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首页> 外文期刊>Journal of chromatography, A: Including electrophoresis and other separation methods >Plant metabolomics: Resolution and quantification of elusive peaks in liquid chromatography-mass spectrometry profiles of complex plant extracts using multi-way decomposition methods
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Plant metabolomics: Resolution and quantification of elusive peaks in liquid chromatography-mass spectrometry profiles of complex plant extracts using multi-way decomposition methods

机译:植物代谢组学:使用多路分解方法解析和定量分析复杂植物提取物的液相色谱-质谱联用图中的峰

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Previous studies on LC-MS metabolomic profiling of 127 F2 Barbarea vulgaris plants derived from a cross of parental glabrous (G) and pubescent (P) type, revealed four triterpenoid saponins (hederagenin cellobioside, oleanolic acid cellobioside, epihederagenin cellobioside, and gypsogenin cellobioside) that correlated with resistance of plants against the insect herbivore, Phyllotreta nemorum. In this study, for the first time, we demonstrate the efficiency of the multi-way decomposition method PARAllel FACtor analysis 2 (PARAFAC2) for exploring complex LC-MS data. PARAFAC2 enabled automated resolution and quantification of several elusive chromatographic peaks (e.g. overlapped, elution time shifted and low s ratio), which could not be detected and quantified by conventional chromatographic data analysis. Raw LC-MS data of 127 F2 B. vulgaris plants were arranged in a three-way array (elution time point × mass spectra × samples), divided into 17 different chromatographic intervals and each interval were individually modeled by PARAFAC2. Three main outputs of the PARAFAC2 models described: (1) elution time profile, (2) relative abundance, and (3) pure mass spectra of the resolved peaks modeled from each interval of the chromatographic data. PARAFAC2 scores corresponding to relative abundances of the resolved peaks were extracted and further used for correlation and partial least squares (PLS) analysis. A total of 71 PARAFAC2 components (which correspond to actual peaks, baselines and tails of neighboring peaks) were modeled from 17 different chromatographic retention time intervals of the LC-MS data. In addition to four previously known saponins, correlation- and PLS-analysis resolved five unknown saponin-like compounds that were significantly correlated with insect resistance. The method also enabled a good separation between resistant and susceptible F2 plants. PARAFAC2 spectral loadings corresponding to the pure mass spectra of chromatographic peaks matched well with experimentally recorded mass spectra (correlation based similarity >95%). This enabled to extract pure mass spectra of highly overlapped and low s ratio peaks.
机译:先前对来自亲本无毛(G)和青春期(P)型杂交的127种F2寻常型Barbarrea寻常型植物的LC-MS代谢组学分析的研究揭示了四种三萜皂苷(硬皮生成素纤维二糖苷,齐墩果酸纤维二糖苷,表皮生成素纤维二糖苷和绞股蓝苷)与植物对昆虫食草动物Phyllotreta nemorum的抗性有关。在本研究中,我们首次展示了多路分解方法PARAllel FACtor分析2(PARAFAC2)用于探索复杂LC-MS数据的效率。 PARAFAC2能够自动解析和定量几个难以捉摸的色谱峰(例如,重叠,洗脱时间偏移和低s / n比),而这是常规色谱数据分析无法检测和定量的。将127个F2寻常型B. B.植株的原始LC-MS数据按三向阵列排列(洗脱时间点×质谱×样品),分为17个不同的色谱间隔,每个间隔分别由PARAFAC2建模。 PARAFAC2模型的三个主要输出描述了:(1)洗脱时间曲线,(2)相对丰度,以及(3)从色谱数据的每个间隔建模的解析峰的纯质谱。提取与解析峰的相对丰度相对应的PARAFAC2分数,并将其进一步用于相关性和偏最小二乘(PLS)分析。从LC-MS数据的17个不同色谱保留时间间隔中对总共71种PARAFAC2组分(对应于实际峰,基线和相邻峰的尾部)进行建模。除了四个先前已知的皂苷外,相关性和PLS分析还解析了五个与昆虫抗性显着相关的未知皂苷样化合物。该方法还可以在抗性和易感F2植物之间实现良好的分离。对应于色谱峰纯质谱的PARAFAC2质谱负载与实验记录的质谱非常匹配(基于相关的相似度> 95%)。这使得能够提取高重叠峰和低s / n比峰的纯质谱。

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