ArticleMetabolic engineering communications2015
Dynamic metabolic flux analysis using B-splines to study the effects of temperature shift on CHO cell metabolism.
Article in Metabolic engineering communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 63 citations in OpenAlex.
- Overcoming the limits of traditional rate calculations from sparse concentration data: a probabilistic framework for bioprocess modeling.Bioprocess and biosystems engineering · 2026Article
- Systematic data-driven genome-scale metabolic model reduction for bioprocess modeling: CHO culture case study.NPJ systems biology and applications · 2026Article
- Preparation of Plasma Membrane Vesicles, Lysosomes, Proteoliposomes and Alternative Sample Types for SSM-Based Electrophysiology.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Article
- Optimum blue light exposure: a means to increase cell-specific productivity in Chinese hamster ovary cells.Applied microbiology and biotechnology · 2024Article
- Building blocks needed for mechanistic modeling of bioprocesses: A critical review based on protein production by CHO cells.Metabolic engineering communications · 2024Review
- Sodium acetate increases the productivity of HEK293 cells expressing the ECD-Her1 protein in batch cultures: experimental results and metabolic flux analysis.Frontiers in bioengineering and biotechnology · 2024Article
- Triple Space-Time Yield in Discontinuous Antibody Biomanufacturing by Combination of Synergetic Process Intensification Strategies.Bioengineering (Basel, Switzerland) · 2023Article
- CHOmpact: A reduced metabolic model of Chinese hamster ovary cells with enhanced interpretability.Biotechnology and bioengineering · 2023Article
- Interpreting metabolic complexity via isotope-assisted metabolic flux analysis.Trends in biochemical sciences · 2023Review
- Isotope-Assisted Metabolic Flux Analysis: A Powerful Technique to Gain New Insights into the Human Metabolome in Health and Disease.Metabolites · 2022Review
- Stress-induced increase of monoclonal antibody production in CHO cells.Engineering in life sciences · 2022Article
- Quantitative metabolic fluxes regulated by trans-omic networks.The Biochemical journal · 2022Review
- Metabolic Modelling as a Framework for Metabolomics Data Integration and Analysis.Metabolites · 2020Review
- Dynamic Flux Balance Analysis to Evaluate the Strain Production Performance on Shikimic Acid Production inMetabolites · 2020Article
- DynamiciScience · 2020Article
- Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion.Nature communications · 2020Article
- The era of big data: Genome-scale modelling meets machine learning.Computational and structural biotechnology journal · 2020Review
- Dynamic Modeling of CHO Cell Metabolism Using the Hybrid Cybernetic Approach With a Novel Elementary Mode Analysis Strategy.Frontiers in bioengineering and biotechnology · 2020Article
- Forecasting and control of lactate bifurcation in Chinese hamster ovary cell culture processes.Biotechnology and bioengineering · 2019Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.