Literature DB >> 29522915

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

Yi Ern Cheah1, Jamey D Young2.   

Abstract

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.
Copyright © 2018 Elsevier Ltd. All rights reserved.

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Year:  2018        PMID: 29522915     DOI: 10.1016/j.copbio.2018.02.013

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  13 in total

1.  Isotopically nonstationary 13C metabolic flux analysis in resting and activated human platelets.

Authors:  Cara L Sake; Alexander J Metcalf; Michelle Meagher; Jorge Di Paola; Keith B Neeves; Nanette R Boyle
Journal:  Metab Eng       Date:  2021-12-22       Impact factor: 9.783

Review 2.  Integrative metabolic flux analysis reveals an indispensable dimension of phenotypes.

Authors:  Richard C Law; Aliya Lakhani; Samantha O'Keeffe; Sevcan Erşan; Junyoung O Park
Journal:  Curr Opin Biotechnol       Date:  2022-03-09       Impact factor: 10.279

3.  The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis.

Authors:  Martin Beyß; Salah Azzouzi; Michael Weitzel; Wolfgang Wiechert; Katharina Nöh
Journal:  Front Microbiol       Date:  2019-05-24       Impact factor: 5.640

Review 4.  Metabolic Modelling as a Framework for Metabolomics Data Integration and Analysis.

Authors:  Svetlana Volkova; Marta R A Matos; Matthias Mattanovich; Igor Marín de Mas
Journal:  Metabolites       Date:  2020-07-24

5.  Whither metabolic flux analysis in plants?

Authors:  Nicholas J Kruger; R George Ratcliffe
Journal:  J Exp Bot       Date:  2021-12-04       Impact factor: 6.992

6.  Systematic identification and elimination of flux bottlenecks in the aldehyde production pathway of Synechococcus elongatus PCC 7942.

Authors:  Yi Ern Cheah; Yao Xu; Sarah A Sacco; Piyoosh K Babele; Amy O Zheng; Carl Hirschie Johnson; Jamey D Young
Journal:  Metab Eng       Date:  2020-03-25       Impact factor: 9.783

Review 7.  Photorespiration: The Futile Cycle?

Authors:  Xiaoxiao Shi; Arnold Bloom
Journal:  Plants (Basel)       Date:  2021-05-01

Review 8.  Metabolic flux analysis of secondary metabolism in plants.

Authors:  Meng-Ling Shih; John A Morgan
Journal:  Metab Eng Commun       Date:  2020-02-01

9.  ScalaFlux: A scalable approach to quantify fluxes in metabolic subnetworks.

Authors:  Pierre Millard; Uwe Schmitt; Patrick Kiefer; Julia A Vorholt; Stéphanie Heux; Jean-Charles Portais
Journal:  PLoS Comput Biol       Date:  2020-04-14       Impact factor: 4.475

10.  Isotope-assisted metabolic flux analysis as an equality-constrained nonlinear program for improved scalability and robustness.

Authors:  Daniel J Lugar; Ganesh Sriram
Journal:  PLoS Comput Biol       Date:  2022-03-24       Impact factor: 4.475

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