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BMC Proceedings 2013, Volume 7 Suppl 6 http://www.biomedcentral.com/bmcproc/supplements/7/S6 Page 30 of 151 • Fed-batch cultivations substantially improved cell and product concentration. Feeding cultures in CD OptiCHO with EfficientFeed A and FunctionMAX or with Feed A and Feed B resulted in similar antibody concentrations and roughly doubled the antibody production compared to feeding with EfficientFeed A only. • The highest titer was achieved in ActiCHO P in combination with Feed A and Feed B. In this medium a 6.3-fold improvement, compared with the previous batch cultivation, was observed. Further addition of FunctionMAX to these cultures did not significantly improve the antibody production. Reference 1. Barrett S, Boniface R, Dhulipala P, Slade P, Tennico Y, Stramaglia M, Lio P, Gorfien S: Attaining Next-Level Titers in CHO Fed-Batch Cultures. BioProcess International 2012, 10:56-62. P14 Advanced off-gas measurement using proton transfer reaction mass spectrometry to predict cell culture parameters Timo Schmidberger 1,2* , Robert Huber 2 1 Department of biotechnology, University of Natural Resources and Life Sciences, 1180 Vienna, Austria; 2 Sandoz GmbH BU Biopharmaceuticals, 6336 Langkampfen, Austria E-mail: timo.schmidberger@sandoz.com BMC Proceedings 2013, 7(Suppl 6):P14 Background: Mass spectrometry is a well-known technology to detect O 2 and CO 2 in the off-gas of cell culture fermentations. In contrast to classical mass spectrometers, the proton transfer reaction mass spectrometer (PTR MS) enables the noninvasive analysis of a broad spectrum of volatile organic compounds (VOCs) in real time. The thereby applied soft ionization technology generates spectra of less fragmentation and facilitates their interpretation. This gave us the possibility to identify process relevant compounds in the bioreactor off-gas stream in addition to O 2 and CO 2 . In our study the PTR-MS technology was applied for the first time to monitor volatile organic compounds (VOC) and to predict cell culture parameters in an industrial mammalian cell culture process. Materials and methods: The aptitude of PTR MS for advanced bioprocess monitoring was assessed by Chinese hamster ovary (CHO) cell culture processes producing a recombinant protein conducted in a modified 7L glass bioreactor (Applikon, Shiedam, Netherlands). The PTR MS-hs (Ionicon, Innsbruck, Austria) was equipped with a QMS422 quadrupole for mass separation and with a secondary electron multiplier detector to measure masses ranging from 18 to 200 m/z. The equipment set-up is illustrated in Figure 1. On a daily basis the glutamine concentration was determined with the BioProfile 100 plus (Nova Biomedical, Waltham, MA) and the viable cell density (VCD) was measured with the Vi-Cell XR cell counter (Beckham Coulter, Fullerton, CA). Samples for the product quantification were pulled daily and analyzed once at the end of a fermentation using affinity liquid chromatography. The PTR-MS data was first filtered with an adaptive online repeated median filter [1] and then correlated to the cell culture parameters with partial least square regression (PLS-R) using the software SIMCA P12+ (Umetrics, Umea, Sweden). Results: The applicability of the PTR-MS technique was studied using eight different fermentations conducted during process optimization to determine key cell culture parameters such as viable cell density, product titer and glutamine by partial least square regression models. Probably the most important parameter in industrial cell culture processes is the viable cell density. The R² of the PLS-R model for the VCD was 0.86 and hence, lower compared to other methods found in literature (such as 2D fluorescence [2]). Especially low values, which were observed only in the first few days of the fermentation, showed a high prediction error. At the beginning of the fermentation the VOC composition in the off-gas is characterized by VOCs from the media preparation (probably impurities of the raw materials used) and only a few VOC can be assigned to the cells. The media was prepared up to one week before the fermentations started and, depending on the storage time, the initial VOC content varied. Within the first days the media assigned VOCs were washed out and the cells started to produce VOCs. Accordingly the effect of the initial condition was weaker and prediction got better. In a second PLS-R model the product concentration was estimated based on the PTR-MS data. The model was better compared to the estimation of the VCD what is reflected in a R² of 0.94. The effect of the early Figure 1(abstract P14) Experimental set-up to monitor VOCs in mammalian cell culture. process phase on the prediction quality is not very distinct since almost no product was produced in the first days. The good model for the titer is a hint that producing the product is correlated with metabolic pathways involving VOCs. However distinct metabolic pathways could not be revealed within this study, since only a few VOC could be assigned to specific compounds yet. The third parameter assessed in this study was the glutamine concentration. The PLS-R model for glutamine concentration showed the lowest R² and Q² of this