descriptive term. It appears that many bacteria spill energy, and the few that do not can be killed (large and often rapid decrease in viability), if the growth medium is nitrogen-limited and the energy source is in 'excess'. The lactic acid bacterium, Streptococcus bovis, is an ideal bacterium for the study of energy spilling. Because it only uses substrate level phosphorylation to generate ATP, ATP generation can be calculated with a high degree of certainty. It does not store glucose as glycogen, and its cell membrane can be easily accessed. Comparative analysis of heat production, membrane voltage, ATP production and Ohm's law indicated that the energy spilling reaction of S. bovis is mediated by a futile cycle of protons through the cell membrane. Less is known about Escherichia coli, but in this bacterium energy spilling could be mediated by a futile cycle of potassium or ammonium ions. Energy spilling is not restricted to prokaryotes and appears to occur in yeasts and in higher organisms. In man, energy spilling may be related to cancer, ageing, ischemia and cardiac failure.

A procedure for the estimation over time of metabolic fluxes in scenarios where measurements are uncertain and/or insufficient

BACKGROUND

An indirect approach is usually used to estimate the metabolic fluxes of an organism: couple the available measurements with known biological constraints (e.g. stoichiometry). Typically this estimation is done under a static point of view. Therefore, the fluxes so obtained are only valid while the environmental conditions and the cell state remain stable. However, estimating the evolution over time of the metabolic fluxes is valuable to investigate the dynamic behaviour of an organism and also to monitor industrial processes. Although Metabolic Flux Analysis can be successively applied with this aim, this approach has two drawbacks: i) sometimes it cannot be used because there is a lack of measurable fluxes, and ii) the uncertainty of experimental measurements cannot be considered. The Flux Balance Analysis could be used instead, but the assumption of optimal behaviour of the organism brings other difficulties.

RESULTS

We propose a procedure to estimate the evolution of the metabolic fluxes that is structured as follows: 1) measure the concentrations of extracellular species and biomass, 2) convert this data to measured fluxes and 3) estimate the non-measured fluxes using the Flux Spectrum Approach, a variant of Metabolic Flux Analysis that overcomes the difficulties mentioned above without assuming optimal behaviour. We apply the procedure to a real problem taken from the literature: estimate the metabolic fluxes during a cultivation of CHO cells in batch mode. We show that it provides a reliable and rich estimation of the non-measured fluxes, thanks to considering measurements uncertainty and reversibility constraints. We also demonstrate that this procedure can estimate the non-measured fluxes even when there is a lack of measurable species. In addition, it offers a new method to deal with inconsistency.

CONCLUSION

This work introduces a procedure to estimate time-varying metabolic fluxes that copes with the insufficiency of measured species and with its intrinsic uncertainty. The procedure can be used as an off-line analysis of previously collected data, providing an insight into the dynamic behaviour of the organism. It can be also profitable to the on-line monitoring of a running process, mitigating the traditional lack of reliable on-line sensors in industrial environments.

Neutral desorption sampling coupled to extractive electrospray ionization mass spectrometry for rapid differentiation of biosamples by metabolomic fingerprinting

It is of increasing interest and practical importance to develop convenient methods based on mass spectrometry for high-throughput analyses of biological samples. This is usually difficult because of the complex matrix and ion suppression effects. Generation of ions at ambient conditions is a promising solution to these problems because the sample is easily accessible and the ion suppression effect is reduced significantly. A new method for rapid on-line detection of metabolic markers in complex biological samples is described here. It combines atmospheric pressure desorption sampling by a gentle stream of air or nitrogen with extractive electrospray ionization (EESI) and mass spectrometric analysis. The resulting mass spectral fingerprints are shown to be able to detect spoilage of meat even in the frozen (-20 degrees C) state and the contamination of spinach by E. coli, and to identify metabolites and contaminants on human skin within seconds, in an on-line and high-throughput fashion. Typical molecular markers are identified using MS/MS data and by comparison with reference compounds. Differences between closely related samples are easily visualized by using principal component analysis (PCA) of the mass spectra data. The detection limit achieved is 10 fg/cm2 (S/N = 3) for histamine on the surface of frozen meat. The technique reported here shows potential for more advanced applications in multiple disciplines, including food regulation, homeland security, in vivo metabolomics, and clinical diagnosis.

