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In the past two decades, 13C metabolic flux analysis (13C-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 mass spectrometry 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 methods paper, we present recent advances in algorithms for incorporating tandem MS measurements into existing 13C-MFA approaches that are based on the elementary metabolite units (EMU). Specifically, EMU-based algorithms are presented for simulating tandem MS data in biochemical network models and for correcting tandem MS data for natural isotope abundances.
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Choi et al. (2019) studied this question.
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