The organelle proteome
Spatial compartmentalization of biological processes is a phenomenon fundamental to life that enables multiple processes to occur in parallel without undesired interference. An organelle is a subunit of the eukaryotic cell with a specialized function. The name "organelle" stems from the analogy between the different roles of organelles in the cells to the different roles of organs in the human body as a whole. A distinction is often made between membrane-bound and non-membrane bound organelles. The membrane-bound organelles, such as the nucleus and the Golgi apparatus, have a clearly defined physical boundary that separates the intra- and extra-organelle space. In contrast, non-membrane bound organelles like the cytoskeleton and nucleoli constitute spatially distinct assemblies of proteins, and sometimes RNA, within the cell. 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, and provides an important opportunity for regulation of cellular processes. As the precise definition of organelles varies, the more inclusive terms of subcellular structure.
A major function of proteins is to catalyze, conduct and control cellular processes in time and space. As different organelles and subcellular structures offer distinct environments, with distinct physiological conditions and interaction partners, the subcellular localization of a protein is an important part of protein function. Consequently, mis-localization of proteins have often been associated with cellular dysfunction and various human diseases (Kau TR et al. (2004); Laurila K et al. (2009); Park S et al. (2011)). Knowledge of the spatial distribution of a protein at the subcellular level is essential for understanding protein function, interactions and cellular mechanisms, and studying how cells generate and maintain their spatial organization is central for understanding the mechanisms of living cells.
Within the Cell Atlas, the subcellular localization of 12813 proteins have been mapped on a single-cell level to 35 subcellular structures, which has enabled the definition of 13 major organelle proteomes. The analysis 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,which include numerous catalogues of proteins with specific and similar patterns of expression, as well as example images illustrating various 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 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.
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 proteins (Thul PJ et al. (2017); 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 mRNA expression of the corresponding gene, using a panel of 35 cell lines. The protein of interest is visualized in green, while reference markers for microtubules (red), endoplasmic reticulum (yellow) and nucleus (blue) are used to outline the cell. From small dots like nuclear bodies, to larger structures such as the nucleoplasm, 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. The localization of each protein is assigned to one or more of the 35 subcellular structures and substructures currently annotated in the Cell Atlas, as exemplified in Figure 1.
Nucleoplasm
Nuclear speckles
Nuclear bodies
Nucleoli
Nucleoli fibrillar center
Nucleoli rim
Mitotic chromosome
Kinetochore
Nuclear membrane
Cytosol
Cytoplasmic bodies
Rods & Rings
Aggresome
Mitochondria
Centrosome
Centriolar satellites
Microtubules
Microtubule ends
Mitotic spindle
Cytokinetic bridge
Midbody
Midbody ring
Cleavage furrow
Intermediate filaments
Actin filaments
Focal adhesion sites
Endoplasmic reticulum
Golgi apparatus
Vesicles
Endosomes
Lysosomes
Lipid droplets
Peroxisomes
Plasma membrane
Cell junctions
Figure 1. Example of confocal immunofluorescence images of different proteins (green) localized to each of the subcellular organelles and substructures currently annotated in the Cell Atlas in a representative set of cell lines. Microtubules are marked with an anti-tubulin antibody (red) and the nucleus is counterstained with DAPI (blue). The side of an image represents 64 μm. For more example images and details describing all the 35 patterns annotated in the Cell Atlas, see the Cell Dictionary.
Protein distribution in the human cell
Figure 2 shows the organelle distribution of all annotations for the 12813 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. 55% (n=7106) of the proteins were detected in more than one location (multilocalizing proteins), and 25% (n=3141) displayed single-cell variation in expression level or spatial distribution.
Figure 2. Bar plot showing the distribution of proteins detected in every organelle, structure and substructure annotated in the Cell Atlas.
Validation of antibodies and location data for the Cell Atlas
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,the Cell Atlas makes an effort in manually scoring 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: Enhanced, Supported, Approved, and Uncertain, as described in detail in the assay & annotation section. The enhanced 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. (2017)) or (iii) independent antibodies targeting different epitopes (Stadler C et al. (2010)). A supportive location is in agreement with external experimental data (UniProt database), while an approved location score indicates that there is no external experimental information available to confirm the observed location. An uncertain location is contradictory compared to complementary information, such as literature or transcriptomics data, and is shown if 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 43% (n=5502) of the protein localizations provided are enhanced or supported. Table 1 details the organelle distribution of all localized proteins and the distribution of reliability scores on the basis of the individual organelle.
Figure 3. Pie chart showing level of reliability of the localized proteins, where each piece is the number of proteins with one type of score, out of the four reliability scores Enhanced, Supported, Approved, and Uncertain.
