Advances in analytical methodologies to guide bioprocess engineering for bio-therapeutics.

This study was performed to monitor the glycoform distribution of a recombinant antibody fusion protein expressed in CHO cells over the course of fed-batch bioreactor runs using high-throughput methods to accurately determine the glycosylation status of the cell culture and its product. Three different bioreactors running similar conditions were analysed at the same five time-points using the advanced methods described here. N-glycans from cell and secreted glycoproteins from CHO cells were analysed by HILIC-UPLC and MS, and the total glycosylation (both N- and O-linked glycans) secreted from the CHO cells were analysed by lectin microarrays. Cell glycoproteins contained mostly high mannose type N-linked glycans with some complex glycans; sialic acid was α-(2,3)-linked, galactose ß-(1,4)-linked, with core fucose. Glycans attached to secreted glycoproteins were mostly complex with sialic acid α-(2,3)-linked, galactose ß-(1,4)-linked, with mostly core fucose. There were no significant differences noted among the bioreactors in either the cell pellets or supernatants using the HILIC-UPLC method and only minor differences at the early time-points of days 1 and 3 by the lectin microarray method. In comparing different time-points, significant decreases in sialylation and branching with time were observed for glycans attached to both cell and secreted glycoproteins. Additionally, there was a significant decrease over time in high mannose type N-glycans from the cell glycoproteins. A combination of the complementary methods HILIC-UPLC and lectin microarrays could provide a powerful and rapid HTP profiling tool capable of yielding qualitative and quantitative data for a defined biopharmaceutical process, which would allow valuable near 'real-time' monitoring of the biopharmaceutical product.

Understanding and Controlling Sialylation in a CHO Fc-Fusion Process.

A Chinese hamster ovary (CHO) bioprocess, where the product is a sialylated Fc-fusion protein, was operated at pilot and manufacturing scale and significant variation of sialylation level was observed. In order to more tightly control glycosylation profiles, we sought to identify the cause of variability. Untargeted metabolomics and transcriptomics methods were applied to select samples from the large scale runs. Lower sialylation was correlated with elevated mannose levels, a shift in glucose metabolism, and increased oxidative stress response. Using a 5-L scale model operated with a reduced dissolved oxygen set point, we were able to reproduce the phenotypic profiles observed at manufacturing scale including lower sialylation, higher lactate and lower ammonia levels. Targeted transcriptomics and metabolomics confirmed that reduced oxygen levels resulted in increased mannose levels, a shift towards glycolysis, and increased oxidative stress response similar to the manufacturing scale. Finally, we propose a biological mechanism linking large scale operation and sialylation variation. Oxidative stress results from gas transfer limitations at large scale and the presence of oxygen dead-zones inducing upregulation of glycolysis and mannose biosynthesis, and downregulation of hexosamine biosynthesis and acetyl-CoA formation. The lower flux through the hexosamine pathway and reduced intracellular pools of acetyl-CoA led to reduced formation of N-acetylglucosamine and N-acetylneuraminic acid, both key building blocks of N-glycan structures. This study reports for the first time a link between oxidative stress and mammalian protein sialyation. In this study, process, analytical, metabolomic, and transcriptomic data at manufacturing, pilot, and laboratory scales were taken together to develop a systems level understanding of the process and identify oxygen limitation as the root cause of glycosylation variability.

Combined metabolomics and proteomics reveals hypoxia as a cause of lower productivity on scale-up to a 5000-liter CHO bioprocess.

Large-scale bioprocessing is key to the successful manufacturing of a biopharmaceutical. However, cell viability and productivity are often lower in the scale-up from laboratory to production. In this study, we analyzed CHO cells, which showed lower percent viabilities and productivity in a 5-KL production scale bioreactor compared to a 20-L bench-top scale under seemingly identical process parameters. An increase in copper concentration in the media from 0.02 µM to 0.4 µM led to a doubling of percent viability in the production scale albeit still at a lower level than the bench-top scale. Combined metabolomics and proteomics revealed the increased copper reduced the presence of reactive oxygen species (ROS) in the 5-KL scale process. The reduction in oxidative stress was supported by the increased level of glutathione peroxidase in the lower copper level condition. The excess ROS was shown to be due to hypoxia (intermittent), as evidenced by the reduction in fibronectin with increased copper. The 20-L scale showed much less hypoxia and thus less excess ROS generation, resulting in little to no impact to productivity with the increased copper in the media. The study illustrates the power of 'Omics in aiding in the understanding of biological processes in biopharmaceutical production.

