The organelle proteome
Spatial partitioning of biological processes is a phenomenon fundamental to life that enables multiple processes to occur in parallel. An organelle is a sub module of the eukaryotic cell with a specialized function. The name "organelle" stems from the analogy between the role of organelles in the cells to the role of organs in the human body. The precise definition of organelles varies, and these sub modules are sometimes also referred to as compartments or structures of the cell. Often a distinction is made between membrane-bound and non-membrane bound organelles. The membrane-bound organelles, such as the nucleus and the Golgi apparatus, create a physical boundary thus separating the intra and extra-organelle space. In contrast, non-membrane bound organelles like the cytoskeleton and nucleoli provide a specialized surface or region. Membranous or not, this partitioning creates a specific environment at the site of the organelle, where the concentration of different molecules can be tailored to fit the purpose of the organelle.
At the cellular level, proteins function to catalyze, conduct and control most processes at specific times and locations. Subcellular localization of a protein helps define the protein function as different organelles offer distinct environments containing a variety of physiological conditions, and interaction partners. Consequently, mis-localizations of proteins have often been associated with cellular dysfunction and disease
(Kau TR et al, 2004;
Laurila K et al, 2009;
Park S et al, 2011). Knowledge of the spatial distribution of proteins at a subcellular level is thus essential for understanding protein function, interactions and cellular mechanisms. And studying the activity of how cells generate and maintain their spatial organization is central to understanding the mechanisms of the living cell.
Within the Cell Atlas, the subcellular localization of 12003 proteins have been mapped on a single-cell level to 32 subcellular structures and enabled the definition of 13 major organelle proteomes. The localization was performed in a panel of 22 human cell lines using transcriptomics data as a starting point. The analysis further reveals that approximately half of the proteins localize to multiple compartments and identifies many proteins with single-cell variation in terms of protein abundance or spatial distribution. The expression pattern and spatial distribution of human proteins in all major cellular organelles can be explored in these interactive knowledge sections, including numerous catalogues of proteins with specific and similar patterns of expression, as well as examples of detailed images illustrating the subcellular spatial distribution patterns.
Subcellular localization of proteins
Several approaches for systematic analysis of protein localizations have been described. Quantitative mass-spectrometric readouts allow identification of proteins with similar distribution profiles across fractionation gradients
(Park S et al, 2011;
Christoforou A et al, 2016;
Itzhak DN et al, 2016) or enzyme-mediated proximity-labelled proteins in cells
(Itzhak DN et al, 2016;
Roux KJ et al, 2012;
Lee SY et al, 2016). In contrast, imaging-based approaches enable the exploration of subcellular distribution of proteins in situ in single cells and have the advantage of also effectively identifying single-cell variability and multi-organelle localization. Imaging based approaches can be performed using tagged proteins
(Huh WK et al, 2003;
Simpson JC et al, 2000;
Stadler C et al, 2013) or affinity reagents as here in the Human Protein Atlas.
In the Cell Atlas, we employ an immunofluorescence (IF) based approach combined with confocal microscopy to enable high-resolution investigation of the spatial distribution of each protein
(Stadler C et al, 2013;
Barbe L et al, 2008;
Stadler C et al, 2010;
Fagerberg L et al, 2011). With the diffraction-limited resolution of about 200 nm, an immunofluorescence image from the Cell Atlas gives a detailed insight into the cellular organization. The spatial distribution of the protein is investigated using indirect IF in the U-2 OS cell line and up to two additional cell lines selected based on RNA-seq data. The protein of interest is visualized in green, while reference markers for microtubules (red), endoplasmic reticulum (yellow) and nucleus (blue) outline the cell. From small dots like nuclear bodies, to larger structures such as the nucleus, the distinct patterns in the images together with the reference markers make it possible to precisely determine the spatial distribution of a protein within the cell. This enables the assignment of the protein's location to one or more of the 32 structures and substructures currently annotated, as exemplified in Figure 1.
Protein distribution in the human cell
Figure 2 shows the organelle distribution of all annotations for the 12003 proteins localized to at least one structure or substructure. The plot is sorted by meta-compartments: cytoplasm, nucleus, and secretory machinery, respectively. Most proteins are found in the nucleus, followed by the cytosol and vesicles, which consist of transport vesicles as well as small membrane-bound organelles like endosomes or peroxisomes. 51% (n=6172) of the proteins were detected at more than one location (multilocalizing proteins), and 15% (n=1855) displayed a (single-cell variation) in expression level or spatial distribution. Explore the organelle proteomes of the human cell in detail here.