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
Parikh K et al., Colonic epithelial cell diversity in health and inflammatory bowel disease. Nature. (2019)
PubMed: 30814735 DOI: 10.1038/s41586-019-0992-y
Menon M et al., Single-cell transcriptomic atlas of the human retina identifies cell types associated with age-related macular degeneration. Nat Commun. (2019)
PubMed: 31653841 DOI: 10.1038/s41467-019-12780-8
Wang L et al., Single-cell reconstruction of the adult human heart during heart failure and recovery reveals the cellular landscape underlying cardiac function. Nat Cell Biol. (2020)
PubMed: 31915373 DOI: 10.1038/s41556-019-0446-7
Wang Y et al., Single-cell transcriptome analysis reveals differential nutrient absorption functions in human intestine. J Exp Med. (2020)
PubMed: 31753849 DOI: 10.1084/jem.20191130
Liao J et al., Single-cell RNA sequencing of human kidney. Sci Data. (2020)
PubMed: 31896769 DOI: 10.1038/s41597-019-0351-8
MacParland SA et al., Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat Commun. (2018)
PubMed: 30348985 DOI: 10.1038/s41467-018-06318-7
Vieira Braga FA et al., A cellular census of human lungs identifies novel cell states in health and in asthma. Nat Med. (2019)
PubMed: 31209336 DOI: 10.1038/s41591-019-0468-5
Vento-Tormo R et al., Single-cell reconstruction of the early maternal-fetal interface in humans. Nature. (2018)
PubMed: 30429548 DOI: 10.1038/s41586-018-0698-6
Qadir MMF et al., Single-cell resolution analysis of the human pancreatic ductal progenitor cell niche. Proc Natl Acad Sci U S A. (2020)
PubMed: 32354994 DOI: 10.1073/pnas.1918314117
Solé-Boldo L et al., Single-cell transcriptomes of the human skin reveal age-related loss of fibroblast priming. Commun Biol. (2020)
PubMed: 32327715 DOI: 10.1038/s42003-020-0922-4
Henry GH et al., A Cellular Anatomy of the Normal Adult Human Prostate and Prostatic Urethra. Cell Rep. (2018)
PubMed: 30566875 DOI: 10.1016/j.celrep.2018.11.086
Chen J et al., PBMC fixation and processing for Chromium single-cell RNA sequencing. J Transl Med. (2018)
PubMed: 30016977 DOI: 10.1186/s12967-018-1578-4
Guo J et al., The adult human testis transcriptional cell atlas. Cell Res. (2018)
PubMed: 30315278 DOI: 10.1038/s41422-018-0099-2
Uhlen M et al., A proposal for validation of antibodies. Nat Methods. (2016)
PubMed: 27595404 DOI: 10.1038/nmeth.3995
Stadler C et al., Systematic validation of antibody binding and protein subcellular localization using siRNA and confocal microscopy. J Proteomics. (2012)
PubMed: 22361696 DOI: 10.1016/j.jprot.2012.01.030
Poser I et al., BAC TransgeneOmics: a high-throughput method for exploration of protein function in mammals. Nat Methods. (2008)
PubMed: 18391959 DOI: 10.1038/nmeth.1199
Skogs M et al., Antibody Validation in Bioimaging Applications Based on Endogenous Expression of Tagged Proteins. J Proteome Res. (2017)
PubMed: 27723985 DOI: 10.1021/acs.jproteome.6b00821
Takahashi H et al., 5' end-centered expression profiling using cap-analysis gene expression and next-generation sequencing. Nat Protoc. (2012)
PubMed: 22362160 DOI: 10.1038/nprot.2012.005
Lein ES et al., Genome-wide atlas of gene expression in the adult mouse brain. Nature. (2007)
PubMed: 17151600 DOI: 10.1038/nature05453
Kircher M et al., Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res. (2012)
PubMed: 22021376 DOI: 10.1093/nar/gkr771
Pollard TD et al., Actin, a central player in cell shape and movement. Science. (2009)
PubMed: 19965462 DOI: 10.1126/science.1175862
Mitchison TJ et al., Actin-based cell motility and cell locomotion. Cell. (1996)
PubMed: 8608590
Pollard TD et al., Molecular Mechanism of Cytokinesis. Annu Rev Biochem. (2019)
PubMed: 30649923 DOI: 10.1146/annurev-biochem-062917-012530
dos Remedios CG et al., Actin binding proteins: regulation of cytoskeletal microfilaments. Physiol Rev. (2003)
PubMed: 12663865 DOI: 10.1152/physrev.00026.2002
Campellone KG et al., A nucleator arms race: cellular control of actin assembly. Nat Rev Mol Cell Biol. (2010)
PubMed: 20237478 DOI: 10.1038/nrm2867
Rottner K et al., Actin assembly mechanisms at a glance. J Cell Sci. (2017)
PubMed: 29032357 DOI: 10.1242/jcs.206433
