Univ. Bordeaux, CNRS, CBMN, UMR 5248, F-33600 Pessac, France.
Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, United States.
Anal Chem. 2021 Dec 14;93(49):16314-16319. doi: 10.1021/acs.analchem.1c03916. Epub 2021 Dec 3.
Besides many other applications, isotopic labeling is commonly used to decipher the metabolism of living biological systems. By giving a stable isotopically labeled compound as a substrate, the biological system will use this labeled nutrient as it would with a regular substrate and incorporate stable heavy atoms into new metabolites. Utilizing mass spectrometry, by comparing heavy atom enriched isotopic profiles and naturally occurring ones, it is possible to identify these metabolites and deduce valuable information about metabolism and biochemical pathways. The coupling of this approach with mass spectrometry imaging (MSI) allows one then to obtain 2D maps of metabolisms used by living specimens. As metabolic networks are convoluted, a global overview of the isotopically labeled data set to detect unexpected metabolites is crucial. Unfortunately, due to the complexity of MSI spectra, such untargeted processing approaches are difficult to decipher. In this technical note, we demonstrate the potential of a variation around the Kendrick analysis concept to detect the incorporation of stable heavy atoms into metabolites. The Kendrick analysis uses as a base unit the difference between the mass of the most abundant isotope and the mass of the corresponding stable isotopic tracer (namely, C and C). The resulting Kendrick plot offers an alternative method to process the MSI data set with a new perspective allowing for the rapid detection of the C-enriched metabolites and separating unrelated compounds. This processing method of MS data could therefore be a useful tool to decipher isotopic labeling and study metabolic networks, especially as it does not require advanced computational capabilities.
除了许多其他应用外,同位素标记通常用于破译活生物系统的代谢。通过给予稳定的同位素标记化合物作为底物,生物系统将像使用常规底物一样使用这种标记的营养物质,并将稳定的重原子掺入新的代谢物中。利用质谱法,通过比较富含重原子的同位素图谱和自然发生的同位素图谱,可以鉴定这些代谢物,并推导出有关代谢和生化途径的有价值信息。将这种方法与质谱成像(MSI)相结合,然后可以获得活标本使用的代谢物的 2D 图谱。由于代谢网络错综复杂,因此需要对同位素标记数据集进行全面概述,以检测意外的代谢物。不幸的是,由于 MSI 光谱的复杂性,这种非靶向处理方法难以解读。在本技术说明中,我们展示了围绕 Kendrick 分析概念的变化来检测稳定重原子掺入代谢物的潜力。Kendrick 分析将最丰富同位素的质量与相应稳定同位素示踪剂(即 C 和 C)的质量之间的差异用作基本单位。所得 Kendrick 图提供了一种替代方法来处理 MSI 数据集,提供了一个新的视角,可以快速检测 C 富集的代谢物并分离无关化合物。因此,这种 MS 数据的处理方法可以成为破译同位素标记和研究代谢网络的有用工具,特别是因为它不需要先进的计算能力。