Modeling fermentations with recombinant microorganisms: Formulation of a structured model

Operator training in recombinant protein production using a structured simulator model

Model-based operator training simulators (OTS) could be powerful tools for virtual training of operational procedures and skills of production personnel in recombinant protein processes. The applied model should describe critical events in the bioprocess so accurately that the operators' ability to observe and alertly act upon these events is trained with a high degree of efficiency. In this work is shown how this is accomplished in a structured multi-compartment model for the production of a recombinant protein in an Escherichia coli fed-batch process where in particular the induction procedure, the stress effects and overflow metabolism were highlighted. The structured model was applied on the OTS platform that virtually simulated the operational bioreactor procedures in real or accelerated time. Evaluation of training using the model-based OTS showed that trained groups of operators exhibited improved capability compared with the untrained groups when subsequently performing real laboratory scale cultivations. The results suggest that this model-based OTS may provide a valuable resource for enhancing operator skills in large scale recombinant protein manufacturing.

Ribosomal protein limitations in Escherichia coli under conditions of high translational activity

Details of the mechanism for ribosome synthesis have been incorporated in the single-cell Escherichia coli model, which enable us to predict the amount of protein synthesizing machinery under different environmental conditions. The predictions agree quite well with available experimental data. The model predicts that ribosomal protein limitations are important when the translational apparatus is in high demand. Ribosomal RNA synthesis is induced by an increase in translational activity, which, in turn, stimulates ribosomal protein synthesis. However, as the demand increases still more, the ribosomal protein mRNA must compete with the plasmid mRNA for ribosomes, and the efficiency of translation of ribosomal proteins is reduced. (c) 1994 John Wiley & Sons, Inc.

Structured modeling of a microbial system: II. Experimental verification of a structured lactic acid fermentation model

A two-compartment model for the lactic acid fermentation with Streptococcus cremoris is experimentally verified. The seven parameters of the model are determined using steady-state chemostat data at varying values of dilution rate, D, but with a constant feed concentration, s(f), of a single carbohydrate source (glucose, lactose, or galactose), and a constant feed concentration of s(Nf) of the N source. Steady-state measurements of the RNA content at different exit concentrations, s, of the carbohydrate are included to calculate kinetic parameters that determine the cell composition for varying operating conditions. The model is tested using data from a large set of steady-state and non-steady-state experiments: batch fermentations and step and pulse experiments in a chemostat. Both qualitatively and quantitatively the major features of the model are confirmed: the external substrates enter into intracellular high-energy building blocks, and lactic acid is formed as a by-product of these reactions. Cell growth depends on the fraction of active components (X(A)) of the cell and is not accompanied by lactic acid production. Possible model modifications are discussed, primarily to obtain a better description of lactic acid fermentation at nongrowth conditions.

Rapid responses of ribosomal RNA synthesis to nutrient shifts

A major challenge in systems biology is to integrate our mechanistic understanding of gene regulation to predict quantitatively how cells will respond to environmental changes. Living cells respond rapidly to the availability of nutrients in part by altering production of ribosomal RNA (rRNA), a limiting component in the biosynthesis of ribosomes. Studies of rRNA transcription by the RNA polymerase of Escherichia coli have identified regulatory roles for guanosine tetraphosphate (ppGpp), the initiating nucleotide, and the protein DksA. To what extent findings from in vitro studies can be used to quantitatively predict in vivo responses to changing nutrient environments is unknown. We developed a mechanistic mathematical model for rRNA transcriptional responses to such changes. Our model accounts for binding of RNAP to its rRNA promoter to form a closed complex, isomerization from a closed complex to an open complex, reversible incorporation of the initiating NTP (iNTP), transcript elongation, and clearance of the promoter. Further, the model incorporates interactions between ppGpp and DksA with transcription intermediates, and it includes an empirical correction to account for salt effects. The model biophysical parameters were determined using 33 single- and multi-round transcription experiments spanning 487 in vitro measurements. By incorporating in vivo measurements of ppGpp and ATP, the model correctly predicted rRNA production rates for cellular responses to nutrient upshifts, downshifts, and outgrowth into fresh medium. Inclusion of DksA was essential in all three cases. Our work provides a foundation for using data-driven computational models to predict the kinetics of in vivo transcriptional responses.

