Dynamic gene expression regulation model for growth and penicillin production in Penicillium chrysogenum

An industrial perspective on metabolic responses of Penicillium chrysogenum to periodic dissolved oxygen feast-famine cycles in a scale-down system

While traveling through different zones in large-scale bioreactors, microbes are most likely subjected to fluctuating dissolved oxygen (DO) conditions at the timescales of global circulation time. In this study, to mimic industrial-scale spatial DO gradients, we present a scale-down setup based on dynamic feast/famine regime (150 s) that leads to repetitive cycles with rapid changes in DO availability in glucose-limited chemostat cultures of Penicillium chrysogenum. Such DO feast/famine regime induced a stable and repetitive pattern with a reproducible metabolic response in time, and the dynamic response of intracellular metabolites featured specific differences in terms of both coverage and magnitude in comparison to other dynamic conditions, for example, substrate feast/famine cycles. Remarkably, intracellular sugar polyols were considerably increased as the hallmark metabolites along with a dynamic and higher redox state (NADH/NAD+) of the cytosol. Despite the increased availability of NADPH for penicillin production under the oscillatory DO conditions, this positive effect may be counteracted by the decreased ATP supply. Moreover, it is interesting to note that not only the penicillin productivity was reduced under such oscillating DO conditions, but also that of the unrecyclable byproduct ortho-hydroxyphenyl acetic acid and degeneration of penicillin productivity. Furthermore, dynamic flux profiles showed the most pronounced variations in central carbon metabolism, amino acid (AA) metabolism, energy metabolism and fatty acid metabolism upon the DO oscillation. Taken together, the metabolic responses of P. chrysogenum to DO gradients reported here are important for elucidating metabolic regulation mechanisms, improving bioreactor design and scale-up procedures as well as for constructing robust cell strains to cope with heterogenous industrial culture conditions.

Developing rational scale-down simulators for mimicking substrate heterogeneities based on cell lifelines in industrial-scale bioreactors

The influence of extracellular variations on the cellular metabolism and thereby the process performance at large-scale can be evaluated using the so-called scale-down simulators. Nevertheless, the major challenge is to design an appropriate scale-down simulator, which can accurately mimic the cell lifelines that record the flow paths and experiences of cells circulating in large-scale bioreactors. To address this, a dedicated SDSA (scale-down simulator application) was purposedly developed on the basis of black box model and process reaction model established for Penicillium chrysogenum strain as well as cell lifelines or trajectories information in an industrial-scale fermentor. Guided by the SDSA, the industrial-relevant metabolic regimes for substrate availability, i.e., excess, limitation and starvation, were successfully reproduced at laboratory-scale three-compartment scale-down (SD) system. In addition, such SDSA can also display individual process dynamics in each compartment, and demonstrate how individual factors influence the entire bioprocess performance, thus serving both educational and research purposes.

Multiple feature fusion transformer for modeling penicillin fermentation process with unequal sampling intervals

The quality prediction of batch processes is an important task in the field of biological fermentation. However, dynamic nonlinearity, unequal sampling intervals, uneven duration, and multiple features of a batch process make this task challenging. Thus, the multiple-feature fusion transformer (MFFT) model is proposed for the time series quality prediction of a batch process. First, the application of sequence-to-sequence architecture enables MFFT to perform a wide range of sequence prediction tasks. Second, the transformer parallel operation model imposes no rigid requirement for the order of sequence input, allowing the model to deal with problems of unequal interval sampling and utilize the sequence information. Third, MFFT integrates a pretrained ResNet50 as a mycelium status classifier for fusing image information into the features. Moreover, a multiple-feature encoding structure is proposed to integrate sampling time and mycelium status. Finally, multiple tasks in penicillin fermentation have shown that MFFT significantly outperforms existing methods for time series prediction.

