Production of high-quality SARS-CoV-2 antigens: Impact of bioprocess and storage on glycosylation, biophysical attributes, and ELISA serologic tests performance.

Serological assays are valuable tools to study SARS-CoV-2 spread and, importantly, to identify individuals that were already infected and would be potentially immune to a virus reinfection. SARS-CoV-2 Spike protein and its receptor binding domain (RBD) are the antigens with higher potential to develop SARS-CoV-2 serological assays. Moreover, structural studies of these antigens are key to understand the molecular basis for Spike interaction with angiotensin converting enzyme 2 receptor, hopefully enabling the development of COVID-19 therapeutics. Thus, it is urgent that significant amounts of this protein became available at the highest quality. In this study, we produced Spike and RBD in two human derived cell hosts: HEK293-E6 and Expi293F™. We evaluated the impact of different and scalable bioprocessing approaches on Spike and RBD production yields and, more importantly, on these antigens' quality attributes. Using negative and positive sera collected from human donors, we show an excellent performance of the produced antigens, assessed in serologic enzyme-linked immunosorbent assay (ELISA) tests, as denoted by the high specificity and sensitivity of the test. We show robust Spike productions with final yields of approx. 2 mg/L of culture that were maintained independently of the production scale or cell culture strategy. To the best of our knowledge, the final yield of 90 mg/L of culture obtained for RBD production, was the highest reported to date. An in-depth characterization of SARS-CoV-2 Spike and RBD proteins was performed, namely the antigen's oligomeric state, glycosylation profiles, and thermal stability during storage. The correlation of these quality attributes with ELISA performance show equivalent reactivity to SARS-CoV-2 positive serum, for all Spike and RBD produced, and for all storage conditions tested. Overall, we provide straightforward protocols to produce high-quality SARS-CoV-2 Spike and RBD antigens, that can be easily adapted to both academic and industrial settings; and integrate, for the first time, studies on the impact of bioprocess with an in-depth characterization of these proteins, correlating antigen's glycosylation and biophysical attributes to performance of COVID-19 serologic tests.

Hybrid metabolic flux analysis and recombinant protein prediction in Pichia pastoris X-33 cultures expressing a single-chain antibody fragment.

Despite the growing importance of the Pichia pastoris expression system as industrial workhorse, the literature is almost absent in systematic studies on how culture medium composition affects central carbon fluxes and heterologous protein expression. In this study we investigate how 26 variations of the BSM+PTM1 medium impact central carbon fluxes and protein expression in a P. pastoris X-33 strain expressing a single-chain antibody fragment. To achieve this goal, we adopted a hybrid metabolic flux analysis (MFA) methodology, which is a modification of standard MFA to predict the rate of synthesis of recombinant proteins. Hybrid MFA combines the traditional parametric estimation of central carbon fluxes with non-parametric statistical modeling of product-related quantitative or qualitative measurements as a function of central carbon fluxes. It was observed that protein yield variability was 53.6 % (relative standard deviation) among the different experiments. Protein yield is much more sensitive to medium composition than biomass growth, which is mainly determined by the carbon source availability and main salts. Hybrid MFA was able to describe accurately the protein yield with normalized RMSE of 6.3 % over 5 independent experiments. The metabolic state that promotes high protein yields is characterized by high overall metabolic rates through main central carbon pathways concomitantly with a relative shift of carbon flux from biosynthetic towards energy generating pathways.

Analysis of culture media screening data by projection to latent pathways: The case of Pichia pastoris X-33.

