86 results found
Antonakoudis A, Barbosa R, Kotidis P, et al., The Era of Big Data: Genome-scale Modelling meets Machine Learning, Computational and Structural Biotechnology Journal, ISSN: 2001-0370
Kis Z, Kontoravdi K, Dey AK, et al., 2020, Rapid development and deployment of high-volumevaccines for pandemic response, Journal of Advanced Manufacturing and Processing, Vol: 2, Pages: 1-10, ISSN: 2637-403X
Overcoming pandemics, such as the current Covid‐19 outbreak, requires the manufacture of several billion doses of vaccines within months. This is an extremely challenging task given the constraints in small‐scale manufacturing for clinical trials, clinical testing timelines involving multiple phases and large‐scale drug substance and drug product manufacturing. To tackle these challenges, regulatory processes are fast‐tracked, and rapid‐response manufacturing platform technologies are used. Here, we evaluate the current progress, challenges ahead and potential solutions for providing vaccines for pandemic response at an unprecedented scale and rate. Emerging rapid‐response vaccine platform technologies, especially RNA platforms, offer a high productivity estimated at over 1 billion doses per year with a small manufacturing footprint and low capital cost facilities. The self‐amplifying RNA (saRNA) drug product cost is estimated at below 1 USD/dose. These manufacturing processes and facilities can be decentralized to facilitate production, distribution, but also raw material supply. The RNA platform technology can be complemented by an a priori Quality by Design analysis aided by computational modeling in order to assure product quality and further speed up the regulatory approval processes when these platforms are used for epidemic or pandemic response in the future.
Kotidis P, Kontoravdi K, 2020, Harnessing the potential of artificial neural networks for predicting protein glycosylation, Metabolic Engineering Communications, Vol: 10, ISSN: 2214-0301
Kinetic models offer incomparable insight on cellular mechanisms controlling protein glycosylation. However, their ability to reproduce site-specific glycoform distributions depends on accurate estimation of a large number of protein-specific kinetic parameters and prior knowledge of enzyme and transport protein levels in the Golgi membrane. Herein we propose an artificial neural network (ANN) for protein glycosylation and apply this to four recombinant glycoproteins produced in Chinese hamster ovary (CHO) cells, two monoclonal antibodies and two fusion proteins. We demonstrate that the ANN model accurately predicts site-specific glycoform distributions of up to eighteen glycan species with an average absolute error of 1.1%, correctly reproducing the effect of metabolic perturbations as part of a hybrid, kinetic/ANN, glycosylation model (HyGlycoM), as well as the impact of manganese supplementation and glycosyltransferase knock out experiments as a stand-alone machine learning algorithm. These results showcase the potential of machine learning and hybrid approaches for rapidly developing performance-driven models of protein glycosylation.
Thaore V, Tsourapas D, Shah N, et al., 2020, Techno-Economic Assessment of Cell-Free Synthesis of Monoclonal Antibodies Using CHO Cell Extracts, PROCESSES, Vol: 8
Papathanasiou MM, Kontoravdi C, 2020, Engineering challenges in therapeutic protein product and process design, CURRENT OPINION IN CHEMICAL ENGINEERING, Vol: 27, Pages: 81-88, ISSN: 2211-3398
Casula E, Traversari G, Fadda S, et al., 2019, Modelling the osmotic behaviour of human mesenchymal stem cells, BIOCHEMICAL ENGINEERING JOURNAL, Vol: 151, ISSN: 1369-703X
Kotidis P, Jedrzejewski P, Sou SN, et al., 2019, Model-based optimization of antibody galactosylation in CHO cell culture, Biotechnology and Bioengineering, Vol: 116, Pages: 1612-1626, ISSN: 1097-0290
Exerting control over the glycan moieties of antibody therapeutics is highly desirable from a product safety and batch-to-batch consistency perspective. Strategies to improve antibody productivity may compromise quality, while interventions for improving glycoform distribution can adversely affect cell growth and productivity. Process design therefore needs to consider the trade-off between preserving cellular health and productivity while enhancing antibody quality. In this work, we present a modeling platform that quantifies the impact of glycosylation precursor feeding - specifically that of galactose and uridine - on cellular growth, metabolism as well as antibody productivity and glycoform distribution. The platform has been parameterized using an initial training data set yielding an accuracy of ±5% with respect to glycoform distribution. It was then used to design an optimized feeding strategy that enhances the final concentration of galactosylated antibody in the supernatant by over 90% compared with the control without compromising the integral of viable cell density or final antibody titer. This work supports the implementation of Quality by Design towards higher-performing bioprocesses.
