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

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

UN SDGs

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

SDG 3 Good Health and Well-being

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

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

TY - GEN

T1 - Metabolic modeling of converging metabolic pathways

T2 - International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2011

AU - Moseley, Hunter N.B.

AU - Higashi, Richard M.

AU - Fan, Teresa W.M.

AU - Lane, Andrew N.

PY - 2011

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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

AN - SCOPUS:79959757798

SN - 9789898425362

T3 - BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms

SP - 108

EP - 115

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

Y2 - 26 January 2011 through 29 January 2011

ER -

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

UN SDGs

Keywords

ASJC Scopus subject areas

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Cite this