A Robust Two-Dimensional Separation for Top-Down Tandem Mass Spectrometry of the Low-Mass Proteome

Ji Eun Lee, John F. Kellie, John C. Tran, Jeremiah D. Tipton, Adam D. Catherman, Haylee M. Thomas, Dorothy R. Ahlf, Kenneth R. Durbin, Adaikkalam Vellaichamy, Ioanna Ntai, Alan G. Marshall, Neil L. Kelleher*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

76 Scopus citations


For fractionation of intact proteins by molecular weight (MW), a sharply improved two-dimensional (2D) separation is presented to drive reproducible and robust fractionation before top-down mass spectrometry of complex mixtures. The "GELFrEE" (i.e., gel-eluted liquid fraction entrapment electrophoresis) approach is implemented by use of Tris-glycine and Tris-tricine gel systems applied to human cytosolic and nuclear extracts from HeLa S3 cells, to achieve a MW-based fractionation of proteins from 5 to >100 kDa in 1 h. For top-down tandem mass spectroscopy (MS/MS) of the low-mass proteome (5-25 kDa), between 5 and 8 gel-elution (GE) fractions are sampled by nanocapillary-LC-MS/MS with 12 or 14.5 tesla Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometers. Single injections give about 40 detectable proteins, about half of which yield automated ProSight identifications. Reproducibility metrics of the system are presented, along with comparative analysis of protein targets in mitotic versus asynchronous cells. We forward this basic 2D approach to facilitate wider implementation of top-down mass spectrometry and a variety of other protein separation and/or characterization approaches.

Original languageEnglish (US)
Pages (from-to)2183-2191
Number of pages9
JournalJournal of the American Society for Mass Spectrometry
Issue number12
StatePublished - Dec 2009

ASJC Scopus subject areas

  • Structural Biology
  • Spectroscopy


Dive into the research topics of 'A Robust Two-Dimensional Separation for Top-Down Tandem Mass Spectrometry of the Low-Mass Proteome'. Together they form a unique fingerprint.

Cite this