Comparative phenotypic analysis of CHO clones and culture media for lactate shift.

We explored the effects of media and clonal variation on the lactate shift which can be considered as one of the desirable features in CHO cell culture. Various culture profiles with the specific growth and antibody production rates under three different media conditions in two CHO producing clones were evaluated by resorting to multivariate statistical analysis. In most cases, glutamine depletion coincided with lactate consumption, suggesting that glutaminolysis rather than glycolysis was the preferred pathway for the pyruvate supply toward lactate production.

Concurrent isotope-assisted metabolic flux analysis and transcriptome profiling reveal responses of poplar cells to altered nitrogen and carbon supply.

Reduced nitrogen is indispensable to plants. However, its limited availability in soil combined with the energetic and environmental impacts of nitrogen fertilizers motivates research into molecular mechanisms toward improving plant nitrogen use efficiency (NUE). We performed a systems-level investigation of this problem by employing multiple 'omics methodologies on cell suspensions of hybrid poplar (Populus tremula × Populus alba).

Mannose metabolism in recombinant CHO cells and its effect on IgG glycosylation.

Understanding the causes of high-mannose (HM) glycosylation of recombinant IgG in CHO cells would facilitate the production of therapeutics. CHO cells grown with mannose as the major carbon source demonstrated a dramatic increase in total HM glycosylation in recombinant IgG, with no effect on cell growth, viability, or titer. Quantitative metabolomics and (13) C flux analysis were used to explore the mechanism for increased HM glycosylation and understand the metabolism of mannose in CHO cells.

Elucidating the role of copper in CHO cell energy metabolism using (13)C metabolic flux analysis.

(13)C-metabolic flux analysis was used to understand copper deficiency-related restructuring of energy metabolism, which leads to excessive lactate production in recombinant protein-producing CHO cells. Stationary-phase labeling experiments with U-(13)C glucose were conducted on CHO cells grown under high and limiting copper in 3 L fed-batch bioreactors. The resultant labeling patterns of soluble metabolites were measured by GC-MS and used to estimate metabolic fluxes in the central carbon metabolism pathways using OpenFlux.

Flux and reflux: metabolite reflux in plant suspension cells and its implications for isotope-assisted metabolic flux analysis.

Isotope-assisted metabolic flux analysis (MFA) is a powerful methodology to quantify intracellular fluxes via isotope labeling experiments (ILEs). In batch cultures, which are often convenient, inexpensive or inevitable especially for eukaryotic systems, MFA is complicated by the presence of the initially present biomass. This unlabeled biomass may either mix with the newly synthesized labeled biomass or reflux into the metabolic network, thus masking the true labeling patterns in the newly synthesized biomass.

Mathematical modeling of isotope labeling experiments for metabolic flux analysis.

Isotope labeling experiments (ILEs) offer a powerful methodology to perform metabolic flux analysis. However, the task of interpreting data from these experiments to evaluate flux values requires significant mathematical modeling skills. Toward this, this chapter provides background information and examples to enable the reader to (1) model metabolic networks, (2) simulate ILEs, and (3) understand the optimization and statistical methods commonly used for flux evaluation.

Nuclear magnetic resonance methods for metabolic fluxomics.

Fluxomics, through its core methodology of metabolic flux analysis (MFA), enables quantification of carbon traffic through cellular biochemical pathways. Isotope labeling experiments aid MFA by providing information on intracellular fluxes, especially through parallel and cyclic pathways. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are two complementary methods to measure abundances of isotopomers generated in these experiments.

Designer labels for plant metabolism: statistical design of isotope labeling experiments for improved quantification of flux in complex plant metabolic networks.

Metabolic fluxes are powerful indicators of cell physiology and can be estimated by isotope-assisted metabolic flux analysis (MFA). The complexity of the compartmented metabolic networks of plants has constrained the application of isotope-assisted MFA to them, principally because of poor identifiability of fluxes from the measured isotope labeling patterns. However, flux identifiability can be significantly improved by a priori design of isotope labeling experiments (ILEs).