Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc

Hunter N.B. Moseley; Richard M. Higashi; Teresa W.M. Fan; Andrew N. Lane

Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc

Hunter N.B. Moseley, Richard M. Higashi, Teresa W.M. Fan, Andrew N. Lane

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

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 ultrahigh 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.

Original language	English
Title of host publication	BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms
Pages	108-115
Number of pages	8
State	Published - 2011
Event	International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2011 - Rome, Italy Duration: Jan 26 2011 → Jan 29 2011

Publication series

Name	BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms

Conference

Conference	International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2011
Country/Territory	Italy
City	Rome
Period	1/26/11 → 1/29/11

Keywords

GAIMS
Mass spectrometry
Metabolic modelling
Model optimization
Model selection
Non-steady state
SIRM
Stable isotope-resolved metabolomics
Systems biochemistry
UDP-GalNAc
UDP-GlcNAc

ASJC Scopus subject areas

Information Systems
Applied Mathematics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

Moseley, H. N. B., Higashi, R. M., Fan, T. W. M., & Lane, A. N. (2011). Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc. In BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (pp. 108-115). (BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms).

Moseley, Hunter N.B. ; Higashi, Richard M. ; Fan, Teresa W.M. et al. / Metabolic modeling of converging metabolic pathways : Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc. BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms. 2011. pp. 108-115 (BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms).

@inproceedings{e8d22855a1f24b31817c63737a05a464,

title = "Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc",

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 ultrahigh 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.",

keywords = "GAIMS, Mass spectrometry, Metabolic modelling, Model optimization, Model selection, Non-steady state, SIRM, Stable isotope-resolved metabolomics, Systems biochemistry, UDP-GalNAc, UDP-GlcNAc",

author = "Moseley, {Hunter N.B.} and Higashi, {Richard M.} and Fan, {Teresa W.M.} and Lane, {Andrew N.}",

year = "2011",

language = "English",

isbn = "9789898425362",

series = "BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms",

pages = "108--115",

booktitle = "BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms",

note = "International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2011 ; Conference date: 26-01-2011 Through 29-01-2011",

}

Moseley, HNB , Higashi, RM , Fan, TWM & Lane, AN 2011, Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc. in BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms. BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms, pp. 108-115, International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2011, Rome, Italy, 1/26/11.

Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc. / Moseley, Hunter N.B.; Higashi, Richard M.; Fan, Teresa W.M. et al.
BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms. 2011. p. 108-115 (BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Lane, Andrew N.

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N2 - 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 ultrahigh 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.

AB - 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 ultrahigh 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.

KW - GAIMS

KW - Mass spectrometry

KW - Metabolic modelling

KW - Model optimization

KW - Model selection

KW - Non-steady state

KW - SIRM

KW - Stable isotope-resolved metabolomics

KW - Systems biochemistry

KW - UDP-GalNAc

KW - UDP-GlcNAc

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M3 - Conference contribution

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SN - 9789898425362

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BT - BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms

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Moseley HNB , Higashi RM , Fan TWM , Lane AN. Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc. In BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms. 2011. p. 108-115. (BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms).

Metabolic modeling of converging metabolic pathways: Analysis of non-steady state stable isotope-resolve metabolism of UDP-GlcNAc and UDP-GalNAc

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

UN SDGs

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Cite this