Quantitative proteomic analysis to profile dynamic changes in the spatial distribution of cellular proteins.
Organelle protein profiles have traditionally been analyzed by subcellular fractionation of a specific organelle followed by the identification of the protein components of specific fractions containing the target organelle(s) using mass spectrometry (MS). However, because of limited resolution of the available fractionation methods, it is often difficult to isolate and thus profile pure organelles. Furthermore, many proteins (e.g., secretory proteins) are often observed to dynamically shuttle between organelles. Therefore, the determination of their true cellular localization requires the concurrent analysis of multiple organelles from the same cell lysate. Here, we report an integrated experimental approach that simultaneously profiles multiple organelles. It is based on the subcellular fractionation of cell lysates by density gradient centrifugation, iTRAQ labeling, and MS analysis of the proteins in selected fractions and principal component analysis (PCA) of the resulting quantitative proteomic data. Quantitative signature patterns of several organelles, including the ribosome, mitochondria, proteasome, lysosome, endoplasmic reticulum (ER), and Golgi apparatus, have been acquired from a single multiplexed proteomic assay using iTRAQ reagents. Through comparison PCA, we compare organelle profiles from cells under different physiological conditions to investigate changes in organelle profiles between control and perturbed samples. Such quantitative proteomics-based subcellular profiling methods thus provide useful tools to dissect the organization of cellular proteins into functional units and to detect dynamic changes in their protein composition.
Yan
Wei
W
Institute for Systems Biology, Seattle, WA, USA.
Hwang
Daehee
D
Aebersold
Ruedi
R
D000818:Animals; D002458:Cell Fractionation / Q000379:methods; D002460:Cell Line; D002852:Chromatography, Ion Exchange / Q000379:methods; D002853:Chromatography, Liquid / Q000379:methods; D019295:Computational Biology; D008264:Macrophages / Q000166:cytology; D013058:Mass Spectrometry / Q000379:methods; D051379:Mice; D015388:Organelles / Q000737:chemistry*; D011506:Proteins / Q000737:chemistry* / Q000302:isolation & purification*; D020543:Proteome; D014357:Trypsin
D011506:Proteins; D020543:Proteome; D014357:Trypsin