University of Natural Resources and Life Sciences, Vienna, Department of Agrobiotechnology (IFA-Tulln), Institute of Bioanalytics and Agro-Metabolomics, Konrad-Lorenz-Straße 20, 3430 Tulln, Austria.
Anal Chem. 2022 Mar 1;94(8):3543-3552. doi: 10.1021/acs.analchem.1c04530. Epub 2022 Feb 15.
The use of stable isotopically labeled tracers is a long-proven way of specifically detecting and tracking derived metabolites through a metabolic network of interest. While the recently developed stable isotope-assisted methods and associated, supporting data analysis tools have greatly improved untargeted metabolomics approaches, no software tool is currently available that allows us to automatically and flexibly search liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) chromatograms for user-definable isotopolog patterns expected for the metabolism of labeled tracer substances. Here, we present Custom Pattern Extract (CPExtract), a versatile software tool that allows for the first time the high-throughput search for user-defined isotopolog patterns in LC-HRMS data. The patterns can be specified via a set of rules including the presence or absence of certain isotopologs, their relative intensity ratios as well as chromatographic coelution. Each isotopolog pattern satisfying the respective rules is verified on an MS scan level and also in the chromatographic domain. The CPExtract algorithm allows the use of both labeled tracer compounds in nonlabeled biological samples as well as a reversed tracer approach, employing nonlabeled tracer compounds along with globally labeled biological samples. In a proof-of-concept study, we searched for metabolites specifically arising from the malonate pathway of the filamentous fungi and . 1,2,3-C-malonic acid diethyl ester and native malonic acid monomethyl ester were used as tracers. We were able to reliably detect expected fatty acids and known polyketides. In addition, up to 46 and 270 further, unknown metabolites presumably including novel polyketides were detected in the and culture samples, respectively, all of which exhibited the user-predicted isotopolog patterns originating from the malonate tracer incorporation. The software can be used for every conceivable tracer approach. Furthermore, the rule sets can be easily adapted or extended if necessary. CPExtract is available free of charge for noncommercial use at https://metabolomics-ifa.boku.ac.at/CPExtract.
使用稳定同位素标记示踪剂是一种经过长期验证的方法,可以特异性地检测和跟踪感兴趣的代谢网络中的衍生代谢物。虽然最近开发的稳定同位素辅助方法和相关的支持数据分析工具极大地改进了非靶向代谢组学方法,但目前还没有软件工具可以允许我们自动灵活地在液相色谱-高分辨率质谱联用 (LC-HRMS) 色谱图中搜索用户定义的标记示踪物代谢预期的同位素模式。在这里,我们介绍了 Custom Pattern Extract (CPExtract),这是一种通用软件工具,首次允许在 LC-HRMS 数据中进行用户定义的同位素模式的高通量搜索。可以通过一组规则来指定模式,包括存在或不存在某些同位素模式、它们的相对强度比以及色谱共洗脱。满足各自规则的每个同位素模式都在 MS 扫描水平和色谱域中进行验证。CPExtract 算法允许同时使用非标记生物样品中的标记示踪化合物和反向示踪方法,即使用非标记示踪化合物以及全球标记的生物样品。在概念验证研究中,我们搜索了专门来自丝状真菌[1,2,3]-C-琥珀酸二乙酯和天然琥珀酸单甲酯途径的代谢物。1,2,3-C-琥珀酸二乙酯和天然琥珀酸单甲酯被用作示踪剂。我们能够可靠地检测到预期的脂肪酸和已知的聚酮化合物。此外,在[1,2,3]-C-琥珀酸二乙酯和琥珀酸单甲酯培养物样品中分别检测到 46 和 270 种未知代谢物,这些代谢物可能包括新型聚酮化合物,所有这些代谢物都表现出源自琥珀酸示踪剂掺入的用户预测的同位素模式。该软件可用于任何可以想象的示踪剂方法。此外,如果需要,规则集可以轻松适应或扩展。CPExtract 可在 https://metabolomics-ifa.boku.ac.at/CPExtract 免费用于非商业用途。