Bird RP., Observation and quantification of aberrant crypts in the murine colon treated with a colon carcinogen: preliminary findings. Cancer Lett. (1987)
PubMed: 3677050 DOI: 10.1016/0304-3835(87)90157-1
HUXLEY AF et al., Structural changes in muscle during contraction; interference microscopy of living muscle fibres. Nature. (1954)
PubMed: 13165697
HUXLEY H et al., Changes in the cross-striations of muscle during contraction and stretch and their structural interpretation. Nature. (1954)
PubMed: 13165698
Svitkina T., The Actin Cytoskeleton and Actin-Based Motility. Cold Spring Harb Perspect Biol. (2018)
PubMed: 29295889 DOI: 10.1101/cshperspect.a018267
Kelpsch DJ et al., Nuclear Actin: From Discovery to Function. Anat Rec (Hoboken). (2018)
PubMed: 30312531 DOI: 10.1002/ar.23959
Malumbres M et al., Cell cycle, CDKs and cancer: a changing paradigm. Nat Rev Cancer. (2009)
PubMed: 19238148 DOI: 10.1038/nrc2602
Massagué J., G1 cell-cycle control and cancer. Nature. (2004)
PubMed: 15549091 DOI: 10.1038/nature03094
Hartwell LH et al., Cell cycle control and cancer. Science. (1994)
PubMed: 7997877 DOI: 10.1126/science.7997877
Barnum KJ et al., Cell cycle regulation by checkpoints. Methods Mol Biol. (2014)
PubMed: 24906307 DOI: 10.1007/978-1-4939-0888-2_2
Weinberg RA., The retinoblastoma protein and cell cycle control. Cell. (1995)
PubMed: 7736585 DOI: 10.1016/0092-8674(95)90385-2
Morgan DO., Principles of CDK regulation. Nature. (1995)
PubMed: 7877684 DOI: 10.1038/374131a0
Teixeira LK et al., Ubiquitin ligases and cell cycle control. Annu Rev Biochem. (2013)
PubMed: 23495935 DOI: 10.1146/annurev-biochem-060410-105307
King RW et al., How proteolysis drives the cell cycle. Science. (1996)
PubMed: 8939846 DOI: 10.1126/science.274.5293.1652
Cho RJ et al., Transcriptional regulation and function during the human cell cycle. Nat Genet. (2001)
PubMed: 11137997 DOI: 10.1038/83751
Whitfield ML et al., Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol Biol Cell. (2002)
PubMed: 12058064 DOI: 10.1091/mbc.02-02-0030.
Boström J et al., Comparative cell cycle transcriptomics reveals synchronization of developmental transcription factor networks in cancer cells. PLoS One. (2017)
PubMed: 29228002 DOI: 10.1371/journal.pone.0188772
Lane KR et al., Cell cycle-regulated protein abundance changes in synchronously proliferating HeLa cells include regulation of pre-mRNA splicing proteins. PLoS One. (2013)
PubMed: 23520512 DOI: 10.1371/journal.pone.0058456
Ohta S et al., The protein composition of mitotic chromosomes determined using multiclassifier combinatorial proteomics. Cell. (2010)
PubMed: 20813266 DOI: 10.1016/j.cell.2010.07.047
Ly T et al., A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells. Elife. (2014)
PubMed: 24596151 DOI: 10.7554/eLife.01630
Pagliuca FW et al., Quantitative proteomics reveals the basis for the biochemical specificity of the cell-cycle machinery. Mol Cell. (2011)
PubMed: 21816347 DOI: 10.1016/j.molcel.2011.05.031
Ly T et al., Proteomic analysis of the response to cell cycle arrests in human myeloid leukemia cells. Elife. (2015)
PubMed: 25555159 DOI: 10.7554/eLife.04534
Dueck H et al., Variation is function: Are single cell differences functionally important?: Testing the hypothesis that single cell variation is required for aggregate function. Bioessays. (2016)
PubMed: 26625861 DOI: 10.1002/bies.201500124
Snijder B et al., Origins of regulated cell-to-cell variability. Nat Rev Mol Cell Biol. (2011)
PubMed: 21224886 DOI: 10.1038/nrm3044
Thul PJ et al., A subcellular map of the human proteome. Science. (2017)
PubMed: 28495876 DOI: 10.1126/science.aal3321
Cooper S et al., Membrane-elution analysis of content of cyclins A, B1, and E during the unperturbed mammalian cell cycle. Cell Div. (2007)
PubMed: 17892542 DOI: 10.1186/1747-1028-2-28
Davis PK et al., Biological methods for cell-cycle synchronization of mammalian cells. Biotechniques. (2001)
PubMed: 11414226 DOI: 10.2144/01306rv01
Domenighetti G et al., Effect of information campaign by the mass media on hysterectomy rates. Lancet. (1988)
PubMed: 2904581 DOI: 10.1016/s0140-6736(88)90943-9
