Nordström Anders, O'Maille Grace, Qin Chuan, Siuzdak Gary
Department of Molecular Biology, Scripps Center for Mass Spectrometry, Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA.
Anal Chem. 2006 May 15;78(10):3289-95. doi: 10.1021/ac060245f.
A nonlinear alignment strategy was examined for the quantitative analysis of serum metabolites. Two small-molecule mixtures with a difference in relative concentration of 20-100% for 10 of the compounds were added to human serum. The metabolomics protocol using UPLC and XCMS for LC-MS data alignment could readily identify 8 of 10 spiked differences among more than 2700 features detected. Normalization of data against a single factor obtained through averaging the XCMS integrated response areas of spiked standards increased the number of identified differences. The original data structure was well preserved using XCMS, but reintegration of identified differences in the original data reduced the number of false positives. Using UPLC for separation resulted in 20% more detected components compared to HPLC. The length of the chromatographic separation also proved to be a crucial parameter for a number of detected features. Moreover, UPLC displayed better retention time reproducibility and signal-to-noise ratios for spiked compounds over HPLC, making this technology more suitable for nontargeted metabolomics applications.
研究了一种用于血清代谢物定量分析的非线性比对策略。将两种小分子混合物添加到人体血清中，这两种混合物中10种化合物的相对浓度相差20 - 100%。使用超高效液相色谱（UPLC）和XCMS进行液相色谱 - 质谱（LC - MS）数据比对的代谢组学方案，能够在检测到的2700多个特征中轻松识别出10种加标差异中的8种。通过对加标标准品的XCMS积分响应面积求平均值获得单一因子对数据进行归一化处理，增加了识别出的差异数量。使用XCMS能很好地保留原始数据结构，但对原始数据中识别出的差异进行重新整合减少了假阳性数量。与高效液相色谱（HPLC）相比，使用UPLC进行分离检测到的组分多20%。色谱分离长度也被证明是影响多个检测特征的关键参数。此外，与HPLC相比，UPLC对加标化合物显示出更好的保留时间重现性和信噪比，使得该技术更适合非靶向代谢组学应用。