The use of 'Omics technology to rationally improve industrial mammalian cell line performance.

Biologics represent an increasingly important class of therapeutics, with 7 of the 10 top selling drugs from 2013 being in this class. Furthermore, health authority approval of biologics in the immuno-oncology space is expected to transform treatment of patients with debilitating and deadly diseases. The growing importance of biologics in the healthcare field has also resulted in the recent approvals of several biosimilars. These recent developments, combined with pressure to provide treatments at lower costs to payers, are resulting in increasing need for the industry to quickly and efficiently develop high yielding, robust processes for the manufacture of biologics with the ability to control quality attributes within narrow distributions. Achieving this level of manufacturing efficiency and the ability to design processes capable of regulating growth, death and other cellular pathways through manipulation of media, feeding strategies, and other process parameters will undoubtedly be facilitated through systems biology tools generated in academic and public research communities. Here we discuss the intersection of systems biology, 'Omics technologies, and mammalian bioprocess sciences. Specifically, we address how these methods in conjunction with traditional monitoring techniques represent a unique opportunity to better characterize and understand host cell culture state, shift from an empirical to rational approach to process development and optimization of bioreactor cultivation processes. We summarize the following six key areas: (i) research applied to parental, non-recombinant cell lines; (ii) systems level datasets generated with recombinant cell lines; (iii) datasets linking phenotypic traits to relevant biomarkers; (iv) data depositories and bioinformatics tools; (v) in silico model development, and (vi) examples where these approaches have been used to rationally improve cellular processes. We critically assess relevant and state of the art research being conducted in academic, government and industrial laboratories. Furthermore, we apply our expertise in bioprocess to define a potential model for integration of these systems biology approaches into biologics development.

Real time monitoring of multiple parameters in mammalian cell culture bioreactors using an in-line Raman spectroscopy probe.

The FDA's process analytical technology initiative encourages drug manufacturers to apply innovative ideas to better understand their processes. There are many challenges to applying these techniques to monitor mammalian cell culture bioreactors for biologics manufacturing. These include the ability to monitor multiple components in complex medium formulations non-invasively and in-line. We report results that demonstrate, for the first time, the technical feasibility of the in-line application of Raman spectroscopy for monitoring a mammalian cell culture bioreactor. A Raman probe was used for the simultaneous prediction of culture parameters including glutamine, glutamate, glucose, lactate, ammonium, viable cell density, and total cell density.

Effects of culture conditions on N-glycolylneuraminic acid (Neu5Gc) content of a recombinant fusion protein produced in CHO cells.

CHO cells express glycoproteins containing both the N-acetylneuraminic acid (Neu5Ac) and minor amounts of the N-glycolylneuraminic acid (Neu5Gc) forms of sialic acid. As Neu5Gc is not expressed in humans and can be recognized as a foreign epitope, there is the potential for immunogenicity issues for glycoprotein therapeutics. During process development of a glycosylated fusion protein expressed by CHO cells, a number of culture conditions were identified that affected the Neu5Gc content of the recombinant glycoprotein. Sodium butyrate (SB), a well-known additive reported to enhance recombinant protein productivity in specific cases, minimally affected product titers here, but did decrease Neu5Gc levels by 50-62%. A shift in culture temperature to a lower value after the exponential growth phase was used to extend the culture period. It was found that the Neu5Gc levels were 59% lower when the temperature shift occurred later near the stationary phase of the culture compared to an early-temperature shift, near the end of the exponential growth phase. Studies on the effects of pCO(2) with this product showed that the Neu5Gc levels were 46% lower at high pCO(2) conditions (140 mmHg) compared to moderate pCO(2) levels (20-80 mmHg). Finally, a comparison of sodium carbonate versus sodium hydroxide as the base used for pH control resulted in a reproducible 33% decrease in Neu5Gc in bioreactors using sodium hydroxide. These results are of practical importance as SB is a commonly tested additive, and the other factors affecting Neu5Gc can conveniently be used to reduce or control Neu5Gc in processes for the manufacture of glycoprotein therapeutics.

Single-cell variability in growing Saccharomyces cerevisiae cell populations measured with automated flow cytometry.

