Isotopically nonstationary metabolic flux analysis (INST-MFA): putting theory into practice

Typically, 13C flux analysis relies on assumptions of both metabolic and isotopic steady state. If metabolism is steady but isotope labeling is not allowed to fully equilibrate, isotopically nonstationary metabolic flux analysis (INST-MFA) can be used to estimate fluxes. This requires solution of di...

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Bibliographic Details
Published in:Current opinion in biotechnology 2018-12, Vol.54, p.80-87
Main Authors: Cheah, Yi Ern, Young, Jamey D
Format: Article
Language:English
Subjects:
Autotrophic Processes
BASIC BIOLOGICAL SCIENCES
Carbon Isotopes - metabolism
Isotope Labeling - methods
Metabolic Flux Analysis - methods
Models, Biological
Software
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Summary:Typically, 13C flux analysis relies on assumptions of both metabolic and isotopic steady state. If metabolism is steady but isotope labeling is not allowed to fully equilibrate, isotopically nonstationary metabolic flux analysis (INST-MFA) can be used to estimate fluxes. This requires solution of differential equations that describe the time-dependent labeling of network metabolites, while iteratively adjusting the flux and pool size parameters to match the transient labeling measurements. INST-MFA holds a number of unique advantages over approaches that rely solely upon steady-state isotope enrichments. First, INST-MFA can be applied to estimate fluxes in autotrophic systems, which consume only single-carbon substrates. Second, INST-MFA is ideally suited to systems that label slowly due to the presence of large intermediate pools or pathway bottlenecks. Finally, INST-MFA provides increased measurement sensitivity to estimate reversible exchange fluxes and metabolite pool sizes, which represents a potential framework for integrating metabolomic analysis with 13C flux analysis. This review highlights the unique capabilities of INST-MFA, describes newly available software tools that automate INST-MFA calculations, presents several practical examples of recent INST-MFA applications, and discusses the technical challenges that lie ahead.
ISSN:0958-1669
1879-0429
DOI:10.1016/j.copbio.2018.02.013