Biokinetics Modelling of Lycopene-Producing E. coli Fermentation using PAT Methodology

Biokinetics Modelling of Lycopene-Producing E. coli Fermentation using PAT Methodology

Biochemical Engineering Journal

10.1016/j.bej.2024.109375

http://dx.doi.org/10.1016/j.bej.2024.109375

Vivek Vasudevan, Nur Eka Fitriani, Dennis Leung, Chew Wee

biokinetics modelling, differential algebraic equations, Escherichia coli, Engineered Escherichia Coli, escherichia coli metabolism, process analytical technology, PAT, in-line monitoring, lycopene

02 June 2024

Vasudevan, V., Fitriani, N. F., Leung, D., & Wee, C. (2024). Biokinetics Modelling of Lycopene-Producing E. coli Fermentation using PAT Methodology. Biochemical Engineering Journal, 109375. https://doi.org/10.1016/j.bej.2024.109375

Process analytical technology (PAT), which espouses the use of in-line analytics to monitor critical process parameters (CPPs), critical quality attributes (CQAs) and mathematical analyses, was employed to elucidate underlying carbon-source metabolism of a lycopene-producing E. coli strain during non-induced and induced batch fermentations. In-line dielectric and Raman spectroscopies were deployed to monitor real-time culture biomass viability (X), primary substrate glucose (S), and intracellular lycopene production (P), together with off-line HPLC quantification of broth acetate (A). In-line PAT monitoring enabled identification of two distinct metabolic regimes during induced batch run with lycopene accumulation. Biokinetics mathematical models using differential-algebraic equations and Monod-type conversions were formulated to explain experimentally measured dynamic trends of the state variables X, S, A and P during the batch runs. Their optimized model parameters and seven dimensionless ratios reflected changes in concentrations or rates relative to glucose, acetate, or lycopene. The calculated rates of culture growth, glucose utilization, acetate accumulation, and lycopene production revealed salient underlying carbon metabolic shifts and transient trends that explained phenomenological observations: such as growth patterns, carbon source usage, overflow mechanism, cellular affinity or inhibitory effects, and lycopene cytotoxicity. These parameters and dimensionless ratios could be used to compare novel strains, develop in silico simulations for scale-up or troubleshoot batch-to-batch variations.

Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

This research / project is supported by the Agency for Science, Technology and Research - IAF-PP: BioTrans Phase 3
Grant Reference no. : H20H6a0028

https://oar.a-star.edu.sg/communities-collections/articles/20126

1369-703X

Singapore Institute of Food and Biotechnology Innovation