The phenomenon of strain degeneration in biotechnologically relevant fungi

Fungi are widely exploited for large-scale production in the biotechnological industry to produce a diverse range of substances due to their versatility and relative ease of growing on various substrates. The occurrence of a phenomenon-the so-called fungal strain degeneration-leads to the spontaneous loss or decline of production capacity and results in an economic loss on a tremendous scale. Some of the most commonly applied genera of fungi in the biotechnical industry, such as Aspergillus, Trichoderma, and Penicillium, are threatened by this phenomenon. Although fungal degeneration has been known for almost a century, the phenomenon and its underlying mechanisms still need to be understood. The proposed mechanisms causing fungi to degenerate can be of genetic or epigenetic origin. Other factors, such as culture conditions, stress, or aging, were also reported to have an influence. This mini-review addresses the topic of fungal degeneration by describing examples of productivity losses in biotechnical processes using Aspergillus niger, Aspergillus oryzae, Trichoderma reesei, and Penicillium chrysogenum. Further, potential reasons, circumvention, and prevention methods are discussed. This is the first mini-review which provides a comprehensive overview on this phenomenon in biotechnologically used fungi, and it also includes a collection of strategies that can be useful to minimize economic losses which can arise from strain degeneration. KEY POINTS: • Spontaneous loss of productivity is evident in many fungi used in biotechnology. • The properties and mechanisms underlying this phenomenon are very versatile. • Only studying these underlying mechanisms enables the design of a tailored solution.

Modeling multiphase fluid flow, mass transfer, and chemical reactions in bioreactors using large-eddy simulation

We present a transient large eddy simulation (LES) modeling approach for simulating the interlinked physics describing free surface hydrodynamics, multiphase mixing, reaction kinetics, and mass transport in bioreactor systems. Presented case-studies include non-reacting and reacting bioreactor systems, modeled through the inclusion of uniform reaction rates and more complex biochemical reactions described using Contois type kinetics. It is shown that the presence of reactions can result in a non-uniform spatially varying species concentration field, the magnitude and extent of which is directly related to the reaction rates and the underlying variations in the local volumetric mass transfer coefficient.

Influence of oxygen concentration on the metabolism of Penicillium chrysogenum

In large-scale bioreactors, there is often insufficient mixing and as a consequence, cells experience uneven substrate and oxygen levels that influence product formation. In this study, the influence of dissolved oxygen (DO) gradients on the primary and secondary metabolism of a high producing industrial strain of Penicillium chrysogenum was investigated. Within a wide range of DO concentrations, obtained under chemostat conditions, we observed different responses from P. chrysogenum: (i) no influence on growth or penicillin production (>0.025 mmol L-1); (ii) reduced penicillin production, but no growth limitation (0.013-0.025 mmol L-1); and (iii) growth and penicillin production limitations (<0.013 mmol L-1). In addition, scale down experiments were performed by oscillating the DO concentration in the bioreactor. We found that during DO oscillation, the penicillin production rate decreased below the value observed when a constant DO equal to the average oscillating DO value was used. To understand and predict the influence of oxygen levels on primary metabolism and penicillin production, we developed a black box model that was linked to a detailed kinetic model of the penicillin pathway. The model simulations represented the experimental data during the step experiments; however, during the oscillation experiments the predictions deviated, indicating the involvement of the central metabolism in penicillin production.

Stochastic parcel tracking in an Euler-Lagrange compartment model for fast simulation of fermentation processes

The compartment model (CM) is a well‐known approach for computationally affordable, spatially resolved hydrodynamic modeling of unit operations. Recent implementations use flow profiles based on Computational Fluid Dynamics (CFD) simulations, and several authors included microbial kinetics to simulate gradients in bioreactors. However, these studies relied on black‐box kinetics that do not account for intracellular changes and cell population dynamics in response to heterogeneous environments. In this paper, we report the implementation of a Lagrangian reaction model, where the microbial phase is tracked as a set of biomass‐parcels, each linked with an intracellular composition vector and a structured reaction model describing their intracellular response to extracellular variations. A stochastic parcel tracking approach is adopted, in contrast to the resolved trajectories used in CFD implementations. A penicillin production process is used as a case study. We show good performance of the model compared with full CFD simulations, both regarding the extracellular gradients and intracellular pool response, using the mixing time as a matching criterion and taking into account that the mixing time is sensitive to the number of compartments. The sensitivity of the model output towards some of the inputs is explored. The coarsest representative CM requires a few minutes to solve 80 h of flow time, compared with approximately 2 weeks for a full Euler–Lagrange CFD simulation of the same case. This alleviates one of the major bottlenecks for the application of such CFD simulations towards the analysis and optimization of industrial fermentation processes.