Scialdone A et al., Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods. (2015)
PubMed: 26142758 DOI: 10.1016/j.ymeth.2015.06.021
Sakaue-Sawano A et al., Visualizing spatiotemporal dynamics of multicellular cell-cycle progression. Cell. (2008)
PubMed: 18267078 DOI: 10.1016/j.cell.2007.12.033
Grant GD et al., Identification of cell cycle-regulated genes periodically expressed in U2OS cells and their regulation by FOXM1 and E2F transcription factors. Mol Biol Cell. (2013)
PubMed: 24109597 DOI: 10.1091/mbc.E13-05-0264
Semple JW et al., An essential role for Orc6 in DNA replication through maintenance of pre-replicative complexes. EMBO J. (2006)
PubMed: 17053779 DOI: 10.1038/sj.emboj.7601391
Kilfoil ML et al., Stochastic variation: from single cells to superorganisms. HFSP J. (2009)
PubMed: 20514130 DOI: 10.2976/1.3223356
Ansel J et al., Cell-to-cell stochastic variation in gene expression is a complex genetic trait. PLoS Genet. (2008)
PubMed: 18404214 DOI: 10.1371/journal.pgen.1000049
Colman-Lerner A et al., Regulated cell-to-cell variation in a cell-fate decision system. Nature. (2005)
PubMed: 16170311 DOI: 10.1038/nature03998
Liberali P et al., Single-cell and multivariate approaches in genetic perturbation screens. Nat Rev Genet. (2015)
PubMed: 25446316 DOI: 10.1038/nrg3768
Elowitz MB et al., Stochastic gene expression in a single cell. Science. (2002)
PubMed: 12183631 DOI: 10.1126/science.1070919
Kaern M et al., Stochasticity in gene expression: from theories to phenotypes. Nat Rev Genet. (2005)
PubMed: 15883588 DOI: 10.1038/nrg1615
Bianconi E et al., An estimation of the number of cells in the human body. Ann Hum Biol. (2013)
PubMed: 23829164 DOI: 10.3109/03014460.2013.807878
Malumbres M., Cyclin-dependent kinases. Genome Biol. (2014)
PubMed: 25180339
Collins K et al., The cell cycle and cancer. Proc Natl Acad Sci U S A. (1997)
PubMed: 9096291
Zhivotovsky B et al., Cell cycle and cell death in disease: past, present and future. J Intern Med. (2010)
PubMed: 20964732 DOI: 10.1111/j.1365-2796.2010.02282.x
Cho RJ et al., A genome-wide transcriptional analysis of the mitotic cell cycle. Mol Cell. (1998)
PubMed: 9702192
Spellman PT et al., Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell. (1998)
PubMed: 9843569
Orlando DA et al., Global control of cell-cycle transcription by coupled CDK and network oscillators. Nature. (2008)
PubMed: 18463633 DOI: 10.1038/nature06955
Rustici G et al., Periodic gene expression program of the fission yeast cell cycle. Nat Genet. (2004)
PubMed: 15195092 DOI: 10.1038/ng1377
Uhlén M et al., Tissue-based map of the human proteome. Science (2015)
PubMed: 25613900 DOI: 10.1126/science.1260419
Nigg EA et al., The centrosome cycle: Centriole biogenesis, duplication and inherent asymmetries. Nat Cell Biol. (2011)
PubMed: 21968988 DOI: 10.1038/ncb2345
Doxsey S., Re-evaluating centrosome function. Nat Rev Mol Cell Biol. (2001)
PubMed: 11533726 DOI: 10.1038/35089575
Bornens M., Centrosome composition and microtubule anchoring mechanisms. Curr Opin Cell Biol. (2002)
PubMed: 11792541
Conduit PT et al., Centrosome function and assembly in animal cells. Nat Rev Mol Cell Biol. (2015)
PubMed: 26373263 DOI: 10.1038/nrm4062
Tollenaere MA et al., Centriolar satellites: key mediators of centrosome functions. Cell Mol Life Sci. (2015)
PubMed: 25173771 DOI: 10.1007/s00018-014-1711-3
Prosser SL et al., Centriolar satellite biogenesis and function in vertebrate cells. J Cell Sci. (2020)
PubMed: 31896603 DOI: 10.1242/jcs.239566
Rieder CL et al., The centrosome in vertebrates: more than a microtubule-organizing center. Trends Cell Biol. (2001)
PubMed: 11567874
Badano JL et al., The centrosome in human genetic disease. Nat Rev Genet. (2005)
PubMed: 15738963 DOI: 10.1038/nrg1557
Clegg JS., Properties and metabolism of the aqueous cytoplasm and its boundaries. Am J Physiol. (1984)
PubMed: 6364846
Luby-Phelps K., The physical chemistry of cytoplasm and its influence on cell function: an update. Mol Biol Cell. (2013)
PubMed: 23989722 DOI: 10.1091/mbc.E12-08-0617
Luby-Phelps K., Cytoarchitecture and physical properties of cytoplasm: volume, viscosity, diffusion, intracellular surface area. Int Rev Cytol. (2000)
