Analysis of mass spectrometry data for nucleolar proteomics experiments

Abstract

With recent advances in experiment design, sample preparation, separation and instruments, mass spectrometry (MS)-based quantitative proteomics is becoming increasingly more popular. This has the potential to usher a new revolution in biology, in which the protein complement of cell populations can be described not only with increasing coverage, but also in all of its dimensions with unprecedented precision. Indeed, while earlier proteomics studies aimed solely at identifying as many as possible of the proteins present in the sample, newer, so-called Next Generation Proteomics studies add to this the aim of determining and quantifying the protein variants present in the sample, their mutual associations within complexes, their posttranslational modifications, their variation across the cell-cycle or in response to stimuli or perturbations, and their subcellular distribution. This has the potential to make MS proteomics much more useful for researchers, but will also mean that researchers with no background in MS will increasingly be confronted with the less-than trivial challenges of preparing samples for MS analysis, then processing and interpreting the results. In Chapter 20, we described a workflow for isolating the protein contents of a specific SILAC-labeled organelle sample (the nucleolus) and processing it into peptides suitable for bottom- up MS analysis. Here, we complete this workflow by describing how to use the freely available MaxQuant software to convert the spectra stored in the Raw files into peptide- and protein-level information. We also briefly describe how to visualize the data using the free R scripting language.