In searching of optimum electrospray ionization using both spray image and electric current measurement

Jing, Yuzhou; Xie, Miao; Wang, Chenlu; Li, Junhui; Gao, Wenqing; Yu, Jiancheng

doi:10.1016/j.ijms.2023.117113

Cited by 3 publications

(1 citation statement)

References 39 publications

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“…Although the TIC chromatogram acquired by using the optimized LC gradient condition has a similar separation trend as the one acquired by using the initial LC gradient condition, the sample is better separated in a wider range of LC separation time. The better LC separation also leads to a reduced charge competition/ion suppression and ionization bias in the nanoelectrospray ionization, 36 which improves the ionization efficiency of the glycopeptides in the sample. A better ionization efficiency can also improve the reproducibility of the MS signal, which leads to the improvement of the reproducibility for the glycopeptide identification results.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

A Fully Automated Online Enrichment and Separation System for Highly Reproducible and In-Depth Analysis of Intact Glycopeptide

Hu,

Liu,

Gao

et al. 2024

Anal. Chem.

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A fully automated online enrichment and separation system for intact glycopeptides, named AutoGP, was developed in this study by integrating three different columns in a nano-LC system. Specifically, the peptide mixture from the enzymatic digestion of a complex biological sample was first loaded on a hydrophilic interaction chromatography (HILIC) column. The nonglycopeptides in the sample were washed off the column, and the glycopeptides retained by the HILIC column were eluted to a C18 trap column to achieve an automated glycopeptide enrichment. The enriched glycopeptides were further eluted to a C18 column for separation, and the separated glycopeptides were eventually analyzed by using an orbitrap mass spectrometer (MS). The optimal operating conditions for AutoGP were systemically studied, and the performance of the fully optimized AutoGP was compared with a conventional manual system used for glycopeptide analysis. The experimental evaluation shows that the total number of glycopeptides identified is at least 1.5-fold higher, and the median coefficient of variation for the analyses is at least 50% lower by using AutoGP, as compared to the results acquired by using the manual system. In addition, AutoGP can perform effective analysis even with a 1-μg sample amount, while a 10-μg sample at least will be needed by the manual system, implying an order of magnitude better sensitivity of AutoGP. All the experimental results have consistently proven that AutoGP can be used for much better characterization of intact glycopeptides.

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Section: ■ Results and Discussionmentioning

confidence: 99%