UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation
UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation
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DOI：
10.1021/ac701807v
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发表时间：
2008-02-01
影响因子：
7.4
通讯作者：
Idle, Jeffrey R.
中科院分区：
文献类型：
--
作者：
Patterson, Andrew D.;Li, Henghong;Idle, Jeffrey R.
全球转录组学和蛋白质组学分析平台对电离辐射（IR）的复杂反应产生了重要的见解。尽管如此，小细胞代谢物浓度变化的方式知之甚少，在响应IR。在这里，代谢组学方法，使用超高效液相色谱法与电喷雾飞行时间质谱法被用来配置文件，随着时间的推移，TK6细胞暴露于IR剂量范围从0.5到8.0戈伊的亲水性代谢组。正离子的多变量数据分析揭示了辐照细胞的剂量和时间依赖性聚类，并确定了水溶性代谢物组的某些成分早在IR后1小时就被显著耗尽。串联质谱法用于确认代谢物身份。许多耗尽的代谢物与氧化应激和DNA修复途径有关。包括还原型谷胱甘肽、腺苷一磷酸、烟酰胺腺嘌呤二核苷酸和精胺。用转化的成纤维细胞系BJ进行了类似的测量，发现鉴定的TK6代谢物的子集在IR剂量辨别中是有效的。GEDI（基因表达动力学检查器）算法，这是基于自组织地图，被用来可视化动态的全球变化TK6代谢组，导致IR。它揭示了剂量依赖性的离子集群共享相同的趋势，在整个辐射剂量的浓度变化。“辐射代谢组学”，代谢组学分析在放射生物学领域的应用，有望增加我们对辐射等应激源的细胞反应的理解。
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. Multivaiiate 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.