Petros D Mitsikaris, Stefanos Kostas, Ioannis Mourtzinos, Urania Menkissoglu-Spiroudi, Athanasios Papadopoulos, Natasa P Kalogiouri
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引用次数: 0
摘要
简介蔷薇属植物以其独特宜人的香气和色彩而闻名：本研究旨在开发一种新型液相色谱三重四极杆飞行时间串联质谱（LC-QTOF-MS/MS）方法，用于研究大马士革蔷薇和百日红蔷薇不同基因型花瓣的生物活性指纹图谱：方法：采用响应面方法（RSM）的中央复合设计（CCD）对 LC-QTOF-MS/MS 方法进行优化。对该方法进行了验证，并应用了目标、疑似和非目标筛选工作流程。统计分析和化学计量学工具被用来探索罗莎物种的代谢指纹：RSM显示，最佳萃取参数是将11毫克样品与1毫升MeOH:H2 O（70:30, v/v）混合。目标分析证实了 11 种分析物的存在，所有分析物的定量限（LOQ；低至 0.048 ng mg-1）都很低，且回收率足够高（RE：85%-107%）。通过可疑分析，共初步确定了 28 种化合物。通过非目标物分析，建立了稳健的 OPLS-DA 和 HCA 模型，根据样品的种类进行分类，准确率达到 100%：开发了一种新的 LC-QTOF-MS/MS 方法，并将其应用于分析 47 朵属于不同基因型的 R. centifolia 和 R. damascena 花。
Investigation of Rosa species by an optimized LC-QTOF-MS/MS method using targeted and non-targeted screening strategies combined with multivariate chemometrics.
Introduction: Plants of the Rosa genus are renowned for their pronounced and pleasant aroma and colors.
Objective: The aim of this work was to develop a novel liquid chromatographic triple quadrupole time-of-flight tandem mass spectrometric (LC-QTOF-MS/MS) method for the investigation of the bioactive fingerprint of petals of different genotypes belonging to Rosa damascena and Rosa centifolia species.
Methodology: Central composite design (CCD) of response surface methodology (RSM) was used for the optimization of the LC-QTOF-MS/MS method. The method was validated and target, suspect, and non-target screening workflows were applied. Statistical analysis and chemometric tools were utilized to explore the metabolic fingerprint of the Rosa species.
Results: RSM revealed that the optimal extraction parameters involved mixing 11 mg of sample with 1 mL of MeOH:H2O (70:30, v/v). Target analysis confirmed the presence of 11 analytes, all of which demonstrated low limits of quantification (LOQs; as low as 0.048 ng mg-1) and sufficient recoveries (RE: 85%-107%). In total, 28 compounds were tentatively identified through suspect analysis. Non-target analysis enabled the generation of robust OPLS-DA and HCA models that classified the samples according to their species with 100% accuracy.
Conclusions: A novel LC-QTOF-MS/MS method was developed and applied in the analysis of 47 R. centifolia and R. damascena flowers belonging to different genotypes.
期刊介绍：
Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.
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