Literature DB >> 28029042

Carbon Isotopomer Analysis with Non-Unifom Sampling HSQC NMR for Cell Extract and Live Cell Metabolomics Studies.

Sujin Lee1, He Wen1,2, Yong Jin An1, Jin Wook Cha1,3, Yoon-Joo Ko4, Sven G Hyberts5, Sunghyouk Park1.   

Abstract

Isotopomer analysis using either 13C NMR or LC/GC-MS has been an invaluable tool for studying metabolic activities in a variety of systems. Traditional challenges are, however, that 13C-detected NMR is insensitive despite its high resolution, and that MS-based techniques cannot easily differentiate positional isotopomers. In addition, current 13C NMR or LC/GC-MS has limitations in detecting metabolites in living cells. Here, we describe a non-uniform sampling-based 2D heteronuclear single quantum coherence (NUS HSQC) approach to measure metabolic isotopomers in both cell lysates and living cells. The method provides a high resolution that can resolve multiplet structures in the 13C dimension while retaining the sensitivity of the 1H-indirect detection. The approach was tested in L1210 mouse leukemia cells labeled with 13C acetate by measuring NUS HSQC with 25% sampling density. The results gave a variety of metabolic information such as (1) higher usage of acetate in acetylation pathway than aspartate synthesis, (2) TCA cycle efficiency changes upon the inhibition of mitochondrial oxidative phosphorylation by pharmacological agents, and (3) position-dependent isotopomer patterns in fatty acids in living cells. In addition, we were able to detect fatty acids along with other hydrophilic molecules in one sample of live cells without extraction. Overall, the high sensitivity and resolution along with the application to live cells should make the NUS HSQC approach attractive in studying carbon flux information in metabolic studies.

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Year:  2016        PMID: 28029042     DOI: 10.1021/acs.analchem.6b02107

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  6 in total

1.  Interpolating and extrapolating with hmsIST: seeking a tmax for optimal sensitivity, resolution and frequency accuracy.

Authors:  Sven G Hyberts; Scott A Robson; Gerhard Wagner
Journal:  J Biomol NMR       Date:  2017-03-22       Impact factor: 2.835

2.  Observation of acetyl phosphate formation in mammalian mitochondria using real-time in-organelle NMR metabolomics.

Authors:  Wen Jun Xu; He Wen; Han Sun Kim; Yoon-Joo Ko; Seung-Mo Dong; In-Sun Park; Jong In Yook; Sunghyouk Park
Journal:  Proc Natl Acad Sci U S A       Date:  2018-04-02       Impact factor: 11.205

3.  Systematic Evaluation of Non-Uniform Sampling Parameters in the Targeted Analysis of Urine Metabolites by 1H,1H 2D NMR Spectroscopy.

Authors:  Trixi von Schlippenbach; Peter J Oefner; Wolfram Gronwald
Journal:  Sci Rep       Date:  2018-03-09       Impact factor: 4.379

4.  Exploratory machine-learned theoretical chemical shifts can closely predict metabolic mixture signals.

Authors:  Kengo Ito; Yuka Obuchi; Eisuke Chikayama; Yasuhiro Date; Jun Kikuchi
Journal:  Chem Sci       Date:  2018-09-10       Impact factor: 9.825

5.  A framework for tracer-based metabolism in mammalian cells by NMR.

Authors:  Raquel Saborano; Zuhal Eraslan; Jennie Roberts; Farhat L Khanim; Patricia F Lalor; Michelle A C Reed; Ulrich L Günther
Journal:  Sci Rep       Date:  2019-02-21       Impact factor: 4.379

Review 6.  13C metabolic flux analysis: Classification and characterization from the perspective of mathematical modeling and application in physiological research of neural cell.

Authors:  Birui Tian; Meifeng Chen; Lunxian Liu; Bin Rui; Zhouhui Deng; Zhengdong Zhang; Tie Shen
Journal:  Front Mol Neurosci       Date:  2022-09-08       Impact factor: 6.261

  6 in total

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