Regulation of alcohol oxidase of a recombinant Pichia pastoris Mut+ strain in transient continuous cultures

In the methylotrophic yeast Pichia pastoris, alcohol oxidase (AOX) is a key enzyme involved in the dissimilation of methanol. Heterologous proteins are usually expressed under the control of the AOX1 promoter, which drives the expression of alcohol oxidase 1 in the wild-type strain. This study investigates the regulation of the alcohol oxidase enzyme of a recombinant P. pastoris Mut+ strain in cultures on glycerol and methanol as sole carbon sources and in mixed substrate cultures on both substrates. The aim was to have a better insight in the transition from growth on glycerol to growth on methanol, which is a key step in standard high cell density P. pastoris cultures for the production of foreign proteins. Nutrient shifts in chemostat cultures showed that after growth on glycerol use of mixed feeds of glycerol and methanol allowed faster induction of alcohol oxidase and faster adaptation of cellular metabolism than with a feed containing methanol as sole carbon source. The results of this study showed also how critical it is to avoid transient methanol accumulation during P. pastoris cultures operated at low residual methanol concentrations. Indeed, pulse experiments during chemostat cultures showed that sudden increase in methanol concentrations in cultures performed under methanol-limited or dual methanol and glycerol-limited growth conditions leads to wash-out of the culture because of too high consumption rate of methanol, which leads to excretion of toxic intermediates. High rate of methanol consumption was due to high specific AOX activities observed at low residual methanol concentrations.

Phase shifts in the stoichiometry of rifamycin B fermentation and correlation with the trends in the parameters measured online

Antibiotic fermentation processes are raw material cost intensive and the profitability is greatly dependent on the product yield per unit substrate consumed. In order to reduce costs, industrial processes use organic nitrogen substrates (ONS) such as corn steep liquor and yeast extract. Thus, although the stoichiometric analysis is the first logical step in process development, it is often difficult to achieve due to the ill-defined nature of the medium. Here, we present a black-box stoichiometric model for rifamycin B production via Amycolatopsis mediterranei S699 fermentation in complex multi-substrate medium. The stoichiometric coefficients have been experimentally evaluated for nine different media compositions. The ONS was quantified in terms of the amino acid content that it provides. Note that the black box stoichiometric model is an overall result of the metabolic reactions that occur during growth. Hence, the observed stoichiometric coefficients are liable to change during the batch cycle. To capture the shifts in stoichiometry, we carried out the stoichiometric analysis over short intervals of 8-16 h in a batch cycle of 100-200 h. An error analysis shows that there are no systematic errors in the measurements and that there are no unaccounted products in the process. The growth stoichiometry shows a shift from one substrate combination to another during the batch cycle. The shifts were observed to correlate well with the shifts in the trends of pH and exit carbon dioxide profiles. To exemplify, the ammonia uptake and nitrate uptake phases were marked by a decreasing pH trend and an increasing pH trend, respectively. Further, we find the product yield per unit carbon substrate to be greatly dependent on the nature of the nitrogen substrate. The analysis presented here can be readily applied to other fermentation systems that employ multi-substrate complex media.

Physiological characterization and fed-batch production of an extracellular maltase of Schizosaccharomyces pombe CBS 356

The fission yeast Schizosaccharomyces pombe CBS 356 exhibits extracellular maltase activity. This activity may be of commercial interest as it exhibited a low pH optimum (3.5) and a high affinity for maltose (Km of 7.0+/-1.8 mM). N-terminal sequencing of the protein indicates that it is the product of the AGL1 gene. Regulation of this gene occurs via a derepression/repression mechanism. In sugar- or nitrogen-limited chemostat cultures, the specific rate of enzyme production (q(p)) was independent of the nature of the carbon source (i.e. glucose or maltose), but synthesis was partially repressed by high sugar concentrations. Furthermore, q(p) increased linearly with specific growth rate (mu) between 0.04 and 0.10 h(-1). The enzyme is easily mass-produced in aerobic glucose-limited fed-batch cultures, in which the specific growth rate is controlled to prevent alcoholic fermentation. In fed-batch cultures in which biomass concentrations of 83 g L(-1) were attained, the enzyme concentration reached 58,000 Units per liter culture supernatant. Extracellular maltase may be used as a dough additive in order to prevent mechanisms such as maltose-induced glucose efflux and maltose-hypersensitivity that occur in maltose-consuming Saccharomyces cerevisiae.

