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Downsizing proteolytic digestion and analysis using dispenser-aided sample handling and nanovial matrix-assisted laser/desorption ionization-target arrays.

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Author

Summary, in English

An efficient technique for enzymatic digestion of proteins in nanovial arrays and identification by peptide mass fingerprinting using matrix-assisted laser desorption/ionization (MALDI-MS) is presented in this work. Through dispensing of a protein solution with simultaneous evaporation the protein (substrate) is concentrated up to 300 times in-vial. At higher substrate concentrations the catalytic turnover numbers increase according to the Michaelis-Menten kinetics. Therefore, the dispenser-aided nanodigestion is valuable for identification of low-level proteins (10 nM-500 nM) as well as for automatic high efficiency digestions performed in 0.2-10 min. As an example of low-level protein identification, a 10 nM solution of lysozyme C was unambiguously identified after 5 min of nanodigestion. Moreover, only 30 s nanodigestion was sufficient to identify hemoglobin (10 microM), exemplifying the fast catalysis of the nanodigestion technique. The developed silicon flow-through piezoelectric dispenser is adapted for low-volume and preconcentrated samples in the nL-microL range and provides fast, accurate and contact-free sample positioning into the nanovials. In this work, the properties of the nanodigestion concept regarding proteins of different characteristics are explored. Furthermore, the potential of automated protein identification using precoated proteolytic nanovial-arrays is demonstrated.

Publishing year

2001

Language

English

Pages

1072-1081

Publication/Series

Proteomics

Volume

1

Issue

9

Document type

Journal article

Publisher

John Wiley & Sons Inc.

Topic

  • Analytical Chemistry

Keywords

  • Silicon flow-through microdispenser
  • Nanovial array
  • On-target proteolytic digestion
  • Protein identification
  • Matrix-assisted laser desorption ionization-mass spectrometry

Status

Published

ISBN/ISSN/Other

  • ISSN: 1615-9861