Molecular researchers working on spatial proteomics look for patterns of protein distribution in cells and subcellular structures. Their work contributes to a growing body of knowledge describing the functional ontology of proteins and their rates of synthesis and decay in different cell lines and different species. While this research area is in formative stages, the distribution of particular proteins in specific locations may play an important future role for disease diagnosis and intervention. Because protein turnover rates impact cellular protein stability they may contribute to the destabilization of biological processes necessary for healthy cell growth and function. In the case of ovarian cancer preliminary studies have isolated and identified potential tissue-specific peptides and protein masses using mass spectometry. The aim is to grade and/or subtype ovarian cancer using specific protein/peptide profiles.1
One study using SILAC (stable isotope labeling with amino acids in cell culture) and mass spectrometry measured protein abundance and the rates of synthesis, degradation and turnover in cell structures to produce a cell-based functional annotation of the human proteome using the HeLa cell line.2 Their measurements showed an average protein turnover of 20 hours with rates as small as 10 minutes and as long as 100 hours. It also showed that the more abundant proteins have longer than average half-lives and a range of functions. Most are either present in large, abundant and stable protein complexes, such as ribosome and spliceosome subunits, RNA polymerase II, the nuclear pore, the exosome and the proteasome, or else they are mitochondrial.
The same team found that proteins with a faster than average turnover are involved in either mitosis, or other aspects of cell cycle regulation, including protein components of the centromere, proteins with microtubule motor activity, proteins involved in cytoskeleton reorganization and proteins involved in chromatin assembly and condensation.
They also identified a subset of proteins with different turnover rates depending on subcellular localization. These proteins correlated with subunits of large, multi-protein complexes, suggesting that protein assembly is controlled in a different subcellular location from their main site of function.
Other studies working with dissimilar cell types and using diverse measurement methodologies have produced differing results. However, it makes sense that protein turnover and localization patterns vary across cell lines, under different growth conditions and in response to drugs or other stimuli. Protein stability also varies naturally as cells progress through interphase and mitosis. Work is in progress to carry out systematic, proteome-wide analyses of how protein properties, including turnover rates and subcellular localization patterns, vary as a function of cell cycle progression.2
While researchers work to discover and define a common best practice method for making protein measurements, the development and integration of many large-scale, spatial proteomic data sets provides a promising future direction for expanding the functional annotation of the human genome, and for the discovery of new biological regulatory mechanisms.
1. Gustafsson, J. et. al. (2011) ‘MALDI Imaging Mass Spectrometry (MALDI-IMS)—Application of Spatial Proteomics for Ovarian Cancer Classification and Diagnosis‘ International Journal of Molecular Science 12(1), (pp 773-794)
2. Boisvert, FM. et.al. (2011) ‘A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells’ http://www.mcponline.org/content/early/2011/09/21/mcp.M111.011429.full.pdf