Using aerobic fermentation, single-cell protein (SCP) can be produced from a wide range of carbon sources (C-sources), including glucose, glycerol, methanol, ethanol, and organic acids. The technical and economic performance of large-scale SCP production varies significantly with C-source, driven by differences in biomass yield, O2 demand, and productivity, for example. To determine the preferred C-source, a techno-economic assessment for continuous SCP production in an industrial bubble column was performed for nine non-gaseous C-sources. This was based on a process model that included microbial kinetics, gas-liquid mass transfer kinetics, downstream operations, and a detailed cost analysis. Per C-source, dilution rate and aeration conditions were optimized to minimize the minimum selling price (MSP) of SCP. The results highlight C-source costs as the dominant MSP driver, with O₂ transfer rates strongly affecting capital and utility costs. At their current prices, glucose, glycerol, methanol and ethanol emerge as the most economically favorable C-sources, achieving MSPs of about 2.5 $/kgₓ due to high biomass yields and low C-source prices. Acetic acid exhibits an MSP of 3.2 $/kgₓ but, lactic, formic, glycolic and oxalic acids exhibit MSPs in the range of 7–20 $/kgₓ due to low biomass yields, high O2 demand, and high C-source prices. Sensitivity analyses confirm that C-source price and biomass yield exert the strongest economic influence, while the electricity price and fixed costs have a more marginal effect. This work identifies promising candidates for further environmental and scale-up assessments, providing a framework to guide C-source selection and process optimization for SCP production.

Flow-following sensor technology offers a method to collect information on flow patterns and local velocities in pilot- and industrial scale reactors, which are practically inaccessible to many measurement techniques. Such data is highly valuable for scale-up of bioprocesses, as well as validation of bioreactor CFD simulations. Flow-following sensors were applied in a pilot-scale (2m3 filled volume) bubble column fermentor, showing that axially resolved data can be acquired under heterogeneous bubbly flow conditions with high gas holdup. Next the use of the collected data for validation of CFD simulations of the pilot-scale reactor is explored, discriminating between models utilizing different interphase interaction models. The CFD simulation was found capable of capturing the velocity profile and circulation behavior, but full validation was found to be challenging. When simulating virtual sensors via Lagrangian particle tracking, differences are observed in terms of particle distribution and sensitivity to particle density between experimental and simulated data, indicating further development of representative CFD simulations is required.

Alternative fermentation feedstocks such as ethanol can be produced from CO2 via electrocatalytic processes that coproduce O2. In this study, industrial-scale fermentation of ethanol with pure O2 for single cell protein (SCP) production was studied using a modeling approach. This approach considered (i) microbial kinetics, (ii) gas-liquid transfer, and (iii) an exploration of potential operational constraints. The technical feasibility for producing up to 58 kt/y of SCP in a 600 m3 bubble column operating in continuous mode was assessed and attributed mainly to a high O2 transfer rate of 1.1 mol/(kg h) through the use of pure O2. However, most of the pure O2 fed to the fermenter remains unconsumed due to the large gas flows needed to maximize mass transfer. In addition, biomass production may be hampered by high dissolved CO2 concentrations and by large heat production. The model estimates a microbial biomass concentration of 114 g/kg, with a yield on ethanol of 0.61 gx/gethanol (> 95% Y x / s max ). Although the large predicted O2 transfer capacity seems technically feasible, it needs further experimental validation. The model structure allows the analysis of alternative substrates in the same way as identifying the best carbon feedstock.

Constraint-based genome-scale models (GEMs) of microorganisms provide a powerful tool for predicting and analyzing microbial phenotypes as well as for understanding how these are affected by genetic and environmental perturbations. Recently, MATLAB and Python-based tools have been developed to incorporate enzymatic constraints into GEMs. These constraints enhance phenotype predictions by accounting for the enzyme cost of catalyzed model´s reactions, thereby reducing the space of possible metabolic flux distributions. In this study, enzymatic constraints were added to an existing GEM of Clostridium ljungdahlii, a model acetogenic bacterium, by including its enzyme turnover numbers (kcats) and molecular masses, using the Python-based AutoPACMEN approach. When compared to the metabolic model iHN637, the enzyme cost-constrained model (ec_iHN637) obtained in our study showed an improved predictive ability of growth rate and product profile. The model ec_iHN637 was then employed to perform in silico metabolic engineering of C. ljungdahlii, by using the OptKnock computational framework to identify knockouts to enhance the production of desired fermentation products. The in silico metabolic engineering was geared towards increasing the production of fermentation products by C. ljungdahlii, with a focus on the utilization of synthesis gas and CO2. This resulted in different engineering strategies for overproduction of valuable metabolites under different feeding conditions, without redundant knockouts for different products. Importantly, the results of the in silico engineering results indicated that the mixotrophic growth of C. ljungdahlii is a promising approach to coupling improved cell growth and acetate and ethanol productivity with net CO2 fixation.

