GS-NS0 Cell Research Articles

A Predictive Mathematical Model of Cell Cycle, Metabolism, and Apoptosis of Monoclonal Antibody‐Producing GS–NS0 Cells

The monoclonal antibody (mAb) industry is witnessing unprecedented growth, with an increasing range of new molecules and biosimilars as well as disease targets approved than ever before. Competition necessitates pharmaceutical companies to reduce development/production costs and time-to-market. To this aim, mathematical modeling can aid traditional experiment-only-based process development by reducing the design space, integrating scales, and assisting in identifying optimal operating conditions in less time and with lower expense. Mathematical models have been employed by other industries for control and optimization purposes and are important decisional tools for testing scenarios, process configurations, operating conditions, etc. Herein, a predictive, experimentally validated mathematical model that captures cellular metabolism and growth with cell cycle, cell death (apoptosis), and mAb production in GS-NS0 cells is presented. The model utilizes cellular, metabolic, and gene expression data, highlighting how multiple data sources can be integrated in one tool with the aim of optimizing mammalian cell bioprocessing.

Energy-based culture medium design for biomanufacturing optimization: A case study in monoclonal antibody production by GS-NS0 cells

Demand for high-value biologics, a rapidly growing pipeline, and pressure from competition, time-to-market and regulators, necessitate novel biomanufacturing approaches, including Quality by Design (QbD) principles and Process Analytical Technologies (PAT), to facilitate accelerated, efficient and effective process development platforms that ensure consistent product quality and reduced lot-to-lot variability. Herein, QbD and PAT principles were incorporated within an innovative in vitro-in silico integrated framework for upstream process development (UPD). The central component of the UPD framework is a mathematical model that predicts dynamic nutrient uptake and average intracellular ATP content, based on biochemical reaction networks, to quantify and characterize energy metabolism and its adaptive response, metabolic shifts, to maintain ATP homeostasis. The accuracy and flexibility of the model depends on critical cell type/product/clone-specific parameters, which are experimentally estimated. The integrated in vitro-in silico platform and the model’s predictive capacity reduced burden, time and expense of experimentation resulting in optimal medium design compared to commercially available culture media (80% amino acid reduction) and a fed-batch feeding strategy that increased productivity by 129%. The framework represents a flexible and efficient tool that transforms, improves and accelerates conventional process development in biomanufacturing with wide applications, including stem cell-based therapies.

Advanced model‐based control strategies for the intensification of upstream and downstream processing in mAb production

Current industrial trends encourage the development of sustainable, environmentally friendly processes with minimal energy and material consumption. In particular, the increasing market demand in biopharmaceutical industry and the tight regulations in product quality necessitate efficient operating procedures that guarantee products of high purity. In this direction, process intensification via continuous operation paves the way for the development of novel, eco-friendly processes, characterized by higher productivity and lower production costs. This work focuses on the development of advanced control strategies for (i) a cell culture system in a bioreactor and (ii) a semicontinuous purification process. More specifically, we consider a fed-batch culture of GS-NS0 cells and the semicontinuous Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) for the purification process. The controllers are designed following the PAROC framework/software platform and their capabilities are assessed in silico, against the process models. It is demonstrated that the proposed controllers efficiently manage to increase the system productivity, returning strategies that can lead to continuous, stable process operation. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:966-988, 2017.

Cyclin and DNA distributed cell cycle model for GS-NS0 cells.

