Vesicles

Vesicles is a collective term for cytoplasmic organelles that are often too small to have distinct features when imaged by light microscopy. The majority of the vesicles are membrane-bound organelles, however, also large protein complexes and cytosolic bodies can fall under this category, as they are difficult to distinguish. Examples of organelles with a vesicle annotation are the members of the endolysosomal pathway, transport vesicles, peroxisomes, and lipid droplets.

In the subcellular section, 2298 genes (11% of all protein-coding human genes) have been shown to encode proteins that localize to vesicles (Figure 2). A Gene Ontology (GO)-based functional enrichment analysis of the vesicle proteome shows enrichment of terms related to lipid metabolism, organization of vesicular organelles, protein transport, endocytosis and exocytosis. About 67% (n=1543) of the vesicle proteins localize to one or more additional compartments, with the plasma membrane, the endoplasmic reticulum and the Golgi apparatus being over represented. Examples of proteins that localize to vesicles can be seen in Figure 1.

SNX1 - HeLa
CLTA - U-251MG
AP2B1 - U2OS

Figure 1. Examples of proteins localized to vesicles. SNX1 is part of the retromer complex that mediates the retrograde transport of cargo proteins from endosomes to the trans-Golgi network (TGN) and is involved in endosome-to-plasma membrane transport for cargo protein recycling (detected in HeLa cells). CLTA is a structural element in clathrin-coated vesicles, which are required for the receptor-mediated endocytosis at the plasma membrane (detected in U-251 MG cells). AP2B1 is a component of the adaptor protein complex 2, which is involved in clathrin-dependent endocytosis (detected in U2OS cells).

Figure 2. 11% of all human protein-coding genes encode proteins localized to vesicles. Each bar is clickable and gives a search result of proteins that belong to the selected category.

The structure of vesicles

Substructures

• Vesicles: 2228
• Peroxisomes: 23
• Endosomes: 17
• Lysosomes: 19
• Lipid droplets: 39

The general structure of organelles annotated as vesicles is a round membrane-enclosed lumen that is less than 1 μm in diameter. There are a few differences in the appearance and distribution of vesicles that can allow further classification (Figure 3), but the true identity of the organelle is often only revealed by co-staining with specific marker proteins in immunofluorescence (IF) images.

Endosomes are membrane-bound compartments that can be further sub-classified into early, recycling, and late endosomes, but there is a continuous transition between these classes. Each of them can be defined by their function, by a distinct set of proteins, and/or by morphological differences. Early endosomes (EE) have a pleomorphic structure, consisting of cisternae from which two distinct subdomains emerge: large vesicular structures (300-400 nm diameter) with internal invaginations and thinner tubular extensions (60 nm diameter) (Gruenberg J. (2001)). Tubular extensions give rise to recycling endosomes (RE), which retain a tubular appearance and are typically located close to the microtubule organizing center (MTOC). The large vesicular compartments of early endosomes give rise to multivesicular bodies that mediate transport to, or matures into, late endosomes. Late endosomes (LE) are again highly complex, with cisternal, tubular, and vesicular regions with numerous membrane invaginations and luminal vesicles (Griffiths G et al. (1988)).

Lysosomes were discovered by the Belgian Nobel laureate de Duve in 1955 and are named after the richness in hydrolytic enzymes. Lysosomes have a tubular morphology of about 0.1-1.2 μm in size and a characteristic acidic pH-value of 4.5-5, which is ideal for the enzymes contained in the lysosomal lumen. The membrane of lysosomes is rich in glycoproteins and consists of an unusual lipid composition that provides protection from the digestive enzymes (Schwake M et al. (2013)).

Peroxisomes were also discovered by de Duve, but not until 1966, and he named them so because of their involvement in peroxidase reactions. Peroxisomes originate from the ER, but they are also able to replicate themselves by division. They differ in size from 0.1-1 μm and have a dynamic structure. The shape is usually spherical, but can change and become more elongated prior to peroxisome division or in adaptation to different conditions, which can help to distinguish peroxisomes from other vesicles in IF (Smith JJ et al. (2013)).

