A Method Detection Limit for the Analysis of Natural Organic Matter via Fourier Transform Ion Cyclotron Resonance Mass Spectrometry
A Method Detection Limit for the Analysis of Natural Organic Matter via Fourier Transform Ion Cyclotron Resonance Mass Spectrometry
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DOI：
10.1021/ac501946m
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发表时间：
2014-08-19
影响因子：
7.4
通讯作者：
Dittmar, Thorsten
中科院分区：
文献类型：
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作者：
Riedel, Thomas;Dittmar, Thorsten
天然有机物的傅里叶变换离子回旋共振质谱 (FT-ICR-MS) 非常复杂，由数千个峰组成。相应的质荷比 (m/z) 和信号强度由分析物和噪声产生。区分分析物和噪声的最常用方法是固定信噪比，低于该值检测到的峰值被视为噪声。然而，这个过程是有问题的，并且可能产生不明确的结果。例如，随机噪声峰值可能略高于信噪比阈值（假阳性），而低丰度分析物的峰值可能偶尔会低于固定阈值（假阴性）。因此，同一样品的重复测量的累积结果比单次测量包含更多的峰。假阳性和假阴性信号很难区分，这会影响样本重复之间的重现性。为了解决这个问题，我们测试了用于分析天然有机物的方法检测限 (MDL) 的可行性，通过估计噪声的不确定性来识别可以可靠地区分噪声的峰。我们使用 15 T FT-ICR-MS 对来自北太平洋深处的溶解有机物样品进行了 556 次重复分析；每个重复运行都包含 500 次累积的宽带扫描。为了明确识别质谱中的分析物峰，样品还在耗时的高灵敏度设置下运行。生成的数据集用于建立并彻底测试 MDL。新方法在软件帮助下很容易建立，只需要额外分析重复空白（时间增加少），并且可以实现样品制备的所有步骤。特别是当分析时间不允许重复运行时，MDL 的主要优点是可靠地去除假阳性（噪声）峰值和更好的重现性，而丢失低信号强度（假阴性）分析物的风险相对较低。当重复分析可行时，进一步建议去除所有单独检测到的峰，因为这些峰成为噪声峰的可能性最高。我们建议此处提出的检测限应成为 FT-ICR-MS 数据处理中的常规。
Fourier Transform Ion Cyclotron Resonance mass spectra (FT-ICR-MS) of natural organic matter are complex and consist of several thousands of peaks. The corresponding mass to charge ratios (m/z) and signal intensities result from analytes and noise. The most commonly applied way of distinguishing between analyte and noise is a fixed signal-to-noise ratio below which a detected peak is considered noise. However, this procedure is problematic and can yield ambiguous results. For example, random noise peaks can occur slightly above the signal-to-noise threshold (false positives), while peaks of low abundance analytes may occasionally fall below the fixed threshold (false negatives). Thus, cumulative results from repeated measurements of the same sample contain more peaks than a single measurement. False positive and false negative signals are difficult to distinguish, which affects the reproducibility between replicates of a sample. To target this issue, we tested the feasibility of a method detection limit (MDL) for the analysis of natural organic matter to identify peaks that can reliably be distinguished from noise by estimating the uncertainty of the noise. We performed 556 replicate analyses of a dissolved organic matter sample from the deep North Pacific on a 15 T FT-ICR-MS; each of these replicate runs consisted of 500 cumulated broadband scans. To unambiguously identify analyte peaks in the mass spectra, the sample was also run at time-consuming high-sensitivity settings. The resulting data set was used to establish and thoroughly test a MDL. The new method is easy to establish with software help, does only require the additional analysis of replicate blanks (low time increase), and can implement all steps of sample preparation. Especially when analysis time does not allow for replicate runs, major merits of the MDL are reliable removal of false positive (noise) peaks and better reproducibility, while the risk of losing analytes with low signal intensities (false negative) is comparatively low. When replicate analyses are feasible, the removal of all singly detected peaks is further recommended, as these have the highest probability of being noise peaks. We suggest that the here proposed detection limit should become routine in FT-ICR-MS data processing.