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Metabolic flux analysis using 13C peptide label measurements

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13C metabolic flux analysis (MFA) has become the experimental method of choice to investigate cellular metabolism. MFA has established flux maps of central metabolism for dozens of microbes, cell cultures, and plant seeds. Steady-state MFA utilizes isotopic labeling measurements of amino acids obtained from protein hydrolysates. Whole cell– or tissue–hydrolysates contain no spatial or temporal information. As a result, flux maps that are tissue specific, or occur only during a short developmental stage such as a phase of the cell cycle, have not yet been reported. To unlock the potential for spatial and temporal flux analysis, we investigated peptide mass distributions (PMDs) as an alternative to amino acid label measurements. PMDs are the discrete convolution of the mass distributions of the constituent amino acids. In principle, amino acid mass distributions (AAMDs) should be obtainable through deconvolution, given a sufficient number of PMDs. This work investigated the requirements for the unique deconvolution of PMDs into AAMDs, the influence of peptide sequence length on parameter sensitivity, and how AAMD and flux estimates determined through deconvolution compared to a conventional GC-MS measurement-based approach. Deconvolution of PMDs of the soy storage protein ß-conglycinin only resulted in good AAMD and flux estimates, if fluxes were directly fitted to PMDs. Unconstrained deconvolution resulted in inferior AAMD estimates. PMDs did not include amino acid backbone fragmentation that increases the information content in GC-MS-derived analyses, nonetheless, the resulting flux maps were of comparable quality and enable spatially and temporally resolved flux analysis.
Dominic E. Mandy , Joshua E. Goldford , Hong Yang , Doug K. Allen , Igor G.L. Libourel
Glycine max , amino acids , beta-conglycinin , cell culture , metabolism , peptides , protein hydrolysates , seeds , soybeans , subcellular fractions
The Plant Journal 2014 11 26 v.77
Journal Articles, USDA Authors, Peer-Reviewed
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