MID Max: LC-MS/MS Method for Measuring the Precursor and Product Mass Isotopomer Distributions of Metabolic Intermediates and Cofactors for Metabolic Flux Analysis Applications.

The analytical challenges to acquire accurate isotopic data of intracellular metabolic intermediates for stationary, nonstationary, and dynamic metabolic flux analysis (MFA) are numerous. This work presents MID Max, a novel LC-MS/MS workflow, acquisition, and isotopomer deconvolution method for MFA that takes advantage of additional scan types that maximizes the number of mass isotopomer distributions (MIDs) that can be acquired in a given experiment. The analytical method was found to measure the MIDs of 97 metabolites, corresponding to 74 unique metabolite-fragment pairs (32 precursor spectra and 42 product spectra) with accuracy and precision. The compounds measured included metabolic intermediates in central carbohydrate metabolism and cofactors of peripheral metabolism (e.g., ATP). Using only a subset of the acquired MIDs, the method was found to improve the precision of flux estimations and number of resolved exchange fluxes for wild-type E. coli compared to traditional methods and previously published data sets.

[1]  Wolfgang Wiechert,et al.  Collisional fragmentation of central carbon metabolites in LC‐MS/MS increases precision of 13C metabolic flux analysis , 2012, Biotechnology and bioengineering.

[2]  M. Antoniewicz,et al.  COMPLETE-MFA: complementary parallel labeling experiments technique for metabolic flux analysis. , 2013, Metabolic engineering.

[3]  Nobuyoshi Ishii,et al.  13C‐metabolic flux analysis for batch culture of Escherichia coli and its pyk and pgi gene knockout mutants based on mass isotopomer distribution of intracellular metabolites , 2010, Biotechnology progress.

[4]  Joerg M. Buescher,et al.  Ultrahigh performance liquid chromatography-tandem mass spectrometry method for fast and robust quantification of anionic and aromatic metabolites. , 2010, Analytical chemistry.

[5]  Adam M. Feist,et al.  Tracing compartmentalized NADPH metabolism in the cytosol and mitochondria of mammalian cells. , 2014, Molecular cell.

[6]  Maciek R Antoniewicz,et al.  Tandem mass spectrometry: a novel approach for metabolic flux analysis. , 2011, Metabolic engineering.

[7]  Masaru Tomita,et al.  Direct measurement of isotopomer of intracellular metabolites using capillary electrophoresis time-of-flight mass spectrometry for efficient metabolic flux analysis. , 2007, Journal of chromatography. A.

[8]  Adam M. Feist,et al.  A pH and solvent optimized reverse-phase ion-paring-LC–MS/MS method that leverages multiple scan-types for targeted absolute quantification of intracellular metabolites , 2015, Metabolomics.

[9]  Daniel Amador-Noguez,et al.  Metabolomic analysis via reversed-phase ion-pairing liquid chromatography coupled to a stand alone orbitrap mass spectrometer. , 2010, Analytical chemistry.

[10]  Gregory Stephanopoulos,et al.  Accurate assessment of amino acid mass isotopomer distributions for metabolic flux analysis. , 2007, Analytical chemistry.

[11]  Christopher P. Long,et al.  Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli. , 2015, Metabolic engineering.

[12]  J. Rabinowitz,et al.  Kinetic flux profiling for quantitation of cellular metabolic fluxes , 2008, Nature Protocols.

[13]  C. Wittmann,et al.  Sampling of intracellular metabolites for stationary and non-stationary (13)C metabolic flux analysis in Escherichia coli. , 2014, Analytical biochemistry.

[14]  Nicola Zamboni,et al.  FiatFlux – a software for metabolic flux analysis from 13C-glucose experiments , 2005, BMC Bioinformatics.

[15]  Wenyun Lu,et al.  Separation and quantitation of water soluble cellular metabolites by hydrophilic interaction chromatography-tandem mass spectrometry. , 2006, Journal of chromatography. A.

[16]  Jamey D. Young,et al.  Isotopically nonstationary 13C flux analysis of changes in Arabidopsis thaliana leaf metabolism due to high light acclimation , 2014, Proceedings of the National Academy of Sciences.

[17]  U. Sauer,et al.  Large-scale in vivo flux analysis shows rigidity and suboptimal performance of Bacillus subtilis metabolism , 2005, Nature Genetics.

[18]  Jamey D. Young,et al.  Isotopically nonstationary 13C metabolic flux analysis. , 2013, Methods in molecular biology.

[19]  Tomer Shlomi,et al.  Efficient Modeling of MS/MS Data for Metabolic Flux Analysis , 2015, PloS one.

[20]  Yves Gibon,et al.  GC-EI-TOF-MS analysis of in vivo carbon-partitioning into soluble metabolite pools of higher plants by monitoring isotope dilution after 13CO2 labelling. , 2007, Phytochemistry.

[21]  Adam M. Feist,et al.  Fast Swinnex filtration (FSF): a fast and robust sampling and extraction method suitable for metabolomics analysis of cultures grown in complex media , 2015, Metabolomics.

[22]  Jamey D. Young,et al.  INCA: a computational platform for isotopically non-stationary metabolic flux analysis , 2014, Bioinform..

[23]  U. Sauer,et al.  High-throughput metabolic flux analysis based on gas chromatography-mass spectrometry derived 13C constraints. , 2004, Analytical biochemistry.

[24]  F. Blattner,et al.  In silico design and adaptive evolution of Escherichia coli for production of lactic acid. , 2005, Biotechnology and bioengineering.

[25]  C. Maranas,et al.  Identification of optimal measurement sets for complete flux elucidation in metabolic flux analysis experiments. , 2008, Biotechnology and bioengineering.

[26]  Gregory Stephanopoulos,et al.  Determination of confidence intervals of metabolic fluxes estimated from stable isotope measurements. , 2006, Metabolic engineering.

[27]  Ralf Takors,et al.  Simultaneous determination of multiple intracellular metabolites in glycolysis, pentose phosphate pathway and tricarboxylic acid cycle by liquid chromatography-mass spectrometry. , 2007, Journal of chromatography. A.

[28]  U. Sauer,et al.  13C-based metabolic flux analysis , 2009, Nature Protocols.

[29]  Bernhard O. Palsson,et al.  Predicting outcomes of steady-state 13C isotope tracing experiments using Monte Carlo sampling , 2012, BMC Systems Biology.