An efficient sample preparation method to enhance carbohydrate ion signals in matrix-assisted laser desorption/ionization mass spectrometry

  • Yu Meng Ou
  • , Shu Yun Kuo
  • , Hsun Lee
  • , Huan Tsung Chang
  • , Yi Sheng Wang*
  • *Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

4 Scopus citations

Abstract

Sample preparation is a critical process in mass spectrometry (MS) analysis of carbohydrates. Although matrix-assisted laser desorption/ ionization (MALDI) MS is the method of choice in carbohydrate analysis, poor ion signal and data reproducibility of carbohydrate samples continue to be severe problems. For quantitative analysis of carbohydrates, an effective analytical protocol providing superior data quality is necessary. This video demonstrates sample preparation protocols to improve signal intensity and minimize data variation of carbohydrates in MALDI-MS. After drying and crystallization of sample droplets, the crystal morphology is reformed by methanol before mass spectrometric analysis. The enhancement in carbohydrate signal is examined with MALDI imaging mass spectrometry (IMS). Experimental results show that crystal reformation adjusts crystalline structures and redistributes carbohydrate analytes. In comparison with the dried droplet preparation method in conventional MALDI-MS, reforming carbohydrate crystal morphologies with methanol shows significantly better signal intensity, ion image distribution, and data stability. Since the protocols demonstrated herein do not involve changes in sample composition, they are generally applicable to various carbohydrates and matrixes.

Original languageEnglish
Article numbere57660
JournalJournal of Visualized Experiments
Volume2018
Issue number137
DOIs
StatePublished - 29 07 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 Journal of Visualized Experiments.

Keywords

  • Carbohydrate
  • Crystalline Structure
  • Dried Droplet Method
  • MALDI
  • Morphology Reforming
  • Recrystallization
  • Sample Morphology
  • Signal Enhancement
  • Substrate Temperature

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