Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China; College of Biology and Food Engineering, Chongqing Three Gorges University 404121, China.
Faculty of Food Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China.
J Chromatogr A. 2022 Dec 6;1685:463640. doi: 10.1016/j.chroma.2022.463640. Epub 2022 Nov 7.
Citrus flavonoids are attracting great interest due to their well-known beneficial effects, but many of them have not been characterized. In this work, ultra-high liquid chromatography coupled to high resolution mass spectrometry (UHPLCHRMS) was used for profiling flavonoids in citrus fruit. We proposed a strategy combining mass defect filtering (MDF) and MS/MS-based molecular networking (MMN) to handle complex UHPLC-HRMS data. The proposed strategy was explained and validated in the fruit of Citrus sinensis (L.) Osbeck, and when specific mass and mass defect windows were pre-defined, MDF enable removal of considerable un-related and/or interference MS peaks. In citrus fruit, the number of MS peaks in positive and negative modes were reduced by 70.80% (from 15,113 to 4413) and 55.30% (from 5617 to 2511), respectively, and thus the potential MS features of flavonoids were retained and exposed. After MDF, an MS/MS similarity-based MMN map was constructed to cluster flavonoids with similar chemical structures. MMN facilitated the annotation of 65 unknown citrus flavonoids by using only 21 pre-identified flavonoids as references. The compounds comprised 42 polymethoxylated flavonoids, 17 flavones, 24 flavanones, and 3 flavonols. Eleven of them had not been previously reported in Citrus sinensis (L.) Osbeck to our knowledge. Results of the current work indicated that the combination of MDF and MMN is a useful strategy for removing interference MS peaks and performing the structural annotation of unkonwn compounds in complex samples.
由于其众所周知的有益作用，类黄酮引起了极大的兴趣，但其中许多尚未被描述。在这项工作中，使用超高效液相色谱与高分辨质谱（UHPLC-HRMS）对柑橘类水果中的类黄酮进行了分析。我们提出了一种结合质量亏损过滤（MDF）和基于 MS/MS 的分子网络（MMN）的策略来处理复杂的 UHPLC-HRMS 数据。该策略在柑橘果实中得到了解释和验证，并在预先定义特定质量和质量亏损窗口时，MDF 可以去除大量不相关和/或干扰的 MS 峰。在柑橘果实中，正、负离子模式下的 MS 峰数分别减少了 70.80%（从 15113 个减少到 4413 个）和 55.30%（从 5617 个减少到 2511 个），从而保留和揭示了类黄酮的潜在 MS 特征。经过 MDF 处理后，构建了基于 MS/MS 相似度的 MMN 图谱，以聚类具有相似化学结构的类黄酮。MMN 仅使用 21 种预先鉴定的类黄酮作为参考，就可以注释 65 种未知的柑橘类黄酮。这些化合物包括 42 种多甲氧基黄酮、17 种黄酮、24 种黄烷酮和 3 种黄酮醇。据我们所知，其中 11 种化合物在柑橘（L.）Osbeck 中尚未有报道。目前工作的结果表明，MDF 和 MMN 的结合是一种有用的策略，可以去除干扰的 MS 峰，并对复杂样品中的未知化合物进行结构注释。
