Department of Biochemistry and Molecular Biology, The University of Texas Medical Branch, 301 University of Blvd, Galveston, Texas 77555, United States.
Anal Chem. 2020 Nov 3;92(21):14747-14753. doi: 10.1021/acs.analchem.0c03343. Epub 2020 Oct 21.
Metabolic labeling with atom-based heavy isotopes, followed by liquid chromatography coupled with mass spectrometry (LC-MS), has been a powerful technique for studies of proteome and metabolome. In proteomics, the protein turnover of thousands of proteins can be estimated from the gradual incorporation of H or N in the diet. Software tools have been developed to automate the estimation of protein turnover. Traditionally, the turnover has been estimated using the time course of the depletion of the normalized abundance of monoisotopes. While the bioinformatic aspects of peak detection and integration, time course modeling, and uncertainty estimation have progressed, mass isotopomer dynamics during label incorporation has only been modeled from approximate approaches or numerical simulations. We derive closed-form equations that describe the dynamics of mass isotopomers during metabolic labeling with an atom-based stable isotope. The derived equations create an alternative method for estimating label incorporation. They also provide opportunities for estimation of precursor-product relationships in species or systems where they are unknown. The equations are useful in bioinformatic tools for analyzing mass spectral data from metabolic labeling.
基于原子的重同位素的代谢标记,随后进行液相色谱与质谱联用(LC-MS),一直是研究蛋白质组和代谢组的强大技术。在蛋白质组学中,可以根据饮食中 H 或 N 的逐渐掺入来估计数千种蛋白质的蛋白质周转率。已经开发了软件工具来自动估计蛋白质周转率。传统上,通过耗尽单同位素归一化丰度的时间过程来估计周转率。虽然峰检测和积分、时间过程建模和不确定性估计的生物信息学方面已经取得了进展,但在标记掺入过程中的质量同量异位素动力学仅通过近似方法或数值模拟进行建模。我们推导出描述基于原子的稳定同位素代谢标记过程中质量同量异位素动力学的封闭形式方程。推导的方程为估计标记掺入提供了一种替代方法。它们还为在未知的物种或系统中估计前体-产物关系提供了机会。这些方程在用于分析代谢标记的质谱数据的生物信息学工具中很有用。