evaluation. Glutamine was added on demand and probably feeding corrupted the correlation. To overcome this problem, the glutamine related physiological parameter specific glutamine uptake (qGln) was used. The descriptive as well as the predictive power was higher when the specific consumption instead of the glutamine concentration was used (0.91 and 0.82). An explanation for this result is that the consumption of glutamine might be correlated to other metabolic pathways which can produce VOCs. In combination with an accurate online VCD measurement, the qGln can be used to estimate the overall glutamine demand of the culture in real-time. A summary of all PLS-R models is given in Table 1. Conclusions: In our study we showed that the VOC profile obtained with the PTR-MS can be used to predict important cell culture parameters, but compared to other on-line techniques such as near infrared spectroscopy the PLS-R models are currently less robust (expressed by a lower R²). Moreover the most important VOCs in the PLS-R model could be used to get deeper insights into the cellular metabolism. At the moment however, this is limited by the lack of identified VOCs and the small literature basis reporting of pathways including volatile metabolites. Finally, further experiments will be necessary to assess the most influential factors on the VOC production and to fully exploit the potential of the PTR-MS. Table 1(abstract P14) Summary PLS-R models Compound R² Q² VCD 0.86 0.76 Product titer 0.94 0.88 Glutamine 0.83 0.62 Specific glutamine uptake 0.91 0.82
BMC Proceedings 2013, Volume 7 Suppl 6 http://www.biomedcentral.com/bmcproc/supplements/7/S6 Page 31 of 151 Acknowledgements: We want to thank Rene Gutmann from Ionicon for the installation and support for the PTR-MS and Karl Bayer for the fruitful discussions. References 1. Schettlinger K, Fried R, Gather U: Real-time signal processing by adaptive repeated median filters. Int J Adapt Control 2009, 24:346-362. 2. Teixeira AP, Portugal CA, Carinhas N, Dias JM, Crespo JP, Alves PM, Carrondo MJ, Oliveira R: In situ 2D fluorometry and chemometric monitoring of mammalian cell cultures. Biotechnol Bioeng 2009, 102:1098-1106. P15 New peptide-based and animal-free coatings for animal cell culture in bioreactors Youlia Serikova 1* , Aurélie Joly 1 , Géraldine Nollevaux 1 , Martin Bousmanne 2 , Wafa Moussa 2 , Jonathan Goffinet 3 , Jean-Christophe Drugmand 3 , Laurent Jeannin 2 , Yves-Jacques Schneider 1 1 Laboratory of Cellular, Nutritional and Toxicological Biochemistry, Institute of Life Sciences, UCLouvain, 1348 Louvain-la-Neuve, Belgium; 2 Peptisyntha sa, 1120 Brussels, Belgium; 3 ATMI, 1120 Brussels, Belgium E-mail: youlia.serikova@uclouvain.be BMC Proceedings 2013, 7(Suppl 6):P15 Background: Anchorage dependent cells require an appropriate extracellular matrix for their survival, migration, proliferation, phenotyping and/or differentiation [1-3]. These cells interact with extracellular matrix proteins, primarily through integrins, which induces focal adhesion contacts assembly and activation of signalling pathways thatregulate diverse cellular processes [4]. Culture supports usually include biochemical components allowing such cells to adhere and to reconstitute an extracellular environment close to that found in vivo. Currently, this artificial environment is achieved by extracellular matrix constituents deposition, adsorption or grafting; among them collagens, fibronectin, laminin, artificial lamina propria... [5]. However, such animal proteins used in cell culture may induce pro-inflammatory stress, be unstable against proteolysis or loose activity after adsorption [6,7]. Synthetic microenvironments should be more suitable for clinical purposes: (i) improved control of physicochemical and mechanical properties, (ii) limited risks of immunogenicity, (iii) increased biosafety (animal free) and (iv) facilitated scale-up [1]. In this framework, research has recently focused on synthetic peptides or peptidomimetics that can mimic the extracellular matrix. Such molecules can be immobilized as recognition motifs on the surface of culture supports with a greater stability and easier surfaces characterization [5]. Self-assembling peptide hydrogels could mimic the chemical and mechanical aspects of the natural extracellular matrix [8,9] by undergoing large deformations, as in mammalian tissues. They have an inherent biocompatibility and should be able to direct cell behaviour [10]. They also can be functionalized with various biologically active ligands constituting good candidates to a new range of smart biomaterials, able to ensure adhesion of different cell types [11-13]. The range of biomimetic peptides that direct cell adhesion and are recognized by integrins is large. Recognition sequences derived from different extracellular matrix proteins include RGD [1], which are specific to different cell lines [1,5,6]. In this context, this work aims at designing animal-free, chemically defined and industrially scalable coatings for animal cell culture, as an alternative to collagen, fibronectin or Matrigel® for laboratory and industrial large scale applications. These are based on self-assembling short peptides bearing adhesion bioactive sequences like RGD-derived or other