A novel fermentation process was developed in which renewable electricity is indirectly used as an energy source in fermentation, synergistically decreasing both the consumption of sugar as a first generation carbon source and emission of the greenhouse gas CO2 . As an illustration, a glucose-based process is co-fed with formic acid, which can be generated by capturing CO2 from fermentation offgas followed by electrochemical reduction with renewable electricity. This "closed carbon loop" concept is demonstrated by a case study in which cofeeding formic acid is shown to significantly increase the yield of biomass on glucose of the industrially relevant yeast species Yarrowia lipolytica. First, the optimal feed ratio of formic acid to glucose is established using chemostat cultivations. Subsequently, guided by a dynamic fermentation process model, a fed-batch protocol is developed and demonstrated on laboratory scale. Finally, the developed fed-batch process is tested and proven to be scalable at pilot scale. Extensions of the concept are discussed to apply the concept to anaerobic fermentations, and to recycle the O2 that is co-generated with the formic acid to aerobic fermentation processes for intensification purposes.

We assess the effect of substrate heterogeneity on the metabolic response of P. chrysogenum in industrial bioreactors via the coupling of a 9-pool metabolic model with Euler-Lagrange CFD simulations. In this work, we outline how this coupled hydrodynamic-metabolic modeling can be utilized in 5 steps. (1) A model response study with a fixed spatial extra-cellular glucose concentration gradient, which reveals a drop in penicillin production rate qp of 18–50% for the simulated reactor, depending on model setup. (2) CFD-based scale-down design, where we design a 1-vessel scale down simulator based on the organism lifelines. (3) Scale-down verification, numerically comparing the model response in the proposed scale-down simulator with large-scale CFD response. (4) Reactor design optimization, reducing the drop in penicillin production by a change of feed location. (5) Long-term fed-batch simulation, where we verify model predictions against experimental data, and discuss population heterogeneity. Overall, these steps present a coupled hydrodynamic-metabolic approach towards bioreactor evaluation, scale-down and optimization.

A powerful approach for the optimization of industrial bioprocesses is to perform detailed simulations integrating large-scale computational fluid dynamics (CFD) and cellular reaction dynamics (CRD). However, complex metabolic kinetic models containing a large number of equations pose formidable challenges in CFD-CRD coupling and computation time afterward. This necessitates to formulate a relatively simple but yet representative model structure. Such a kinetic model should be able to reproduce metabolic responses for short-term (mixing time scale of tens of seconds) and long-term (fed-batch cultivation of hours/days) dynamics in industrial bioprocesses. In this paper, we used Penicillium chrysogenum as a model system and developed a metabolically structured kinetic model for growth and production. By lumping the most important intracellular metabolites in 5 pools and 4 intracellular enzyme pools, linked by 10 reactions, we succeeded in maintaining the model structure relatively simple, while providing informative insight into the state of the organism. The performance of this 9-pool model was validated with a periodic glucose feast-famine cycle experiment at the minute time scale. Comparison of this model and a reported black box model for this strain shows the necessity of employing a structured model under feast-famine conditions. This proposed model provides deeper insight into the in vivo kinetics and, most importantly, can be straightforwardly integrated into a computational fluid dynamic framework for simulating complete fermentation performance and cell population dynamics in large scale and small scale fermentors. Biotechnol. Bioeng. 2017;114: 1733-1743. © 2017 Wiley Periodicals, Inc.

