Identification of novel inhibitory metabolites and impact verification on growth and protein synthesis in mammalian cells

Abstract

Mammalian cells consume large amount of nutrients during growth and production. However, endogenous metabolic inefficiencies often prevent cells to fully utilize nutrients to support growth and protein production. Instead, significant fraction of fed nutrients is diverted into extracellular accumulation of waste by-products and metabolites, further inhibiting proliferation and protein synthesis. In this study, an LC-MS/MS based metabolomics pipeline was used to screen Chinese hamster ovary (CHO) extracellular metabolites. Six out of eight identified inhibitory metabolites, caused by the inefficient cell metabolism, were not previously studied in CHO cells: aconitic acid, 2-hydroxyisocaproic acid, methylsuccinic acid, cytidine monophosphate, trigonelline, and n-acetyl putrescine. When supplemented back into a fed-batch culture, significant reduction in cellular growth was observed in the presence of each metabolite and all the identified metabolites were shown to impact the glycosylation of a model secreted antibody, with seven of these also reducing CHO cellular productivity (titer) and all eight inhibiting the formation of mono-galactosylated biantennary (G1F) and biantennary galactosylated (G2F) N-glycans. These inhibitory metabolites further impact the metabolism of cells, leading to a significant reduction in CHO cellular growth and specific productivity in fed-batch culture (maximum reductions of 27.2% and 40.6% respectively). In-depth pathway analysis revealed that these metabolites are produced when cells utilize major energy sources such as glucose and select amino acids (tryptophan, arginine, isoleucine, and leucine) for growth, maintenance, and protein production. Furthermore, these novel inhibitory metabolites were observed to accumulate in multiple CHO cell lines (CHO–K1 and CHO-GS) as well as HEK293 cell line. This study provides a robust and holistic methodology to incorporate global metabolomic analysis into cell culture studies for elucidation and structural verification of novel metabolites that participate in key metabolic pathways to growth, production, and post-translational modification in biopharmaceutical production.

Modulation of nutrient precursors for controlling metabolic inhibitors by genome‐scale flux balance analysis

“…Interestingly, negative impact on cell culture performance at two times spiking for group 2 (G2‐2×) was not as significant as three times spiking (G2‐3×, see Figure 5a–c). These findings were consistent with the results from another study which reported that spiking of NAP back into cell culture at millimolar level did not seem to show toxic effect on the growth of cells 7 . It was speculated that the observation as shown here, along with the data previously reported in other studies, suggested that NAP was re‐directed into the arginine metabolism pathway.…”

“…These findings were consistent with the results from another study which reported that spiking of NAP back into cell culture at millimolar level did not seem to show toxic effect on the growth of cells. 7 It was speculated that the observation as shown here, along with the data previously reported in other studies, suggested that NAP was re-directed into the arginine metabolism pathway. Specifically, NAP potentially can be converted back to putrescine which is a substrate from the polyamine At 3Â spiking level, however, the inhibitory effect of NAP on cellular performance was apparent, at cells realized a 16.2% decrease in VCD, 8.7% decrease in total IVCD and 17.6% decrease in peak growth rate (see Figure 5a-c).…”

“…These advances in metabolomics have enabled identification of additional cell generated inhibitory metabolites, other than lactate and ammonia 6 . In our most recent work, it has been shown that untargeted global metabolomics coupled LC–MS/MS can be applied to batch and fed‐batch CHO bioprocess to identify six growth and titer production metabolic inhibitors generated from CHO metabolism 7 …”

“…Generic CHO‐K1 metabolic model was tailored and further integrated with CHO fed‐batch metabolomic data to obtain a cell line‐ and process‐specific model. Metabolic by‐product cytidine monophosphate (CMP), guanosine monophosphate (GMP) and n‐acetylputrescine (NAP), all of which previously reported to generate from endogenous cell metabolism and verified to be toxic to cells, 7,12 were further mapped to a compartmentalized carbon utilization network. Flux balance analysis was conducted at both the genome‐scale level and simplified carbon utilization network level to gain a deeper mechanistic understanding in generation of toxic metabolites and to identify the critical medium components toward cell growth and generation of metabolic by‐products.…”

Debottlenecking and reformulating feed media for improved CHO cell growth and titer by data-driven and model-guided analyses

“…[13,14] In addition, media redesign or optimization benefits by fine-tuning certain media components to eliminate cellular bottleneck impacting the culture performance such as cell growth, viability, productivity, product quality and functionality. [15,16] It is largely affected by the frequent accumulation of inhibitory metabolites or toxic by-products, e.g., lactate and ammonia, due to the inefficient CHO cell metabolism, which can be alleviated by adjusting certain media components as a source of nutrients and growth factors such as amino acids, glucose, vitamins, and trace metals. [17][18][19] To provide an efficient manufacturing environment, each CHO cell culture medium typically contains 50-100 components, which are then tested and balanced with feed media using high-throughput experimental approaches.…”