Towards industrial application of quasi real-time metabolic flux analysis for mammalian cell culture

Cellular physiology and metabolism were monitored using a quasi real-time combination of on-line and off-line data to estimate metabolic fluxes in an established bioreaction network. The utility of this approach towards optimizing bioreactor operation was demonstrated for CHO cells cultivated in 15 L perfusion reactors at 20 x 10(6) cells/mL. Medium composition and dilution rates were changed to obtain several steady states with varying glucose and glutamine concentrations. When cells were restored to initial culture medium and perfusion rate conditions after being exposed to lower glucose and glutamine concentrations, the pyruvate flux into the TCA cycle was increased 30% while the pyruvate flux through lactate was decreased 30%, suggesting steady-state multiplicity. By appropriately altering cellular metabolism, perfusion bioreactors can operate at lower perfusion rates without significant accumulation of inhibitory metabolites such as lactate. Changes in glucose, lactate and glutamine uptake/production rates had significant effects on the calculation of other fluxes in the network. Sensitivity analysis of these key metabolic fluxes highlighted the need for accurate and reliable real-time sensors. Overall, rapid observation of metabolic fluxes can be a valuable tool for bioprocess development, monitoring and control. The framework presented in this study offers a convenient means for quasi real-time estimation of metabolic fluxes and represents a step towards realizing the potential of metabolic flux analysis for accelerated bioprocess optimization.

Short-term metabolome dynamics and carbon, electron, and ATP balances in chemostat-grown Saccharomyces cerevisiae CEN.PK 113-7D following a glucose pulse

The in vivo kinetics in Saccharomyces cerevisiae CEN.PK 113-7D was evaluated during a 300-second transient period after applying a glucose pulse to an aerobic, carbon-limited chemostat culture. We quantified the responses of extracellular metabolites, intracellular intermediates in primary metabolism, intracellular free amino acids, and in vivo rates of O(2) uptake and CO(2) evolution. With these measurements, dynamic carbon, electron, and ATP balances were set up to identify major carbon, electron, and energy sinks during the postpulse period. There were three distinct metabolic phases during this time. In phase I (0 to 50 seconds after the pulse), the carbon/electron balances closed up to 85%. The accumulation of glycolytic and storage compounds accounted for 60% of the consumed glucose, caused an energy depletion, and may have led to a temporary decrease in the anabolic flux. In phase II (50 to 150 seconds), the fermentative metabolism gradually became the most important carbon/electron sink. In phase III (150 to 300 seconds), 29% of the carbon uptake was not identified in the measurements, and the ATP balance had a large surplus. These results indicate an increase in the anabolic flux, which is consistent with macroscopic balances of extracellular fluxes and the observed increase in CO(2) evolution associated with nonfermentative metabolism. The identified metabolic processes involving major carbon, electron, and energy sinks must be taken into account in in vivo kinetic models based on short-term dynamic metabolome responses.

Respirometric 13C flux analysis, Part I: design, construction and validation of a novel multiple reactor system using on-line membrane inlet mass spectrometry

A novel method for (13)C flux analysis based on on-line CO(2) labeling measurements is presented. This so-called respirometric (13)C flux analysis requires multiple parallel (13)C labeling experiments using differently labeled tracer substrates. In Part I of the work, a membrane-inlet mass spectrometry-based measurement system with 6 parallel reactors with each 12 ml liquid volume and associated experimental and computational methods for the respirometric (13)C data acquisition and evaluation are described. Signal dynamics after switching between membrane probes follow exactly first-order allowing extrapolation to steady state. Each measurement cycle involving 3 reactors takes about 2 min. After development of a dynamic calibration method, the suitability and reliability of the analysis was examined with a lysine-producing mutant of Corynebacterium glutamicum using [1-(13)C(1)], [6-(13)C(1)], [1,6-(13)C(2)] glucose. Specific rates of oxygen uptake and CO(2) production were estimated with an error less than +/-0.3 mmol g(-1) h(-1) and had +/-3% to +/-10% deviations between parallel reactors which is primarily caused by inaccuracies in initial biomass concentration. The respiratory quotient could be determined with an uncertainty less than +/-0.02 and varied only +/-3% between reactors. Fractional labeling of CO(2) was estimated with much higher precision of about +/-0.001 to +/-0.005. The detailed statistical analysis suggested that these data should be of sufficient quality to allow physiological interpretation and metabolic flux estimation. The obtained data were applied for the respirometric (13)C metabolic flux analysis in Part II.