Modeling of enzyme production kinetics

Models of single cells, cell populations, and cultures can be most useful in organizing information in a comprehensive system description, as well as in optimizing and controlling actual production operations. Models discussed in this article are of various degrees of biological structure and mathematical complexity. The models are developed based on the biomass formation, substrate consumption, and product formation. the potentials asn the limitations of all the models have been reported. The parameter estimation by different methods has been discussed in this communication. These parameters will be helpful to explore the areas where future-modeling studies may be especially valuable.

Using a kinetic model that considers cell segregation to optimize hEGF expression in fed-batch cultures of recombinant Escherichia coli

Growth inhibition of recombinant Escherichia coli during the expression of human epidermal growth factor was observed. The recombinant cells could be segregated into three populations based on their cell division and plasmid maintenance abilities: dividing and plasmid-bearing cells, dividing and plasmid-free cells, and viable-but-non-culturable (VBNC) cells. Fed-batch fermentations were performed to investigate the effect of cell segregation on the kinetics of growth and foreign protein production. The results showed that a low concentration of inducer caused weak induction, whereas high levels cause strong induction, resulting in cells segregating into VBNC bacteria and producing a low foreign protein yield. A kinetic model for cell segregation was proposed and its predictions correlated well with experimental data for cell growth and protein expression. The optimal induction strategy could then be predicted by the model, and this prediction was then verified by experimentally deriving the conditions necessary for maximum expression of recombinant protein.

Modeling of the pyruvate production with Escherichia coli in a fed-batch bioreactor

A family of 10 competing, unstructured models has been developed to model cell growth, substrate consumption, and product formation of the pyruvate producing strain Escherichia coli YYC202 ldhA::Kan strain used in fed-batch processes. The strain is completely blocked in its ability to convert pyruvate into acetyl-CoA or acetate (using glucose as the carbon source) resulting in an acetate auxotrophy during growth in glucose minimal medium. Parameter estimation was carried out using data from fed-batch fermentation performed at constant glucose feed rates of q(VG)=10 mL h(-1). Acetate was fed according to the previously developed feeding strategy. While the model identification was realized by least-square fit, the model discrimination was based on the model selection criterion (MSC). The validation of model parameters was performed applying data from two different fed-batch experiments with glucose feed rate q(VG)=20 and 30 mL h(-1), respectively. Consequently, the most suitable model was identified that reflected the pyruvate and biomass curves adequately by considering a pyruvate inhibited growth (Jerusalimsky approach) and pyruvate inhibited product formation (described by modified Luedeking-Piret/Levenspiel term).

Metabolomics: quantification of intracellular metabolite dynamics

The rational improvement of microbial strains for the production of primary and secondary metabolites ('metabolic engineering') requires a quantitative understanding of microbial metabolism. A process by which this information can be derived from dynamic fermentation experiments is presented. By applying a substrate pulse to a substrate-limited, steady state culture, cellular metabolism is shifted away from its metabolic steady state. With the aid of a rapid sampling and quenching routine it is possible to take 4-5 samples per second during this process, thus capturing the metabolic response to this stimulus. Over 30 metabolites, nucleotides and cofactors from Escherichia coli metabolism can be extracted and analysed using a range of different techniques, for example enzymatic assays, HPLC and LC-MS methods. Using different substrates as limiting and pulse-substrates (glucose, glycerol), different metabolic pathways and substrate uptake systems are investigated. The resulting plots of intracellular metabolite concentrations against time serve as a data basis for modelling microbial metabolic networks.

Modelling plasmid instability in batch and continuous fermentors

The probability of complete loss of plasmid material from plasmid bearing cells undergoing active growth has been modelled and incorporated into predictions for the dynamic concentrations of plasmid bearing cells in both batch and continuous flow, stirred tank bioreactors. The new model is based on an extension of the well-used model of Imanaka and Aiba [Ann. New York Acad. Sci. 369 (1981) 1] and is relatively easy to use compared to complex structured models. The new model predicts that both accelerating and decelerating rates of plasmid loss occur in both batch and continuous flow operation, and agrees well with data collected here and published earlier by others.