Mammalian cell cultures are intrinsically heterogeneous at different scales (molecular to bioreactor). The cell cycle is at the centre of capturing heterogeneity since it plays a critical role in the growth, death, and productivity of mammalian cell cultures. Current cell cycle models use biological variables (mass/volume/age) that are non-mechanistic, and difficult to experimentally determine, to describe cell cycle transition and capture culture heterogeneity. To address this problem, cyclins—key molecules that regulate cell cycle transition—have been utilized. Herein, a novel integrated experimental-modelling platform is presented whereby experimental quantification of key cell cycle metrics (cell cycle timings, cell cycle fractions, and cyclin expression determined by flow cytometry) is used to develop a cyclin and DNA distributed model for the industrially relevant cell line, GS-NS0. Cyclins/DNA synthesis rates were linked to stimulatory/inhibitory factors in the culture medium, which ultimately affect cell growth. Cell antibody productivity was characterized using cell cycle-specific production rates. The solution method delivered fast computational time that renders the model’s use suitable for model-based applications. Model structure was studied by global sensitivity analysis (GSA), which identified parameters with a significant effect on the model output, followed by re-estimation of its significant parameters from a control set of batch experiments. A good model fit to the experimental data, both at the cell cycle and viable cell density levels, was observed. The cell population heterogeneity of disturbed (after cell arrest) and undisturbed cell growth was captured proving the versatility of the modelling approach. Cell cycle models able to capture population heterogeneity facilitate in depth understanding of these complex systems and enable systematic formulation of culture strategies to improve growth and productivity. It is envisaged that this modelling approach will pave the model-based development of industrial cell lines and clinical studies.

On the model-based optimization of secreting mammalian cell (GS-NS0) cultures.

The global bio-manufacturing industry requires improved process efficiency to satisfy the increasing demands for biochemicals, biofuels, and biologics. The use of model-based techniques can facilitate the reduction of unnecessary experimentation and reduce labor and operating costs by identifying the most informative experiments and providing strategies to optimize the bioprocess at hand. Herein, we investigate the potential of a research methodology that combines model development, parameter estimation, global sensitivity analysis, and selection of optimal feeding policies via dynamic optimization methods to improve the efficiency of an industrially relevant bioprocess. Data from a set of batch experiments was used to estimate values for the parameters of an unstructured model describing monoclonal antibody (mAb) production in GS-NS0 cell cultures. Global Sensitivity Analysis (GSA) highlighted parameters with a strong effect on the model output and data from a fed-batch experiment were used to refine their estimated values. Model-based optimization was used to identify a feeding regime that maximized final mAb titer. An independent fed-batch experiment was conducted to validate both the results of the optimization and the predictive capabilities of the developed model. The successful integration of wet-lab experimentation and mathematical model development, analysis, and optimization represents a unique, novel, and interdisciplinary approach that addresses the complicated research and industrial problem of model-based optimization of cell based processes.

Cell cycle and apoptosis: a map for the GS-NS0 cell line at the genetic level and the link to environmental stress

Background Large scale mammalian cell culture systems, especially fed-batch systems, are currently utilised to manufacture monoclonal antibodies (MAbs) in order to meet the continuously growing global demand [1]. Nutrient deprivation and toxic metabolite accumulation commonly encountered in such systems influence the cell cycle and trigger apoptosis, resulting in shorter culture times and a lower final MAb titre. Control of the cell cycle has been previously studied in order to achieve higher titre through apoptosis inhibition by bcl-2 overexpression and cell cycle arrest in G1/G0 by p21 transfection. However, the above mentioned strategies have not always been successful; no improvement in titre was often observed though bcl-2 over-expression helped prolong the culture viability whereby the majority of cells were arrested at G1/G0 to avoid apoptosis [2-4]. Thus, a systematic insight of the dynamic relation between metabolic stress, cell cycle and apoptosis is still required. To this end, we aim to establish a novel map of the dynamic interplay between cell cycle and apoptosis at the genetic level, and provide a link with the culture conditions at the metabolic level.

Discrimination Among IgG1-κ Monoclonal Antibodies Produced by Two Cell Lines Using Charge State Distributions in nanoESI-TOF Mass Spectra

Charge state distributions (CSDs) of proteins in nanoESI mass spectra are affected by the instrumental settings and experimental conditions, in addition to the conformations of the proteins in the analyzed solutions. In the presented study, instrumental and experimental parameters--the desolvation gas flow rate, temperature, pH, buffer (ammonium acetate), and organic modifier (methanol) concentrations--were optimized according to a reduced central composite face experimental design to maximize the separation of CSDs of monoclonal IgG1-kappa antibodies produced by two production systems (CHO and GS-NS0 cell lines). Principal component analysis and Fisher linear discriminant analysis were then used to reduce the dimensions of the acquired dataset and quantify the separation of the protein classes, respectively. The results show that the IgG1-kappa molecules produced by the two production systems can be clearly distinguished using the described approach, which could be readily applied to other proteins and production systems.