Dynamic effects related to steady-state multiplicity in continuous Saccharomyces cerevisiae cultivations

The behavioral differences between chemostat and productostat cultivation of aerobic glucose-limited Saccharomyces cerevisiae were investigated. Three types of experiments were conducted: a chemostat, where the dilution rate was shifted up or down in stepwise manner; and a productostat, with either stepwise changed or a rampwise increased ethanol setpoint, i.e., an accelero-productostat. The transient responses from chemostat and productostat experiments were interpreted using a simple metabolic flux model. In a productostat it was possible to obtain oxido-reductive steady states at dilution rates far below Dcrit due to a strong repression of the respiratory system. However, these steady states could not be obtained in a chemostat, since a dilution rate shift-down from an oxido-reductive steady state led to a derepression of the respiratory system. It can therefore be concluded that the range of dilution rates where steady-state multiplicity can be obtained differs depending on the operation mode and that this dilution rate multiplicity range may appear larger in a productostat than in a chemostat. A more narrow multiplicity range, however, was obtained when the productostat was operated as an accelero-productostat.

Real-time update of calibration model for better monitoring of batch processes using spectroscopy

In order to reduce the large calibration matrix usually required for calibrating multiwavelength optical sensors, a simple algorithm based on the addition in process of new standards is proposed. A small calibration model, based on 14 standards, is periodically updated by spectra collected on-line during fermentation operation. Concentrations related to these spectra are reconciled into best-estimated values, by considering carbon and oxygen balances. Using this method, fructose, acetate, and gluconacetan were monitored during batch fermentations of Gluconacetobacter xylinus 12281 using mid-infrared spectroscopy. It is shown that this algorithm compensates for noncalibrated events such as production or consumption of by-products. The standard error of prediction (SEP) values were 0.99, 0.10, and 0.90 g/L for fructose, acetate, and gluconacetan, respectively. By contrast, without an updating of the calibration model, the SEP values were 2.46, 0.92, and 1.04 g/L for fructose, acetate, and gluconacetan, respectively. Using only 14 standards, it was therefore possible to approach the performance of an 88-standard-based calibration model having SEP values of 1.11, 0.37, and 0.79 g/L for fructose, acetate, and gluconacetan, respectively. Therefore, the proposed algorithm is a valuable approach to reduce the calibration time of multiwavelength optical sensors.

Modification of A-stat for the characterization of microorganisms

Two novel modifications of continuous culture with gradual change of dilution rate (A-stat): D-stat and auxo-accelerostat were evaluated in the studies of the effect of changing individual environmental parameters (T, pH, pO(2), substrate concentration, etc.) on growth characteristics of different microorganisms. Common for those cultivation methods is that one environmental parameter is programmed to change with constant change rate (change-stat) while the others are kept constant or in the range not affecting the growth characteristics. The environment response growth curves were obtained starting with chemostat (in A-stat and D-stat) or auxostat (in auxo-accelerostat) steady-state cultures followed by change of set-point value of the desired cultivation parameter. Physiological studies of Saccharomyces sp. and Lactococcus lactis were combined with validation of the different modifications of the A-stat method based on well-known cultivation techniques: chemostat, pH-auxostat, pO(2)-auxostat CO(2)-auxostat and fed-batch. The auxo-accelerostat was shown to be very efficient for cell characterization and dynamic studies in growth environments with excess of essential substrates. Choosing the rate of change of environmental parameters was shown to be critical in comparative physiological studies of microorganisms.