Biosynthetic process and strain improvement approaches for industrial penicillin production

Penicillins and cephalosporins are the most important class of beta (β) lactam antibiotics, accounting for 65% total antibiotic market. Penicillins are produced by Penicillium rubens (popularly known as P. chrysogenum) were used to synthesize the active pharmaceutical intermediate (API), 6-aminopenicillinic acid (6-APA) employed in semisynthetic antibiotic production. The wild strains produce a negligible amount of penicillin (Pen). High antibiotic titre-producing P. chrysogenum strains are necessitating for industrial Pen production to meet global demand at lower prices. Classical strain improvement (CSI) approaches such as random mutagenesis, medium engineering, and fermentation are the cornerstones for high-titer Pen production. Since, Sir Alexander Fleming Discovery of Pen, great efforts are expanded to develop at a commercial scale antibiotics producing strains. Breakthroughs in genetic engineering, heterologous expression and CRISPR/Cas9 genome editing tools opened a new window for Pen production at a commercial scale to assure health crisis. The current state of knowledge, limitations of CSI and genetic engineering approaches to Pen production are discussed in this review.

Changes in Oxygen Availability during Glucose-Limited Chemostat Cultivations of Penicillium chrysogenum Lead to Rapid Metabolite, Flux and Productivity Responses

Bioreactor scale-up from the laboratory scale to the industrial scale has always been a pivotal step in bioprocess development. However, the transition of a bioeconomy from innovation to commercialization is often hampered by performance loss in titer, rate and yield. These are often ascribed to temporal variations of substrate and dissolved oxygen (for instance) in the environment, experienced by microorganisms at the industrial scale. Oscillations in dissolved oxygen (DO) concentration are not uncommon. Furthermore, these fluctuations can be exacerbated with poor mixing and mass transfer limitations, especially in fermentations with filamentous fungus as the microbial cell factory. In this work, the response of glucose-limited chemostat cultures of an industrial Penicillium chrysogenum strain to different dissolved oxygen levels was assessed under both DO shift-down (60% → 20%, 10% and 5%) and DO ramp-down (60% → 0% in 24 h) conditions. Collectively, the results revealed that the penicillin productivity decreased as the DO level dropped down below 20%, while the byproducts, e.g., 6-oxopiperidine-2-carboxylic acid (OPC) and 6-aminopenicillanic acid (6APA), accumulated. Following DO ramp-down, penicillin productivity under DO shift-up experiments returned to its maximum value in 60 h when the DO was reset to 60%. The result showed that a higher cytosolic redox status, indicated by NADH/NAD+, was observed in the presence of insufficient oxygen supply. Consistent with this, flux balance analysis indicated that the flux through the glyoxylate shunt was increased by a factor of 50 at a DO value of 5% compared to the reference control, favoring the maintenance of redox status. Interestingly, it was observed that, in comparison with the reference control, the penicillin productivity was reduced by 25% at a DO value of 5% under steady state conditions. Only a 14% reduction in penicillin productivity was observed as the DO level was ramped down to 0. Furthermore, intracellular levels of amino acids were less sensitive to DO levels at DO shift-down relative to DO ramp-down conditions; this difference could be caused by different timescales between turnover rates of amino acid pools (tens of seconds to minutes) and DO switches (hours to days at steady state and minutes to hours at ramp-down). In summary, this study showed that changes in oxygen availability can lead to rapid metabolite, flux and productivity responses, and dynamic DO perturbations could provide insight into understanding of metabolic responses in large-scale bioreactors.

Monte Carlo-Based Error Propagation for a More Reliable Regression Analysis across Specific Rates in Bioprocesses

During process development, bioprocess data need to be converted into applicable knowledge. Therefore, it is crucial to evaluate the obtained data under the usage of transparent and reliable data reduction and correlation techniques. Within this contribution, we show a generic Monte Carlo error propagation and regression approach applied to two different, industrially relevant cultivation processes. Based on measurement uncertainties, errors for cell-specific growth, uptake, and production rates were determined across an evaluation chain, with interlinked inputs and outputs. These uncertainties were subsequently included in regression analysis to derive the covariance of the regression coefficients and the confidence bounds for prediction. The usefulness of the approach is shown within two case studies, based on the relations across biomass-specific rate control limits to guarantee high productivities in E. coli, and low lactate formation in a CHO cell fed-batch could be established. Besides the possibility to determine realistic errors on the evaluated process data, the presented approach helps to differentiate between reliable and unreliable correlations and prevents the wrong interpretations of relations based on uncertain data.