Lipid droplets (LDs) have been known for a long time, but were believed to be a rather inert storage for lipids. The discovery of the first LD-associated protein in 1991 by Londos and coworkers (Greenberg AS et al. (1991)) changed this view, and today LDs are considered organelles. LDs originate from the ER and have a simple, yet conserved structure: a hydrophobic core containing lipids surrounded by a membrane monolayer (instead of a bilayer found in all other organelles) to which proteins are attached (Walther TC et al. (2012)). The size of LDs ranges from hundreds of nanometers to the single 100 micrometer large LD that fills adipocytes. Under normal conditions, cells have no or only a few small LDs, but if those few LDs are large enough, LD-associated proteins appear in perfectly round rings and the protein location can be annotated more precisely.

A list of proteins that are suitable as markers for vesicles can be found in Table 1. Highly expressed genes encoding proteins that localize to vesicles are listed in Table 2.

Table 1. Selection of proteins suitable as markers for different vesicular organelles.

Table 2. Highly expressed single localizing proteins with a vesicular staining across different cell lines.

RAB5C - U2OS
LAMTOR4 - U2OS
ABCD3 - A-431

PLIN3 - A-431
EPS15L1 - MCF-7
REX1BD - U2OS

Figure 3. Examples of the different types of vesicles found in the subcellular section. Endosomal protein RAB5C in U2OS cells. Lysosomal protein LAMTOR4 in U2OS cells. Peroxisomal protein ABCD3 in A-431 cells. LD-associated protein PLIN3 in A-431 cells. Clathrin-coated vesicle protein EPS15L1 in MCF7 cells. Vesicle-front forming protein REX1BD in U2OS cells.

Figure 4. 3D-view of peroxisomes in U2OS, visualized by immunofluorescent staining of ABCD3. The morphology of Endosomes, Lysosomes, and Peroxisomes in human induced stem cells can be seen in the Allen Cell Explorer.

The function of vesicles

The function of vescles varies with the type. Endocytosis is a process by which cells internalize extracellular solutes, ligands and proteins as well as lipids and proteins located in the plasma membrane (Gruenberg J. (2001)). Endocytic vesicles are typically transported to early endosomes, where efficient sorting takes place. Some lipids and membrane proteins are recycled back to the plasma membrane, either by direct routes or via recycling endosomes (Taguchi T. (2013)). Other cargo molecules enter the retrograde pathway and are delivered to the Golgi apparatus (Bonifacino JS et al. (2006)). Proteins and lipids destined for degradation are instead transported to late endosomes, which then fuse with lysosomes. Lysosomes also receive materials taken up from the cytosol by autophagy, and contain a large spectrum of enzymes for degrading both proteins, nucleic acids and carbohydrates.

Peroxisomes are multifunctional organelles that harbor a variety of enzymes. The main function of peroxisomes is β-oxidation of long- and very long-chain fatty acids. They also contribute to the utilization and production of reactive oxygen species in the cell. In addition, peroxisomes carry out other important anabolic and catabolic reactions, such as phospholipid biosynthesis, chemical detoxification or oxidation of purines, polyamines, and some amino acids (Antonenkov VD et al. (2010)).

Nearly all cells are able to form LDs and use them as the main storage site for cellular neutral lipids. These lipids, which are mainly triacylglycerol and cholesterol, are utilized for the generation of energy and serve as building blocks for the synthesis of other lipids. LDs have been linked to a growing number of diseases, but most prominent is their role in obesity and diabetes (Walther TC et al. (2012)).

