Dynamic Metabolic Flux Analysis (DMFA)

Metabolic flux analysis is a powerful tool for measuring metabolic fluxes in vivo at metabolic homeostatic systems. However, cellular metabolism is generally dynamic, the accurate quantification of non-stationary metabolic fluxes has posed unique computational challenges. In order to evaluate the dynamic evolution of the metabolic fluxes, a new method for dynamic metabolic flux analysis of systems that are not at metabolic steady state has been designed and employed to exactly determined the system. With the aim of helping our clients to gain a comprehensive understanding of the dynamics of metabolism, Creative Proteomics has developed an efficient dynamic metabolic flux analysis framework for modeling central carbon fluxes over time.

Advantages of Our DMFA Services

• Time-series of metabolite concentration data can be used directly to estimate dynamic fluxes
• Flux estimation can be achieved without integrating ODE or iterations
• Characteristic metabolic stages in fermentation data are automatically identified by the algorithm instead of being manually/arbitrarily selected

Figure 1. Dynamic ¹³C Flux Analysis. (Quek, L. E.; et al. 2020)

Our Services

Creative Proteomics has developed a novel metabolic flux analysis platform to provide dynamic metabolic flux analysis (DMFA) service in a competitive fashion. We have developed a ¹³C-DMFA workflow to estimate non-steady-state fluxes from temporal tracer metabolite data.

• Our built-in algorithm is able to model a variety of flux trajectories
• Our well-designed ¹³C-DMFA strategy enables us to compare the speed and magnitude of pathway fluxes and facilitated detailed carbon book-keeping
• We use the available knowledge of the metabolic network and information provided by the time evolution of extracellular component concentrations to determine the bounded intervals for the fluxes
• Creative Proteomics metabolic flux analysis platform supports stable isotope labeling for liquid-mass (LC-MS) analysis for studying dynamic metabolism, in which the dynamics of specific pathways can be studied based on which compounds absorb the relabeled feedstock during biosynthesis

Figure 2. (A) Trajectories of metabolic response and information missed by steady-state measurements; (B) The trajectory of metabolite P enrichment. (Quek, L. E.; et al. 2020)

DMFA Workflow

• DMFA model construction
• Dynamic characteristics analysis, in which objective functions and constraints are carefully designed
• Multi-objective particle swarm optimization

Powerful Quantitative Capabilities

• Rapid mass spectrometry (MS) with high quantitative dynamic range
• Quadrupole time-of-flight mass spectrometry (QTOF) capable of providing advanced metabolomics data
• Highly sensitive and reliable triple quadrupole-wire
• Differential separator mobility mass spectrometry to achieve the separation of multiple dimensions

Figure 3. Overview of the ¹³C-DMFA workflow. (Quek, L. E.; et al. 2020)

Technical Advantages

• Does not require additional constraints or objective functions
• Provides relatively narrow intervals for the intracellular metabolic fluxes
• Our isotope labeling methods enable to capture specific and definitive data, quantifying specific reactions accurately
• Comprehensive and complete data to locate the marker and trace its source
• High-performance quantitative techniques are available for predictive metabolic pathways and global dynamic analysis without compromising data integrity

Features of Our MFA Platform

• Developed based on the most updated knowledge of biology, bioinformatics and software development
• Widely applicable to a wide range of metabolic system
• Professional bioinformatics teams & personalized bioinformatics analysis services.
• Advanced instrument platform
• Integrated quantitative methodologies and comprehensive solutions for metabolomics

Based on high-performance quantitative techniques and advanced equipment, Creative Proteomics has constantly updating our metabolic flux analysis platform and is committed to offering professional, rapid and high-quality services of dynamic metabolic flux analysis (DMFA) at competitive prices for global customers. Our personalized and comprehensive services can satisfy any innovative scientific study demands, please contact our specialists to discuss your specific needs. We are looking forward to cooperating with you!

Reference

1. Quek, L. E.; et al. Dynamic ¹³C Flux Analysis Captures the Reorganization of Adipocyte Glucose Metabolism in Response to Insulin. iScience. 2020. 23(2).