Moya-Ramirez I, Kontoravdi K, Polizzi K, 2019, Low-cost and user-friendly biosensor to test the integrity of mRNA molecules suitable for field applications, Biosensors and Bioelectronics, Vol: 137, Pages: 199-206, ISSN: 0956-5663
The use of mRNA in biotechnology has expanded with novel applications such as vaccines and therapeutic mRNA delivery recently demonstrated. For mRNA to be used in patients, quality control assays will need to be routinely established. Currently, there is a gap between the highly sophisticated RNA integrity tests available and broader application of mRNA-based products by non-specialist users, e.g. in mass vaccination campaigns. Therefore, the aim of this work was to develop a low-cost biosensor able to test the integrity of a mRNA molecule with low technological requirements and easy end-user application. The biosensor is based on a bi-functional fusion protein, composed by the λN peptide that recognizes its cognate aptamer encoded on the 5’ end of the RNA under study and β-lactamase, which is able to produce a colorimetric response through a simple test. We propose two different mechanisms for signal processing adapted to two levels of technological sophistication, one based on spectrophotometric measurements and other on visual inspection. We show that the proposed λN-βLac chimeric protein specifically targets its cognate RNA aptamer, boxB, using both gel shift and biolayer interferometry assays. More importantly, the results presented confirm the biosensor performs reliably, with a wide dynamic range and a proportional response at different percentages of full-length RNA, even when gene-sized mRNAs were used. Thus, the features of the proposed biosensor would allow to end-users of products such as mRNA vaccines to test the integrity of the product before its application in a low-cost fashion, enabling a more reliable application of these products.
Kis Z, Papathanasiou M, CalvoSerrano R, et al., 2019, A model‐based quantification of the impact of new manufacturing technologies on developing country vaccine supply chain performance: A Kenyan case study, Journal of Advanced Manufacturing and Processing, Vol: 1, ISSN: 2637-403X
Kis Z, Shattock R, Shah N, et al., 2019, Correction: Emerging technologies for low‐cost, rapid vaccine manufacture, Biotechnology Journal, Vol: 14, Pages: 1-2, ISSN: 1860-6768
Kotidis P, Demis P, Goey C, et al., 2019, Constrained global sensitivity analysis for bioprocess design space identification, Computers and Chemical Engineering, Vol: 125, Pages: 558-568, ISSN: 1873-4375
The manufacture of protein-based therapeutics presents unique challenges due to limited control over the biotic phase. This typically gives rise to a wide range of protein structures of varying safety and in vivo efficacy. Herein we propose a computational methodology, enabled by the application of constrained Global Sensitivity Analysis, for efficiently exploring the operatingrange of process inputs in silico and identifying a design space that meets output constraints. The methodology was applied to an antibody-producing Chinese hamster ovary (CHO) cell culture system: we explored >8000 feeding strategies to identify a subset of manufacturing conditions that meet constraints on antibody titre and glycan distribution as an attribute of product quality. Our computational findings were then verified experimentally, confirming the applicability of this approach to a challenging production system. We envisage that this methodology can significantly expedite bioprocess development and increase operational flexibility.
