A nano ultra-performance liquid chromatography-high resolution mass spectrometry approach for global metabolomic profiling and case study on drug-resistant multiple myeloma.
A nano ultra-performance liquid chromatography-high resolution mass spectrometry approach for global metabolomic profiling and case study on drug-resistant multiple myeloma.
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DOI：
10.1021/ac500476a
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发表时间：
2014-04-01
影响因子：
7.4
通讯作者：
Peng J
中科院分区：
文献类型：
--
作者：
Jones DR;Wu Z;Chauhan D;Anderson KC;Peng J
全球代谢组学依赖于对生物样品中广泛的代谢物的高度可重复和灵敏的检测。在这里，我们报告了优化的代谢组分析纳米流超高效液相色谱耦合高分辨率轨道阱质谱。根据空白进样，基于一式两份的强制检测和额外的噪声过滤，从LC-MS运行中提取了可靠的峰特征。峰面积的运行间变化显示中位数为14%，并评价了模拟比较期间的错误发现率。为了最大限度地提高识别的峰特征的数量，我们系统地表征了样品加载量、梯度长度和MS分辨率的影响。特征的数量最初上升，后来达到一个平台作为样本量的函数，拟合双曲线。较长的梯度改善了独特的功能检测部分时间分辨同量异位素的物种。将MS分辨率提高到120，000也有助于区分近同量异位代谢物，但更高的MS分辨率降低了数据采集速率，并且没有带来任何好处，正如从可能的代谢物的理论模拟中预测的那样。此外，双相LC梯度允许峰特征在洗脱液中均匀分布，产生比线性梯度明显更多的峰特征。使用这个强大的nUPLC-HRMS平台，我们能够在单个60分钟梯度中从2毫克酵母（相当于约5000万个细胞）中一致地分析约6，500种代谢物特征。我们将这种优化的方法应用于药物（硼替佐米）耐药和药物敏感的多发性骨髓瘤细胞的案例研究。总体而言，18%的代谢产物特征与KEGG标识符匹配，从而能够进行途径富集分析。主成分分析和热图数据正确地聚类了同基因表型，突出了数百种癌症耐药性小分子生物标志物的潜力。
Global metabolomics relies on highly reproducible and sensitive detection of a wide range of metabolites in biological samples. Here we report the optimization of metabolome analysis by nanoflow ultra-performance liquid chromatography coupled to high resolution orbitrap mass spectrometry. Reliable peak features were extracted from the LC-MS run based on mandatory detection in duplicates and additional noise filtering according to blank injections. The run-to-run variation in peak area showed a median of 14%, and the false discovery rate during a mock comparison was evaluated. To maximize the number of peak features identified, we systematically characterized the effect of sample loading amount, gradient length, and MS resolution. The number of features initially rose and later reached a plateau as a function of sample amount, fitting a hyperbolic curve. Longer gradients improved unique feature detection in part by time-resolving isobaric species. Increasing the MS resolution up to 120,000 also aided in the differentiation of near isobaric metabolites, but higher MS resolution reduced the data acquisition rate and conferred no benefits, as predicted from a theoretical simulation of possible metabolites. Moreover, a biphasic LC gradient allowed even distribution of peak features across the elution, yielding markedly more peak features than the linear gradient. Using this robust nUPLC-HRMS platform, we were able to consistently analyze ~6,500 metabolite features in a single 60 min gradient from 2 milligram of yeast, equivalent to ~50 million cells. We applied this optimized method in a case study of drug (bortezomib) resistant and drug-sensitive multiple myeloma cells. Overall, 18% of metabolite features were matched to KEGG identifiers enabling pathway enrichment analysis. Principal component analysis and heat map data correctly clustered isogenic phenotypes, highlighting the potential for hundreds of small molecule biomarkers of cancer drug resistance.
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影响因子：
3.7
作者：
Sana TR;Gordon DB;Fischer SM;Tichy SE;Kitagawa N;Lai C;Gosnell WL;Chang SP
通讯作者：
Chang SP
影响因子：
7.4
作者：
Merenbloom, Samuel I.;Glaskin, Rebecca S.;Henson, Zachary B.;Clemmer, David E.
通讯作者：
Clemmer, David E.
影响因子：
--
作者：
Lee, Jennifer S.;Yaffe, Kristine;Lui, Li-Yung;Cauley, Jane;Taylor, Brent;Browner, Warren;Cummings, Steven
通讯作者：
Cummings, Steven
影响因子：
7.4
作者：
Myint, Khin Than;Uehara, Taisuke;Oda, Yoshiya
通讯作者：
Oda, Yoshiya
影响因子：
2.9
作者：
Maeda, Eilki;Kataoka, Masatoshi;Baba, Yoshinobu
通讯作者：
Baba, Yoshinobu