Bean Heather D, Hill Jane E, Dimandja Jean-Marie D
Dartmouth College, Thayer School of Engineering, Hanover, NH, USA.
Spelman College, Department of Chemistry and Biochemistry, Atlanta, GA, USA.
J Chromatogr A. 2015 May 15;1394:111-7. doi: 10.1016/j.chroma.2015.03.001. Epub 2015 Mar 7.
The potential of high-resolution analytical technologies like GC×GC/TOF MS in untargeted metabolomics and biomarker discovery has been limited by the development of fully automated software that can efficiently align and extract information from multiple chromatographic data sets. In this work we report the first investigation on a peak-by-peak basis of the chromatographic factors that impact GC×GC data alignment. A representative set of 16 compounds of different chromatographic characteristics were followed through the alignment of 63 GC×GC chromatograms. We found that varying the mass spectral match parameter had a significant influence on the alignment for poorly-resolved peaks, especially those at the extremes of the detector linear range, and no influence on well-chromatographed peaks. Therefore, optimized chromatography is required for proper GC×GC data alignment. Based on these observations, a workflow is presented for the conservative selection of biomarker candidates from untargeted metabolomics analyses.
像全二维气相色谱/飞行时间质谱（GC×GC/TOF MS）这样的高分辨率分析技术在非靶向代谢组学和生物标志物发现中的潜力，一直受到能够有效对齐并从多个色谱数据集提取信息的全自动软件发展的限制。在这项工作中，我们首次逐峰研究了影响GC×GC数据对齐的色谱因素。通过对63张GC×GC色谱图的对齐，追踪了一组具有不同色谱特征的16种代表性化合物。我们发现，改变质谱匹配参数对分辨率较差的峰的对齐有显著影响，特别是那些在检测器线性范围极值处的峰，而对色谱分离良好的峰没有影响。因此，为了实现正确的GC×GC数据对齐，需要优化色谱条件。基于这些观察结果，提出了一种从非靶向代谢组学分析中保守选择生物标志物候选物的工作流程。
