UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation

Andrew D. Patterson, Henghong Li, Gabriel S. Eichler, Kristopher W. Krausz, John N. Weinstein, Albert J. Fornace, Frank J. Gonzalez, Jeffrey R. Idle

Research output: Contribution to journalArticle

115 Citations (Scopus)

Abstract

Global transcriptomic and proteomic profiling platforms have yielded important insights into the complex response to ionizing radiation (IR). Nonetheless, little is known about the ways in which small cellular metabolite concentrations change in response to IR. Here, a metabolomics approach using ultraperformance liquid chromatography coupled with electrospray time-of-flight mass spectrometry was used to profile, over time, the hydrophilic metabolome of TK6 cells exposed to IR doses ranging from 0.5 to 8.0 Gy. Multivariate data analysis of the positive ions revealed dose- and time-dependent clustering of the irradiated cells and identified certain constituents of the water-soluble metabolome as being significantly depleted as early as 1 h after IR. Tandem mass spectrometry was used to confirm metabolite identity. Many of the depleted metabolites are associated with oxidative stress and DNA repair pathways. Included are reduced glutathione, adenosine monophosphate, nicotinamide adenine dinucleotide, and spermine. Similar measurements were performed with a transformed fibroblast cell line, BJ, and it was found that a subset of the identified TK6 metabolites were effective in IR dose discrimination. The GEDI (Gene Expression Dynamics Inspector) algorithm, which is based on self-organizing maps, was used to visualize dynamic global changes in the TK6 metabolome that resulted from IR. It revealed dose-dependent clustering of ions sharing the same trends in concentration change across radiation doses. "Radiation metabolomics," the application of metabolomic analysis to the field of radiobiology, promises to increase our understanding of cellular responses to stressors such as radiation.

Original languageEnglish (US)
Pages (from-to)665-674
Number of pages10
JournalAnalytical chemistry
Volume80
Issue number3
DOIs
StatePublished - Feb 1 2008

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Ionizing radiation
Gene expression
Metabolites
Dosimetry
Mass spectrometry
Cells
Radiation
Oxidative stress
Spermine
Liquid chromatography
Self organizing maps
Adenosine Monophosphate
Fibroblasts
NAD
Glutathione
Metabolomics
Repair
Positive ions
Ions
Water

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry

Cite this

Patterson, Andrew D. ; Li, Henghong ; Eichler, Gabriel S. ; Krausz, Kristopher W. ; Weinstein, John N. ; Fornace, Albert J. ; Gonzalez, Frank J. ; Idle, Jeffrey R. / UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation. In: Analytical chemistry. 2008 ; Vol. 80, No. 3. pp. 665-674.
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UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation. / Patterson, Andrew D.; Li, Henghong; Eichler, Gabriel S.; Krausz, Kristopher W.; Weinstein, John N.; Fornace, Albert J.; Gonzalez, Frank J.; Idle, Jeffrey R.

In: Analytical chemistry, Vol. 80, No. 3, 01.02.2008, p. 665-674.

Research output: Contribution to journalArticle

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