Transcriptome and proteome analysis of antibody‐producing mouse myeloma NS0 cells cultivated at different cell densities in perfusion culture

A combined gene and protein expression profiling was performed to gain a deeper insight into the intracellular response of the antibody-producing GS-NS0 cell line in continuous perfusion culture. Growth rate, production rate, metabolic activity and viability declined with increasing cell density, dilution rate and time. Transcriptome and proteome analyses of cells at three different densities revealed 53 genes and 47 proteins as having significantly altered expression levels at HCD (high cell density). The results showed an increased up-regulation of genes/proteins involved in cellular energy production with increasing cell density. Furthermore, the intensified process triggered a cellular response to external stress stimuli, revealed by an overexpression of the genes/proteins implicated in cell-cycle arrest [e.g. Rb1 (retinoblastoma 1 gene) and Cdkn1b (cyclin-dependent kinase inhibitor 1B gene)] and in the induction of pro-apoptotic genes/proteins [e.g. Tnfrsf (tumour necrosis factor receptor superfamily gene), Nfkappa bia (gene coding for nuclear factor-kappaB inhibitor), HSP60 (heat-shock protein of molecular mass 60 kDa) and heterogeneous nuclear ribonucleoprotein K]. Interestingly, we observed a down-regulation of the transcription factor interferon regulatory factor 4 involved in the unfolded-protein-response process and protein disulfide-isomerase family members responsible for protein folding and assembly. Additionally, subunits of proteasome complex were highly expressed at HCD. Microarray, real-time quantitative reverse-transcription PCR and Western-blot analyses demonstrated a consistent trend of decrease in IgG heavy-chain level with increasing cell density. HSP60, which inhibits apoptosis by complexing with pro-apoptotic proteins such as Bax and Bak, was repressed at HCD. Overall, the data suggested that the balance among several factors involved in energy metabolism might be essential for fine-tuning the cell choice between survival and apoptosis, leaning towards the side of apoptosis at HCD. The results provide significant information for cell-engineering strategies and solutions to problems that prevail in HCD culture.

Development and Analysis of a Mathematical Model for Antibody-Producing GS-NS0 Cells Under Normal and Hyperosmotic Culture Conditions

The GS-NS0 cell line is industrially important and is currently used for the large-scale production of several therapeutic monoclonal antibodies. A novel hybrid model, consisting of both unstructured and structured elements, has been developed to describe cell growth and death, metabolism, and antibody production in the GS-NS0 system under normal culture conditions. A comparison between the hybrid model and a large-scale single-cell model (SCM) describing detailed metabolic processes verified the predictive ability of the hybrid model (when compared with experimental data) and highlighted the practical difficulties involved in utilizing complex models. Global sensitivity analysis (GSA) on the hybrid model identified the specific transcription and translation rates of heavy and light immunoglobulin chains as parameters with the largest impact on the antibody production process. This information, together with the addition of a 24-h lag phase, resulted in the successful extension of the hybrid model to represent GS-NS0 system behavior under hyperosmotic culture conditions.

Dynamic analysis of GS‐NS0 cells producing a recombinant monoclonal antibody during fed‐batch culture