Biotechnology and BioengineeringVolume 114, Issue 8 p. 1633-1637 Issue Information - TOCFree Access Biotechnology and Bioengineering: Volume 114, Number 8, August 2017 First published: 26 June 2017 https://doi.org/10.1002/bit.26150AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume114, Issue8August 2017Pages 1633-1637 RelatedInformation

Our quantitative knowledge of carbon fluxes in the long slender bloodstream form (BSF) Trypanosoma brucei is mainly based on non-proliferating parasites, isolated from laboratory animals and kept in buffers. In this paper we present a carbon balance for exponentially growing bloodstream form trypanosomes. The cells grew with a doubling time of 5.3h, contained 46μmol of carbon (108 cells)−1 and had a glucose consumption flux of 160nmolmin−1 (108 cells)−1. The molar ratio of pyruvate excreted versus glucose consumed was 2.1. Furthermore, analysis of the 13C label distribution in pyruvate in 13C-glucose incubations of exponentially growing trypanosomes showed that glucose was the sole substrate for pyruvate production. We conclude that the glucose metabolised in glycolysis was hardly, if at all, used for biosynthetic processes. Carbon flux through glycolysis in exponentially growing trypanosomes was 10 times higher than the incorporation of carbon into biomass. This biosynthetic carbon is derived from other precursors present in the nutrient rich growth medium. Furthermore, we found that the glycolytic flux was unaltered when the culture went into stationary phase, suggesting that most of the ATP produced in glycolysis is used for processes other than growth.

In this study, a previously developed mini-bioreactor, the Biocurve, was used to identify an informative stimulus-response experiment. The identified stimulus-response experiment was a modest 50% shift-up in glucose uptake rate (qGLC) that unexpectedly resulted in a disproportionate transient metabolic response. The 50% shift-up in qGLC in the Biocurve resulted in a near tripling of the online measured oxygen uptake (qO2) and carbon dioxide production (qCO2) rates, suggesting a considerable mobilization of glycogen and trehalose. The 50% shift-up in qGLC was subsequently studied in detail in a conventional bioreactor (4 l working volume), which confirmed the results obtained with the Biocurve. Especially relevant is the observation that the 50% increase in glucose uptake rate led to a three-fold increase in glycolytic flux, due to mobilization of storage materials. This explains the unexpected ethanol and acetate secretion after the shift-up, in spite of the fact that after the shift-up the qGLC was far less than the critical value. Moreover, these results show that the correct in vivo fluxes in glucose pulse experiments cannot be obtained from the uptake and secretion rates only. Instead, the storage fluxes must also be accurately quantified. Finally, we speculate on the possible role that the transient increase in dissolved CO2 immediately after the 50% shift-up in qGLC could have played a part in triggering glycogen and trehalose mobilization.

The in vivo flux through the oxidative branch of the pentose phosphate pathway (oxPPP) in Penicillium chrysogenum was determined during growth in glucose/ethanol carbon-limited chemostat cultures, at the same growth rate. Non-stationary 13C flux analysis was used to measure the oxPPP flux. A nearly constant oxPPP flux was found for all glucose/ethanol ratios studied. This indicates that the cytosolic NADPH supply is independent of the amount of assimilated ethanol. The cofactor assignment in the model of van Gulik et al. (Biotechnol Bioeng 68(6):602–618, 2000) was supported using the published genome annotation of P. chrysogenum. Metabolic flux analysis showed that NADPH requirements in the cytosol remain nearly the same in these experiments due to constant biomass growth. Based on the cytosolic NADPH balance, it is known that the cytosolic aldehyde dehydrogenase in P. chrysogenum is NAD + dependent. Metabolic modeling shows that changing the NAD + -aldehyde dehydrogenase to NADP + -aldehyde dehydrogenase can increase the penicillin yield on substrate.