PubMed: 10553280
Ellis RJ., Macromolecular crowding: obvious but underappreciated. Trends Biochem Sci. (2001)
PubMed: 11590012
Bright GR et al., Fluorescence ratio imaging microscopy: temporal and spatial measurements of cytoplasmic pH. J Cell Biol. (1987)
PubMed: 3558476
Kopito RR., Aggresomes, inclusion bodies and protein aggregation. Trends Cell Biol. (2000)
PubMed: 11121744
Aizer A et al., Intracellular trafficking and dynamics of P bodies. Prion. (2008)
PubMed: 19242093
Carcamo WC et al., Molecular cell biology and immunobiology of mammalian rod/ring structures. Int Rev Cell Mol Biol. (2014)
PubMed: 24411169 DOI: 10.1016/B978-0-12-800097-7.00002-6
Lang F., Mechanisms and significance of cell volume regulation. J Am Coll Nutr. (2007)
PubMed: 17921474
Schwarz DS et al., The endoplasmic reticulum: structure, function and response to cellular signaling. Cell Mol Life Sci. (2016)
PubMed: 26433683 DOI: 10.1007/s00018-015-2052-6
Friedman JR et al., The ER in 3D: a multifunctional dynamic membrane network. Trends Cell Biol. (2011)
PubMed: 21900009 DOI: 10.1016/j.tcb.2011.07.004
Travers KJ et al., Functional and genomic analyses reveal an essential coordination between the unfolded protein response and ER-associated degradation. Cell. (2000)
PubMed: 10847680
Roussel BD et al., Endoplasmic reticulum dysfunction in neurological disease. Lancet Neurol. (2013)
PubMed: 23237905 DOI: 10.1016/S1474-4422(12)70238-7
Neve EP et al., Cytochrome P450 proteins: retention and distribution from the endoplasmic reticulum. Curr Opin Drug Discov Devel. (2010)
PubMed: 20047148
Kulkarni-Gosavi P et al., Form and function of the Golgi apparatus: scaffolds, cytoskeleton and signalling. FEBS Lett. (2019)
PubMed: 31378930 DOI: 10.1002/1873-3468.13567
Short B et al., The Golgi apparatus. Curr Biol. (2000)
PubMed: 10985372 DOI: 10.1016/s0960-9822(00)00644-8
Wei JH et al., Unraveling the Golgi ribbon. Traffic. (2010)
PubMed: 21040294 DOI: 10.1111/j.1600-0854.2010.01114.x
Wilson C et al., The Golgi apparatus: an organelle with multiple complex functions. Biochem J. (2011)
PubMed: 21158737 DOI: 10.1042/BJ20101058
Farquhar MG et al., The Golgi apparatus: 100 years of progress and controversy. Trends Cell Biol. (1998)
PubMed: 9695800
Brandizzi F et al., Organization of the ER-Golgi interface for membrane traffic control. Nat Rev Mol Cell Biol. (2013)
PubMed: 23698585 DOI: 10.1038/nrm3588
Potelle S et al., Golgi post-translational modifications and associated diseases. J Inherit Metab Dis. (2015)
PubMed: 25967285 DOI: 10.1007/s10545-015-9851-7
Leduc C et al., Intermediate filaments in cell migration and invasion: the unusual suspects. Curr Opin Cell Biol. (2015)
PubMed: 25660489 DOI: 10.1016/j.ceb.2015.01.005
Lowery J et al., Intermediate Filaments Play a Pivotal Role in Regulating Cell Architecture and Function. J Biol Chem. (2015)
PubMed: 25957409 DOI: 10.1074/jbc.R115.640359
Robert A et al., Intermediate filament dynamics: What we can see now and why it matters. Bioessays. (2016)
PubMed: 26763143 DOI: 10.1002/bies.201500142
Fuchs E et al., Intermediate filaments: structure, dynamics, function, and disease. Annu Rev Biochem. (1994)
PubMed: 7979242 DOI: 10.1146/annurev.bi.63.070194.002021
Janmey PA et al., Viscoelastic properties of vimentin compared with other filamentous biopolymer networks. J Cell Biol. (1991)
PubMed: 2007620
Köster S et al., Intermediate filament mechanics in vitro and in the cell: from coiled coils to filaments, fibers and networks. Curr Opin Cell Biol. (2015)
PubMed: 25621895 DOI: 10.1016/j.ceb.2015.01.001
Herrmann H et al., Intermediate filaments: from cell architecture to nanomechanics. Nat Rev Mol Cell Biol. (2007)
PubMed: 17551517 DOI: 10.1038/nrm2197
Gauster M et al., Keratins in the human trophoblast. Histol Histopathol. (2013)
PubMed: 23450430 DOI: 10.14670/HH-28.817
Janke C., The tubulin code: molecular components, readout mechanisms, and functions. J Cell Biol. (2014)
PubMed: 25135932 DOI: 10.1083/jcb.201406055
Goodson HV et al., Microtubules and Microtubule-Associated Proteins. Cold Spring Harb Perspect Biol. (2018)