Impact of Altered Trehalose Metabolism on Physiological Response of Penicillium chrysogenum Chemostat Cultures during Industrially Relevant Rapid Feast/Famine Conditions

Due to insufficient mass transfer and mixing issues, cells in the industrial-scale bioreactor are often forced to experience glucose feast/famine cycles, mostly resulting in reduced commercial metrics (titer, yield and productivity). Trehalose cycling has been confirmed as a double-edged sword in the Penicillium chrysogenum strain, which facilitates the maintenance of a metabolically balanced state, but it consumes extra amounts of the ATP responsible for the repeated breakdown and formation of trehalose molecules in response to extracellular glucose perturbations. This loss of ATP would be in competition with the high ATP-demanding penicillin biosynthesis. In this work, the role of trehalose metabolism was further explored under industrially relevant conditions by cultivating a high-yielding Penicillium chrysogenum strain, and the derived trehalose-null strains in the glucose-limited chemostat system where the glucose feast/famine condition was imposed. This dynamic feast/famine regime with a block-wise feed/no feed regime (36 s on, 324 s off) allows one to generate repetitive cycles of moderate changes in glucose availability. The results obtained using quantitative metabolomics and stoichiometric analysis revealed that the intact trehalose metabolism is vitally important for maintaining penicillin production capacity in the Penicillium chrysogenum strain under both steady state and dynamic conditions. Additionally, cells lacking such a key metabolic regulator would become more sensitive to industrially relevant conditions, and are more able to sustain metabolic rearrangements, which manifests in the shrinkage of the central metabolite pool size and the formation of ATP-consuming futile cycles.

Establishing the relationship between molecular biomarkers and biotransformation rates: Extension of knowledge for dechlorination of polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs)

Anaerobic reductive treatment technologies offer cost-effective and large-scale treatment of chlorinated compounds, including polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs). The information about the degradation rates of these compounds in natural settings is critical but difficult to obtain because of slow degradation processes. Establishing a relationship between biotransformation rate and abundance of biomarkers is one of the most critical challenges faced by the bioremediation industry. When solved for a given contaminant, it may result in significant cost savings because of serving as a basis for action. In the current review, we have summarized the studies highlighting the use of biomarkers, particularly DNA and RNA, as a proxy for reductive dechlorination of chlorinated ethenes. As the use of biomarkers for predicting biotransformation rates has not yet been executed for PCDD/Fs, we propose the extension of the same knowledge for dioxins, where slow degradation rates further necessitate the need for developing the biomarker-rate relationship. For this, we have first retrieved and calculated the bioremediation rates of different PCDD/Fs and then highlighted the key sequences that can be used as potential biomarkers. We have also discussed the implications and hurdles in developing such a relationship. Improvements in current techniques and collaboration with some other fields, such as biokinetic modeling, can improve the predictive capability of the biomarkers so that they can be used for effectively predicting biotransformation rates of dioxins and related compounds. In the future, a valid and established relationship between biomarkers and biotransformation rates of dioxin may result in significant cost savings, whilst also serving as a basis for action.

Optimal process design space to ensure maximum viability and productivity in Penicillium chrysogenum pellets during fed-batch cultivations through morphological and physiological control

Background

Biomass growth of Pencillium chrysogenum is characterised by a distinct pellet morphology consisting of compact hyphal agglomerates. Fungal pellets are advantageous in industrial process control due to rheological advantages but lead to biomass degradation due to diffusional limitations of oxygen and substrate in the pellet’s core. Several fermentation parameters are known to affect key pellet characteristics regarding morphology, viability and productivity. Pellet morphology and size are affected by agitation. Biomass viability and productivity are tightly interlinked with substrate uptake and dissolved oxygen concentration.