Goey CH, Bell D, Kontoravdi C, 2019, CHO cell cultures in shake flasks and bioreactors present different host cell protein profiles in the supernatant, Biochemical Engineering Journal, Vol: 144, Pages: 185-192, ISSN: 1369-703X
Several studies on the impact of cell culture parameters on the profile of host cell protein (HCP) impurities have been carried out in shake flasks. Herein, we explore how transferable the findings and conclusions of such investigations are to lab-scale bioreactors. Experiments were performed in both systems in fed-batch mode under physiological temperature and with a shift to mild hypothermia and the impact on key upstream performance indicators was quantified. Under both temperatures, bioreactors produced a richer HCP pool despite the overall concentration being similar at both scales and temperatures. The number of different HCPs detected in bioreactor supernatants was four times higher than that in flasks under physiological temperature and more than eight times higher under mild hypothermia. The origin of HCPs was also altered from mostly naturally secreted proteins in flasks to mainly intracellular proteins in bioreactors at the lower temperature. Although the number of species correlated with apoptotic cell density in bioreactors, this was not the case in flasks. Even though the level of HCP impurities and mAb/HCP concentration ratio were similar under all four conditions with an average of approximately 330 μg HCP/mL culture and 0.3 mg HCP/mg IgG4, respectively, the fact that culture method significantly affects the number of species present in the supernatant can have implications for downstream processing steps.
Kotidis P, Kontoravdi C, 2019, Strategic framework for parameterization of cell culture models, Processes, Vol: 7, ISSN: 2227-9717
Global Sensitivity Analysis (GSA) is a technique that numerically evaluates the significance of model parameters with the aim of reducing the number of parameters that need to be estimated accurately from experimental data. In the work presented herein, we explore different methods and criteria in the sensitivity analysis of a recently developed mathematical model to describe Chinese hamster ovary (CHO) cell metabolism in order to establish a strategic, transferable framework for parameterizing mechanistic cell culture models. For that reason, several types of GSA employing different sampling methods (Sobol’, Pseudo-random and Scrambled-Sobol’), parameter deviations (10%, 30% and 50%) and sensitivity index significance thresholds (0.05, 0.1 and 0.2) were examined. The results were evaluated according to the goodness of fit between the simulation results and experimental data from fed-batch CHO cell cultures. Then, the predictive capability of the model was tested against four different feeding experiments. Parameter value deviation levels proved not to have a significant effect on the results of the sensitivity analysis, while the Sobol’ and Scrambled-Sobol’ sampling methods and a 0.1 significance threshold were found to be the optimum settings. The resulting framework was finally used to calibrate the model for another CHO cell line, resulting in a good overall fit. The results of this work set the basis for the use of a single mechanistic metabolic model that can be easily adapted through the proposed sensitivity analysis method to the behavior of different cell lines and therefore minimize the experimental cost of model development.
Kis Z, Shattock R, Shah N, et al., 2019, Emerging technologies for low-cost, rapid vaccine manufacture, Biotechnology Journal, Vol: 14, ISSN: 1860-6768
To stop the spread of future epidemics and meet infant vaccination demands in low‐ and middle‐income countries, flexible, rapid and low‐cost vaccine development and manufacturing technologies are required. Vaccine development platform technologies that can produce a wide range of vaccines are emerging, including: a) humanized, high‐yield yeast recombinant protein vaccines; b) insect cell‐baculovirus ADDomer vaccines; c) Generalized Modules for Membrane Antigens (GMMA) vaccines; d) RNA vaccines. Herein, existing and future platforms are assessed in terms of addressing challenges of scale, cost, and responsiveness. To assess the risk and feasibility of the four emerging platforms, the following six metrics are applied: 1) technology readiness; 2) technological complexity; 3) ease of scale‐up; 4) flexibility for the manufacturing of a wide range of vaccines; 5) thermostability of the vaccine product at tropical ambient temperatures; and 6) speed of response from threat identification to vaccine deployment. The assessment indicated that technologies in the order of increasing feasibility and decreasing risk are the yeast platform, ADDomer platform, followed by RNA and GMMA platforms. The comparative strengths and weaknesses of each technology are discussed in detail, illustrating the associated development and manufacturing needs and priorities.
