4.8 Article

LC-MS/MS analysis of peptides with methanol as organic modifier: Improved limits of detection

期刊

ANALYTICAL CHEMISTRY
卷 76, 期 23, 页码 7028-7038

出版社

AMER CHEMICAL SOC
DOI: 10.1021/ac0493368

关键词

-

资金

  1. NINDS NIH HHS [NS 42843] Funding Source: Medline

向作者/读者索取更多资源

With the advent of soft ionization methods such as MALDI and ESI, mass spectrometry has become the most important technique for the analysis of proteins and peptides. ESI-MS is often preceded by separation of the peptide sample by reversed-phase liquid chromatography (LC). Acetonitrile (ACN) is the most commonly employed organic solvent in LC-ESI-MS analysis of peptides. In this report, we demonstrate that the use of methanol (MeOH) as the organic modifier improves the detection limits for analysis of peptide mixtures such as those found in tryptic digests of proteins. A nanoLC-ESI-quadrupole ion trap instrument (LCQ Deca, ThermoFinnigan) was used to analyze peptide standards, protein digests of known concentrations, and tryptic digests of 2-DGE-separated proteins. MeOH displayed excellent chromatographic performance (separation and sensitivity), and shorter gradient times were possible for chromatographic separation with MeOH versus ACN. Sensitivity levels of a few hundred attomoles were achieved with MeOH; those levels could not be achieved with ACN. In addition, MeOH-based nanoLC-MS/MS yielded superior results for the analysis of digests of 2-DGE-separated proteins. For the 14 protein spots analyzed, the success rate of protein identification with MeOH-based nanoLC-ESI-MS/MS was 100%, with multiple proteins identified in several of the spots. In contrast, ACN-based procedure failed to identify any proteins in 21% of the spots and overall identified 33% fewer proteins than the MeOH-based procedure. In summary, higher sensitivity and shorter gradient times make MeOH an excellent organic modifier for the use in nanoLC-ESI-MS/MS analysis of peptides.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据