Results

The goal of this study was to study the impact of the fermentation parameters power input, dissolved oxygen content and specific substrate uptake rate on morphology, biomass viability and productivity. A design of experiments (DoE) approach was conducted and corresponding responses were analysed using novel morphological descriptors analysed by a previously established flow cytometry method. Results clearly display inverse correlations between power input and pellet size, specific morphological parameters related to pellet density can be increased in direct proportion to power input. Biomass viability and productivity are negatively affected by high specific substrate uptake rates.

Conclusions

Based upon multiple linear regression, it was possible to obtain an optimal design space for enhanced viability and productivity at beneficial morphological conditions. We could maintain a high number of pellets with favourable morphology at a power input of 1500 W/m³. A sound compromise between viability and high productivity is possible at a specific glucose uptake rate of 0.043 g/g/h at dissolved oxygen levels of 40% minimum.

Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses

Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.

Lecithin is the key material attribute in soy bean oil affecting filamentous bioprocesses

Complex raw materials are widely used as supplements in biopharmaceutical production processes due to their positive effect on biomass growth and productivity at low cost. However, their use negatively impacts process reproducibility due to high lot-to-lot variability which contradicts current regulatory guidelines. In this study we investigated crude soy bean oil (SBO) which is a common complex raw material for filamentous fungi. We demonstrated that lecithin, which we define as phosphatidylcholines, is in fact the key material attribute in crude SBO positively affecting fungal growth and consequently productivity. The methodological toolbox we present here allows the straightforward isolation of lecithin from crude SBO, its semi-quantification by HPLC and the consequent supplementation thereof in defined amounts. Thus, over-dosage and potential resulting negative impacts on fungal growth and productivity can be omitted.

Simultaneous removal of dihydroxybenzenes and toxicity reduction by Penicillium chrysogenum var. halophenolicum under saline conditions

The dihydroxybenzenes are widely found in wastewater and usually more than one of these aromatic compounds co-exist as pollutants of water resources. The current study investigated and compared the removal efficiency of hydroquinone, catechol and resorcinol in binary substrate systems under saline conditions by Penicillium chrysogenum var. halophenolicum, to clarify the potential of this fungal strain to degrade these aromatic compounds. Since P. chrysogenum is a known penicillin producer, biosynthetic penicillin genes were examined and antibiotic was quantified in mono and binary dihydroxybenzene systems to elucidate the carbon flux of dihydroxybenzenes metabolism in the P. chrysogenum var. halophenolicum to the secondary metabolism. In binary substrate systems, the three assayed dihydroxybenzene compounds were found to be co-metabolized by fungal strain. The fungal strain preferentially degraded hydroquinone and catechol. Resorcinol was degraded slower and supports higher antibiotic titers than either catechol or hydroquinone. Dihydroxybenzenes were faster removed in mixtures compared to mono substrate systems, except for the case of hydroquinone. In this context, the expression of penicillin biosynthetic gene cluster was not related to the removal of dihydroxybenzenes. Penicillin production was triggered simultaneously or after dihydroxybenzene degradation, but penicillin yields, under these conditions, did not compromise dihydroxybenzene biological treatment. To investigate the decrease in dihydroxybenzenes toxicity due to the fungal activity, viability tests with human colon cancer cells (HCT116) and DNA damage by alkaline comet assays were performed. For all the conditions assays, a decrease in saline medium toxicity was observed, indicating its potential as detoxification agent.

Comparative performance of different scale-down simulators of substrate gradients in Penicillium chrysogenum cultures: the need of a biological systems response analysis

In a 54 m³ large‐scale penicillin fermentor, the cells experience substrate gradient cycles at the timescales of global mixing time about 20–40 s. Here, we used an intermittent feeding regime (IFR) and a two‐compartment reactor (TCR) to mimic these substrate gradients at laboratory‐scale continuous cultures. The IFR was applied to simulate substrate dynamics experienced by the cells at full scale at timescales of tens of seconds to minutes (30 s, 3 min and 6 min), while the TCR was designed to simulate substrate gradients at an applied mean residence time (τc) of 6 min. A biological systems analysis of the response of an industrial high‐yielding P. chrysogenum strain has been performed in these continuous cultures. Compared to an undisturbed continuous feeding regime in a single reactor, the penicillin productivity (q_PenG) was reduced in all scale‐down simulators. The dynamic metabolomics data indicated that in the IFRs, the cells accumulated high levels of the central metabolites during the feast phase to actively cope with external substrate deprivation during the famine phase. In contrast, in the TCR system, the storage pool (e.g. mannitol and arabitol) constituted a large contribution of carbon supply in the non‐feed compartment. Further, transcript analysis revealed that all scale‐down simulators gave different expression levels of the glucose/hexose transporter genes and the penicillin gene clusters. The results showed that q_PenG did not correlate well with exposure to the substrate regimes (excess, limitation and starvation), but there was a clear inverse relation between q_PenG and the intracellular glucose level.