Kontoravdi K, Jimenez Del Val I, 2018, Computational tools for predicting and controlling the glycosylation of biopharmaceuticals, Current Opinion in Chemical Engineering, Vol: 22, Pages: 89-97, ISSN: 2211-3398
Glycosylation is a critical quality attribute of biopharmaceuticals because it is a major source of structural variability that influences the in vivo safety and therapeutic efficacy of these products. Manufacturing process conditions are known to influence the monosaccharide composition and relative abundance of the complex carbohydrates bound to therapeutic proteins. Multiple computational tools have been developed to describe these process/product quality relationships in order to control and optimise the glycosylation of biopharmaceuticals. This review will provide a summary highlighting the strengths and weaknesses of each modelling strategy in their application towards cellular glycoengineering or bioprocess design and control. To conclude, potential unified glycosylation modelling approaches for biopharmaceutical quality assurance are proposed.
Goey CH, Alhuthali S, Kontoravdi C, 2018, Host cell protein removal from biopharmaceutical preparations: toward the Implementation of Quality by Design, Biotechnology Advances, ISSN: 0734-9750
Goey CH, Bell D, Kontoravdi K, 2018, Mild hypothermic culture conditions impact residual host cell protein composition post-protein a chromatography, mAbs, Vol: 10, Pages: 476-487, ISSN: 1942-0862
Host cell proteins (HCPs) are endogenous impurities, and their proteolytic and binding properties can compromise the integrity, and, hence, the stability and efficacy of recombinant therapeutic proteins such as monoclonal antibodies (mAbs). Nonetheless, purification of mAbs currently presents a challenge because they often co-elute with certain HCP species during the capture step of protein A affinity chromatography. A Quality-by-Design (QbD) strategy to overcome this challenge involves identifying residual HCPs and tracing their source to the harvested cell culture fluid (HCCF) and the corresponding cell culture operating parameters. Then, problematic HCPs in HCCF may be reduced by cell engineering or culture process optimization. Here, we present experimental results linking cell culture temperature and post-protein A residual HCP profile. We had previously reported that Chinese hamster ovary cell cultures conducted at standard physiological temperature and with a shift to mild hypothermia on day 5 produced HCCF of comparable product titer and HCP concentration, but with considerably different HCP composition. In this study, we show that differences in HCP variety at harvest cascaded to downstream purification where different residual HCPs were present in the two sets of samples post-protein A purification. To detect low-abundant residual HCPs, we designed a looping liquid chromatography-mass spectrometry experiment with continuous expansion of a preferred, exclude, and targeted peptide list. Mild hypothermic cultures produced 20% more residual HCP species, especially cell membrane proteins, distinct from the control. Critically, we identified that half of the potentially immunogenic residual HCP species were different between the two sets of samples.
Heide C, Ces O, Polizzi K, et al., 2018, Creating cell-free protein synthesis factories, Pharmaceutical Bioprocessing, ISSN: 2048-9145
Alhuthali S, Fadda S, Goey CH, et al., 2017, Multi-stage population balance model to understand the dynamics of fed-batch CHO cell culture, 27th European Symposium on Computer Aided Process Engineering
Sou SN, Ken L, Nayyar K, et al., 2017, Exploring cellular behaviour under transient geneexpression and its impact on mAb productivity and Fc glycosylation, Biotechnology and Bioengineering, Vol: 115, Pages: 512-518, ISSN: 1097-0290
Transient gene expression (TGE) is a methodology employed in bioprocessing for the fast provision of recombinant protein material. Mild hypothermia is often introduced to overcome the low yield typically achieved with TGE and improve specific protein productivity. It is therefore of interest to examine the impact of mild hypothermic temperatures on both the yield and quality of transiently-expressed proteins and the relationship to changes in cellular processes and metabolism. In this study, we focus on the ability of a Chinese hamster ovary cell line to galactosylate a recombinant monoclonal antibody (mAb) product. Through experimentation and flux balance analysis, our results show that TGE in mild hypothermic conditions led to a 76% increase in qP compared to TGE at 36.5°C in our system. This increase is accompanied by increased consumption of nutrients and amino acids, together with increased production of intracellular nucleotide sugar species and higher rates of mAb galactosylation, despite a reduced rate of cell growth. The reduction in biomass accumulation allowed cells to redistribute their energy and resources towards mAb synthesis and Fc-glycosylation. Interestingly, the higher capacity of cells to galactosylate the recombinant product in TGE at 32°C appears not to have been assisted by the upregulation of galactosyltransferases (GalTs), but by the increased expression of N-acetylglucosaminyltransferase II (GnTII) in this cell line, which facilitated the production of bi-antennary glycan structures for further processing.