Optimizing initial plasmid copy number distribution for improved protein activity in a recombinant fermentation

Recombinant bacterial cells in a fermentation broth rarely contain the same number of plasmids, even though this simplification is often used. Recent work has however indicated limitations of the simplified approach. Based on these studies, the distribution of plasmid copy numbers per cell has been represented macroscopically here in a Gaussian form for the fraction of biomass as a function of the copy number. Applying this distribution and an experimentally validated kinetic model to glyceraldehyde-3-phosphate dehydrogenase (GAPDH) synthesis by Escherichia coli containing the plasmid pBR Eco gap, it is seen that GAPDH production in a batch fermentation is maximized by a particular initial (non-zero) copy number variance and an optimal duration. To implement this distribution in a bioreactor, it is suggested that the profile may be discretized, inocula corresponding to the mean copy number of each fraction prepared, and then combined to obtain the seed culture.

Characterization of stress and protein turnover from protein overexpression in fed-batch E. coli cultures

A structured kinetic model that accounts for proteolytic degradation due to recombinant protein overexpression is introduced and its performance evaluated by comparison with previously reported fed-batch experimental data. This mathematical model contains an additional pool for a generic key precursor (in our case phenylalanine), an improved IPTG transport term, a phenylalanine transport term, and a variable protein turnover expression that accounts for proteolytic activity. The model predictions concerning proteolytic activity, glucose level, and cell growth are in very good agreement with an amino acid depletion hypothesis. Cultures exposed to greater stress showed higher and/or longer proteolysis, whereas less overall proteolytic activity was observed when the effect of induction was somewhat ameliorated.

Characterization and some reaction-engineering aspects of thermostable extracellular beta-galactosidase from a new Bacillus species

A new strain of Bacillus sp. was isolated from a hot water spring in India. This strain generated a high activity of extracellular beta-galactosidase at 37 degrees C in shake flasks. The beta-galactosidase activity was found to increase continuously but the production rate was slower than with some other organisms reported in the literature. There were noteworthy differences in the time-domain profiles of bacterial concentration and beta-galactosidase activity when the starting concentration of substrate (glucose) was tripled from 10 g/L. These differences may be explained in terms of the relative rates of enzyme synthesis and its diffusion across the cell wall. The enzyme produced by this organism is more stable than other beta-galactosidases; its half-life is 408 h at 50 degrees C and 94 h at 55 degrees C, while the reported enzymes showed perceptible loss of activity within 2 h.

Host-vector interactions in Escherichia coli

Introduction of a DNA vector into E. coli for the purposes of cloned gene expression can perturb native cell functions at many levels. The presence of foreign DNA can alter regulation of chromosomal DNA replication, regulation of transcription of chromosomal genes, ribosome functions and RNA turnover, activities of regulatory proteins, chaperone and protease levels, membrane energetics and protein post-translational processing, as well as energy and intermediary metabolism of the cell. The combined effects of these interactions on the metabolic characteristics of the host-vector system have major implications for yields of cloned biotechnological products and interactions of genetically engineered organisms with their environment.

Runaway–Replication Plasmids as Tools to Produce Large Quantities of Proteins from Cloned Genes in Bacteria

Here we review the properties and uses of runaway-replication vectors, a class of versatile plasmids discovered and developed in Escherichia coli. They are based on the IncFII plasmid, R1, in which an antisense RNA (CopA RNA) negatively controls the formation of a protein that is rate-limiting for replication. The copy number of the plasmid is determined by the balance between the rates of formation of CopA RNA and RepA mRNA. A small increase in the rate of formation of the latter drastically reduces the rate of formation of CopA RNA due to convergent transcription, which may lead to a total loss of copy number control (runaway replication), resulting in massive DNA amplification, and plasmid copy numbers up to 1000 per genome. Since this amplification occurs in the presence of protein synthesis, the protein that is encoded by a cloned gene can also be amplified, and may constitute 10-50% of the total protein.