Combined multivariate statistical and flux balance analyses uncover media bottlenecks to the growth and productivity of Chinese hamster ovary cell cultures

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. The culture profiles of Chinese hamster ovary (CHO)‐DG44 under one commercial and two in‐house media were compared and their culture performance was systematically evaluated by combining multivariate statistical analysis with flux balance analysis of a genome‐scale metabolic model of CHO cells, thereby uncovering media bottlenecks to the growth and productivity.