PubMed: 29858272 DOI: 10.1101/cshperspect.a022608
Wade RH., On and around microtubules: an overview. Mol Biotechnol. (2009)
PubMed: 19565362 DOI: 10.1007/s12033-009-9193-5
Desai A et al., Microtubule polymerization dynamics. Annu Rev Cell Dev Biol. (1997)
PubMed: 9442869 DOI: 10.1146/annurev.cellbio.13.1.83
Conde C et al., Microtubule assembly, organization and dynamics in axons and dendrites. Nat Rev Neurosci. (2009)
PubMed: 19377501 DOI: 10.1038/nrn2631
Wloga D et al., Post-translational modifications of microtubules. J Cell Sci. (2010)
PubMed: 20930140 DOI: 10.1242/jcs.063727
Schmoranzer J et al., Role of microtubules in fusion of post-Golgi vesicles to the plasma membrane. Mol Biol Cell. (2003)
PubMed: 12686609 DOI: 10.1091/mbc.E02-08-0500
Skop AR et al., Dissection of the mammalian midbody proteome reveals conserved cytokinesis mechanisms. Science. (2004)
PubMed: 15166316 DOI: 10.1126/science.1097931
Waters AM et al., Ciliopathies: an expanding disease spectrum. Pediatr Nephrol. (2011)
PubMed: 21210154 DOI: 10.1007/s00467-010-1731-7
Matamoros AJ et al., Microtubules in health and degenerative disease of the nervous system. Brain Res Bull. (2016)
PubMed: 27365230 DOI: 10.1016/j.brainresbull.2016.06.016
Jordan MA et al., Microtubules as a target for anticancer drugs. Nat Rev Cancer. (2004)
PubMed: 15057285 DOI: 10.1038/nrc1317
Nunnari J et al., Mitochondria: in sickness and in health. Cell. (2012)
PubMed: 22424226 DOI: 10.1016/j.cell.2012.02.035
Friedman JR et al., Mitochondrial form and function. Nature. (2014)
PubMed: 24429632 DOI: 10.1038/nature12985
Calvo SE et al., The mitochondrial proteome and human disease. Annu Rev Genomics Hum Genet. (2010)
PubMed: 20690818 DOI: 10.1146/annurev-genom-082509-141720
McBride HM et al., Mitochondria: more than just a powerhouse. Curr Biol. (2006)
PubMed: 16860735 DOI: 10.1016/j.cub.2006.06.054
Schaefer AM et al., The epidemiology of mitochondrial disorders--past, present and future. Biochim Biophys Acta. (2004)
PubMed: 15576042 DOI: 10.1016/j.bbabio.2004.09.005
Lange A et al., Classical nuclear localization signals: definition, function, and interaction with importin alpha. J Biol Chem. (2007)
PubMed: 17170104 DOI: 10.1074/jbc.R600026200
Ashmarina LI et al., 3-Hydroxy-3-methylglutaryl coenzyme A lyase: targeting and processing in peroxisomes and mitochondria. J Lipid Res. (1999)
PubMed: 9869651
Wang SC et al., Nuclear translocation of the epidermal growth factor receptor family membrane tyrosine kinase receptors. Clin Cancer Res. (2009)
PubMed: 19861462 DOI: 10.1158/1078-0432.CCR-08-2813
Jeffery CJ., Moonlighting proteins. Trends Biochem Sci. (1999)
PubMed: 10087914
Jeffery CJ., Why study moonlighting proteins? Front Genet. (2015)
PubMed: 26150826 DOI: 10.3389/fgene.2015.00211
Pancholi V., Multifunctional alpha-enolase: its role in diseases. Cell Mol Life Sci. (2001)
PubMed: 11497239 DOI: 10.1007/pl00000910
Chapple CE et al., Extreme multifunctional proteins identified from a human protein interaction network. Nat Commun. (2015)
PubMed: 26054620 DOI: 10.1038/ncomms8412
Dechat T et al., Nuclear lamins: major factors in the structural organization and function of the nucleus and chromatin. Genes Dev. (2008)
PubMed: 18381888 DOI: 10.1101/gad.1652708
Gruenbaum Y et al., The nuclear lamina comes of age. Nat Rev Mol Cell Biol. (2005)
PubMed: 15688064 DOI: 10.1038/nrm1550
Stuurman N et al., Nuclear lamins: their structure, assembly, and interactions. J Struct Biol. (1998)
PubMed: 9724605 DOI: 10.1006/jsbi.1998.3987
Paine PL et al., Nuclear envelope permeability. Nature. (1975)
PubMed: 1117994
Reichelt R et al., Correlation between structure and mass distribution of the nuclear pore complex and of distinct pore complex components. J Cell Biol. (1990)
PubMed: 2324201
CALLAN HG et al., Experimental studies on amphibian oocyte nuclei. I. Investigation of the structure of the nuclear membrane by means of the electron microscope. Proc R Soc Lond B Biol Sci. (1950)
PubMed: 14786306
WATSON ML., The nuclear envelope; its structure and relation to cytoplasmic membranes. J Biophys Biochem Cytol. (1955)
PubMed: 13242591
