A multistep approach was taken to investigate the intrinsic kinetics of the cellulase enzyme complex as observed with hydrolysis of noncrystalline cellulose (NCC). In the first stage, published initial rate mechanistic models were built and critically evaluated for their performance in predicting time-course kinetics, using the data obtained from enzymatic hydrolysis experiments performed on two substrates: NCC and alpha-cellulose. In the second stage, assessment of the effect of reaction intermediates and products on intrinsic kinetics of enzymatic hydrolysis was performed using NCC hydrolysis experiments, isolating external factors such as mass transfer effects, physical properties of substrate, etc. In the final stage, a comprehensive intrinsic kinetics mechanism was proposed. From batch experiments using NCC, the time-course data on cellulose, cello-oligosaccharides (COS), cellobiose, and glucose were taken and used to estimate the parameters in the kinetic model. The model predictions of NCC, COS, cellobiose, and glucose profiles show a good agreement with experimental data generated from hydrolysis of different initial compositions of substrate (NCC supplemented with COS, cellobiose, and glucose). Finally, sensitivity analysis was performed on each model parameter; this analysis provides some insights into the yield of glucose in the enzymatic hydrolysis. The proposed intrinsic kinetic model parametrized for dilute cellulose systems forms a basis for modeling the complex enzymatic kinetics of cellulose hydrolysis in the presence of limiting factors offered by substrate and enzyme characteristics.
Conventionally cell cultures are modeled using either structured/unstructured average cell models to capture the intracellular processes or population balance models (PBM) to account for the cell cycle propagation. The former is based on average cell population behavior and cannot describe the heterogeneities within, whereas the latter cannot alone probe into the detailed phenomena of intracellular metabolism. In this work, a multiscale modeling approach is proposed to unify the understanding of intracellular metabolism and the probabilistic nature of intercellular heterogeneities arising because of cell cycle apportioning. As a first step, average culture dynamics are described using an unstructured model encompassing cell growth, cell death, nutrient consumption, metabolite, and protein production and their dependency on various environmental factors. The model parameter identification is performed on the data obtained from the batch Chinese Hamster Ovary (CHO) cell cultures in spinner flasks. Then, a one-dimensional age-based PBM is formulated with three flow-cytometry identifiable cell cycle phases G 1 /G 0 , S, and G 2 /M. The cell metabolism for each cell cycle phase is considered to be different to account for the heterogeneity arising from cell cycle propagation and cycle specific intracellular activities. Simulated annealing is used for PBM specific parameter identification. It is found that the PBM combined with average cell model can explain the CHO cell cultures accurately in different aspects of cell cycle apportioning, culture media concentration dynamics, and protein production.
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