A comprehensive evaluation of constraining amino acid biosynthesis in compartmented models for metabolic flux analysis

Recent advances in the availability and applicability of genetic tools for non-conventional yeasts have raised high hopes regarding the industrial applications of such yeasts; however, quantitative physiological data on these yeasts, including intracellular flux distributions, are scarce and have rarely aided in the development of novel yeast applications. The compartmentation of eukaryotic cells adds to model complexity. Model constraints are ideally based on biochemical evidence, which is rarely available for non-conventional yeast and eukaryotic cells. A small-scale model for ¹³C-based metabolic flux analysis of central yeast carbon metabolism was developed that is universally valid and does not depend on localization information regarding amino acid anabolism. The variable compartmental origin of traced metabolites is a feature that allows application of the model to yeasts with uncertain genomic and transcriptional backgrounds. The presented test case includes the baker's yeast Saccharomyces cerevisiae and the methylotrophic yeast Hansenula polymorpha. Highly similar flux solutions were computed using either a model with undefined pathway localization or a model with constraints based on curated (S. cerevisiae) or computationally predicted (H. polymorpha) localization information, while false solutions were found with incorrect localization constraints. These results indicate a potentially adverse effect of universally assuming Saccharomyces-like constraints on amino acid biosynthesis for non-conventional yeasts and verify the validity of neglecting compartmentation constraints using a small-scale metabolic model. The model was specifically designed to investigate the intracellular metabolism of wild-type yeasts under various growth conditions but is also expected to be useful for computing fluxes of other eukaryotic cells.

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Compartmentation influences computed intracellular fluxes.

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Improper localization constraints potentially produce false flux solutions.

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Minimal compartmentation constraints result in high-quality flux computations.

What can mathematical modelling say about CHO metabolism and protein glycosylation?

Chinese hamster ovary cells have been in the spotlight for process optimization in recent years, due to being the major, long established cell factory for the production of recombinant proteins. A deep, quantitative understanding of CHO metabolism and mechanisms involved in protein glycosylation has proven to be attainable through the development of high throughput technologies. Here we review the most notable accomplishments in the field of modelling CHO metabolism and protein glycosylation.

Dynamic metabolic flux analysis using B-splines to study the effects of temperature shift on CHO cell metabolism

Metabolic flux analysis (MFA) is widely used to estimate intracellular fluxes. Conventional MFA, however, is limited to continuous cultures and the mid-exponential growth phase of batch cultures. Dynamic MFA (DMFA) has emerged to characterize time-resolved metabolic fluxes for the entire culture period. Here, the linear DMFA approach was extended using B-spline fitting (B-DMFA) to estimate mass balanced fluxes. Smoother fits were achieved using reduced number of knots and parameters. Additionally, computation time was greatly reduced using a new heuristic algorithm for knot placement. B-DMFA revealed that Chinese hamster ovary cells shifted from 37 °C to 32 °C maintained a constant IgG volume-specific productivity, whereas the productivity for the controls peaked during mid-exponential growth phase and declined afterward. The observed 42% increase in product titer at 32 °C was explained by a prolonged cell growth with high cell viability, a larger cell volume and a more stable volume-specific productivity.

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New dynamic MFA framework using B-spline (B-DMFA) generates smooth fit.

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B-DMFA performs better than linear DMFA when fitting fast dynamic changes.

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Heuristic algorithm for knot placement dramatically reduced computation time.

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Temperature shifted cultures maintain a constant IgG volume specific productivity.

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CHO cells shifted to 32 °C have a 42% higher IgG titer due to larger cell volume.

ER calcium release promotes mitochondrial dysfunction and hepatic cell lipotoxicity in response to palmitate overload

Palmitate overload induces hepatic cell dysfunction characterized by enhanced apoptosis and altered citric acid cycle (CAC) metabolism; however, the mechanism of how this occurs is incompletely understood. We hypothesize that elevated doses of palmitate disrupt intracellular calcium homeostasis resulting in a net flux of calcium from the ER to mitochondria, activating aberrant oxidative metabolism. We treated primary hepatocytes and H4IIEC3 cells with palmitate and calcium chelators to identify the roles of intracellular calcium flux in lipotoxicity. We then applied ¹³C metabolic flux analysis (MFA) to determine the impact of calcium in promoting palmitate-stimulated mitochondrial alterations. Co-treatment with the calcium-specific chelator BAPTA resulted in a suppression of markers for apoptosis and oxygen consumption. Additionally, ¹³C MFA revealed that BAPTA co-treated cells had reduced CAC fluxes compared to cells treated with palmitate alone. Our results demonstrate that palmitate-induced lipoapoptosis is dependent on calcium-stimulated mitochondrial activation, which induces oxidative stress.