Cell culture media formulations contain hundreds of individual components in water solutions which have complex interactions with metabolic pathways. The currently used statistical design methods are empirical and very limited to explore such a large design space. In a previous work we developed a computational method called projection to latent pathways (PLP), which was conceived to maximize covariance between envirome and fluxome data under the constraint of metabolic network elementary flux modes (EFM). More specifically, PLP identifies a minimal set of EFMs (i.e., pathways) with the highest possible correlation with envirome and fluxome measurements. In this paper we extend the concept for the analysis of culture media screening data to investigate how culture medium components up-regulate or down-regulate key metabolic pathways. A Pichia pastoris X-33 strain was cultivated in 26 shake flask experiments with variations in trace elements concentrations and basal medium dilution, based on the standard BSM+PTM1 medium. PLP identified 3 EFMs (growth, maintenance and by-product formation) describing 98.8% of the variance in observed fluxes. Furthermore, PLP presented an overall predictive power comparable to that of PLS regression. Our results show iron and manganese at concentrations close to the PTM1 standard inhibit overall metabolic activity, while the main salts concentration (BSM) affected mainly energy expenditures for cellular maintenance.

Design of pathway-level bioprocess monitoring and control strategies supported by metabolic networks.

In this chapter we explore the basic tools for the design of bioprocess monitoring, optimization, and control algorithms that incorporate a priori knowledge of metabolic networks. The main advantage is that this ultimately enables the targeting of intracellular control variables such as metabolic reactions or metabolic pathways directly linked with productivity and product quality. We analyze in particular design methods that target elementary modes of metabolic networks. The topics covered include the analysis of the structure of metabolic networks, computation and reduction of elementary modes, measurement methods for the envirome, envirome-guided metabolic reconstruction, and macroscopic dynamic modeling and control. These topics are illustrated with applications to a cultivation process of a recombinant Pichia pastoris X33 strain expressing a single-chain antibody fragment (scFv).

Cell functional enviromics: unravelling the function of environmental factors.

BACKGROUND: While functional genomics, focused on gene functions and gene-gene interactions, has become a very active field of research in molecular biology, equivalent methodologies embracing the environment and gene-environment interactions are relatively less developed. Understanding the function of environmental factors is, however, of paramount importance given the complex, interactive nature of environmental and genetic factors across multiple time scales. RESULTS: Here, we propose a systems biology framework, where the function of environmental factors is set at its core. We set forth a "reverse" functional analysis approach, whereby cellular functions are reconstructed from the analysis of dynamic envirome data. Our results show these data sets can be mapped to less than 20 core cellular functions in a typical mammalian cell culture, while explaining over 90% of flux data variance. A functional enviromics map can be created, which provides a template for manipulating the environmental factors to induce a desired phenotypic trait. CONCLUSION: Our results support the feasibility of cellular function reconstruction guided by the analysis and manipulation of dynamic envirome data.

Merging bioreactor technology with 3D hepatocyte-fibroblast culturing approaches: Improved in vitro models for toxicological applications.

During the last years an increasing number of in vitro models have been developed for drug screening and toxicity testing. Primary cultures of hepatocytes are, by far, the model of choice for those high-throughput studies but their spontaneous dedifferentiation after some time in culture hinders long-term studies. Thus, novel cell culture systems allowing extended hepatocyte maintenance and more predictive long term in vitro studies are required. It has been shown that hepatocytes functionality can be improved and extended in time when cultured as 3D-cell aggregates in environmental controlled stirred bioreactors. In this work, aiming at further improving hepatocytes functionality in such 3D cellular structures, co-cultures with fibroblasts were performed. An inoculum concentration of 1.2×10(5) cell/mL and a 1:2 hepatocyte:mouse embryonic fibroblast ratio allowed to improve significantly the albumin secretion rate and both ECOD (phase I) and UGT (phase II) enzymatic activities in 3D co-cultures, as compared to the routinely used 2D hepatocyte monocultures. Significant improvements were also observed in relation to 3D monocultures of hepatocytes. Furthermore, hepatocytes were able to respond to the addition of beta-Naphtoflavone by increasing ECOD activity showing CYP1A inducibility. The dependence of CYP activity on oxygen concentration was also observed. In summary, the improved hepatocyte specific functions during long term incubation of 3D co-cultures of hepatocytes with fibroblasts indicate that this system is a promising in vitro model for long term toxicological studies.