In this study we have analyzed the dynamic covariation of the mammalian cell proteome with respect to functional phenotype during fed-batch culture of NS0 murine myeloma cells producing a recombinant IgG(4) monoclonal antibody. GS-NS0 cells were cultured in duplicate 10 L bioreactors (36.5 degrees C, 15% DOT, pH 7.0) for 335 h and supplemented with a continuous feed stream after 120 h. Cell-specific growth rate declined continuously after 72 h of culture. Cell-specific recombinant monoclonal antibody production rate (qP) varied sixfold through culture. Whilst qP correlated with relative recombinant heavy chain mRNA abundance up to 216 h, qP subsequently declined, independent of recombinant heavy chain or light chain mRNA abundance. GS-NS0 cultures were sampled at 48 h intervals between 24 and 264 h of culture for proteomic analyses. Total protein abundance and nascent polypeptide synthesis was determined by 2D PAGE of unlabeled proteins visualized by SYPRO Ruby and autoradiography of (35)S-labeled polypeptides, respectively. Covariation of nascent polypeptide synthesis and abundance with biomass-specific cell growth, glucose and glutamate consumption, lactate and Mab production rates were then examined using two partial least squares regression models. Most changes in polypeptide synthesis or abundance for proteins previously identified by mass spectrometry were positively correlated with biomass-specific growth rate. We conclude that the substantial transitions in cell physiology and qP that occur during culture utilize a relatively constant complement of the most abundant host cell machines that vary primarily with respect to induced changes in cell growth rate.

Molecular analysis of successful cell line selection in transfected GS‐NS0 myeloma cells

The production of recombinant proteins from mammalian cells is now an essential part of biotechnology. However, despite this importance, the detailed characteristics of good producing cell lines remain largely unknown. The industrially important GS-NS0 mammalian expression system is able to produce large amounts of protein from relatively few copies of recombinant genes. This makes GS-NS0 cell lines ideal candidates to study the consequence of recombinant plasmid transfection in mammalian cells. This study investigated the molecular features of a panel of 17 randomly chosen GS-NS0 cell lines engineered to produce a recombinant antibody. The research analysed antibody production via enzyme-linked immunosorbent assay (ELISA), and investigated the molecular features of the transfectants by Northern, Southern and copy number analysis. The cell lines generated produced a range of antibody concentrations. In addition, for transfectants defined as producers of recombinant antibody there was a positive correlation between specific productivity and heavy chain mRNA expression. The use of Northern and Southern analysis allowed determination of the functional integrity of the transfected plasmid. Over 50% of the transfectants studied had molecular defects at the level of mRNA and/or cDNA. Cell lines were identified with suspected defects in the regulatory regions of transfected genes in addition to cell lines which lacked recombinant genes. Also, "false-positive" cell lines were generated which were able to overcome the GS selection pressure without producing any recombinant antibody. This article discusses these findings in relation to vector design.

On the statistical analysis of the GS-NS0 cell proteome: Imputation, clustering and variability testing

We have undertaken two-dimensional gel electrophoresis proteomic profiling on a series of cell lines with different recombinant antibody production rates. Due to the nature of gel-based experiments not all protein spots are detected across all samples in an experiment, and hence datasets are invariably incomplete. New approaches are therefore required for the analysis of such graduated datasets. We approached this problem in two ways. Firstly, we applied a missing value imputation technique to calculate missing data points. Secondly, we combined a singular value decomposition based hierarchical clustering with the expression variability test to identify protein spots whose expression correlates with increased antibody production. The results have shown that while imputation of missing data was a useful method to improve the statistical analysis of such data sets, this was of limited use in differentiating between the samples investigated, and highlighted a small number of candidate proteins for further investigation.

Functional proteomic analysis of GS-NS0 murine myeloma cell lines with varying recombinant monoclonal antibody production rate

We previously compared changes in individual protein abundance between the proteomes of GS-NS0 cell lines with varying rates of cell-specific recombinant monoclonal antibody production (qMab). Here we extend analyses of our proteomic dataset to statistically determine if particular cell lines have distinct functional capabilities that facilitate production of secreted recombinant Mab. We categorized 79 proteins identified by mass spectrometry according to their biological function or location in the cell and statistically compared the relative abundance of proteins in each category between GS-NS0 cell lines with varying qMab. We found that the relative abundance of proteins in ER chaperone, non-ER chaperone, cytoskeletal, cell signaling, metabolic, and mitochondrial categories were significantly increased with qMab. As the GS-NS0 cell line with highest qMab also had an increased intracellular abundance of unassembled Mab heavy chain (HC), we tested the hypothesis that the increased ER chaperone content was caused by induction of an unfolded protein response (UPR) signaling pathway. Immunoblot analyses revealed that spliced X-box binding protein 1 (XBP1), a marker for UPR induction, was not detectable in the GS-NS0 cells with elevated qMab, although it was induced by chemical inhibitors of protein folding. These data suggest that qMab is functionally related to the abundance of specific categories of proteins that together facilitate recombinant protein production. We infer that individual cells within parental populations are more functionally equipped for high-level recombinant protein production than others and that this bias could be used to select cells that are more likely to achieve high qMab.

