Characterization of Isotopic Abundance Measurements in High Resolution FT-ICR and Orbitrap Mass Spectra for Improved Confidence of Metabolite Identification
Characterization of Isotopic Abundance Measurements in High Resolution FT-ICR and Orbitrap Mass Spectra for Improved Confidence of Metabolite Identification
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DOI：
10.1021/ac2001803
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发表时间：
2011-05-15
影响因子：
7.4
通讯作者：
Viant, Mark R.
中科院分区：
文献类型：
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作者：
Weber, Ralf J. M.;Southam, Andrew D.;Viant, Mark R.
当前，使用高分辨率直接输注质谱法（HR DIMS）的相对同位素丰度（RIA）测量的准确性和精度有限的信息有限，尚不清楚该信息是否可以使代谢组学中自动化的峰值注释受益。在这里，我们表征了RIA测量值在Thermo LTQ FT Ultra（分辨率为100 000-750 000）和LTQ Orbitrap（R = 100 000）质谱器上的准确性。这首先涉及重新调整Sim-stitching方法（Southam，A。D. Anal。2007，79，4595-4602）的LTQ FT Ultra，该方法实现了CA。与原始方法相比，敏感性提高了3倍，同时保持了0.16 ppm的根平方质量误差。使用这种方法，我们显示了RIA测量值的质量高度取决于信噪比（SNR），而RIA的精度随着较高的SNR的进一步提高，观察到理论和经验计算的碳原子数量之间的负偏移，用于两个质谱仪。增加LTQ FT Ultra的分辨率降低了RIA测量的灵敏度和质量。总体而言，尽管经验计算的碳数量中的误差可能很大（例如10碳碳），但我们证明了RIA测量确实可以改善自动峰注释，从而增加了单个经验公式分配的数量，而与使用精确相比，单个经验公式分配的数量> 3倍弥撒一个人。
Currently there is limited information available on the accuracy and precision of relative isotopic abundance (RIA) measurements using high-resolution direct-infusion mass spectrometry (HR DIMS), and it is unclear if this information can benefit automated peak annotation in metabolomics. Here we characterize the accuracy of RIA measurements on the Thermo LTQ FT Ultra (resolution of 100 000-750 000) and LTQ Orbitrap (R = 100 000) mass spectrometers. This first involved reoptimizing the SIM-stitching method (Southam, A. D. Anal. Chem. 2007, 79, 4595-4602) for the LTQ FT Ultra, which achieved a ca. 3-fold sensitivity increase compared to the original method while maintaining a root-mean-squared mass error of 0.16 ppm. Using this method, we show the quality of RIA measurements is highly dependent on signal-to-noise ratio (SNR), with RIA accuracy increasing with higher SNR Furthermore, a negative offset between the theoretical and empirically calculated numbers of carbon atoms was observed for both mass spectrometers. Increasing the resolution of the LTQ FT Ultra lowered both the sensitivity and the quality of RIA measurements. Overall, although the errors in the empirically calculated number of carbons can be large (e.g., 10 carbons), we demonstrate that RIA measurements do improve automated peak annotation, increasing the number of single empirical formula assignments by >3-fold compared to using accurate mass alone.