Gene Ontology (GO)-based enrichment analysis of genes encoding proteins that localize to vesicles reveals several functions associated with this group of organelles. The highly enriched terms for the GO domain Biological Process are related mainly to structural organization and function of various vesicles, vesicle-mediated transport, lipid metabolism, antigen presentation and certain cell signaling pathways (Figure 5a). For the GO domain Molecular Function, genes encoding vesicle proteins are enriched for functions related to transporter activity, lipid transfer activity, receptor binding and receptor activities, and binding to proteins that are involved in vesicle formation and fusion, such as clathrin and SNARES (Figure 5b).

Figure 5a Gene Ontology-based enrichment analysis for the vesicles proteome showing the significantly enriched terms for the GO domain Biological Process. Each bar is clickable and gives a search result of proteins that belong to the selected category.

Figure 5b Gene Ontology-based enrichment analysis for the vesicles proteome showing the significantly enriched terms for the GO domain Molecular Function. Each bar is clickable and gives a search result of proteins that belong to the selected category.

Vesicle proteins with multiple locations

Approximately 67% (n=1543) of the proteins that localize to vesicles in the subcellular section also localize to other compartments in the cell. The network plot (Figure 6) shows that the additional locations that are overrepresented in combination with vesicles are the plasma membrane, the ER, and the Golgi apparatus. Given the function of vesicles, co-localization of proteins to the ER and Golgi apparatus is in agreement with their role in the secretory pathway. Examples of multilocalizing proteins within the proteome of vesicles can be seen in Figure 7.

Figure 6. Interactive network plot of vesicle-associated proteins with multiple localizations. The numbers in the connecting nodes show the proteins that are localized to vesicles and to one or more additional locations. Only connecting nodes containing more than one protein and at least 0.7% of proteins in the vesicle proteome are shown. The circle sizes are related to the number of proteins. The cyan colored nodes show combinations that are significantly overrepresented, while magenta colored nodes show combinations that are significantly underrepresented as compared to the probability of observing that combination based on the frequency of each annotation and a hypergeometric test (p≤0.05). Note that this calculation is only done for proteins with dual localizations. Each node is clickable and results in a list of all proteins that are found in the connected organelles.

VTI1B - U2OS
GPRC5A - U2OS
EPN3 - HaCaT

Figure 7. Examples of multilocalizing proteins in the vesicle proteome. The examples show common or overrepresented combinations for multilocalizing proteins in the proteome. VTI1B promotes the fusion of vesicles with the target membrane at the Golgi apparatus (detected in U2OS cells). GPRC5A, detected at the plasma membrane and vesicles, is an orphan receptor, which might be involved in the interaction between retinoic acid and G-protein signaling pathways (detected in U2OS cells). EPN3 co-localizes with clathrin-coated vesicles and shuttles into the nucleus (detected in HaCaT cells).

Expression levels of vesicle proteins in tissue

Transcriptome analysis and classification of genes into tissue distribution categories (Figure 8) shows that a larger portion of genes that encode proteins localizing to vesicles are detected in some or in many tissues, while a smaller portion are detected in all tissues or non-detected, compared to all genes presented in the subcellular section. This may reflect a variety of partially tissue-specific functions involving vesicle proteins, particularly in the transport of secretory proteins and other biomolecules to the extracellular space.

Figure 8. Bar plot showing the percentage of genes in different tissue distribution categories for vesicle-associated protein-coding genes, compared to all genes in the subcellular section. Asterisk marks a statistically significant deviation (p≤0.05) in the number of genes in a category based on a binomial statistical test. Each bar is clickable and gives a search result of proteins that belong to the selected category.