Bioprocess iterative batch-to-batch optimization based on hybrid parametric/nonparametric models.

This paper presents a novel method for iterative batch-to-batch dynamic optimization of bioprocesses. The relationship between process performance and control inputs is established by means of hybrid grey-box models combining parametric and nonparametric structures. The bioreactor dynamics are defined by material balance equations, whereas the cell population subsystem is represented by an adjustable mixture of nonparametric and parametric models. Thus optimizations are possible without detailed mechanistic knowledge concerning the biological system. A clustering technique is used to supervise the reliability of the nonparametric subsystem during the optimization. Whenever the nonparametric outputs are unreliable, the objective function is penalized. The technique was evaluated with three simulation case studies. The overall results suggest that the convergence to the optimal process performance may be achieved after a small number of batches. The model unreliability risk constraint along with sampling scheduling are crucial to minimize the experimental effort required to attain a given process performance. In general terms, it may be concluded that the proposed method broadens the application of the hybrid parametric/nonparametric modeling technique to "newer" processes with higher potential for optimization.

A procedure for high-yield spore production by Bacillus subtilis.

Bacillus subtilis spores have a number of potential applications, which include their use as probiotics and competitive exclusion agents to control zoonotic pathogens in animal production. The effect of cultivation conditions on Bacillus subtilis growth and sporulation was investigated in batch bioreactions performed at a 2-L scale. Studies of the cultivation conditions (pH, dissolved oxygen concentration, and media composition) led to an increase of the maximum concentration of vegetative cell from 2.6 x 10(9) to 2.2 x 10(10) cells mL(-)(1) and the spore concentration from 4.2 x 10(8) to 5.6 x 10(9) spores mL(-)(1). A fed-batch bioprocess was developed with the addition of a nutrient feeding solution using an exponential feeding profile obtained from the mass balance equations. Using the developed feeding profile, starting at the middle of the exponential growth phase and finishing in the late exponential phase, an increase of the maximum vegetative cell concentration and spore concentration up to 3.6 x 10(10) cells mL(-)(1) and 7.4 x 10(9) spores mL(-)(1), respectively, was obtained. Using the developed fed-batch bioreaction a 14-fold increase in the concentration of the vegetative cells was achieved. Moreover, the efficiency of sporulation under fed-batch bioreaction was 21%, which permitted a 19-fold increase in the final spore concentration, to a final value of 7.4 x 10(9) spores mL(-)(1). This represents a 3-fold increase relative to the highest reported value for Bacillus subtilis spore production.

On-line detection of microbial contaminations in animal cell reactor cultures using an electronic nose device.

An electronic nose (EN) device was used to detect microbial and viral contaminations in a variety of animal cell culture systems. The emission of volatile components from the cultures accumulated in the bioreactor headspace, was sampled and subsequently analysed by the EN device. The EN, which was equipped with an array of 17 chemical gas sensors of varying selectivity towards the sampled volatile molecules, generated response patterns of up to 85 computed signals. Each 15 or 20 min a new gas sample was taken generating a new response pattern. A software evaluation tool visualised the data mainly by using principal component analysis. The EN was first used to detect microbial contaminations in a Chinese hamster ovary (CHO) cell line producing a recombinant human macrophage colony stimulating factor (rhM-CSF). The CHO cell culture was contaminated by Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Candida utilis which all were detected. The response patterns from the CHO cell culture were compared with monoculture references of the microorganisms. Second, contaminations were studied in an Sf-9 insect cell culture producing another recombinant protein (VP2 protein). Contaminants were detected from E. coli, a filamentous fungus and a baculovirus. Third, contamination of a human cell line, HEK-293, infected with E. coli exhibited comparable results. Fourth, bacterial contaminations could also be detected in cultures of a MLV vector producer cell line. Based on the overall experiences in this study it is concluded that the EN method has in a number of cases the potential to be developed into a useful on-line contamination alarm in order to support safety and economical operation for industrial cultivation.