College of Environmental and Chemical Engineering, Dalian University, Dalian, 116622, China.
Technology Center of China Tobacco Yunnan Industrial Co. Ltd, Kunming, 650231, China.
Anal Bioanal Chem. 2024 Nov;416(26):5639-5654. doi: 10.1007/s00216-024-05478-4. Epub 2024 Aug 21.
The chemical components of natural fragrant plant extracts are of high complexity, and the strategies for quality control (QC) and further discovery of fragrance mechanisms still need to be further investigated. This study integrated the strategies and methods of untargeted metabolomics and chemometrics and statistical modeling to attain the goal. The techniques of reversed-phase and HILIC analysis of ultra-performance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS) were simultaneously used to collect data in both positive and negative ion modes. The pattern analysis of fingerprints and discovery of characteristic molecular markers for QC analysis were comprehensively employed to reach in-depth analysis of the quality variation and discovery of differential molecules among natural fragrant plant extracts. The former uses fingerprint technique to analyze their overall similarities and differences, and the latter comprehensively discovers molecular substances characterizing the chemical characteristics of fragrant extracts with the help of metabolomics and univariate and multivariate methods. The findings are expected to be used as the molecular markers in product manufacturing, sales, and consumption to achieve accurate quality control and recognition of targeted molecules for potential quality monitoring using spectroscopy techniques. In this work, 27 natural fragrant extracts were applied as examples, and their chemical components were comprehensively analyzed with discovery of markers for quality control. After data integration, 1178 molecules were annotated, and 267 differential metabolite molecules with the values of variable importance in the projection (VIP) larger than 1.0 were found. The results show that the method proposed in this work is of great significance for high-coverage analysis, QC marker discovery, and aroma mechanism elucidation, which has potential applications in the areas of food, cosmetics, pharmaceuticals, tobacco, and others.
天然香薰植物提取物的化学成分高度复杂,其质量控制(QC)和香气机制进一步发现的策略仍需进一步研究。本研究整合了非靶向代谢组学和化学计量学及统计建模的策略和方法来实现这一目标。采用反相和亲水作用色谱分析超高效液相色谱-高分辨质谱(UPLC-HRMS)的技术,同时在正离子和负离子模式下收集数据。综合运用指纹图谱分析模式和 QC 分析特征分子标志物的发现,深入分析天然香薰植物提取物的质量变化和差异分子的发现。前者采用指纹技术分析其整体相似性和差异性,后者利用代谢组学和单变量及多变量方法全面发现表征香薰提取物化学特征的分子物质。预期这些发现可作为产品制造、销售和消费过程中的分子标志物,以实现基于光谱技术的精准质量控制和靶向分子的识别,从而达到潜在质量监测的目的。在本工作中,应用 27 种天然香薰提取物作为实例,全面分析其化学成分,并发现用于 QC 的标志物。在数据整合后,注释了 1178 种分子,发现了 267 种具有投影变量重要性(VIP)值大于 1.0 的差异代谢物分子。结果表明,本工作提出的方法对高覆盖率分析、QC 标志物发现和香气机制阐明具有重要意义,在食品、化妆品、制药、烟草等领域具有潜在的应用价值。