Orthogonal Separation Techniques for the Characterization of the Yeast Nuclear Proteome
datasetposted on 06.07.2009 by Sharon Gauci, Liesbeth M. Veenhoff, Albert J. R. Heck, Jeroen Krijgsveld
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
The presence of the nucleus is the distinguishing feature of eukaryotic cells, separating the genome from the cytoplasm. Key cellular events, including transcription, DNA replication, RNA-processing and ribosome biogenesis all take place in the nucleus. All of these processes can be regulated through controlled and bidirectional translocation of proteins across the nuclear envelope, making the nucleus a highly dynamic organelle. In this study, we present four orthogonal multidimensional separation techniques for the comprehensive characterization of the yeast nuclear proteome. By combining methods on the peptide level (SCX chromatography, isoelectric focusing) and protein level (SDS-PAGE, phosphocellulose chromatography) coupled with mass spectrometry, we identified 1889 proteins from highly purified nuclei, of which 1032 were previously annotated as nuclear proteins. In particular, the most successful setup was the use of phosphocellulose P11 chromatography in combination with SDS-PAGE and reversed phase chromatography. Phosphocellulose P11 chromatography has been classically used for the purification of functional protein complexes involved in transcription regulation. Here, by its coupling with LC-MS, this method resulted in approximately 1.5 times more protein identifications than the other three combined, thereby contributing significantly to the coverage of nuclear proteins. In addition, the use of this technique resulted in the enrichment of DNA binding proteins and proved to be a valuable tool for the simultaneous analysis of multiple protein complexes. The enrichment for specific nuclear complexes has resulted in high protein sequence coverage, which will be particularly useful for the detailed characterization of subunits.