A transient isotopic labeling methodology for 13C metabolic flux analysis of photo auto trophic microorganisms

被引:73
|
作者
Shastri, Avantika A. [1 ]
Morgan, John A. [1 ]
机构
[1] Purdue Univ, Sch Chem Engn, W Lafayette, IN 47907 USA
关键词
synechocystis sp PCC 6803; transient C-13-MFA; photosynthesis; modeling; calvin cycle; instationary C-13-MFA; NUCLEAR-MAGNETIC-RESONANCE; CHROMATOGRAPHY-MASS SPECTROMETRY; BIDIRECTIONAL REACTION STEPS; FED-BATCH CULTIVATION; IN-VIVO KINETICS; ESCHERICHIA-COLI; INTRACELLULAR METABOLITES; ELECTROSPRAY-IONIZATION; C-13-LABELED GLUCOSE; SAMPLING TECHNIQUE;
D O I
10.1016/j.phytochem.2007.03.042
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Metabolic flux analysis is increasingly recognized as an integral component of systems biology. However, techniques for experimental measurement of system-wide metabolic fluxes in purely photoautotrophic systems (growing on CO2 as the sole carbon source) have not yet been developed due to the unique problems posed by such systems. In this paper, we demonstrate that an approach that balances positional isotopic distributions transiently is the only route to obtaining system-wide metabolic flux maps for purely autotrophic metabolism. The outlined transient C-13-MFA methodology enables measurement of fluxes at a metabolic steady-state, while following changes in C-13-labeling patterns of metabolic intermediates as a function of time, in response to a step-change in C-13-label input. We use mathematical modeling of the transient isotopic labeling patterns of central intermediates to assess various experimental requirements for photoautotrophic MFA. This includes the need for intracellular metabolite concentration measurements and isotopic labeling measurements as a function of time. We also discuss photobioreactor design and operation in order to measure fluxes under precise environmental conditions. The transient MFA technique can be used to measure and compare fluxes under different conditions of light intensity, nitrogen sources or compare strains with various mutations or gene deletions and additions. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2302 / 2312
页数:11
相关论文
共 50 条
  • [21] A guide to 13C metabolic flux analysis for the cancer biologist
    Antoniewicz, Maciek R.
    EXPERIMENTAL AND MOLECULAR MEDICINE, 2018, 50 : 1 - 13
  • [22] 13C metabolic flux analysis of recombinant expression hosts
    Young, Jamey D.
    CURRENT OPINION IN BIOTECHNOLOGY, 2014, 30 : 238 - 245
  • [23] A scientific workflow framework for 13C metabolic flux analysis
    Dalman, Tolga
    Wiechert, Wolfgang
    Noeh, Katharina
    JOURNAL OF BIOTECHNOLOGY, 2016, 232 : 12 - 24
  • [24] 13C Metabolic flux analysis at the genome-scale
    Gopalakrishnan, Saratram
    Maranas, Costas
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2015, 249
  • [25] A guide to 13C metabolic flux analysis for the cancer biologist
    Maciek R. Antoniewicz
    Experimental & Molecular Medicine, 2018, 50 : 1 - 13
  • [26] High-resolution 13C metabolic flux analysis
    Christopher P. Long
    Maciek R. Antoniewicz
    Nature Protocols, 2019, 14 : 2856 - 2877
  • [27] A 13C isotope labeling method for the measurement of lignin metabolic flux in Arabidopsis stems
    Wang, Peng
    Guo, Longyun
    Jaini, Rohit
    Klempien, Antje
    McCoy, Rachel M.
    Morgan, John A.
    Dudareva, Natalia
    Chapple, Clint
    PLANT METHODS, 2018, 14
  • [28] A 13C isotope labeling method for the measurement of lignin metabolic flux in Arabidopsis stems
    Peng Wang
    Longyun Guo
    Rohit Jaini
    Antje Klempien
    Rachel M. McCoy
    John A. Morgan
    Natalia Dudareva
    Clint Chapple
    Plant Methods, 14
  • [29] p13CMFA: Parsimonious 13C metabolic flux analysis
    Foguet, Carles
    Jayaraman, Anusha
    Marin, Silvia
    Selivanov, Vitaly A.
    Moreno, Pablo
    Messeguer, Ramon
    de Atauri, Pedro
    Cascante, Marta
    PLOS COMPUTATIONAL BIOLOGY, 2019, 15 (09)
  • [30] Synergizing 13C Metabolic Flux Analysis and Metabolic Engineering for Biochemical Production
    Guo, Weihua
    Sheng, Jiayuan
    Feng, Xueyang
    SYNTHETIC BIOLOGY - METABOLIC ENGINEERING, 2018, 162 : 265 - 299