BAHR GF et al., The fine structure of the nuclear membrane in the larval salivary gland and midgut of Chironomus. Exp Cell Res. (1954)
PubMed: 13173504
Terasaki M et al., A new model for nuclear envelope breakdown. Mol Biol Cell. (2001)
PubMed: 11179431
Dultz E et al., Systematic kinetic analysis of mitotic dis- and reassembly of the nuclear pore in living cells. J Cell Biol. (2008)
PubMed: 18316408 DOI: 10.1083/jcb.200707026
Salina D et al., Cytoplasmic dynein as a facilitator of nuclear envelope breakdown. Cell. (2002)
PubMed: 11792324
Beaudouin J et al., Nuclear envelope breakdown proceeds by microtubule-induced tearing of the lamina. Cell. (2002)
PubMed: 11792323
Gerace L et al., The nuclear envelope lamina is reversibly depolymerized during mitosis. Cell. (1980)
PubMed: 7357605
Ellenberg J et al., Nuclear membrane dynamics and reassembly in living cells: targeting of an inner nuclear membrane protein in interphase and mitosis. J Cell Biol. (1997)
PubMed: 9298976
Yang L et al., Integral membrane proteins of the nuclear envelope are dispersed throughout the endoplasmic reticulum during mitosis. J Cell Biol. (1997)
PubMed: 9182656
Bione S et al., Identification of a novel X-linked gene responsible for Emery-Dreifuss muscular dystrophy. Nat Genet. (1994)
PubMed: 7894480 DOI: 10.1038/ng1294-323
Boisvert FM et al., The multifunctional nucleolus. Nat Rev Mol Cell Biol. (2007)
PubMed: 17519961 DOI: 10.1038/nrm2184
Scheer U et al., Structure and function of the nucleolus. Curr Opin Cell Biol. (1999)
PubMed: 10395554 DOI: 10.1016/S0955-0674(99)80054-4
Németh A et al., Genome organization in and around the nucleolus. Trends Genet. (2011)
PubMed: 21295884 DOI: 10.1016/j.tig.2011.01.002
Cuylen S et al., Ki-67 acts as a biological surfactant to disperse mitotic chromosomes. Nature. (2016)
PubMed: 27362226 DOI: 10.1038/nature18610
Stenström L et al., Mapping the nucleolar proteome reveals a spatiotemporal organization related to intrinsic protein disorder. Mol Syst Biol. (2020)
PubMed: 32744794 DOI: 10.15252/msb.20209469
Derenzini M et al., Nucleolar size indicates the rapidity of cell proliferation in cancer tissues. J Pathol. (2000)
PubMed: 10861579 DOI: 10.1002/(SICI)1096-9896(200006)191:2<181::AID-PATH607>3.0.CO;2-V
Visintin R et al., The nucleolus: the magician's hat for cell cycle tricks. Curr Opin Cell Biol. (2000)
PubMed: 10801456
Marciniak RA et al., Nucleolar localization of the Werner syndrome protein in human cells. Proc Natl Acad Sci U S A. (1998)
PubMed: 9618508
Tamanini F et al., The fragile X-related proteins FXR1P and FXR2P contain a functional nucleolar-targeting signal equivalent to the HIV-1 regulatory proteins. Hum Mol Genet. (2000)
PubMed: 10888599
Willemsen R et al., Association of FMRP with ribosomal precursor particles in the nucleolus. Biochem Biophys Res Commun. (1996)
PubMed: 8769090 DOI: 10.1006/bbrc.1996.1126
Isaac C et al., Characterization of the nucleolar gene product, treacle, in Treacher Collins syndrome. Mol Biol Cell. (2000)
PubMed: 10982400
Drygin D et al., The RNA polymerase I transcription machinery: an emerging target for the treatment of cancer. Annu Rev Pharmacol Toxicol. (2010)
PubMed: 20055700 DOI: 10.1146/annurev.pharmtox.010909.105844
Spector DL., Macromolecular domains within the cell nucleus. Annu Rev Cell Biol. (1993)
PubMed: 8280462 DOI: 10.1146/annurev.cb.09.110193.001405
Lamond AI et al., Structure and function in the nucleus. Science. (1998)
PubMed: 9554838
SWIFT H., Studies on nuclear fine structure. Brookhaven Symp Biol. (1959)
PubMed: 13836127
Lamond AI et al., Nuclear speckles: a model for nuclear organelles. Nat Rev Mol Cell Biol. (2003)
PubMed: 12923522 DOI: 10.1038/nrm1172
Thiry M., The interchromatin granules. Histol Histopathol. (1995)
PubMed: 8573995
Sleeman JE et al., Newly assembled snRNPs associate with coiled bodies before speckles, suggesting a nuclear snRNP maturation pathway. Curr Biol. (1999)
PubMed: 10531003
Darzacq X et al., Cajal body-specific small nuclear RNAs: a novel class of 2'-O-methylation and pseudouridylation guide RNAs. EMBO J. (2002)
PubMed: 12032087 DOI: 10.1093/emboj/21.11.2746