Relevant links and publications

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

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

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

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

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

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

Lukassen S et al., SARS-CoV-2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells. EMBO J. (2020)
PubMed: 32246845 DOI: 10.15252/embj.20105114

De Micheli AJ et al., A reference single-cell transcriptomic atlas of human skeletal muscle tissue reveals bifurcated muscle stem cell populations. Skelet Muscle. (2020)
PubMed: 32624006 DOI: 10.1186/s13395-020-00236-3

Hildreth AD et al., Single-cell sequencing of human white adipose tissue identifies new cell states in health and obesity. Nat Immunol. (2021)
PubMed: 33907320 DOI: 10.1038/s41590-021-00922-4

He S et al., Single-cell transcriptome profiling of an adult human cell atlas of 15 major organs. Genome Biol. (2020)
PubMed: 33287869 DOI: 10.1186/s13059-020-02210-0

Tabula Sapiens Consortium* et al., The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans. Science. (2022)
PubMed: 35549404 DOI: 10.1126/science.abl4896

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

Bhat-Nakshatri P et al., A single-cell atlas of the healthy breast tissues reveals clinically relevant clusters of breast epithelial cells. Cell Rep Med. (2021)
PubMed: 33763657 DOI: 10.1016/j.xcrm.2021.100219

Man L et al., Comparison of Human Antral Follicles of Xenograft versus Ovarian Origin Reveals Disparate Molecular Signatures. Cell Rep. (2020)
PubMed: 32783948 DOI: 10.1016/j.celrep.2020.108027

Guo J et al., The adult human testis transcriptional cell atlas. Cell Res. (2018)
PubMed: 30315278 DOI: 10.1038/s41422-018-0099-2

Wang W et al., Single-cell transcriptomic atlas of the human endometrium during the menstrual cycle. Nat Med. (2020)
PubMed: 32929266 DOI: 10.1038/s41591-020-1040-z

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

Uhlén M et al., The human secretome. Sci Signal. (2019)
PubMed: 31772123 DOI: 10.1126/scisignal.aaz0274

Uhlen M et al., A genome-wide transcriptomic analysis of protein-coding genes in human blood cells. Science. (2019)
PubMed: 31857451 DOI: 10.1126/science.aax9198

Zhong W et al., The neuropeptide landscape of human prefrontal cortex. Proc Natl Acad Sci U S A. (2022)
PubMed: 35947618 DOI: 10.1073/pnas.2123146119

Sjöstedt E et al., An atlas of the protein-coding genes in the human, pig, and mouse brain. Science. (2020)
PubMed: 32139519 DOI: 10.1126/science.aay5947

Schubert M et al., Perturbation-response genes reveal signaling footprints in cancer gene expression. Nat Commun. (2018)
PubMed: 29295995 DOI: 10.1038/s41467-017-02391-6

Jiang P et al., Systematic investigation of cytokine signaling activity at the tissue and single-cell levels. Nat Methods. (2021)
PubMed: 34594031 DOI: 10.1038/s41592-021-01274-5

Jin L et al., Targeting of CD44 eradicates human acute myeloid leukemic stem cells. Nat Med. (2006)
PubMed: 16998484 DOI: 10.1038/nm1483

Magis AT et al., Untargeted longitudinal analysis of a wellness cohort identifies markers of metastatic cancer years prior to diagnosis. Sci Rep. (2020)
PubMed: 33004987 DOI: 10.1038/s41598-020-73451-z

Santarius T et al., GLO1-A novel amplified gene in human cancer. Genes Chromosomes Cancer. (2010)
PubMed: 20544845 DOI: 10.1002/gcc.20784

Berggrund M et al., Identification of Candidate Plasma Protein Biomarkers for Cervical Cancer Using the Multiplex Proximity Extension Assay. Mol Cell Proteomics. (2019)
PubMed: 30692274 DOI: 10.1074/mcp.RA118.001208

Virgilio L et al., Deregulated expression of TCL1 causes T cell leukemia in mice. Proc Natl Acad Sci U S A. (1998)
PubMed: 9520462 DOI: 10.1073/pnas.95.7.3885

Saberi Hosnijeh F et al., Proteomic markers with prognostic impact on outcome of chronic lymphocytic leukemia patients under chemo-immunotherapy: results from the HOVON 109 study. Exp Hematol. (2020)
PubMed: 32781097 DOI: 10.1016/j.exphem.2020.08.002

