Multiobjective Optimization for Enhanced Production of Therapeutic Proteins in Escherichia coli: Application of Real-Time Dielectric Spectroscopy

Heparosan biosynthesis in recombinant Bacillus megaterium: Influence of N-acetylglucosamine supplementation and kinetic modeling

Heparosan, an unsulfated polysaccharide, plays a pivotal role as a primary precursor in the biosynthesis of heparin-an influential anticoagulant with diverse therapeutic applications. To enhance heparosan production, the utilization of metabolic engineering in nonpathogenic microbial strains is emerging as a secure and promising strategy. In the investigation of heparosan production by recombinant Bacillus megaterium, a kinetic modeling approach was employed to explore the impact of initial substrate concentration and the supplementation of precursor sugars. The adapted logistic model was utilized to thoroughly analyze three vital parameters: the B. megaterium growth dynamics, sucrose utilization, and heparosan formation. It was noted that at an initial sucrose concentration of 30 g L-1 (S1), it caused an inhibitory effect on both cell growth and substrate utilization. Intriguingly, the inclusion of N-acetylglucosamine (S2) resulted in a significant 1.6-fold enhancement in heparosan concentration. In addressing the complexities of the dual substrate system involving S1 and S2, a multi-substrate kinetic models, specifically the double Andrew's model was employed. This approach not only delved into the intricacies of dual substrate kinetics but also effectively described the relationships among the primary state variables. Consequently, these models not only provide a nuanced understanding of the system's behavior but also serve as a roadmap for optimizing the design and management of the heparosan production method.

Intranasal Delivery of Antigen-Coated Polymer Particles Protects against Pseudomonas aeruginosa Infection

Pseudomonas aeruginosa is an opportunistic human pathogen that is intrinsically resistant to multiple antibiotics, causing severe and persistent infections in immunocompromised individuals. This bacterium has been listed as a priority pathogen by the WHO in 2017, and there is no vaccine available for human use. In this study, 10 vaccine candidate antigens were selected for particulate vaccine design. We engineered Escherichia coli to assemble biopolymer particles (BPs) that were either coated with epitopes (Ag) derived from OprF/I-AlgE proteins or PopB or PopB-Ag or coated with single or double copies of epitopes (10Ag and 10Ag(2x)) derived from OprF, OprI, AlgE, OprL, PopB, PilA, PilO, FliC, Hcp1, and CdrA. Antigen-coated BPs showed a diameter of 0.93-1.16 μm with negative surface charge. Antigens attached to BPs were identified by mass spectrometry. Vaccination with BP-Ag, BP-PopB, BP-PopBAg, PB-10Ag, and BP-10Ag(2x) with and without Alhydrogel adjuvant induced significant antigen-specific humoral and cell-mediated immune responses in mice. All particulate vaccines with Alhydrogel induced protection in an acute pneumonia murine model of P. aeruginosa infection, contributing to up to 80% survival when administered intramuscularly, and the addition of Alhydrogel boosted immunity. The BP-10Ag(2x) vaccine candidate showed the best performance and even induced protective immunity in the absence of Alhydrogel. Intramuscular administration of the BP-10Ag(2x) without Alhydrogel vaccine resulted in 60% survival. Intranasal vaccination induced immunity, contributing to about 90% survival. Overall, our data suggest that vaccination with BPs coated with P. aeruginosa antigens induce protective immunity against P. aeruginosa infections. The possibility of intranasal delivery will strongly facilitate administration and use of BP vaccines.

High cell density cultivation of E. coli in shake flasks for the production of recombinant proteins

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True fed-batch strategy for high cell density cultivation of E. coli in shake flask.

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Cybernetic model-based optimization of the feeding recipe.

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Biomass of 19.9–21.5 g DCW/L, in agreement with the model prediction.

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Volumetric productivity for tested proteins increased 8–34-fold compared to batch.

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Scale up of fed-batch recipe to bioreactor resulted in further 2.8-fold increase.

Batch cultivation of recombinant bacteria in shake flasks typically results in low cell density due to nutrient depletion. Previous studies on high cell density cultivation in shake flasks have relied mainly on controlled release mechanisms. Here, we report a true fed-batch strategy to achieve high cell density of recombinant E. coli in shake flasks in 24 h by feeding a mixture of glycerol and yeast extract with a syringe pump. Feed composition and feed rate were obtained by cybernetic model-based, multi-objective optimization. Model parameters were estimated from time-course measurement of substrate, biomass, and dissolved oxygen levels. The optimized process yielded 20.7 g dry cell weight/L, in agreement with the model prediction. Volumetric protein productivity improved by 10–34-fold compared to batch cultivation with 2.8-fold further improvement when the fed-batch process was replicated in a 3 L bioreactor. The process has significance in the routine laboratory cultivations and in scaleup studies.

Cole-Cole modeling of real-time capacitance data for estimation of cell physiological properties in recombinant Escherichia coli cultivation

Real-time estimation of physiological properties of the cell during recombinant protein production would ensure enhanced process monitoring. In this study, we explored the application of dielectric spectroscopy to track the fed-batch phase of recombinant Escherichia coli cultivation for estimating the physiological properties, viz. cell diameter and viable cell concentration (VCC). The scanning capacitance data from the dielectric spectroscopy were pre-processed using moving average (MA). Later, it was modelled through a nonlinear theoretical Cole-Cole model and further solved using a global evolutionary genetic algorithm (GA). The parameters obtained from the GA were further applied for the estimation of the aforementioned physiological properties. The offline cell diameter and cell viability data were obtained from particle size analyzer and flow cytometry measurements to validate the Cole-Cole model. The offline VCC was calculated from the cell viability % from flow cytometry data and dry cell weight concentration (DCW). The Cole-Cole model predicted the cell diameter and VCC with an error of 1.03% and 7.72%, respectively. The proposed approach can enable the operator to take real-time process decisions in order to achieve desired productivity and product quality. This article is protected by copyright. All rights reserved.

Practical monitoring technologies for cells and substrates in biomanufacturing

Precise control over bioreactor operation is desired for optimal productivity and product quality, and there is an increased drive to automation in biomanufacturing. All of these goals require sensors, not only of the basic parameters of temperature, pH, and dissolved oxygen, but of the biomass and substrate concentrations, which directly determine the outcome of the bioprocess. While there are many innovative sensing concepts for biomass and substrate concentrations, this review focuses on sensors that are in-line with the bioreactor, providing data continuously without the removal of sample from the system. The discussion emphasizes the requirements of industry for these sensors, including performance, ease of use, and cost. As the bioeconomy grows, advances in sensing technologies will be needed to achieve the automation of the future for a wider array of bioreactors.