Euler-Lagrange computational fluid dynamics for (bio)reactor scale down: An analysis of organism lifelines

The trajectories, referred to as lifelines, of individual microorganisms in an industrial scale fermentor under substrate limiting conditions were studied using an Euler‐Lagrange computational fluid dynamics approach. The metabolic response to substrate concentration variations along these lifelines provides deep insight in the dynamic environment inside a large‐scale fermentor, from the point of view of the microorganisms themselves. We present a novel methodology to evaluate this metabolic response, based on transitions between metabolic “regimes” that can provide a comprehensive statistical insight in the environmental fluctuations experienced by microorganisms inside an industrial bioreactor. These statistics provide the groundwork for the design of representative scale‐down simulators, mimicking substrate variations experimentally. To focus on the methodology we use an industrial fermentation of Penicillium chrysogenum in a simplified representation, dealing with only glucose gradients, single‐phase hydrodynamics, and assuming no limitation in oxygen supply, but reasonably capturing the relevant timescales. Nevertheless, the methodology provides useful insight in the relation between flow and component fluctuation timescales that are expected to hold in physically more thorough simulations. Microorganisms experience substrate fluctuations at timescales of seconds, in the order of magnitude of the global circulation time. Such rapid fluctuations should be replicated in truly industrially representative scale‐down simulators.

Kinetic models in industrial biotechnology - Improving cell factory performance

An increasing number of industrial bioprocesses capitalize on living cells by using them as cell factories that convert sugars into chemicals. These processes range from the production of bulk chemicals in yeasts and bacteria to the synthesis of therapeutic proteins in mammalian cell lines. One of the tools in the continuous search for improved performance of such production systems is the development and application of mathematical models. To be of value for industrial biotechnology, mathematical models should be able to assist in the rational design of cell factory properties or in the production processes in which they are utilized. Kinetic models are particularly suitable towards this end because they are capable of representing the complex biochemistry of cells in a more complete way compared to most other types of models. They can, at least in principle, be used to in detail understand, predict, and evaluate the effects of adding, removing, or modifying molecular components of a cell factory and for supporting the design of the bioreactor or fermentation process. However, several challenges still remain before kinetic modeling will reach the degree of maturity required for routine application in industry. Here we review the current status of kinetic cell factory modeling. Emphasis is on modeling methodology concepts, including model network structure, kinetic rate expressions, parameter estimation, optimization methods, identifiability analysis, model reduction, and model validation, but several applications of kinetic models for the improvement of cell factories are also discussed.

A conceptual model linking functional gene expression and reductive dechlorination rates of chlorinated ethenes in clay rich groundwater sediment

We used current knowledge of cellular processes involved in reductive dechlorination to develop a conceptual model to describe the regulatory system of dechlorination at the cell level; the model links bacterial growth and substrate consumption to the abundance of messenger RNA of functional genes involved in the dechlorination process. The applicability of the model was tested on a treatability study of biostimulated and bioaugmented microcosms. Using quantitative real time PCR, high-resolution expression profiles of the functional reductive dehalogenase genes bvcA and vcrA were obtained during two consecutive dechlorination events of trichlorethene, cis-dichlorethene and vinyl chloride. Up-regulation of the bvcA (for the biostimulated microcosms) and vcrA (for the bioaugmented microcosms) gene expression fitted well with high rates of dechlorination of vinyl chloride, while no known transcripts could be measured during trichloroethene and cis-dichlorethene dechlorination. Maximum concentrations of 2.1 and 1.7 transcripts per gene of the bvcA and vcrA genes, respectively, were measured at the same time points as maximum dechlorination rates were observed. The developed model compared well with the experimental data for both biostimulated and bioaugmented microcosms under non-steady state conditions and was supported by results from a recently published study under steady state conditions.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.