Gao L et al., Integrative analysis the characterization of peroxiredoxins in pan-cancer. Cancer Cell Int. (2021)
PubMed: 34246267 DOI: 10.1186/s12935-021-02064-x

Satelli A et al., Galectin-4 functions as a tumor suppressor of human colorectal cancer. Int J Cancer. (2011)
PubMed: 21064109 DOI: 10.1002/ijc.25750

Harlid S et al., A two-tiered targeted proteomics approach to identify pre-diagnostic biomarkers of colorectal cancer risk. Sci Rep. (2021)
PubMed: 33664295 DOI: 10.1038/s41598-021-83968-6

Sun X et al., Prospective Proteomic Study Identifies Potential Circulating Protein Biomarkers for Colorectal Cancer Risk. Cancers (Basel). (2022)
PubMed: 35805033 DOI: 10.3390/cancers14133261

Bhardwaj M et al., Comparison of Proteomic Technologies for Blood-Based Detection of Colorectal Cancer. Int J Mol Sci. (2021)
PubMed: 33530402 DOI: 10.3390/ijms22031189

Chen H et al., Head-to-Head Comparison and Evaluation of 92 Plasma Protein Biomarkers for Early Detection of Colorectal Cancer in a True Screening Setting. Clin Cancer Res. (2015)
PubMed: 26015516 DOI: 10.1158/1078-0432.CCR-14-3051

Thorsen SB et al., Detection of serological biomarkers by proximity extension assay for detection of colorectal neoplasias in symptomatic individuals. J Transl Med. (2013)
PubMed: 24107468 DOI: 10.1186/1479-5876-11-253

Mahboob S et al., A novel multiplexed immunoassay identifies CEA, IL-8 and prolactin as prospective markers for Dukes' stages A-D colorectal cancers. Clin Proteomics. (2015)
PubMed: 25987887 DOI: 10.1186/s12014-015-9081-x

He W et al., Attenuation of TNFSF10/TRAIL-induced apoptosis by an autophagic survival pathway involving TRAF2- and RIPK1/RIP1-mediated MAPK8/JNK activation. Autophagy. (2012)
PubMed: 23051914 DOI: 10.4161/auto.22145

Enroth S et al., A two-step strategy for identification of plasma protein biomarkers for endometrial and ovarian cancer. Clin Proteomics. (2018)
PubMed: 30519148 DOI: 10.1186/s12014-018-9216-y

Jung CS et al., Serum GFAP is a diagnostic marker for glioblastoma multiforme. Brain. (2007)
PubMed: 17998256 DOI: 10.1093/brain/awm263

Jaworski DM et al., BEHAB (brain enriched hyaluronan binding) is expressed in surgical samples of glioma and in intracranial grafts of invasive glioma cell lines. Cancer Res. (1996)
PubMed: 8625302 

Zhang X et al., CEACAM5 stimulates the progression of non-small-cell lung cancer by promoting cell proliferation and migration. J Int Med Res. (2020)
PubMed: 32993395 DOI: 10.1177/0300060520959478

Xu F et al., A Linear Discriminant Analysis Model Based on the Changes of 7 Proteins in Plasma Predicts Response to Anlotinib Therapy in Advanced Non-Small Cell Lung Cancer Patients. Front Oncol. (2021)
PubMed: 35070967 DOI: 10.3389/fonc.2021.756902

Dagnino S et al., Prospective Identification of Elevated Circulating CDCP1 in Patients Years before Onset of Lung Cancer. Cancer Res. (2021)
PubMed: 33574093 DOI: 10.1158/0008-5472.CAN-20-3454

Wik L et al., Proximity Extension Assay in Combination with Next-Generation Sequencing for High-throughput Proteome-wide Analysis. Mol Cell Proteomics. (2021)
PubMed: 34715355 DOI: 10.1016/j.mcpro.2021.100168

