title: Organelle proteomics by label-free and SILAC-based protein correlation profiling.
abstract: The ability to purify cell organelles and protein complexes on a large scale, combined with advances in protein identification using mass spectrometry, has provided a wealth of information regarding protein localization and function. A major challenge in these studies has been the ability to identify bona fide organelle components from a background of co-purifying contaminants because none of the available biochemical purification protocols afford pure preparations. Since this situation is unlikely to change alternative strategies have been devised to meet this challenge by making use of the information inherent in the fractionation profile of organelles isolated by density gradient centrifugation. In this chapter we describe strategies based on protein correlation profiling and quantitative mass spectrometry to sort out likely candidates. The organelle inventories defined by these methods are suitable to guide future functional experiments.
authors.affiliation: Center for Experimental BioInformatics, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark.
authors.forename: Joern
authors.initials: J
authors.lastname: Dengjel
authors.forename: Lis
authors.initials: L
authors.lastname: Jakobsen
authors.forename: Jens S
authors.initials: JS
authors.lastname: Andersen
mesh_terms: D000596:Amino Acids / Q000737:chemistry*; D002478:Cells, Cultured; D002853:Chromatography, Liquid; D004591:Electrophoresis, Polyacrylamide Gel; D006801:Humans; D007553:Isotope Labeling / Q000379:methods*; D013058:Mass Spectrometry; D015388:Organelles / Q000737:chemistry*; D011506:Proteins / Q000032:analysis* / Q000737:chemistry*; D040901:Proteomics / Q000379:methods*
chemical_list: D000596:Amino Acids; D011506:Proteins