adhesion sequences developed to coat polystyrene or polyethylene terephthalate surfaces. Adhesion sequences should be recognized by cells, which should favour their anchorage and spreading. Experimental: Bioactive self-assembling peptide sequences were synthesized in liquid phase, purified, analytically characterised and manufactured by Peptisyntha (Brussels, Be) in GMP conditions, as sterile coating solutions. They were used to coat polystyrene flasks (Corning Inc., NY) in comparison with animal-derived coatings i.e. collagen and fibronectin. Human Adipose Derived Stem Cells (hADSC) were purchased from Lonza (Verviers, Be); Caco-2, MRC-5 and CHO cells, obtained from ATCC. Cells were seeded at 8 000 cells/cm 2 and cultured until 7 days. After 60 h or 7 days of culture, cells were harvested and counted on Bürker cell in Trypan blue or fixed. Nuclei were then stained with DAPI and actin filaments with Rhodamin-Phalloidin. Fluorescence microscopy was used to observe cell morphology and NIS software allowed cell-spreading determination. Results and discussion: The absence of cytotoxicity was assayed with necrosis (LDH) and cell metabolic activity (MTT) tests on different cell lines (Caco-2, MRC-5, CHO, hADSC). No cytotoxicity was detected. Two variants of bioactive self-assembling peptides, both containing RGDderived sequences, were compared with animal-derived coatings (collagen and fibronectin) in serum-poor of free medium. Cytocompatibility and dose dependent response studies revealed that peptides promote cell adhesion and growth. As for hADSC culture, these cells were first incubated in a serum-free medium during 6 to 24 h and the proportion of adherent cells and their spreading was evaluated. hADSC cells needed more than 6 h to fully adhere to the culture surface and the adhesion effectiveness appeared better for collagen and the first variant of peptide than for the other substrate coatings. Initial spreading was more marked on fibronectin, but then increased from 6 to 24 hours on all coatings. A second experiment consisted in a first cell incubation in DMEM supplemented with 1% Fetal Bovine Serum (FBS) and, after 24 h, the medium was replaced by DMEM supplemented with 10% FBS. After 7 days, the best cell growth was observed for substrates coated with collagen and peptide 1, fibronectin and peptide 2 being slightly less efficient. In parallel, cell spreading decreased or remained constant upon cell proliferation (Figure 1). As for Caco-2 cells culture, these cells were incubated in a serum-free, hormono-defined medium (BDM) during 6 to 24 h and the proportion of adherent cells and their spreading were evaluated. These cells required a shorter duration than hADSC to adhere on the surface and the adhesion effectiveness appeared a little bit better for collagen and fibronectin. Initial spreading was more marked on collagen and its importance varies between 6 and 24 h on different coatings. The second experiment consisted in a first cell incubation in a serum-free medium and, after 24 h, the nutritive medium was replaced by a medium supplemented with 1% FBS. After 60 h, there was almost no difference between the different coatings. Nevertheless, after 7 days, cells cultured on peptides reached the same effectiveness as on fibronectin, but slightly lower than collagen. As for hADSC, cell spreading decreased upon cells proliferation. Conclusion: Designed self-assembling bioactive peptides are not cytotoxic and are cytocompatible. Cell adhesion and growth on peptide coatings appear as effective as on animal-derived coatings and the peptide coatings allow easy cell harvesting after culture. Globally, the results indicate that self-assembling bioactive peptides constitute chemically defined, entirely synthetic and effective promoters of cell adhesion, spreading and proliferation. Acknowledgements: This work is supported by Innoviris (Brussels Region) in the scope of a Doctiris PhD grant. References 1. Petrie TA, Garcia AJ: Extracellular Matrix-derived Ligand for Selective Integrin Binding to Control Cell Function. Biol Interact Mater Surf 2009, 1:133-156. 2. Hynes RO: The Extracellular Matrix: Not Just Pretty Fibrils. Sci 2009, 326:1216-1219. 3. Rahmany MB, Van Dyke M: Biomimetic approaches to modulate cellular adhesion in biomaterials: A review. Acta Biomater 2013, 9:5431-5437. 4. Badami AS, Kreke MR, Thompson MS, Riffle JS, Goldstein AS: Effect of fiber diameter on spreading, proliferation, and differentiation of osteoblastic cells on electrospun poly(lactic acid) substrates. Biomater 2006, 27:596-606. 5. Shin H, Jo S, Mikos AG: Biomimetic materials for tissue engineering. Biomater 2003, 24:4353-4364. 6. Hersel U, Dahmen C, Kessler H: RGD modified polymers: biomaterials for stimulated cell adhesion and beyond. Biomater 2003, 24:4385-4415. 7. Lin CC, Metters AT: Hydrogels in controlled release formulations: Network design and mathematical modeling. Adv Drug Deliv Rev 2006, 58:1379-1408. 8. Wu EC, Zhang S, Hauser CAE: Self-Assembling Peptides as Cell-Interactive Scaffolds. Adv Funct Mater 2012, 22:456-468. 9. Hamilton SK, Lu H, Temenoff JS: Micropatterned Hydrogels for Stem Cell Culture. Stud Mechanobiol Tissue Eng Biomater 2010, 2:119-152.
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