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Authors: Hunter N. B. Moseley 1 ; Richard M. Higashi 1 ; Teresa W-M. Fan 1 and Andrew N. Lane 2

Affiliations: 1 University of Louisville; Structural Biology Program, JG Brown Cancer Center and University of Louisville, United States ; 2 University of Louisville; Structural Biology Program, JG Brown Cancer Center and University of Louisville; Clinical Translational Research Building, United States

ISBN: 978-989-8425-36-2

Keyword(s): Metabolic modelling, Systems biochemistry, Model optimization, Model selection, Non-steady state, Stable isotope-resolved metabolomics, SIRM, GAIMS, Mass spectrometry, UDP-GlcNAc, UDP-GalNAc.

Related Ontology Subjects/Areas/Topics: Bioinformatics ; Biomedical Engineering ; Model Design and Evaluation ; Systems Biology

Abstract: We have developed a novel metabolic modeling methodology that traces the flow of functional moieties (chemical substructures) through metabolic pathways via the deconvolution of mass isotopologue data of specific metabolites. We have implemented a general simulated annealing/genetic algorithm for parameter optimization called Genetic Algorithm for Isotopologues in Metabolic Systems (GAIMS), with a model selection method developed from the Akaike information criterion. GAIMS is tailored for analysis of ultra-high resolution, high mass-accuracy isotopologue data from Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR-MS) for interpretation of non-steady state stable isotope-resolved metabolomics (SIRM) experiments. We applied GAIMS to a time-course of uridine diphospho-N-acetylglucosamine (UDP-GlcNAc) and uridine diphospho-N-acetylgalactosamine (UDP-GalNAc) isotopologue data obtained from LNCaP-LN3 prostate cancer cells grown in [U-13C]-glucose. The best metabolic model was identified, which revealed the relative contribution of specific metabolic pathways to 13C incorporation from glucose into individual functional moieties of UDP-GlcNAc and UDP-GalNAc. Furthermore, this analysis allows direct comparison of MS isotopologue data with NMR positional isotopomer data for independent experimental cross-verification. (More)

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Paper citation in several formats:
N. B. Moseley, H.; M. Higashi, R.; W-M. Fan, T. and N. Lane, A. (2011). METABOLIC MODELING OF CONVERGING METABOLIC PATHWAYS - Analysis of Non-steady State Stable Isotope-resolve Metabolism of UDP-GlcNAc and UDP-GalNAc.In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2011) ISBN 978-989-8425-36-2, pages 108-115. DOI: 10.5220/0003129401080115

@conference{bioinformatics11,
author={Hunter N. B. Moseley. and Richard M. Higashi. and Teresa W{-}M. Fan. and Andrew N. Lane.},
title={METABOLIC MODELING OF CONVERGING METABOLIC PATHWAYS - Analysis of Non-steady State Stable Isotope-resolve Metabolism of UDP-GlcNAc and UDP-GalNAc},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2011)},
year={2011},
pages={108-115},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003129401080115},
isbn={978-989-8425-36-2},
}

TY - CONF

JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2011)
TI - METABOLIC MODELING OF CONVERGING METABOLIC PATHWAYS - Analysis of Non-steady State Stable Isotope-resolve Metabolism of UDP-GlcNAc and UDP-GalNAc
SN - 978-989-8425-36-2
AU - N. B. Moseley, H.
AU - M. Higashi, R.
AU - W-M. Fan, T.
AU - N. Lane, A.
PY - 2011
SP - 108
EP - 115
DO - 10.5220/0003129401080115

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