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用于大神经肽直接灵敏定量液相色谱-轨道阱质谱校准曲线制作的实用方案

Practical Protocol for Making Calibration Curves for Direct and Sensitive Quantitative LC Orbitrap-MS of Large Neuropeptides.

作者信息

Yamagaki Tohru, Yamazaki Takashi

机构信息

Suntory Institute for Bioorganic Research, Suntory Foundation for Life Sciences.

出版信息

Mass Spectrom (Tokyo). 2020;9(1):A0087. doi: 10.5702/massspectrometry.A0087. Epub 2020 Aug 3.

Abstract

Peptides larger than 3-4 kDa, such as neuropeptide Y (NPY), orexin-B, and alpha-MSH, have practical issues that arise when conducting direct and sensitive quantitative liquid chromatography (LC) orbitrap-FT mass spectrometry (MS) due to their adsorption and low ionization efficiency, especially in standard solutions. A mixing solvent consisting of 0.5% trifluoroacetic acid (TFA) and 35-50% aq. acetonitrile was developed as the standard NPY for creating calibration curves, as well as a matrix to block the experimental tube surface to minimize adsorption. The mixture matrix effectively blocked non-specific adsorption of the standard peptides with tryptic digested bovine serum albumin (BSA) (small fragment peptides) and orexin-B (a large chain peptide). A sample containing 1 : 100 peptide:water was detected in the developed sample solution. Finally, 2 to 1,000 fmol/μL NPY could be analyzed quantitatively and reproducibly using conventional LC-MS. Parameters of the calibration curves, such as X-intercept, Bias (%), and relative standard deviation (RSD), were adjusted to optimize the sample solutions and the sensitive and quantitative LC-MS analyses.

摘要

大于3-4 kDa的肽,如神经肽Y(NPY)、食欲素B和α-促黑素,在进行直接且灵敏的定量液相色谱(LC)-轨道阱傅里叶变换质谱(MS)分析时会出现实际问题,因为它们存在吸附现象且电离效率低,尤其是在标准溶液中。一种由0.5%三氟乙酸(TFA)和35-50%水相乙腈组成的混合溶剂被开发用作标准NPY来创建校准曲线,同时作为一种基质来封闭实验管表面以尽量减少吸附。该混合基质有效地阻止了标准肽与经胰蛋白酶消化的牛血清白蛋白(BSA)(小片段肽)和食欲素B(大链肽)的非特异性吸附。在开发的样品溶液中检测到了含有1:100肽:水的样品。最后,使用传统的LC-MS能够对2至1000 fmol/μL的NPY进行定量且可重复的分析。校准曲线的参数,如X轴截距、偏差(%)和相对标准偏差(RSD),经过调整以优化样品溶液以及灵敏且定量的LC-MS分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c16/7392841/44afe3eb9731/massspectrometry-9-1-A0087-figure01.jpg

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