Secreted proteins

Secreted proteins, together forming the secretome, can be defined as proteins that are actively transported out of the cell. In humans, cells such as endocrine cells and B-lymphocytes are specialized in protein secretion, but all cells secrete proteins to a certain extent. Proteins that are secreted from the cell play a crucial role in many physiological, developmental and pathological processes and are important for both intercellular and intracellular communication. In addition to being a rich source of new therapeutics and drug targets, a large fraction of the blood diagnostic tests used in the clinic are directed towards secreted proteins, emphasizing the importance of this class of proteins for medicine and biology. Medically important secreted proteins include cytokines, coagulation factors, growth factors and other signaling molecules. We predict that 1903 proteins, or 9% of the human proteome, are secreted based on results from multiple prediction methods.

Function of the secretory pathway

The most common pathway for transportation of proteins out of the cell is the secretory pathway (Figure 1). Newly synthetized proteins are transported from the endoplasmic reticulum (ER), passing the Golgi apparatus and packed into vesicles. The vesicles are then transported to the plasma membrane, where membrane fusion results in release of the proteins into the extracellular space (exocytosis). The signal sequence that targets proteins destined for secretion to the ER is called a signal peptide (SP) and consists of a short hydrophobic N-terminal sequence (von Heijne G. (1985)). However, SPs can also present in proteins that are destined for compartments in the sectretory pathway, such as the ER, the Golgi apparatus, different kind of vesicles and the plasma membrane. The SP is recognized by chaperone proteins, together forming a signal recognition particle (SRP), that guide the synthesizing ribosomes to the rough ER. At the ER membrane co-translational translocation of the newly synthesized peptide occurs with the help of a protein complex referred to as the translocon, resulting in release of the newly synthesized protein into the ER lumen (Johnson AE et al. (1999)). Proteins that pass the quality control in the ER lumen are transported via vesicles to the Golgi apparatus, where they are further modified and sorted for transport to their final destination, most commonly the plasma membrane, lysosomes or secretion to the extracellular space.

Figure 1. Overview of the secretory pathway.

The functions of secreted proteins are diverse, but cell signalling is an important example. Signaling between or within cells via secreted signaling molecules can be paracrine, autocrine, endocrine or neuroendocrine depending on the target. Among the most important signaling proteins are cytokines, kinases, hormones and growth factors (Farhan H et al. (2011)).

A large fraction of the clinically approved treatment regimens today use drugs directed towards (or consisting of) secreted proteins or cell surface-associated membrane proteins. Out of the 812 protein targets with known pharmacological action for approved drugs on the market at present (Wishart DS et al. (2006)), 109 are predicted to be secreted.

Secreted proteins are often enriched in the organelles of the secretory pathway (ER, Golgi apparatus, vesicles), before they are released to the extracellular matrix. This enables a detection of the protein by IF, although their final destination lies outside of the cell. In Figure 2, IF images of three predicted secreted proteins are shown.

CHGB - SH-SY5Y
SCG3 - SH-SY5Y
NPY - SH-SY5Y

Figure 2. Examples of three different predicted secreted proteins are shown in the neuron-like SH-SY5Y cell line: CHGB and SCG3 are found in secretory vesicles, while NPY is enriched in the Golgi apparatus.

Prediction of secreted proteins

Secreted proteins can often be identified based on their SPs, which have a number of features suitable for computational prediction models. The SP is typically 15-30 amino acids long and primarily recognized by a short hydrophobic and mostly positive N-terminal alpha-helix (n-region) combined with a hydrophobic h-region and a C-terminal polar uncharged c-region (Emanuelsson O et al. (2007)). There are many algorithms which use these features to predict the presence of SPs in proteins, and there are also a number of methods which incorporate a SP prediction model into transmembrane (TM) topology prediction algorithms, to allow for more reliable results when it comes to distinguishing an SP and a TM segment.

The human 'secretome' can be defined as all genes encoding at least one secreted protein and has been analyzed here by performing a whole-proteome scan using three methods for SP prediction: SignalP4.0 (Petersen TN et al. (2011); Käll L et al. (2004)), Phobius and SPOCTOPUS (Viklund H et al. (2008)), which have all been shown to give reliable prediction results in comparative analyses. A majority decision-based method (MDSEC) has been constructed using the results from the three different SP prediction methods to obtain a list of predicted secreted proteins (Uhlén M et al. (2015)). We selected all proteins with a predicted SP by at least two of the three methods and annotated these further in order to exclude genes that are predicted to reside in intracellular locations such as ER or Golgi, despite having a signal peptide prediction. In order to achive this, the genes predicted to encode protein with an SP were filtered using the majority decision-based method (MDM) for membrane protein topology prediction (Fagerberg L et al. (2010)). All proteins with a predicted SP in combination with a predicted TM region according to the MDM were considered membrane-spanning and therefore not secreted. The resulting numbers of genes encoding predicted secreted proteisn based on the three methods as well as the majority-decision based method and the result from annotation of the secretome are shown in Table 1. The resulting lists of predicted secreted proteins as well as predicted membrane proteins were used in our classification of the human proteome.

Table 1. Prediction of the human secretome by three different prediction methods for signal peptides as well as the MDSEC and the final prediction resulting from manual annotation.

Expression levels of secreted proteins in tissue

An analysis of tissue distribution categories based on RNA-sequencing data shows that a larger fraction of the genes encoding secreted proteins belongs to the tissue enhanced, tissue enriched or group enriched genes, compared to all genes presented in the Subcellular Section (Uhlén M et al. (2015)) (Figure 3). Only a relatively small portion of the genes in the secretome show low tissue specificity. This is in agreement with the tissue specific functions for many secreted proteins. The secreted class contains many of the most abundantly expressed genes and the highest expression levels of secreted proteins are found in pancreas and salivary gland.

Figure 3. Bar plot showing the percentage of genes in different tissue specificity categories for secreted 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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 

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