期刊
BIOTECHNOLOGY AND BIOENGINEERING
卷 119, 期 7, 页码 1740-1754出版社
WILEY
DOI: 10.1002/bit.28104
关键词
CHO cells; flux balance analysis; media reformulation; metabolic bottlenecks; multivariate statistical analysis; systems biotechnology
资金
- Korea Institute of Energy Technology Evaluation and Planning [20214000000500]
- Korea Innovation Foundation [2021-DD-UP-0369]
- Korea Institute of Energy Technology Evaluation & Planning (KETEP) [20214000000500] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
This study combined partial least square regression (PLS-R) with flux balance analysis to systematically investigate the metabolic bottlenecks of CHO cells under different media conditions. By analyzing metabolite exchanges and metabolic states, the study identified the factors hindering cell growth and productivity, providing nutrient targets for media reformulation.
Chinese hamster ovary (CHO) cells are widely used for producing recombinant proteins. To enhance their productivity and product quality, media reformulation has been a key strategy, albeit with several technical challenges, due to the myriad of complex molecular mechanisms underlying media effects on culture performance. Thus, it is imperative to characterize metabolic bottlenecks under various media conditions systematically. To do so, we combined partial least square regression (PLS-R) with the flux balance analysis of a genome-scale metabolic model to elucidate the physiological states and metabolic behaviors of human alpha-1 antitrypsin producing CHO-DG44 cells grown in one commercial and another two in-house media under development. At the onset, PLS-R was used to identify metabolite exchanges that were correlated to specific growth and productivity. Then, by comparing metabolic states described by resultant flux distributions under two of the media conditions, we found suboptimal level of four nutrients and two metabolic wastes, which plausibly hindered cellular growth and productivity; mechanistically, lactate and ammonia recycling were modulated by glutamine and asparagine metabolisms in the media conditions, and also by hitherto unsuspected folate and choline supplements. Our work demonstrated how multivariate statistical analysis can be synergistically combined with metabolic modeling to uncover the mechanistic elements underlying differing media performance. It thus paved the way for the systematic identification of nutrient targets for medium reformulation to enhance recombinant protein production in CHO cells.
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