Exploring CHO cell stability during prolonged passaging via eXplainable AI driven flux balance analysis

Area of Science:

• Biotechnology
• Cell Biology
• Metabolic Engineering

Background:

• Production stability in Chinese hamster ovary (CHO) cell lines is crucial for therapeutic protein manufacturing but is often compromised during extended cell passaging.
• The underlying mechanisms driving instability and reduced productivity in late-passage CHO cultures remain poorly understood.

Purpose of the Study:

• To mechanistically characterize the phenotypic and metabolic differences between early-passage (EP) and late-passage (LP) CHO cultures.
• To identify key metabolic pathways responsible for the divergence in cell behavior and productivity over extended passaging.

Main Methods:

• Multivariate data analysis (MVDA) of temporal exometabolite profiles.
• Flux balance analysis (FBA) integrated with explainable artificial intelligence (xAI) to interrogate metabolic rewiring.
• Comparison of cell growth, therapeutic protein (IgG) titers, and key metabolite concentrations between EP and LP cultures.

Main Results:

• Late-passage (LP) CHO cultures showed comparable peak viable cell densities but a significant reduction (~35%) in peak IgG titers compared to early-passage (EP) cultures.
• LP cultures exhibited increased accumulation of lactate and ammonia, indicating altered metabolic function.
• MVDA identified the exponential growth phase as the critical window for metabolic divergence between EP and LP cultures.

Conclusions:

• Early-passage (EP) CHO cells prioritize acetyl-CoA for fatty acid biosynthesis to support proliferation.
• Late-passage (LP) CHO cells shift metabolic focus towards oxidative stress mitigation via the trans-sulfuration pathway (cysteine and glutathione synthesis) and heightened TCA cycle activity for energy homeostasis.
• The cysteine-glutathione axis represents a critical metabolic target for improving the long-term stability and productivity of CHO cell cultures.