Goey CH, Tsang J, Bell D, et al., 2017, Cascading effects in bioprocessing – The impact of mild hypothermia on CHO cell behaviour and host cell protein composition, Biotechnology and Bioengineering, Vol: 114, Pages: 2771-2781, ISSN: 1097-0290
A major challenge in downstream purification of monoclonal antibodies (mAb) is the removal of host cell proteins (HCPs). Previous studies have shown that cell culture decisions significantly impact the HCP content at harvest. However, it is currently unclear how process conditions affect physiological changes in the host cell population, and how these changes, in turn, cascade down to change the HCP profile. We examined how temperature downshift (TDS) to mild hypothermia affects key upstream performance indicators, i.e. antibody titre, HCP concentration and HCP species, across the cell culture decline phase and at harvest through the lens of changes in cellular behaviour. Mild hypothermic conditions introduced on day 5 of fed-batch Chinese hamster ovary (CHO) cell bioreactors resulted in a lower cell proliferation rate but larger percentages of healthier cells across the cell culture decline phase compared to bioreactors maintained at standard physiological temperature. Moreover, the onset of apoptosis was less evident in mild hypothermic cultures. Consequently, mild hypothermic cultures took an extra five days to reach an integral viable cell concentration (IVCC) and antibody yield similar to that of the control at standard physiological temperature. When cell viability dropped below 80%, mild hypothermic cell cultures had a reduced variety of HCP species by 36%, including approximately 44% and 27% lower proteases and chaperones, respectively, despite having similar HCP concentration. This study suggests that TDS may be a good strategy to provide cleaner downstream feedstocks by reducing the variety of HCPs and to maintain product integrity by reducing the number of proteases and chaperones.
Cover Legend The cover image, by Lisa Goers et al., is based on the Article Whole-cell Escherichia coli lactate biosensor for monitoring mammalian cell cultures during biopharmaceutical production, DOI: 10.1002/bit.26254.
Cardenas-Fernandez M, Bawn M, Hamley-Bennett C, et al., 2017, An integrated biorefinery concept for conversion of sugar beet pulp into value-added chemicals and pharmaceutical intermediates, Faraday Discussions, Vol: 202, Pages: 415-431, ISSN: 1359-6640
Over 8 million tonnes of sugar beet are grown annually in the UK. Sugar beet pulp (SBP) is the main by-product of sugar beet processing which is currently dried and sold as a low value animal feed. SBP is a rich source of carbohydrates, mainly in the form of cellulose and pectin, including D-glucose (Glu), L-arabinose (Ara) and D-galacturonic acid (GalAc). This work describes the technical feasibility of an integrated biorefinery concept for the fractionation of SBP and conversion of these monosaccharides into value-added products. SBP fractionation is initially carried out by steam explosion under mild conditions to yield soluble pectin and insoluble cellulose fractions. The cellulose is readily hydrolysed by cellulases to release Glu that can then be fermented by a commercial yeast strain to produce bioethanol at a high yield. The pectin fraction can be either fully hydrolysed, using physico-chemical methods, or selectively hydrolysed, using cloned arabinases and galacturonases, to yield Ara-rich and GalAc-rich streams. These monomers can be separated using either Centrifugal Partition Chromatography (CPC) or ultrafiltration into streams suitable for subsequent enzymatic upgrading. Building on our previous experience with transketolase (TK) and transaminase (TAm) enzymes, the conversion of Ara and GalAc into higher value products was explored. In particular the conversion of Ara into L-gluco-heptulose (GluHep), that has potential therapeutic applications in hypoglycaemia and cancer, using a mutant TK is described. Preliminary studies with TAm also suggest GluHep can be selectively aminated to the corresponding chiral aminopolyol. The current work is addressing the upgrading of the remaining SBP monomer, GalAc, and the modelling of the biorefinery concept to enable economic and Life Cycle Analysis (LCA).
