基于极性反转纳喷雾的氨基酸质谱测量方法

Amino Acid Mass Spectrometry Based on Polarity-Reversing Nano-Electrospray Ionization

氨基酸分析一直是化学和生物学分析研究的重要内容,在众多氨基酸分析方法中,质谱法在灵敏度和准确度上具有较大优势。液质联用是目前最为常用的氨基酸质谱分析方法,需要使用到电喷雾离子源。然而,电喷雾离子源对氨基酸离子化效率有限,尤其是酸性氨基酸,这严重影响了氨基酸质谱分析方法检测灵敏度的进一步提升。基于自主搭建的极性反转纳喷雾离子源(PR-nESI),建立了20种常见氨基酸的质谱检测方法。与基于普通纳喷雾离子源(nano-ESI)的检测方法相比,PR-nESI显著提高了检测信噪比,提升幅度最高可达数十倍。此外,PRnESI具有较强的除盐效果,能有效抑制氨基酸金属离子加合物的形成,极大地方便了后期谱图指认。该氨基酸检测方法未来在临床、食品等领域中具有较为广阔的应用前景。

Amino acid analysis has always been a crucial aspect of chemical and biological research due to its essential biological significance and diverse roles in living organisms,including catalyzing chemical reactions,signaling,and supporting cell structure.Mass spectrometry possesses significant advantages in terms of sensitivity and accuracy among various amino acid analysis methods.Liquid chromatography-mass spectrometry(LC-MS)is the most commonly used method for amino acid mass spectrometry analysis,requiring an electrospray ion source.While the electrospray ion source has many advantages,such as high sensitivity,high selectivity,simple operation,compatibility with various types of mass spectrometers,and a wide range of analyzable substances,its ionization efficiency for amino acids is limited,particularly for acidic amino acids.This limitation hinders further improvement of the detection sensitivity of analytical methods.A mass spectrometry method for determining 20 common amino acids was established based on a self-developed Polarity-Reversing Nano-Electrospray Ionization(PR-nESI)ion source.PR-nESI enhances detection by altering the high-voltage strategy during the nano-spray process.Compared to conventional Nano-Electrospray Ionization(nano-ESI)methods,PR-nESI significantly improves the detection signal-to-noise ratio,increasing up to tens of times.Moreover,PR-nESI exhibits strong desalting effects,effectively inhibiting the formation of metal ion adducts of amino acids,which significantly facilitates spectral identification,particularly for biomolecules in salt buffer systems.The amino acid detection method presented in this study holds promising future application prospects in clinical and food fields.