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Inferring Metabolic Flux from Time-Course Metabolomics

  • Scott Campit
  • Sriram ChandrasekaranEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 2088)

Abstract

The metabolic activity of a mammalian cell changes dynamically over time and is tied to the changing metabolic demands of cellular processes such as cell differentiation and proliferation. While experimental tools like time-course metabolomics and flux tracing can measure the dynamics of a few pathways, they are unable to infer fluxes at the whole network level. To address this limitation, we have developed the Dynamic Flux Activity (DFA) algorithm, a genome-scale modeling approach that uses time-course metabolomics to predict dynamic flux rewiring during transitions between metabolic states. This chapter provides a protocol for applying DFA to characterize the dynamic metabolic activity of various cancer cell lines.

Key words

Dynamic flux activity Constraint-based modeling Flux balance analysis Genome-scale metabolic models Time-course metabolomics Cancer metabolism 

Supplementary material

465987_1_En_13_MOESM1_ESM.docx (51 kb)
Data 1 (DOCX 20 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  1. 1.Program in Chemical BiologyUniversity of MichiganAnn ArborUSA
  2. 2.Department of Biomedical EngineeringUniversity of MichiganAnn ArborUSA

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