Dynamic Modeling of CHO Cell Metabolism Using the Hybrid Cybernetic Approach With a Novel Elementary Mode Analysis Strategy

Abstract

Chinese hamster ovary (CHO) cell culture has a major importance on the production of biopharmaceuticals, including recombinant therapeutic proteins such as monoclonal antibodies (MAb). Mathematical modeling of biological systems can successfully assess metabolism complexity while providing logical and systematic methods for relevant genetic target and culture parameter identification toward cell growth and productivity improvements. Most modeling approaches on CHO cells have been performed under stationary constraints, and only a few dynamic models have been presented on simplified reaction sets, due to substantial overparameterization problems. The hybrid cybernetic modeling (HCM) approach has been recently used to describe the dynamic behavior by incorporating regulation between different metabolic states by elementary mode participation control, with sets of equations evaluated by objective functions. However, as metabolic networks evaluated are constructed toward a genomic scale, and cell compartmentalization is considered, identification of the active set becomes more difficult as EM number exponentially grows. Thus, the development of robust approaches for EM active set selection and analysis with smaller computational requirements is required to impulse the use of cybernetic modeling on larger up to genome-scale networks. In this report, a novel elementary mode selection strategy, based on a polar representation of the convex solution space is presented and coupled to a cybernetic approach to model the dynamic physiologic and metabolic behavior of CHO-S cell cultures. The proposed Polar Space Yield Analysis (PSYA) was compared to other reported elementary mode selection approaches derived from Common Metabolic Objective Analysis (CMOA) used in Flux Balance Analysis (FBA), Yield Space Analysis (YSA), and Lumped Yield Space Analysis (LYSA). For this purpose, exponential growth phase dynamic metabolic models were calculated using kinetic rate equations based on previously modeled growth parameters. Finally, complete culture dynamic metabolic flux models were constructed using the HCM approach with selected elementary mode sets. The yield space elementary mode-and Martínez et al.Dynamic Modeling of CHO Cells the polar space elementary mode-hybrid cybernetic models presented the best fits and performances. Also, a flux reaction perturbation prediction approach based on the polar yield solution space resulted useful for metabolic network flux distribution capability analysis and identification of potential genetic modifications targets.

Using MVDA with stoichiometric balances to optimize amino acid concentrations in chemically defined CHO cell culture medium for improved culture performance

“…The increased death rate during the latter half of the culture is attributed to several factors including increased concentration of harmful byproducts such as NH3, increased packed cell volume, and rapid nutrient elimination Pascoe et al, 2007). Death rates as a result, are either calculated quantitatively by measuring differential levels of extracellular LDH accumulation (assuming that LDH expression is constant through time) that is released from lysed cells or theoretically by adjusting the net growth rate by a factor correlating to viability decline (assuming constant decay of dead cells through time) (Martínez et al, 2020;Martins Conde Pdo et al, 2016;Templeton et al, 2017). Although the net growth rate was used in our calculation for theoretical demand, the growth model only predicted important variables up to Day 9 in the culture at which point the viabilities of the cultures were relatively similar suggesting minute differences between gross and net growth rates.…”

Using MVDA with Stoichiometric Balances to Optimize Amino Acid Concentrations in Chemically Defined CHO Cell Culture Medium for Improved Culture Performance

“…The increased death rate during the latter half of the culture is attributed to several factors including increased concentration of harmful byproducts such as NH3, increased packed cell volume, and rapid nutrient elimination (Pan, Dalm, Wijffels, & Martens, 2017b;Pascoe, Arnott, Papoutsakis, Miller, & Andersen, 2007). Death rates as a result, are either calculated quantitatively by measuring differential levels of extracellular LDH accumulation that is released from lysed or apoptotic cells or theoretically by adjusting the net growth rate by a factor correlating to viability decline (Martínez, Bulté, Contreras, Palomares, & Ramírez, 2020;Martins Conde Pdo, Sauter, & Pfau, 2016;Templeton et al, 2017). Although the net growth rate was used in our calculation for theoretical demand, the growth model only predicted important variables up to day 9 in the culture at which point the viabilities of the cultures were relatively similar suggesting minute differences between gross and net growth rates.…”

Controlling microbial co-culture based on substrate pulsing can lead to stability through differential fitness advantages

“…This representative enzyme encompasses all the actual enzymes, co-factors, and other resources necessary for the metabolic reactions regarding a particular substrate consumption and fate [15]. The cybernetic approach has been previously used to February 18, 2022 4/23 address the diauxic behaviour in Kleibsiela oxytoca [16], and more recently to derive full dynamic models into the metabolic fluxes across several microorganisms [17][18][19] and even mammalian cells [17,20]. A full description of the cybernetic approach can be found in Ramkrishna et al reports [15,16,[18][19][20].…”