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首页> 外文期刊>Metabolites >Fully Automated Trimethylsilyl (TMS) Derivatisation Protocol for Metabolite Profiling by GC-MS
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Fully Automated Trimethylsilyl (TMS) Derivatisation Protocol for Metabolite Profiling by GC-MS

机译：通过GC-MS进行代谢物分析的全自动三甲基甲硅烷基（TMS）衍生协议

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Gas Chromatography-Mass Spectrometry (GC-MS) has long been used for metabolite profiling of a wide range of biological samples. Many derivatisation protocols are already available and among these, trimethylsilyl (TMS) derivatisation is one of the most widely used in metabolomics. However, most TMS methods rely on off-line derivatisation prior to GC-MS analysis. In the case of manual off-line TMS derivatisation, the derivative created is unstable, so reduction in recoveries occurs over time. Thus, derivatisation is carried out in small batches. Here, we present a fully automated TMS derivatisation protocol using robotic autosamplers and we also evaluate a commercial software, Maestro available from Gerstel GmbH. Because of automation, there was no waiting time of derivatised samples on the autosamplers, thus reducing degradation of unstable metabolites. Moreover, this method allowed us to overlap samples and improved throughputs. We compared data obtained from both manual and automated TMS methods performed on three different matrices, including standard mix, wine, and plasma samples. The automated TMS method showed better reproducibility and higher peak intensity for most of the identified metabolites than the manual derivatisation method. We also validated the automated method using 114 quality control plasma samples. Additionally, we showed that this online method was highly reproducible for most of the metabolites detected and identified (RSD < 20) and specifically achieved excellent results for sugars, sugar alcohols, and some organic acids. To the very best of our knowledge, this is the first time that the automated TMS method has been applied to analyse a large number of complex plasma samples. Furthermore, we found that this method was highly applicable for routine metabolite profiling (both targeted and untargeted) in any metabolomics laboratory.
机译：气相色谱-质谱（GC-MS）长期以来一直用于各种生物样品的代谢物分析。许多衍生化方案已经可用，其中，三甲基甲硅烷基（TMS）衍生化是代谢组学中使用最广泛的一种。但是，大多数TMS方法在进行GC-MS分析之前都依赖于离线衍生化。在手动离线TMS衍生化的情况下，生成的衍生品不稳定，因此随着时间的流逝回收率会降低。因此，衍生化以小批量进行。在这里，我们介绍了使用机器人自动进样器的全自动TMS衍生化协议，并且我们还评估了可从Gerstel GmbH获得的商业软件Maestro。由于自动化，自动进样器上没有衍生样品的等待时间，因此减少了不稳定代谢物的降解。而且，这种方法使我们能够重叠样本并提高了通量。我们比较了从手动和自动TMS方法对三种不同基质（包括标准混合物，葡萄酒和血浆样品）执行的数据。对于大多数鉴定出的代谢物，自动化TMS方法显示出比手动衍生方法更好的重现性和更高的峰强度。我们还使用114个质量控制血浆样品验证了该自动化方法。此外，我们表明，这种在线方法对于检测和鉴定的大多数代谢物（RSD <20）具有高度可重复性，特别是对于糖，糖醇和某些有机酸而言，均获得了优异的结果。据我们所知，这是首次将自动TMS方法用于分析大量复杂血浆样品。此外，我们发现该方法非常适用于任何代谢组学实验室中的常规代谢物谱分析（有针对性和无针对性）。

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