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

Mechanistic platform knowledge of concomitant sugar uptake in Escherichia coli BL21(DE3) strains

When producing recombinant proteins, the use of Escherichia coli strain BL21(DE3) in combination with the T7-based pET-expression system is often the method of choice. In a recent study we introduced a mechanistic model describing the correlation of the specific glucose uptake rate (q_s,glu) and the corresponding maximum specific lactose uptake rate (q_s,lac,max) for a pET-based E. coli BL21(DE3) strain producing a single chain variable fragment (scFv). We showed the effect of q_s,lac,max on productivity and product location underlining its importance for recombinant protein production. In the present study we investigated the mechanistic q_s,glu/q_s,lac,max correlation for four pET-based E. coli BL21(DE3) strains producing different recombinant products and thereby proved the mechanistic model to be platform knowledge for E. coli BL21(DE3). However, we found that the model parameters strongly depended on the recombinant product. Driven by this observation we tested different dynamic bioprocess strategies to allow a faster investigation of this mechanistic correlation. In fact, we succeeded and propose an experimental strategy comprising only one batch cultivation, one fed-batch cultivation as well as one dynamic experiment, to reliably determine the mechanistic model for q_s,glu/q_s,lac,max and get trustworthy model parameters for pET-based E. coli BL21(DE3) strains which are the basis for bioprocess development.

Bioprocess monitoring: minimizing sample matrix effects for total protein quantification with bicinchoninic acid assay

Determining total protein content is a routine operation in many laboratories. Despite substantial work on assay optimization interferences, the widely used bicinchoninic acid (BCA) assay remains widely recognized for its robustness. Especially in the field of bioprocess engineering the inaccuracy caused by interfering substances remains hardly predictable and not well understood. Since the introduction of the assay, sample pre-treatment by trichloroacetic acid (TCA) precipitation has been indicated as necessary and sufficient to minimize interferences. However, the sample matrix in cultivation media is not only highly complex but also dynamically changing over process time in terms of qualitative and quantitative composition. A significant misestimation of the total protein concentration of bioprocess samples is often observed when following standard work-up schemes such as TCA precipitation, indicating that this step alone is not an adequate means to avoid measurement bias. Here, we propose a modification of the BCA assay, which is less influenced by sample complexity. The dynamically changing sample matrix composition of bioprocessing samples impairs the conventional approach of compensating for interfering substances via a static offset. Hence, we evaluated the use of a correction factor based on an internal spike measurement for the respective samples. Using protein spikes, the accuracy of the BCA protein quantification could be improved fivefold, taking the BCA protein quantification to a level of accuracy comparable to other, more expensive methods. This will allow reducing expensive iterations in bioprocess development to due inaccurate total protein analytics.

The E. coli pET expression system revisited-mechanistic correlation between glucose and lactose uptake

Therapeutic monoclonal antibodies are mainly produced in mammalian cells to date. However, unglycosylated antibody fragments can also be produced in the bacterium Escherichia coli which brings several advantages, like growth on cheap media and high productivity. One of the most popular E. coli strains for recombinant protein production is E. coli BL21(DE3) which is usually used in combination with the pET expression system. However, it is well known that induction by isopropyl β-d-1-thiogalactopyranoside (IPTG) stresses the cells and can lead to the formation of insoluble inclusion bodies. In this study, we revisited the pET expression system for the production of a novel antibody single-chain variable fragment (scFv) with the goal of maximizing the amount of soluble product. Thus, we (1) investigated whether lactose favors the recombinant production of soluble scFv compared to IPTG, (2) investigated whether the formation of soluble product can be influenced by the specific glucose uptake rate (q_s,glu) during lactose induction, and (3) determined the mechanistic correlation between the specific lactose uptake rate (q_s,lac) and q_s,glu. We found that lactose induction gave a much greater amount of soluble scFv compared to IPTG, even when the growth rate was increased. Furthermore, we showed that the production of soluble protein could be tuned by varying q_s,glu during lactose induction. Finally, we established a simple model describing the mechanistic correlation between q_s,lac and q_s,glu allowing tailored feeding and prevention of sugar accumulation. We believe that this mechanistic model might serve as platform knowledge for E. coli.

Quantitative comparison of dynamic physiological feeding profiles for recombinant protein production with Pichia pastoris

Pichia pastoris is widely used for the production of recombinant proteins in industrial biotechnology. In general, industrial production processes describe fed-batch processes based on the specific growth rate. Recently, we introduced the specific substrate uptake rate (q_s) as a novel parameter to design fed-batch strategies for P. pastoris. We showed that a dynamic feeding strategy where the feed was adjusted in steps to the maximum specific substrate uptake rate was superior to more traditional strategies in terms of specific productivity. In the present study, we compare three different dynamic feeding strategies based on q_s for a recombinant P. pastoris strain with respect to cell physiology, methanol accumulation, productivity and product quality. By comparing (A) a feeding profile at constant high q_s, (B) a periodically adjusted feeding profile for a stepwise q_s ramp, and (C) a feeding profile at linear increasing q_s, we evaluated potential effects of the mode of feeding. Although a dynamic feeding strategy with stepwise increases of q_s to q_{s max} resulted in the highest specific productivity, a feeding profile where the feeding rate was stepwise increased to a constant high q_s value was superior in terms of the amount of active enzyme produced and in the amount of accumulated methanol. Furthermore, this feeding strategy could be run automatically by integrating an online calculator tool, thus rendering manual interventions by the operator unnecessary.

Microbials for the production of monoclonal antibodies and antibody fragments

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Glycosylated full length antibodies are currently produced in mammalian cells.

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Antibody fragments can be produced in microbial organisms.

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Strain engineering allows production of full length antibodies in microbials.

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Microbials provide several advantages over mammalian cells.

Monoclonal antibodies (mAbs) and antibody fragments represent the most important biopharmaceutical products today. Because full length antibodies are glycosylated, mammalian cells, which allow human-like N-glycosylation, are currently used for their production. However, mammalian cells have several drawbacks when it comes to bioprocessing and scale-up, resulting in long processing times and elevated costs. By contrast, antibody fragments, that are not glycosylated but still exhibit antigen binding properties, can be produced in microbial organisms, which are easy to manipulate and cultivate. In this review, we summarize recent advances in the expression systems, strain engineering, and production processes for the three main microbials used in antibody and antibody fragment production, namely Saccharomyces cerevisiae, Pichia pastoris, and Escherichia coli.

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

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.