Development and Analysis of a Mathematical Model for Antibody-Producing GS-NS0 Cells Under Normal and Hyperosmotic Culture Conditions

Development and Analysis of a Mathematical Model for Antibody-Producing GS-NS0 Cells Under Normal and Hyperosmotic Culture Conditions

Proteomic analysis of enriched microsomal fractions from GS-NS0 murine myeloma cells with varying secreted recombinant monoclonal antibody productivities

The folding, transport and modification of recombinant proteins in the constitutive secretory pathway of eukaryotic cell expression systems are reported to be a bottleneck in their production. We have utilised a proteomic approach to investigate the processes catalysed by proteins constituting the secretory pathway to further our understanding of those processes involved in high-level antibody secretion. We used GS-NS0 cell populations differing in qmAb to prepare enriched microsome fractions from each cell population at mid-exponential growth phase. These were analysed by 2-D PAGE to characterise the microsome protein component and test the hypothesis that bottlenecks in recombinant protein synthesis exist in these compartments, which are alleviated in high producers by the up-regulation of key secretory pathway proteins. Proteins whose abundance changed in a statistically significant manner with increasing qmAb were involved in a range of cellular functions: energy metabolism, mAb folding/assembly, cytoskeletal organisation and protein turnover. Amongst these were BiP and PDI, chaperones resident in the ER that interact with nascent immunoglobulins during their folding/assembly. However, our results suggest that there are diverse mechanisms by which these cells achieve qmAb. The results imply that cell-engineering strategies for improving qmAb should target proteins associated with altered functional phenotype identified in this study.

Stability and Suitability of GS-NS0 Cell Lines for Manufacturing Antibodies

Stability and Suitability of GS-NS0 Cell Lines for Manufacturing Antibodies

The response of GS-NS0 myeloma cells to single and multiple pH perturbations.

Animal cells are cultured in several types of vessels at laboratory and industrial scale the most common being the stirred tank and the air-lift. Economically, it is preferable to culture animal cells at the largest possible scale but the perceived sensitivity of animal cells to hydrodynamic shear has, until now, limited the aeration and agitation rates used. This has been reported to cause inhomogeneities in operational parameters such as dissolved oxygen concentration, temperature and pH. pH is of special interest during the latter stages of many animal cell fermentation because alkali additions, used for pH control, can cause large local pH perturbations of varying size and duration. The effect of single and multiple pH perturbations on the cell growth of a widely used GS-NS0 mouse myeloma cell line grown in batch culture was investigated. The effect of perturbation amplitude and duration was investigated using a single stirred tank reactor (STR). In the single STR system cells were subjected to one pH 8.0 or 9.0 perturbation ranging in duration from 0-90 minutes. No measurable decrease in viable cell number was seen for pH 8.0 perturbations of any duration whereas pH 9.0 perturbations lasting for 10 minutes caused a 15% decrease in viable cell number. The proportion of viable cells decreased with increasing perturbation time and a 90-minute exposure killed all of the cells. The effect of multiple pH perturbations on GS-NS0 cells was investigated using two connected STR's. More specifically the number of perturbations and the perturbation frequency were investigated. Cells were subjected to between 0 and 100 perturbations at pH 8.0; the time between each perturbation (frequency) was 6 minutes and each perturbation lasted for 200 seconds. Viable cell number decreased with increasing perturbation number, with 100 perturbations causing death of 27.5% of cells. Cells were also exposed to 10 perturbations at pH 9.0, each of 200 second duration at frequencies of either 6, 18 or 60 minutes. Approximately 8 times more cells were killed with perturbations at a 6-minute frequency (28.3% cell death) than at a 60-minute frequency (3.4% cell death).

