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Evaluation of freely available software tools for untargeted quantification of 13C isotopic enrichment in cellular metabolome from HR-LC/MS data

机译:免费评估可用于从HR-LC / MS数据对细胞代谢组中13C同位素富集进行无目标定量的软件工具的评估

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摘要

C Metabolic Flux Analysis ( C-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 C enrichment can be quantified accurately. Experimental techniques for tracking C 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 C-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 X CMS, DynaMet, geoRge, and HiResTEC with three diverse datasets. The tools provided a global, untargeted view of C 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.
机译:C代谢通量分析(C-MFA)涉及对细胞代谢产物中同位素富集的量化,并将所得数据拟合至生物的代谢网络模型。最终通量图的覆盖范围和分辨率取决于可以准确定量C富集的代谢物和碎片的总数。跟踪C富集的实验技术正在迅速发展,现在通过使用液相色谱结合高分辨率质谱(HR-LC / MS)常规生成大量数据。因此,当前的手稿着重于对此类大型数据集进行高通量分析的挑战。当前的C-MFA研究通常必须依赖于一小部分代谢产物的目标定量,从而使大部分数据无法开发。近年来,已经有许多公共领域的软件工具用于同位素富集的非目标定量。但是,尚未研究其在不同数据集中的适用性。在这里,我们使用三个不同的数据集测试软件工具X CMS,DynaMet,geoRge和HiResTEC。这些工具提供了所有三个数据集中代谢物中C富集的全局,非目标视图,以及数据分析中急需的自动化。从不同工具获得的结果中观察到一些不一致之处,这可能部分归因于缺乏基线分离和潜在的质量冲突。手动消除误报后,可以在大量代谢物中可靠地定量同位素富集。在所探索的软件工具中,george和HiResTEC在针对所有测试数据集的非目标分析中始终表现良好。

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