Sou SN, Jedrzejewski PM, Lee K, et al., 2017, Model-based investigation of intracellular processes determining antibody Fc-glycosylation under mild hypothermia, Biotechnology and Bioengineering, Vol: 114, Pages: 1570-1582, ISSN: 1097-0290
Despite the positive effects of mild hypothermic conditions on monoclonal antibody (mAb) productivity (qmAb) during mammalian cell culture, the impact of reduced culture temperature on mAb Fc-glycosylation and the mechanism behind changes in the glycan composition is not fully established. The lack of knowledge about the regulation of dynamic intracellular processes under mild hypothermia restricts bioprocess optimisation. To address this issue, a mathematical model that quantitatively describes CHO cell behaviour and metabolism, mAb synthesis and its N-linked glycosylation profiles before and after the induction of mild hypothermia is constructed using two sets of parameters. Results from this study show that the model is capable of representing experimental results well in all of the aspects mentioned above, including the N-linked glycosylation profile of mAb produced under mild hypothermia. Most importantly, comparison between model simulation results for different culture temperatures suggest the reduced rates of nucleotide sugar donor production and galactosyltransferase (GalT) expression to be critical contributing factors that determine the variation in Fc-glycan profiles between physiological and mild hypothermic conditions in stable CHO transfectants. This is then confirmed using experimental measurements of GalT expression levels, thereby closing the loop between the experimental and the computational system. The identification of bottlenecks within CHO cell metabolism under mild hypothermic conditions will aid bioprocess optimisation, e.g., by tailoring feeding stradegies to improve NSD production, or manipulating the expression of specific glycosyltransferases through cell line engineering.
Goers L, Ainsworth C, Goey CH, et al., 2017, Whole-cell Escherichia coli lactate biosensor for monitoring mammalian cell cultures during biopharmaceutical production, Biotechnology and Bioengineering, Vol: 114, Pages: 1290-1300, ISSN: 1097-0290
Many high-value added recombinant proteins, such as therapeutic glycoproteins, are produced using mammalian cell cultures. In order to optimise the productivity of these cultures it is important to monitor cellular metabolism, for example the utilisation of nutrients and the accumulation of metabolic waste products. One metabolic waste product of interest is lactic acid (lactate), overaccumulation of which can decrease cellular growth and protein production. Current methods for the detection of lactate are limited in terms of cost, sensitivity, and robustness. Therefore, we developed a whole-cell Escherichia coli lactate biosensor based on the lldPRD operon and successfully used it to monitor lactate concentration in mammalian cell cultures. Using real samples and analytical validation we demonstrate that our biosensor can be used for absolute quantification of metabolites in complex samples with high accuracy, sensitivity and robustness. Importantly, our whole-cell biosensor was able to detect lactate at concentrations more than two orders of magnitude lower than the industry standard method, making it useful for monitoring lactate concentrations in early phase culture. Given the importance of lactate in a variety of both industrial and clinical contexts we anticipate that our whole-cell biosensor can be used to address a range of interesting biological questions. It also serves as a blueprint for how to capitalise on the wealth of genetic operons for metabolite sensing available in Nature for the development of other whole-cell biosensors.
Klymenko O, Royle K, Polizzi KM, et al., 2016, Designing an Artificial Golgi Reactor to achieve targeted glycosylation of monoclonal antibodies, AICHE Journal, Vol: 62, Pages: 2959-2973, ISSN: 0001-1541
The therapeutic efficacy of monoclonal antibodies (mAbs) is dependent upon their glycosylationpatterns. As the largest group of currently approved biopharmaceuticals, the microheterogeneity inmAb oligosaccharide profiles deriving from mammalian cell production is a challenge to thebiopharmaceutical industry. Disengaging the glycosylation process from the cell may offer significantenhancement of product quality and allow better control and reproducibility in line with the Quality byDesign paradigm. Three potential designs of an Artificial Golgi reactor implementing targeted sequentialglycosylation of mAbs are proposed including a (i) microcapillary film reactor, (ii) packed bed reactorwith non-porous pellets, and (iii) packed bed reactor with porous pellets. Detailed mathematical modelsare developed to predict their performance for a range of design and operational parameters. While allthree reactor designs can achieve desired conversion levels, the choice of a particular one depends onthe required throughput and the associated cost of enzymes and co-substrates.