Metabolic control of recombinant monoclonal antibody N-glycosylation in GS-NS0 cells.

Variable N-glycosylation at Asn(297) in the Fc region of recombinant therapeutic immunoglobulin G (IgG) molecules, specifically terminal galactosylation and sialylation, may affect both pharmacokinetic behavior and effector functions of recombinant therapeutic antibodies. We investigated the hypothesis that IgG Fc glycosylation can be controlled by manipulation of cellular nucleotide-sugar metabolism. In control cultures, N-glycans associated with the Fc domain of a recombinant humanized IgG1 produced by GS-NS0 cells in culture were predominantly biantennary, variably beta-galactosylated (average 0.3 mol galactose complex N-glycan(-1)) structures with no bisecting N-acetylglucosamine residues, sialylation, or alpha1,3-linked galactosylation evident. However, a variable proportion (5% to 15%) of high-mannose (Man5 to Man9) oligosaccharides were present. To manipulate the cellular content of the nucleotide sugar precursor required for galactosylation, UDP-Gal, we included either 10 mM glucosamine or 10 mM galactose in the culture medium. In the case of the former, a 17-fold increase in cellular UDP-N-acetylhexosamine content was observed, with a concomitant reduction (33%) in total UDP-hexose, although the ratio of UDP-Glc:UDP-Gal (4:1) was unchanged. Associated with these alterations in cellular UDP-sugar content was a significant reduction (57%) in the galactosylation of Fc-derived oligosaccharides. The proportion of high-mannose-type N-glycans (specifically Man5, the substrate for N-acetylglucosaminyltransferase I) at Asn(297) was unaffected. In contrast, inclusion of 10 mM galactose in culture specifically stimulated UDP-Gal content almost five-fold. However, this resulted in only a minimal, insignificant increase (6%) in beta1,4-galactosylation of Fc N-glycans. Sialylation was not improved upon the addition of the CMP-sialic acid (CMP-SA) precursor N-acetylmannosamine (20 mM), even with an associated 44-fold increase in cellular CMP-SA content. Analysis of recombinant IgG1 Fc glycosylation during batch culture showed that beta1,4-linked galactosylation declined slightly during culture, although, in the latter stages of culture, the release of proteases and glycosidases by lysed cells were likely to have contributed to the more dramatic drop in galactosylation. These data demonstrate: (i) the effect of steric hindrance on Fc N-glycan processing; (ii) the extent to which alterations in cellular nucleotide-sugar content may affect Fc N-glycan processing; and (iii) the potential for direct metabolic control of Fc N-glycosylation.

Characterization of the stability of recombinant protein production in the GS-NS0 expression system.

The GS-NS0 system is an important mammalian expression system used largely within industry for the high-level expression of recombinant proteins for therapeutic use. It is essential that the productivity of this system remains stable throughout culture expansion for the successful long-term production of recombinant proteins. Here we present a study of the stability of recombinant protein production from unamplified GS-NS0 cell lines over extended period of continuous culture. The cell lines used in this study were generated by the transfection of NS0 cells with DNA encoding for a secreted recombinant protein and by two subsequent rounds of limiting dilution cloning prior to analysis of stability. The stability of recombinant protein production was assessed at intervals over a period of 134 days using repeated batch culture in shake flasks. Heterogeneous stability was identified. The productivity of some clones remained consistent throughout 134 days of continuous culture. Others exhibit rapid and progressive loss of productivity. Analysis of the causal relationships underlying stability indicates that the initial transfectant determines the susceptibility to loss or retention of productivity. Selection of production clones on the basis of growth and productivity alone will not predict stability during long-term culture. Our research indicates that stable high-producing clones can readily be obtained from use of the GS-NS0 system in the absence of amplification but there may be molecular features of the original transfectants that could serve as very important predictive indicators of the stability of recombinant protein production.