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用于C代谢通量分析的串联质谱法:基于EMU框架的方法和算法

Tandem Mass Spectrometry for C Metabolic Flux Analysis: Methods and Algorithms Based on EMU Framework.

作者信息

Choi Jungik, Antoniewicz Maciek R

机构信息

Department of Chemical and Biomolecular Engineering, Metabolic Engineering and Systems Biology Laboratory, University of Delaware, Newark, DE, United States.

出版信息

Front Microbiol. 2019 Jan 24;10:31. doi: 10.3389/fmicb.2019.00031. eCollection 2019.

Abstract

In the past two decades, C metabolic flux analysis (C-MFA) has matured into a powerful and widely used scientific tool in metabolic engineering and systems biology. Traditionally, metabolic fluxes have been determined from measurements of isotopic labeling by means of mass spectrometry (MS) or nuclear magnetic resonance (NMR). In recent years, tandem MS has emerged as a new analytical technique that can provide additional information for high-resolution quantification of metabolic fluxes in complex biological systems. In this paper, we present recent advances in methods and algorithms for incorporating tandem MS measurements into existing C-MFA approaches that are based on the elementary metabolite units (EMU) framework. Specifically, efficient EMU-based algorithms are presented for simulating tandem MS data, tracing isotopic labeling in biochemical network models and for correcting tandem MS data for natural isotope abundances.

摘要

在过去二十年中,碳代谢通量分析(C-MFA)已发展成为代谢工程和系统生物学中一种强大且广泛使用的科学工具。传统上,代谢通量是通过质谱(MS)或核磁共振(NMR)对同位素标记的测量来确定的。近年来,串联质谱已成为一种新的分析技术,它可以为复杂生物系统中代谢通量的高分辨率定量提供额外信息。在本文中,我们介绍了将串联质谱测量纳入基于基本代谢物单元(EMU)框架的现有C-MFA方法的方法和算法的最新进展。具体而言,提出了基于EMU的高效算法,用于模拟串联质谱数据、追踪生化网络模型中的同位素标记以及校正串联质谱数据的天然同位素丰度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8457/6353858/e695180672de/fmicb-10-00031-g001.jpg

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