Zeiler M et al., A Protein Epitope Signature Tag (PrEST) library allows SILAC-based absolute quantification and multiplexed determination of protein copy numbers in cell lines. Mol Cell Proteomics. (2012)
PubMed: 21964433 DOI: 10.1074/mcp.O111.009613

Peng Y et al., Identification of key biomarkers associated with cell adhesion in multiple myeloma by integrated bioinformatics analysis. Cancer Cell Int. (2020)
PubMed: 32581652 DOI: 10.1186/s12935-020-01355-z

Gyllensten U et al., Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer. Cancers (Basel). (2022)
PubMed: 35406529 DOI: 10.3390/cancers14071757

Enroth S et al., High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer. Commun Biol. (2019)
PubMed: 31240259 DOI: 10.1038/s42003-019-0464-9

Wang Z et al., DNER promotes epithelial-mesenchymal transition and prevents chemosensitivity through the Wnt/β-catenin pathway in breast cancer. Cell Death Dis. (2020)
PubMed: 32811806 DOI: 10.1038/s41419-020-02903-1

Liu S et al., Discovery of CASP8 as a potential biomarker for high-risk prostate cancer through a high-multiplex immunoassay. Sci Rep. (2021)
PubMed: 33828176 DOI: 10.1038/s41598-021-87155-5

Robinson JL et al., An atlas of human metabolism. Sci Signal. (2020)
PubMed: 32209698 DOI: 10.1126/scisignal.aaz1482

Uhlen M et al., A pathology atlas of the human cancer transcriptome. Science. (2017)
PubMed: 28818916 DOI: 10.1126/science.aan2507

Hikmet F et al., The protein expression profile of ACE2 in human tissues. Mol Syst Biol. (2020)
PubMed: 32715618 DOI: 10.15252/msb.20209610

Gordon DE et al., A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature. (2020)
PubMed: 32353859 DOI: 10.1038/s41586-020-2286-9

Karlsson M et al., A single-cell type transcriptomics map of human tissues. Sci Adv. (2021)
PubMed: 34321199 DOI: 10.1126/sciadv.abh2169

Jumper J et al., Highly accurate protein structure prediction with AlphaFold. Nature. (2021)
PubMed: 34265844 DOI: 10.1038/s41586-021-03819-2

Varadi M et al., AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Nucleic Acids Res. (2022)
PubMed: 34791371 DOI: 10.1093/nar/gkab1061

Berman HM et al., The Protein Data Bank. Nucleic Acids Res. (2000)
PubMed: 10592235 DOI: 10.1093/nar/28.1.235

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

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

Mahdessian D et al., Spatiotemporal dissection of the cell cycle with single-cell proteogenomics. Nature. (2021)
PubMed: 33627808 DOI: 10.1038/s41586-021-03232-9

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

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 

Becht E et al., Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. (2018)
PubMed: 30531897 DOI: 10.1038/nbt.4314

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

Yoon TY et al., SNARE complex assembly and disassembly. Curr Biol. (2018)
PubMed: 29689222 DOI: 10.1016/j.cub.2018.01.005

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

Ouyang W et al., Analysis of the Human Protein Atlas Image Classification competition. Nat Methods. (2019)
PubMed: 31780840 DOI: 10.1038/s41592-019-0658-6

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

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

Jacobson K et al., The Lateral Organization and Mobility of Plasma Membrane Components. Cell. (2019)
PubMed: 31051105 DOI: 10.1016/j.cell.2019.04.018

Kobayashi T et al., Transbilayer lipid asymmetry. Curr Biol. (2018)
PubMed: 29689220 DOI: 10.1016/j.cub.2018.01.007

Krapf D., Compartmentalization of the plasma membrane. Curr Opin Cell Biol. (2018)
PubMed: 29656224 DOI: 10.1016/j.ceb.2018.04.002

