Pyridinium-based ionic liquid matrices can improve the identification of proteins by peptide mass-fingerprint analysis with matrix-assisted laser desorption/ionization mass spectrometry

Masoud Zabet-Moghaddam, Elmar Heinzle, Maria Lasaosa, Andreas Tholey

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

Matrix-assisted laser desorption/ionization mass spectrometry has become an indispensable tool for identification of proteins by peptide mass-fingerprint analysis. Selection of the matrix, addition of matrix additives, and sample-preparation techniques are known to affect the quality of the spectra and hence protein identification. We investigated the effect of pyridine as matrix additive for the commonly used crystalline matrix α-cyano-4- hydroxycinnamic acid (CCA), forming a pyridinium based ionic liquid matrix, on the mass spectra of synthetic peptides and tryptic protein digests. Beside the equimolar mixture of CCA and pyridine, the effect of addition of substoichiometric amounts of the base to the acid was tested. Optimum results in terms of signal-to-noise ratios, reduction of chemical noise, and reduced formation of alkali adducts and matrix clusters were observed for the matrix CCA-pyridine in the molar ratio 2:1. The optimized ionic liquid matrix was used for identification of tryptic digests of six model proteins and for identification of a protein extracted from a two-dimensional gel with the proteome of the bacterium Corynebacterium glutamicum, and shown to facilitate protein identification, yielding higher scores and increased sequence coverage compared with pure CCA. Thus CCA-Py 2:1 is a potential alternative for identification and characterization of proteins by peptide mass-fingerprint analysis.

Original languageEnglish
Pages (from-to)215-224
Number of pages10
JournalAnalytical and Bioanalytical Chemistry
Volume384
Issue number1
DOIs
StatePublished - Jan 2006

Keywords

  • Ionic liquid matrices
  • Limit of detection
  • Mass spectrometry
  • Matrix additives
  • Proteomics

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