Jimenez del Val I, Polizzi K, Kontoravdi C, 2016, A theoretical estimate for nucleotide sugar demand towards Chinese Hamster Ovary cellular glycosylation, Scientific Reports, Vol: 6, ISSN: 2045-2322
Glycosylation greatly influences the safety and efficacy of many of the highest-selling recombinant therapeutic proteins (rTPs). In order to define optimal cell culture feeding strategies that control rTP glycosylation, it is necessary to know how nucleotide sugars (NSs) are consumed towards host cell and rTP glycosylation. Here, we present a theoretical framework that integrates the reported glycoproteome of CHO cells, the number of N-linked and O-GalNAc glycosylation sites on individual host cell proteins (HCPs), and the carbohydrate content of CHO glycosphingolipids to estimate the demand of NSs towards CHO cell glycosylation. We have identified the most abundant N-linked and O-GalNAc CHO glycoproteins, obtained the weighted frequency of N-linked and O-GalNAc glycosites across the CHO cell proteome, and have derived stoichiometric coefficients for NS consumption towards CHO cell glycosylation. By combining the obtained stoichiometric coefficients with previously reported data for specific growth and productivity of CHO cells, we observe that the demand of NSs towards glycosylation is significant and, thus, is required to better understand the burden of glycosylation on cellular metabolism. The estimated demand of NSs towards CHO cell glycosylation can be used to rationally design feeding strategies that ensure optimal and consistent rTP glycosylation.
Niu H, Shah N, Kontoravdi C, 2015, Modelling of Amorphous Cellulose Depolymerisation by Cellulases, Parametric Studies and Optimisation, Biochemical Engineering Journal, Vol: 105, Pages: 455-472, ISSN: 1873-295X
Improved understanding of heterogeneous cellulose hydrolysis by cellulases is the basis for optimising enzymatic catalysis-based cellulosic biorefineries. A detailed mechanistic model is developed to describe the dynamic adsorption/desorption and synergistic chain-end scissions of cellulases (endoglucanase, exoglucanase, and β-glucosidase) upon amorphous cellulose. The model can predict evolutions of the chain lengths of insoluble cellulose polymers and production of soluble sugars during hydrolysis. Simultaneously, a modelling framework for uncertainty analysis is built based on a quasi-Monte-Carlo method and global sensitivity analysis, which can systematically identify key parameters, help refine the model and improve its identifiability. The model, initially comprising 27 parameters, is found to be over-parameterized with structural and practical identification problems under usual operating conditions (low enzyme loadings). The parameter estimation problem is therefore mathematically ill posed. The framework allows us, on the one hand, to identify a subset of 13 crucial parameters, of which more accurate confidence intervals are estimated using a given experimental dataset, and, on the other hand, to overcome the identification problems. The model’s predictive capability is checked against an independent set of experimental data. Finally, the optimal composition of cellulases cocktail is obtained by model-based optimisation both for enzymatic hydrolysis and for the process of simultaneous saccharification and fermentation.
Fan Y, Del Val IJ, Muller C, et al., 2015, A multi-pronged investigation into the effect of glucose starvation and culture duration on fed-batch CHO cell culture, BIOTECHNOLOGY AND BIOENGINEERING, Vol: 112, Pages: 2172-2184, ISSN: 0006-3592
Sou SN, Sellick C, Lee K, et al., 2015, How does mild hypothermia affect monoclonal antibody glycosylation?, Biotechnology and Bioengineering, Vol: 112, Pages: 1165-1176, ISSN: 1097-0290
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