Abstract Liquid chromatography-mass spectrometry (LC/MS) is a major technique for the analysis of complex samples. Data processing for LC/MS untargeted analysis is very challenging due to the presence of asymmetric, co-eluted at trace-level peaks. We report a multivariate curve resolution approach based on entropy minimization to resolve LC/MS data. Our liquid chromatography band-target entropy minimization (lc-BTEM) approach enables automated resolution of complex LC/MS peaks without the requirement of any parameter inputs. We demonstrated the performance of our approach on a co-eluted and trace-level peaks in an American ginseng extract. Consequently, we were able to putatively annotate the presence of more than 50 ginsenosides. The extracted pure mass spectra and in-source fragments information further enabled the annotation of [M+H]+, [M+H-Neu]+ and [M-H]- ions. This approach is expected to benefit LC/MS untargeted analysis and data independent analysis of complex samples.

中文翻译：

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使用熵最小化对 LC/MS 数据进行质谱重建

摘要 液相色谱-质谱法 (LC/MS) 是分析复杂样品的主要技术。LC/MS 非靶向分析的数据处理非常具有挑战性，因为存在不对称的、在痕量级共洗脱的峰。我们报告了一种基于熵最小化的多元曲线分辨率方法来解析 LC/MS 数据。我们的液相色谱谱带目标熵最小化 (lc-BTEM) 方法可以自动解析复杂的 LC/MS 峰，而无需任何参数输入。我们在西洋参提取物中的共洗脱峰和痕量峰上展示了我们的方法的性能。因此，我们能够推断出超过 50 种人参皂苷的存在。提取的纯质谱和源内碎片信息进一步启用了[M+H]+的注释，[M+H-Neu]+ 和 [MH]- 离子。这种方法有望有益于复杂样品的 LC/MS 非靶向分析和数据独立分析。