Jády BE et al., Modification of Sm small nuclear RNAs occurs in the nucleoplasmic Cajal body following import from the cytoplasm. EMBO J. (2003)
PubMed: 12682020 DOI: 10.1093/emboj/cdg187
Liu Q et al., A novel nuclear structure containing the survival of motor neurons protein. EMBO J. (1996)
PubMed: 8670859
Lefebvre S et al., Identification and characterization of a spinal muscular atrophy-determining gene. Cell. (1995)
PubMed: 7813012
Fischer U et al., The SMN-SIP1 complex has an essential role in spliceosomal snRNP biogenesis. Cell. (1997)
PubMed: 9323130
Lallemand-Breitenbach V et al., PML nuclear bodies. Cold Spring Harb Perspect Biol. (2010)
PubMed: 20452955 DOI: 10.1101/cshperspect.a000661
Booth DG et al., Ki-67 and the Chromosome Periphery Compartment in Mitosis. Trends Cell Biol. (2017)
PubMed: 28838621 DOI: 10.1016/j.tcb.2017.08.001
Ljungberg O et al., A compound follicular-parafollicular cell carcinoma of the thyroid: a new tumor entity? Cancer. (1983)
PubMed: 6136320 DOI: 10.1002/1097-0142(19830915)52:6<1053::aid-cncr2820520621>3.0.co;2-q
Melcák I et al., Nuclear pre-mRNA compartmentalization: trafficking of released transcripts to splicing factor reservoirs. Mol Biol Cell. (2000)
PubMed: 10679009
Spector DL et al., Associations between distinct pre-mRNA splicing components and the cell nucleus. EMBO J. (1991)
PubMed: 1833187
Misteli T et al., Protein phosphorylation and the nuclear organization of pre-mRNA splicing. Trends Cell Biol. (1997)
PubMed: 17708924 DOI: 10.1016/S0962-8924(96)20043-1
Cmarko D et al., Ultrastructural analysis of transcription and splicing in the cell nucleus after bromo-UTP microinjection. Mol Biol Cell. (1999)
PubMed: 9880337
Van Hooser AA et al., The perichromosomal layer. Chromosoma. (2005)
PubMed: 16136320 DOI: 10.1007/s00412-005-0021-9
Booth DG et al., Ki-67 is a PP1-interacting protein that organises the mitotic chromosome periphery. Elife. (2014)
PubMed: 24867636 DOI: 10.7554/eLife.01641
Kau TR et al., Nuclear transport and cancer: from mechanism to intervention. Nat Rev Cancer. (2004)
PubMed: 14732865 DOI: 10.1038/nrc1274
Laurila K et al., Prediction of disease-related mutations affecting protein localization. BMC Genomics. (2009)
PubMed: 19309509 DOI: 10.1186/1471-2164-10-122
Park S et al., Protein localization as a principal feature of the etiology and comorbidity of genetic diseases. Mol Syst Biol. (2011)
PubMed: 21613983 DOI: 10.1038/msb.2011.29
Christoforou A et al., A draft map of the mouse pluripotent stem cell spatial proteome. Nat Commun. (2016)
PubMed: 26754106 DOI: 10.1038/ncomms9992
Itzhak DN et al., Global, quantitative and dynamic mapping of protein subcellular localization. Elife. (2016)
PubMed: 27278775 DOI: 10.7554/eLife.16950
Roux KJ et al., A promiscuous biotin ligase fusion protein identifies proximal and interacting proteins in mammalian cells. J Cell Biol. (2012)
PubMed: 22412018 DOI: 10.1083/jcb.201112098
Lee SY et al., APEX Fingerprinting Reveals the Subcellular Localization of Proteins of Interest. Cell Rep. (2016)
PubMed: 27184847 DOI: 10.1016/j.celrep.2016.04.064
Huh WK et al., Global analysis of protein localization in budding yeast. Nature. (2003)
PubMed: 14562095 DOI: 10.1038/nature02026
Simpson JC et al., Systematic subcellular localization of novel proteins identified by large-scale cDNA sequencing. EMBO Rep. (2000)
PubMed: 11256614 DOI: 10.1093/embo-reports/kvd058
Stadler C et al., Immunofluorescence and fluorescent-protein tagging show high correlation for protein localization in mammalian cells. Nat Methods. 2013 Apr;10(4):315-23 (2013)
PubMed: 23435261 DOI: 10.1038/nmeth.2377
Barbe L et al., Toward a confocal subcellular atlas of the human proteome. Mol Cell Proteomics. (2008)
PubMed: 18029348 DOI: 10.1074/mcp.M700325-MCP200
Stadler C et al., A single fixation protocol for proteome-wide immunofluorescence localization studies. J Proteomics. (2010)
PubMed: 19896565 DOI: 10.1016/j.jprot.2009.10.012
Fagerberg L et al., Mapping the subcellular protein distribution in three human cell lines. J Proteome Res. (2011)
PubMed: 21675716 DOI: 10.1021/pr200379a
Baker M., Reproducibility crisis: Blame it on the antibodies. Nature. (2015)
PubMed: 25993940 DOI: 10.1038/521274a