Garcia MA et al., Cell-Cell Junctions Organize Structural and Signaling Networks. Cold Spring Harb Perspect Biol. (2018)
PubMed: 28600395 DOI: 10.1101/cshperspect.a029181

Orlando K et al., Membrane organization and dynamics in cell polarity. Cold Spring Harb Perspect Biol. (2009)
PubMed: 20066116 DOI: 10.1101/cshperspect.a001321

Eaton RC et al., D2 receptors in the paraventricular nucleus regulate genital responses and copulation in male rats. Pharmacol Biochem Behav. (1991)
PubMed: 1833780 DOI: 10.1016/0091-3057(91)90418-2

Simons K et al., Cholesterol, lipid rafts, and disease. J Clin Invest. (2002)
PubMed: 12208858 DOI: 10.1172/JCI16390

von Heijne G., Signal sequences. The limits of variation. J Mol Biol. (1985)
PubMed: 4032478 

Johnson AE et al., The translocon: a dynamic gateway at the ER membrane. Annu Rev Cell Dev Biol. (1999)
PubMed: 10611978 DOI: 10.1146/annurev.cellbio.15.1.799

Farhan H et al., Signalling to and from the secretory pathway. J Cell Sci. (2011)
PubMed: 21187344 DOI: 10.1242/jcs.076455

Wishart DS et al., DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res. (2006)
PubMed: 16381955 DOI: 10.1093/nar/gkj067

Emanuelsson O et al., Locating proteins in the cell using TargetP, SignalP and related tools. Nat Protoc. (2007)
PubMed: 17446895 DOI: 10.1038/nprot.2007.131

Petersen TN et al., SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods. (2011)
PubMed: 21959131 DOI: 10.1038/nmeth.1701

Käll L et al., A combined transmembrane topology and signal peptide prediction method. J Mol Biol. (2004)
PubMed: 15111065 DOI: 10.1016/j.jmb.2004.03.016

Viklund H et al., SPOCTOPUS: a combined predictor of signal peptides and membrane protein topology. Bioinformatics. (2008)
PubMed: 18945683 DOI: 10.1093/bioinformatics/btn550

Fagerberg L et al., Prediction of the human membrane proteome. Proteomics. (2010)
PubMed: 20175080 DOI: 10.1002/pmic.200900258

Gruenberg J., The endocytic pathway: a mosaic of domains. Nat Rev Mol Cell Biol. (2001)
PubMed: 11584299 DOI: 10.1038/35096054

Griffiths G et al., The mannose 6-phosphate receptor and the biogenesis of lysosomes. Cell. (1988)
PubMed: 2964276 

Schwake M et al., Lysosomal membrane proteins and their central role in physiology. Traffic. (2013)
PubMed: 23387372 DOI: 10.1111/tra.12056

Smith JJ et al., Peroxisomes take shape. Nat Rev Mol Cell Biol. (2013)
PubMed: 24263361 DOI: 10.1038/nrm3700

Greenberg AS et al., Perilipin, a major hormonally regulated adipocyte-specific phosphoprotein associated with the periphery of lipid storage droplets. J Biol Chem. (1991)
PubMed: 2040638 

Walther TC et al., Lipid droplets and cellular lipid metabolism. Annu Rev Biochem. (2012)
PubMed: 22524315 DOI: 10.1146/annurev-biochem-061009-102430

Taguchi T., Emerging roles of recycling endosomes. J Biochem. (2013)
PubMed: 23625997 DOI: 10.1093/jb/mvt034

Bonifacino JS et al., Retrograde transport from endosomes to the trans-Golgi network. Nat Rev Mol Cell Biol. (2006)
PubMed: 16936697 DOI: 10.1038/nrm1985

Antonenkov VD et al., Peroxisomes are oxidative organelles. Antioxid Redox Signal. (2010)
PubMed: 19958170 DOI: 10.1089/ars.2009.2996