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同位素分布校准质谱法。

Isotopic Distribution Calibration for Mass Spectrometry.

机构信息

Department of Laboratory Medicine and Pathology, Divisions of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, Minnesota 55905, United States.

Laboratory Services, The Royal Children's Hospital Melbourne, Victoria 3052, Australia.

出版信息

Anal Chem. 2021 Sep 21;93(37):12532-12540. doi: 10.1021/acs.analchem.1c01672. Epub 2021 Sep 7.

Abstract

Mass spectrometry (MS) is widely used in science and industry. It allows accurate, specific, sensitive, and reproducible detection and quantification of a huge range of analytes. Across MS applications, quantification by MS has grown most dramatically, with >50 million experiments/year in the USA alone. However, quantification performance varies between instruments, compounds, different samples, and within- and across runs, necessitating normalization with analyte-similar internal standards (IS) and use of IS-corrected multipoint external calibration curves for each analyte, a complicated and resource-intensive approach, which is particularly ill-suited for multi-analyte measurements. We have developed an internal calibration method that utilizes the natural isotope distribution of an IS for a given analyte to provide internal multipoint calibration. Multiple isotope distribution calibrators for different targets in the same sample facilitate multiplex quantification, while the emerging random-access automated MS platforms should also greatly benefit from this approach. Finally, isotope distribution calibration allows mathematical correction for suboptimal experimental conditions. This might also enable quantification of hitherto difficult, or impossible to quantify, targets, if the distribution is adjusted to mimic the analyte. The approach works well for high resolution, accurate mass MS for analytes with at least a modest-sized isotopic envelope. As shown herein, the approach can also be applied to lower molecular weight analytes, but the reduction in calibration points does reduce quantification performance.

摘要

质谱 (MS) 在科学和工业中得到了广泛应用。它允许对大量分析物进行准确、具体、灵敏和可重复的检测和定量。在 MS 的各种应用中,定量 MS 的发展最为显著,仅在美国每年就有超过 5000 万次实验。然而,仪器之间、化合物之间、不同样本之间以及样本内和样本间的定量性能存在差异,因此需要使用与分析物相似的内标 (IS) 进行归一化,并针对每个分析物使用 IS 校正的多点外部校准曲线,这是一种复杂且资源密集型的方法,特别不适合多分析物测量。我们已经开发了一种内部校准方法,该方法利用给定分析物的 IS 的自然同位素分布提供内部多点校准。同一样本中不同目标的多个同位素分布校准器有助于实现多重定量,而新兴的随机访问自动化 MS 平台也应该从这种方法中受益。最后,同位素分布校准允许对不理想的实验条件进行数学校正。如果分布被调整以模拟分析物,则这种方法还可能允许对迄今为止难以定量或无法定量的目标进行定量。该方法适用于具有适度大小同位素包络的高分辨率、精确质量 MS 的分析物。如本文所示,该方法也可应用于低分子量分析物,但校准点的减少确实会降低定量性能。

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