Abstract
13C Metabolic Flux Analysis (13C-MFA) involves the quantification of isotopic enrichment in cellular metabolites and fitting the resultant data to the metabolic network model of the organism. Coverage and resolution of the resultant flux map depends on the total number of metabolites and fragments in which 13C enrichment can be quantified accurately. Experimental techniques for tracking 13C enrichment are evolving rapidly and large volumes of data are now routinely generated through the use of Liquid Chromatography coupled with High-Resolution Mass Spectrometry (HR-LC/MS). Therefore, the current manuscript is focused on the challenges in high-throughput analyses of such large datasets. Current 13C-MFA studies often have to rely on the targeted quantification of a small subset of metabolites, thereby leaving a large fraction of the data unexplored. A number of public domain software tools have been reported in recent years for the untargeted quantitation of isotopic enrichment. However, the suitability of their application across diverse datasets has not been investigated. Here, we test the software tools X13CMS, DynaMet, geoRge, and HiResTEC with three diverse datasets. The tools provided a global, untargeted view of 13C enrichment in metabolites in all three datasets and a much-needed automation in data analysis. Some inconsistencies were observed in results obtained from the different tools, which could be partially ascribed to the lack of baseline separation and potential mass conflicts. After removing the false positives manually, isotopic enrichment could be quantified reliably in a large repertoire of metabolites. Of the software tools explored, geoRge and HiResTEC consistently performed well for the untargeted analysis of all datasets tested.
Highlights
Metabolomic studies with stable isotopic tracers have made significant contributions in furthering our understanding of cellular metabolism
We chose to test the software tools, X13CMS (Patti and CMS, 2014), geoRge (Capellades et al, 2016), DynaMet (Kiefer et al, 2015) and HiResTEC (Hoffmann et al, 2018) to quantify 13C enrichment in intracellular metabolites from HR-LC/MS data derived from three independent studies that were diverse in the biological systems, LC methods and MS hardware used (Table S1)
Despite the applicability of these software tools for 13C Metabolic Flux Analysis (13C-MFA), very few cited studies could be found that have implemented them for this purpose
Summary
Metabolomic studies with stable isotopic tracers have made significant contributions in furthering our understanding of cellular metabolism. The knowledge gained through the study of metabolic fluxes is often critical to the comprehensive understanding of the factors governing the phenome of a biological system and for the construction of designer microbes with applications in biotechnology (Wiechert, 2001) (Zamboni and Sauer, 2009) (Young, 2014) (Jawed et al, 2019). The conventional, stationary state 13C-MFA technique involves feeding cultures with isotopically labeled substrate and quantification of the label incorporation in terminal metabolites such as the proteogenic amino acids at isotopic steady state (Alagesan et al, 2013). Non-stationary 13C MFA approach, the dynamics of incorporation of the isotopic label in intermediate metabolites and their fragments need to be monitored (Young et al, 2011) (Hendry et al, 2017) (Prasannan et al, 2019). Quantification of 13C enrichment in a wider array of metabolites and their fragments would facilitate the generation of license (http://creativecommons.org/licenses/by/4.0/)
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