Spatial proteome profiling of the compartments of the human cell using an antibody-based approach

The human cell is complex, with countless processes ongoing in parallel in specialized compartments, the organelles. Cells can be studied in vitro by using immortalized cell lines that represent cells in vivo to a varying degree. Gene expression varies between cell types and an average cell line expresses around 10,000-12,000 genes, as measured with RNA sequencing. These genes encode the cell’s proteome; the full set of proteins that perform functions in the cell. In paper I we show that RNA sequencing is a necessary tool for studying the proteome of the human cell. By studying the proteome, and proteins’ localization in the cell, information can be assembled on how the cell functions. Image-based methods allow for detailed spatial resolution of protein localization as well as enable the study of temporal events. Visualization of a protein can be accomplished by using either a cell line that is transfected to express the protein with a fluorescent tag, or by targeting the protein with an affinity reagent such as an antibody. In paper II we present subcellular data for a majority of the human proteins, showing that there is a high degree of complexity in regard to where proteins localize in the cell. Cellular energy is generated in the mitochondria, an important organelle that is also active in many other different functions. Today approximately only a third of the estimated mitochondrial proteome has been validated experimentally, indicating that there is much more to understand with regard to the functions of the mitochondria. In paper III we explore the mitochondrial proteome, based on the results of paper II. We also present a method for sublocalizing proteins to subcompartments that can be performed in a high-throughput manner. To conclude, this thesis shows that transcriptomics is a useful tool for proteome-wide subcellular localization, and presents high-resolution spatial distribution data for the human cell with a deeper analysis of the mitochondrial proteome.QC 20170512