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植物种子蛋白衍生的氨基酸三甲基硅烷化衍生物的 N/N 比化合物分析。

Compound-Specific N/N Analysis of Amino Acid Trimethylsilylated Derivatives from Plant Seed Proteins.

机构信息

Institut de Recherche en Horticulture et Semences, Université d'Angers, INRAe, 42 Rue Georges Morel, 49070 Beaucouzé, France.

Research School of Biology, Australian National University, Canberra, ACT 2601, Australia.

出版信息

Int J Mol Sci. 2022 Apr 28;23(9):4893. doi: 10.3390/ijms23094893.

Abstract

Isotopic analyses of plant samples are now of considerable importance for food certification and plant physiology. In fact, the natural nitrogen isotope composition (δN) is extremely useful to examine metabolic pathways of N nutrition involving isotope fractionations. However, δN analysis of amino acids is not straightforward and involves specific derivatization procedures to yield volatile derivatives that can be analysed by gas chromatography coupled to isotope ratio mass spectrometry (GC-C-IRMS). Derivatizations other than trimethylsilylation are commonly used since they are believed to be more reliable and accurate. Their major drawback is that they are not associated with metabolite databases allowing identification of derivatives and by-products. Here, we revisit the potential of trimethylsilylated derivatives via concurrent analysis of δN and exact mass GC-MS of plant seed protein samples, allowing facile identification of derivatives using a database used for metabolomics. When multiple silylated derivatives of several amino acids are accounted for, there is a good agreement between theoretical and observed N mole fractions, and δN values are satisfactory, with little fractionation during derivatization. Overall, this technique may be suitable for compound-specific δN analysis, with pros and cons.

摘要

对植物样本进行同位素分析在食品认证和植物生理学领域具有重要意义。事实上,天然氮同位素组成(δN)对于研究涉及同位素分馏的氮营养代谢途径非常有用。然而,氨基酸的δN 分析并不简单,需要进行特定的衍生化处理,以生成可通过气相色谱-同位素比质谱联用(GC-C-IRMS)分析的挥发性衍生物。除了三甲基硅烷基化之外,通常使用其他衍生化方法,因为它们被认为更可靠和准确。它们的主要缺点是它们与代谢物数据库不相关,无法识别衍生物和副产物。在这里,我们通过同时分析植物种子蛋白样品的δN 和精确质量 GC-MS,重新审视了三甲基硅烷基化衍生物的潜力,允许使用代谢组学数据库轻松识别衍生物。当考虑到几种氨基酸的多种硅烷基化衍生物时,理论和观察到的 N 摩尔分数之间存在良好的一致性,并且δN 值令人满意,衍生化过程中几乎没有分馏。总的来说,这项技术可能适用于化合物特异性的δN 分析,具有优缺点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d52e/9105707/5ed0dcf388ae/ijms-23-04893-g001.jpg

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