In this research, two dynamic (13)C-labeling experiments confirmed turnover and rapid mobilization of stored glycogen and trehalose in an aerobic glucose-limited chemostat (D=0.05 h(-1)) culture of Saccharomyces cerevisiae. In one experiment, the continuous feed to an aerobic glucose-limited chemostat culture of S. cerevisiae was instantaneously switched from naturally labeled to fully (13)C labeled while maintaining the same feed rate before and after the switch. The dynamic replacements of naturally labeled intracellular glycolytic intermediates and CO(2) (in the off-gas) with their (13)C-labeled equivalents were measured. The data of this experiment suggest that the continuous turnover of glycogen and trehalose is substantial (c. 1/3 of the glycolytic flux). The second experiment combined the medium switch with a shiftup in the glucose feeding rate (dilution rate shiftup from 0.05 to 0.10 h(-1)). This experiment triggered a strong but transient mobilization of storage carbon, that was channelled into glycolysis, causing a significant disruption in the dynamic labeling profile of glycolytic intermediates. The off-gas measurements in the shiftup experiment confirmed a considerable transient influx of (12)C-carbon into glycolysis after the combined medium switch and dilution rate shiftup. This study shows that for accurate in vivo kinetic interpretation of rapid pulse experiments, glycogen and trehalose metabolism must be taken into account.

The response of Escherichia coli cells to transient exposure (step increase) in substrate concentration and anaerobiosis leading to mixed-acid fermentation metabolism was studied in a two-compartment bioreactor system consisting of a stirred tank reactor (STR) connected to a mini-plug-flow reactor (PFR: BioScope, 3.5 mL volume). Such a system can mimic the situation often encountered in large-scale, fed-batch bioreactors. The STR represented the zones of a large-scale bioreactor that are far from the point of substrate addition and that can be considered as glucose limited, whereas the PFR simulated the region close to the point of substrate addition, where glucose concentration is much higher than in the rest of the bioreactor. In addition, oxygen-poor and glucose-rich regions can occur in large-scale bioreactors. The response of E. coli to these large-scale conditions was simulated by continuously pumping E. coli cells from a well stirred, glucose limited, aerated chemostat (D = 0.1 h(-1)) into the mini-PFR. A glucose pulse was added at the entrance of the PFR. In the PFR, a total of 11 samples were taken in a time frame of 92 s. In one case aerobicity in the PFR was maintained in order to evaluate the effects of glucose overflow independently of oxygen limitation. Accumulation of acetate and formate was detected after E. coli cells had been exposed for only 2 s to the glucose-rich (aerobic) region in the PFR. In the other case, the glucose pulse was also combined with anaerobiosis in the PFR. Glucose overflow combined with anaerobiosis caused the accumulation of formate, acetate, lactate, ethanol, and succinate, which were also detected as soon as 2 s after of exposure of E. coli cells to the glucose and O(2) gradients. This approach (STR-mini-PFR) is useful for a better understanding of the fast dynamic phenomena occurring in large-scale bioreactors and for the design of modified strains with an improved behavior under large-scale conditions.

A new sensitive and accurate analytical method has been developed for quantification of intracellular nucleotides in complex biological samples from cultured cells of different microorganisms such as Saccharomyces cerevisiae, Escherichia coli, and Penicillium chrysogenum. This method is based on ion pair reversed phase liquid chromatography electrospray ionization isotope dilution tandem mass spectrometry (IP–LC–ESI–ID–MS/MS. A good separation and low detection limits were observed for these compounds using dibutylamine as volatile ion pair reagent in the mobile phase of the LC. Uniformly 13C-labeled isotopes of nucleotides were used as internal standards for both extraction and quantification of intracellular nucleotides. The method was validated by determining the linearity, sensitivity, and repeatability.

In this work, we present a time-scale analysis based model reduction and parameter identifiability analysis method for metabolic reaction networks. The method uses the information obtained from short term chemostat perturbation experiments. We approximate the time constant of each metabolite pool by their turn-over time and classify the pools accordingly into two groups: fast and slow pools. We performed a priori model reduction, neglecting the dynamic term of the fast pools. By making use of the linlog approximative kinetics, we obtained a general explicit solution for the fast pools in terms of the slow pools by elaborating the degenerate algebraic system resulting from model reduction. The obtained relations yielded also analytical relations between a subset of kinetic parameters. These relations also allow to realize an analytical model reduction using lumped reaction kinetics. After solving these theoretical identifiability problems and performing model reduction, we carried out a Monte Carlo approach to study the practical identifiability problems. We illustrated the methodology on model reduction and theoretical/practical identifiability analysis on an example system representing the glycolysis in Saccharomyces cerevisiae cells. (C) 2008 Elsevier Inc. All rights reserved.