Morphological changes induced by class III chitin synthase gene silencing could enhance penicillin production of Penicillium chrysogenum

Chitin synthases catalyze the formation of β-(1,4)-glycosidic bonds between N-acetylglucosamine residues to form the unbranched polysaccharide chitin, which is the major component of cell walls in most filamentous fungi. Several studies have shown that chitin synthases are structurally and functionally divergent and play crucial roles in the growth and morphogenesis of the genus Aspergillus although little research on this topic has been done in Penicillium chrysogenum. We used BLAST to find the genes encoding chitin synthases in P. chrysogenum related to chitin synthase genes in Aspergillus nidulans. Three homologous sequences coding for a class III chitin synthase CHS4 and two hypothetical proteins in P. chrysogenum were found. The gene which product showed the highest identity and encoded the class III chitin synthase CHS4 was studied in detail. To investigate the role of CHS4 in P. chrysogenum morphogenesis, we developed an RNA interference system to silence the class III chitin synthase gene chs4. After transformation, mutants exhibited a slow growth rate and shorter and more branched hyphae, which were distinct from those of the original strain. The results also showed that the conidiation efficiency of all transformants was reduced sharply and indicated that chs4 is essential in conidia development. The morphologies of all transformants and the original strain in penicillin production were investigated by light microscopy, which showed that changes in chs4 expression led to a completely different morphology during fermentation and eventually caused distinct penicillin yields, especially in the transformants PcRNAi1-17 and PcRNAi2-1 where penicillin production rose by 27 % and 41 %, respectively.

Development of quantitative metabolomics for Pichia pastoris

Accurate, reliable and reproducible measurement of intracellular metabolite levels has become important for metabolic studies of microbial cell factories. A first critical step for metabolomic studies is the establishment of an adequate quenching and washing protocol, which ensures effective arrest of all metabolic activity and removal of extracellular metabolites, without causing leakage of metabolites from the cells. Five different procedures based on cold methanol quenching and cell separation by filtration were tested for metabolomics of Pichia pastoris regarding methanol content and temperature of the quenching solution as key parameters. Quantitative evaluation of these protocols was carried out through mass balance analysis, based on metabolite measurements in all sample fractions, those are whole broth, quenched and washed cells, culture filtrate and quenching and washing solution. Finally, the optimal method was used to study the time profiles of free amino acid and central carbon metabolism intermediates in glucose-limited chemostat cultures. Acceptable recoveries (>90%) were obtained for all quenching procedures tested. However, quenching at -27°C in 60% v/v methanol performed slightly better in terms of leakage minimization. We could demonstrate that five residence times under glucose limitation are enough to reach stable intracellular metabolite pools. Moreover, when comparing P. pastoris and S. cerevisiae metabolomes, under the same cultivation conditions, similar metabolite fingerprints were found in both yeasts, except for the lower glycolysis, where the levels of these metabolites in P. pastoris suggested an enzymatic capacity limitation in that part of the metabolism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0308-1) contains supplementary material, which is available to authorized users.

Real-time monitoring of metabolic shift and transcriptional induction of yciG::luxCDABE E. coli reporter strain to a glucose pulse of different concentrations

Ineffective mixing entailing heterogeneity issue within industrial bioreactors has been reported to affect microbial physiology and consequently bioprocess performances. Alteration of these performances results from microorganism ability to modulate their physiology at metabolic and/or transcriptional levels in order to survive in a given environment. Until now, dynamics of both metabolic and transcriptional microbial response to external stimuli have been investigated using mainly ex situ measurements with sampling and/or quenching constraints. This work showed an in situ bioluminescence approach for real-time monitoring of characteristic stress responses of Escherichia coli containing yciG::luxCDABE reporter to glucose pulses in well-controlled steady-state chemostat cultures. Reproducibility of in situ bioluminescence profiles was assessed. A dramatic transient increase in the bioluminescence intensity (sharp peak) was observed for a complete depletion of sugars and for a sudden decrease in the dilution rate. This response was connected to a sudden change of the metabolic activity. On the contrary a bell curve of bioluminescence intensity, dose-dependent, was related to an induction of transcriptional activity. Real-time monitoring of the bioluminescence signal with time-span less than a second gave access to the characteristic times of the metabolic shift and transcriptional induction of the stress response.