Validation of antibodies and location data for the Cell Atlas
Recently, the quality and use of antibodies in research have been frequently debated
(Baker M. 2015). As antibody off-target binding can cause false positive results, we have made an effort in manually annotating all results regarding reliability of the staining. In the Cell Atlas a reliability score for every annotated location at a four-graded scale is provided: Validated, Supported, Approved, and Uncertain, as described in detail in the assay & annotation section. The validated locations are obtained through antibody validation according to one of the validation "pillars" proposed by an international working group
(Uhlen M et al, 2016): (i) genetic methods using siRNA silencing
(Stadler C et al, 2012) or CRISPR/Cas9 knock-out, (ii) expression of a fluorescent protein-tagged protein at endogenous levels
(Skogs M et al, 2016) or (iii) independent antibodies targeting different epitopes
(Stadler C et al, 2010). A supportive location is defined by agreement with external experimental data (UniProt database). An approved location score indicates that there is no external experimental information available to confirm the observed location. An uncertain location shows contradictory results compared to complementary information, such as literature or transcriptomics data. Also uncertain locations are shown, since it cannot be ruled out that the data is correct, and further experiments are needed to establish the reliability of the antibody staining. The distribution of reliability scores for the localized proteins is shown in Figure 3. Approximately 45% (n=5344) of the protein localizations provided are validated or supported. Table 1 details the organelle distribution of all localized proteins and the distribution of reliability scores per organelle.
Table 1. Table showing the number of proteins localized to every organelle, structure, and substructure in the Cell Atlas, along with the distribution of reliability scores.
Relevant links and publications
Baker M. 2015. Reproducibility crisis: Blame it on the antibodies. Nature.
PubMed: 25993940 DOI: 10.1038/521274a Barbe L et al, 2008. Toward a confocal subcellular atlas of the human proteome. Mol Cell Proteomics.
PubMed: 18029348 DOI: 10.1074/mcp.M700325-MCP200 Christoforou A et al, 2016. A draft map of the mouse pluripotent stem cell spatial proteome. Nat Commun.
PubMed: 26754106 DOI: 10.1038/ncomms9992 Fagerberg L et al, 2011. Mapping the subcellular protein distribution in three human cell lines. J Proteome Res.
PubMed: 21675716 DOI: 10.1021/pr200379a Foster LJ et al, 2006. A mammalian organelle map by protein correlation profiling. Cell.
PubMed: 16615899 DOI: 10.1016/j.cell.2006.03.022 Huh WK et al, 2003. Global analysis of protein localization in budding yeast. Nature.
PubMed: 14562095 DOI: 10.1038/nature02026 Itzhak DN et al, 2016. Global, quantitative and dynamic mapping of protein subcellular localization. Elife.
PubMed: 27278775 DOI: 10.7554/eLife.16950 Kau TR et al, 2004. Nuclear transport and cancer: from mechanism to intervention. Nat Rev Cancer.
PubMed: 14732865 DOI: 10.1038/nrc1274 Laurila K et al, 2009. Prediction of disease-related mutations affecting protein localization. BMC Genomics.
PubMed: 19309509 DOI: 10.1186/1471-2164-10-122 Lee SY et al, 2016. APEX Fingerprinting Reveals the Subcellular Localization of Proteins of Interest. Cell Rep.
PubMed: 27184847 DOI: 10.1016/j.celrep.2016.04.064 Park S et al, 2011. Protein localization as a principal feature of the etiology and comorbidity of genetic diseases. Mol Syst Biol.
PubMed: 21613983 DOI: 10.1038/msb.2011.29 Roux KJ et al, 2012. A promiscuous biotin ligase fusion protein identifies proximal and interacting proteins in mammalian cells. J Cell Biol.
PubMed: 22412018 DOI: 10.1083/jcb.201112098 Simpson JC et al, 2000. Systematic subcellular localization of novel proteins identified by large-scale cDNA sequencing. EMBO Rep.
PubMed: 11256614 DOI: 10.1093/embo-reports/kvd058 Skogs M et al, 2016. Antibody validation in bioimaging applications based on endogenous expression of tagged proteins. J Proteome Res.
PubMed: 27723985 DOI: 10.1021/acs.jproteome.6b00821 Stadler C et al, 2012. Systematic validation of antibody binding and protein subcellular localization using siRNA and confocal microscopy. J Proteomics.
PubMed: 22361696 DOI: 10.1016/j.jprot.2012.01.030 Stadler C et al, 2013. Immunofluorescence and fluorescent-protein tagging show high correlation for protein localization in mammalian cells. Nat Methods. 2013 Apr;10(4):315-23
PubMed: 23435261 DOI: 10.1038/nmeth.2377 Stadler C et al, 2010. A single fixation protocol for proteome-wide immunofluorescence localization studies. J Proteomics.
PubMed: 19896565 DOI: 10.1016/j.jprot.2009.10.012 Uhlen M et al, 2016. A proposal for validation of antibodies. Nat Methods.
PubMed: 27595404 DOI: 10.1038/nmeth.3995
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