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Rational design and construction of multi-copy biomanufacturing islands in mammalian cells.

ABSTRACT: Cell line development is a critical step in the establishment of a biopharmaceutical manufacturing process. Current protocols rely on random transgene integration and amplification. Due to considerable variability in transgene integration profiles, this workflow results in laborious screening campaigns before stable producers can be identified. Alternative approaches for transgene dosage increase and integration are therefore highly desirable. In this study, we present a novel strategy for the rapid design, construction, and genomic integration of engineered multiple-copy gene constructs consisting of up to 10 gene expression cassettes. Key to this strategy is the diversification, at the sequence level, of the individual gene cassettes without altering their protein products. We show a computational workflow for coding and regulatory sequence diversification and optimization followed by experimental assembly of up to nine gene copies and a sentinel reporter on a contiguous scaffold. Transient transfections in CHO cells indicates that protein expression increases with the gene copy number on the scaffold. Further, we stably integrate these cassettes into a pre-validated genomic locus. Altogether, our findings point to the feasibility of engineering a fully mapped multi-copy recombinant protein 'production island' in a mammalian cell line with greatly reduced screening effort, improved stability, and predictable product titers.

SUBMITTER: Altamura R

PROVIDER: S-EPMC8754653 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background¹³C-Metabolic flux analysis (¹³C-MFA) is a standard technique to probe cellular metabolism and elucidate in vivo metabolic fluxes. 13C-Tracer selection is an important step in conducting ¹³C-MFA, however, current methods are restricted to trial-and-error approaches, which commonly focus on an arbitrary subset of the tracer design space. To systematically probe the complete tracer design space, especially for complex systems such as mammalian cells, there is a pressing need for new rational approaches to identify optimal tracers.ResultsRecently, we introduced a new framework for optimal ¹³C-tracer design based on elementary metabolite units (EMU) decomposition, in which a measured metabolite is decomposed into a linear combination of so-called EMU basis vectors. In this contribution, we applied the EMU method to a realistic network model of mammalian metabolism with lactate as the measured metabolite. The method was used to select optimal tracers for two free fluxes in the system, the oxidative pentose phosphate pathway (oxPPP) flux and anaplerosis by pyruvate carboxylase (PC). Our approach was based on sensitivity analysis of EMU basis vector coefficients with respect to free fluxes. Through efficient grouping of coefficient sensitivities, simple tracer selection rules were derived for high-resolution quantification of the fluxes in the mammalian network model. The approach resulted in a significant reduction of the number of possible tracers and the feasible tracers were evaluated using numerical simulations. Two optimal, novel tracers were identified that have not been previously considered for ¹³C-MFA of mammalian cells, specifically [2,3,4,5,6-¹³C]glucose for elucidating oxPPP flux and [3,4-¹³C]glucose for elucidating PC flux. We demonstrate that ¹³C-glutamine tracers perform poorly in this system in comparison to the optimal glucose tracers.ConclusionsIn this work, we have demonstrated that optimal tracer design does not need to be a pure simulation-based trial-and-error process; rather, rational insights into tracer design can be gained through the application of the EMU basis vector methodology. Using this approach, rational labeling rules can be established a priori to guide the selection of optimal ¹³C-tracers for high-resolution flux elucidation in complex metabolic network models.

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Rational design and construction of multi-copy biomanufacturing islands in mammalian cells.

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