Degeneration of penicillin production in ethanol-limited chemostat cultivations of Penicillium chrysogenum: A systems biology approach

Background

In microbial production of non-catabolic products such as antibiotics a loss of production capacity upon long-term cultivation (for example chemostat), a phenomenon called strain degeneration, is often observed. In this study a systems biology approach, monitoring changes from gene to produced flux, was used to study degeneration of penicillin production in a high producing Penicillium chrysogenum strain during prolonged ethanol-limited chemostat cultivations.

Results

During these cultivations, the biomass specific penicillin production rate decreased more than 10-fold in less than 22 generations. No evidence was obtained for a decrease of the copy number of the penicillin gene cluster, nor a significant down regulation of the expression of the penicillin biosynthesis genes. However, a strong down regulation of the biosynthesis pathway of cysteine, one of the precursors of penicillin, was observed. Furthermore the protein levels of the penicillin pathway enzymes L-α-(δ-aminoadipyl)-L-α-cystenyl-D-α-valine synthetase (ACVS) and isopenicillin-N synthase (IPNS), decreased significantly. Re-cultivation of fully degenerated cells in unlimited batch culture and subsequent C-limited chemostats did only result in a slight recovery of penicillin production.

Conclusions

Our findings indicate that the observed degeneration is attributed to a significant decrease of the levels of the first two enzymes of the penicillin biosynthesis pathway, ACVS and IPNS. This decrease is not caused by genetic instability of the penicillin amplicon, neither by down regulation of the penicillin biosynthesis pathway. Furthermore no indications were obtained for degradation of these enzymes as a result of autophagy. Possible causes for the decreased enzyme levels could be a decrease of the translation efficiency of ACVS and IPNS during degeneration, or the presence of a culture variant impaired in the biosynthesis of functional proteins of these enzymes, which outcompeted the high producing part of the population.

Impact of the Penicillium chrysogenum genome on industrial production of metabolites

The genome sequence of Penicillium chrysogenum has initiated a range of fundamental studies, deciphering the genetic secrets of the industrial penicillin producer. More than 60 years of classical strain improvement has resulted in major but delicate rebalancing of the intracellular metabolism leading to the impressive penicillin titres of the current production strains. Several leads for further improvement are being followed up, including the use of P. chrysogenum as a cell factory for other products than β-lactam antibiotics.

Intracellular metabolite determination in the presence of extracellular abundance: Application to the penicillin biosynthesis pathway in Penicillium chrysogenum

Important steps in metabolic pathways are formed by the transport of substrates and products over the cell membrane. The study of in vivo transport kinetics requires accurate quantification of intra- and extracellular levels of the transported compounds. Especially in case of extracellular abundance, the proper determination of intracellular metabolite levels poses challenges. Efficient removal of extracellular substrates and products is therefore important not to overestimate the intracellular amounts. In this study we evaluated two different rapid sampling methods, one combined with cold filtration and the other with centrifugation, for their applicability to determine intracellular amounts of metabolites which are present in high concentrations in the extracellular medium. The filtration-based method combines fast sampling and immediate quenching of cellular metabolism in cold methanol, with rapid and effective removal of all compounds present outside the cells by means of direct filtration and subsequent filtration-based washing. In the centrifugation-based method, removal of the extracellular metabolites from the cells was achieved by means of multiple centrifugation and resuspension steps with the cold quenching solution. The cold filtration method was found to be highly superior to the centrifugation method to determine intracellular amounts of metabolites related to penicillin-G biosynthesis and allowed the quantification of compounds of which the extracellular amounts were 3-4 orders of magnitude higher than the intracellular amounts. Using this method for the first time allowed to measure the intracellular levels of the side chain precursor phenylacetic acid (PAA) and the product penicillin-G of the penicillin biosynthesis pathway, compounds of which the transport mechanism in Penicillium chrysogenum is still far from being sufficiently understood.