Cell cultures normally are heterogeneous due to factors such as the cell cycle, inhomogeneous cell microenvironments, and genetic differences. However, distributions of cell properties usually are not taken into account in the characterization of a culture when only population averaged values are measured. In this study, the cell size, green fluorescence protein (Gfp) content, and viability after automated staining with propidium iodide (PI) are monitored at the single-cell level in Saccharomyces cerevisiae cultures growing in a batch bioreactor using an automated flow injection flow cytometer system. To demonstrate the wealth of information that can be obtained with this system, three cultures containing three different plasmids are compared. The first plasmid is a centromeric plasmid expressing under the control of a TEF2 promoter the S65T mutant form of Gfp. The other two plasmids are 2 microm plasmids and express the FM2 mutant of Gfp under the control of either the TEF1 or the TEF2 promoter. The automated sampling, cell preparation, and analysis permitted frequent quantification of the culture characteristics. The time course of the data representing not only population average values but also their variability, provides a detailed and reproducible "fingerprint" of the culture dynamics. The data demonstrate that small changes in the genetic make up of the recombinant system can result in large changes in the culture Gfp production and viability. Thus, the developed instrumentation is valuable for rapidly testing promoter strength, plasmid stability, cell viability, and culture variability.

Automated flow cytometry for acquisition of time-dependent population data.

BACKGROUND: The implementation of flow cytometry in many experimental settings can be limited by the extensive amount of sample handling and preparation required for analysis. We describe a system that automatically performs sample handling and flow cytometric analysis, thus allowing one to construct detailed pictures of changes in cell population distributions as a function of time. METHODS: Cell samples from bioreactors were loaded into a microchamber designed to perform all sample preparation steps including washing, fixation, staining, and dilution. The sample was then transported into a sample loop of known volume from which it was injected into the flow cell for determination of cell counts and measurement of scattering and fluorescence parameters. The apparatus was fully automated and controlled with a personal computer equipped with a data acquisition card. An inexpensive mechanism that continuously replenished the sheath fluid was implemented to ensure continuous and uninterrupted operation of the flow cytometer for several days. The device was interfaced with a FACSCalibur equipped with CellQuest software for data acquisition and analysis. RESULTS: The set-up was tested with batch cultures of Saccharomyces cerevisiae expressing the green fluorescent protein (GFP). On-line cell counts showed close agreement with off-line measurements throughout the exponential growth of a yeast culture. The time course of light scattering, GFP fluorescence, and viability distributions provided a detailed description of changes occurring in growing cell cultures based on sampling approximately every 15 min for more than 40 consecutive hours. Therefore, the device could be used to obtain descriptions of the dynamic behavior of cell populations with no user intervention required for several days. CONCLUSIONS: The system significantly expanded the utility of flow cytometry by eliminating cumbersome and time-consuming steps that make the application of flow cytometry impractical in certain situations. It is anticipated that the described set-up will find utility in biotechnology applications such as monitoring of cell cultures, screening of biologically active compounds, and in functional genomics efforts for phenotypic characterizations of cells.

Instantaneous evaluation of mammalian cell culture growth rates through analysis of the mitotic index.

Since a culture increases in cell number when dividing cells separate into two newborn cells, the fraction of mitotic cells in a growing cell population directly reflects the overall growth behavior of a cell culture. To rapidly assess the effects of growth conditions on the fraction of mitotic cells we have employed an antibody specific for the phosphorylated form of histone H3 for the identification of mitotic cells using flow cytometry. The phosphorylation of histone H3 closely correlates with the chromosomal condensation that accompanies the onset of mitosis, and, therefore, it represents a convenient marker for dividing cells. We have optimized the protocol for the staining of mitotic cells for both Chinese hamster ovary and hybridoma cell cultures. Fluorescence micrographs taken of stained cells show that cells in the various stages of mitosis can be detected based on the morphological characteristics of the chromosomes. The variation in the mitotic cell fraction has been determined throughout the batch growth phases of cultures under different growth conditions. The dynamics of the mitotic index show that balanced growth was never truly reached and that the growth rate is in fact quite variable for these cultures since large variations in the mitotic index are observed. In addition, a large increase in the fraction of mitotic cells just prior to the exponential growth phase for all cultures indicates that they are partially synchronized at the exit from the lag phase. According to a two-staged, age structured population balance model, the mitotic index is directly proportional to the growth rate of a culture. The proportionality constant for this case is shown to be the time required for cells to progress through mitosis. This time is believed to be constant for a particular cell line, as shown by experimental data. Thus, growth rates can be determined solely by measurement of the fraction of cells in mitosis. The mitotic index measurements were then used to calculate the growth in cell number of the cultures, and these simulations accurately reflect observed cell counts. Other simulations also show that changes in cell growth can be predicted before they are reflected in the cell count data. This technique can be used as a sensitive indicator of cell growth and could be useful as a process monitoring technique and for developing better feeding strategies for animal cell cultures.