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A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions

Producción científica: Articlerevisión exhaustiva

64 Citas (Scopus)

Resumen

Background: Stable isotope tracing is a powerful technique for following the fate of individual atoms through metabolic pathways. Measuring isotopic enrichment in metabolites provides quantitative insights into the biosynthetic network and enables flux analysis as a function of external perturbations. NMR and mass spectrometry are the techniques of choice for global profiling of stable isotope labeling patterns in cellular metabolites. However, meaningful biochemical interpretation of the labeling data requires both quantitative analysis and complex modeling. Here, we demonstrate a novel approach that involved acquiring and modeling the timecourses of 13C isotopologue data for UDP-N-acetyl-D-glucosamine (UDP-GlcNAc) synthesized from [U-13C]-glucose in human prostate cancer LnCaP-LN3 cells. UDP-GlcNAc is an activated building block for protein glycosylation, which is an important regulatory mechanism in the development of many prominent human diseases including cancer and diabetes.Results: We utilized a stable isotope resolved metabolomics (SIRM) approach to determine the timecourse of 13C incorporation from [U-13C]-glucose into UDP-GlcNAc in LnCaP-LN3 cells. 13C Positional isotopomers and isotopologues of UDP-GlcNAc were determined by high resolution NMR and Fourier transform-ion cyclotron resonance-mass spectrometry. A novel simulated annealing/genetic algorithm, called 'Genetic Algorithm for Isotopologues in Metabolic Systems' (GAIMS) was developed to find the optimal solutions to a set of simultaneous equations that represent the isotopologue compositions, which is a mixture of isotopomer species. The best model was selected based on information theory. The output comprises the timecourse of the individual labeled species, which was deconvoluted into labeled metabolic units, namely glucose, ribose, acetyl and uracil. The performance of the algorithm was demonstrated by validating the computed fractional 13C enrichment in these subunits against experimental data. The reproducibility and robustness of the deconvolution were verified by replicate experiments, extensive statistical analyses, and cross-validation against NMR data.Conclusions: This computational approach revealed the relative fluxes through the different biosynthetic pathways of UDP-GlcNAc, which comprises simultaneous sequential and parallel reactions, providing new insight into the regulation of UDP-GlcNAc levels and O-linked protein glycosylation. This is the first such analysis of UDP-GlcNAc dynamics, and the approach is generally applicable to other complex metabolites comprising distinct metabolic subunits, where sufficient numbers of isotopologues can be unambiguously resolved and accurately measured.

Idioma originalEnglish
Número de artículo37
PublicaciónBMC Biology
Volumen9
DOI
EstadoPublished - may 31 2011

Nota bibliográfica

Funding Information:
This work was supported in part by National Science Foundation EPSCoR grant numbers EPS-0447479, NIH NCRR 5P20RR018733, 1R01CA118434-01A2 (TWMF), 1RO1CA101199-01 (TWMF), R21CA133668-01 (ANL) from the National Cancer Institute, DOE DE-EM0000197 (HNBM), the Kentucky Challenge for Excellence, the Brown Foundation, and the University of Louisville Cardinal Research Cluster.

Financiación

This work was supported in part by National Science Foundation EPSCoR grant numbers EPS-0447479, NIH NCRR 5P20RR018733, 1R01CA118434-01A2 (TWMF), 1RO1CA101199-01 (TWMF), R21CA133668-01 (ANL) from the National Cancer Institute, DOE DE-EM0000197 (HNBM), the Kentucky Challenge for Excellence, the Brown Foundation, and the University of Louisville Cardinal Research Cluster.

FinanciadoresNúmero del financiador
Kentucky Challenge for Excellence
National Science Foundation/EPSCoREPS-0447479
TWMF1RO1CA101199-01, R21CA133668-01
National Institutes of Health (NIH)NCRR 5P20RR018733, 1R01CA118434-01A2
U.S. Department of Energy EPSCoRDE-EM0000197
National Childhood Cancer Registry – National Cancer InstituteR01CA101199
Brown Foundation
University of Kentucky, University of Louisville

    ODS de las Naciones Unidas

    Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

    1. Good health and well being
      Good health and well being

    ASJC Scopus subject areas

    • Biotechnology
    • Structural Biology
    • Ecology, Evolution, Behavior and Systematics
    • Physiology
    • General Biochemistry, Genetics and Molecular Biology
    • General Agricultural and Biological Sciences
    • Plant Science
    • Developmental Biology
    • Cell Biology

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