Endoplasmic reticulum

The endoplasmic reticulum (ER) is a delicate membranous network composed of sheets and tubules that spread throughout the cytoplasm and are contiguous with the nuclear membrane. The expanded surface of the ER membrane as well as the distinct composition of the ER lumen provides a platform for various biochemical reactions, but especially for protein biosynthesis and production of lipids.

In the Cell Atlas, 483 genes (2% of all protein-coding human genes) have been shown to encode proteins that localize to the ER (Figure 2). Around 52% (n=250) of the ER proteins localize to other cellular compartments in addition to the ER, the most common ones being the cytosol and vesicles. A Gene Ontology (GO)-based functional enrichment analysis of the ER proteins shows enriched terms for biological processes related to protein synthesis, protein folding, protein modification, mRNA degradation and metabolic processes. Examples of ER-associated proteins can be found in Figure 1.

ELOVL5 - A-431
STIM1 - A549
VAPA - A-431

Figure 1. Examples of proteins localized to the endoplasmic reticulum. ELOVL5 is an ER membrane protein that catalyzes the first and rate limiting reaction in the elongation of long and very long-chain polyunsaturated fatty acids (detected in A-431 cells). STIM1 is a transmembrane protein that is involved in the regulation of calcium ions (detected in A549 cells). VAPA may regulate the morphology of the ER by interacting with the cytoskeleton (detected in A-431 cells).

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

The structure of the endoplasmic reticulum

LRRC59 - U-2 OS
LRRC59 - U-251 MG
LRRC59 - A-431

Figure 3. Examples of the morphology of the ER in different cell lines, represented by immunofluorescent staining of the protein encoded by LRRC59 in U-2 OS, U-251 MG, and A-431 cells.

The ER is a large and dynamic structure (Schwarz DS et al. (2016), made up of flat cisternal, often stacked sheets, and reticulated tubules, which are mostly connected by three-way junctions, which result in a polygonal pattern. The different membrane-to-lumen ratios in these two domains reflect their different functions. The sheets with their large surface are studded with ribosomes, forming the "rough ER", and is the primary location for translation. In contrast, areas in the tubules are largely devoid of ribosomes, forming the "smooth ER". and is involved in many other functions, depending on cell type. (Friedman JR et al. (2011)). There are also areas that are partially smooth and partially rough, referred to as the transitional ER.

Proteins that are suitable as markers for the ER can be found in Table 1. Highly expressed genes encoding proteins that localize to the ER are listed in Table 2.

Table 1. Selection of proteins suitable as markers for the endoplasmic reticulum.

Table 2. Highly expressed single localizing endoplasmic reticulum proteins across different cell lines.

Figure 4. 3D-view of the ER in U-2 OS,visualized by immunofluorescent staining of HSP90B1. The morphology of the ER in human induced stem cells can be seen in the Allen Cell Explorer.

The function of the endoplasmic reticulum

The ER is known to serve multiple roles in human cells (Schwarz DS et al. (2016). One of the major functions of ER is in translation of mRNA to certain groups of proteins, including secreted proteins and integral membrane proteins, but also some cytosolic proteins. Translation of these proteins is initiated in the cytosol, but the emergence of an N-terminal signal peptide guides the nascent protein and the ribosome to SRP receptors in the rough ER. After docking to the ER, translation continues and the nascent protein gets translocated across the ER membrane through channels referred to as translocons. If a transmembrane domain is present, the protein gets incorporated in the lipid bilayer of the ER. The ER lumen contains proteins that mediate proper protein folding, post-translational modifications and quality control of the newly synthesized proteins. Proteins that are targeted for other parts of the secretory pathway, the plasma membrane or other organelles begin the process of transport from the ER, using exit sites present in the transitional ER.

Only correctly folded proteins are transported out of the ER. Unfolded or misfolded proteins can cause ER stress by accumulating in the lumen. This process activates the unfolded protein response (UPR), which resolves the stress by reducing the overall protein synthesis, increasing the capacity for protein folding, and promoting the removal of misfolded proteins by the ER-associated degradation (ERAD) (Travers KJ et al. (2000)). However, if the stress is not alleviated, it ultimately induces apoptosis. Several pathological processes, especially neurological diseases like Parkinson's- and Alzheimer's disease, have been linked to ER stress and an imbalance in the UPR (Roussel BD et al. (2013)).

The smooth ER contains enzymes involved in carbohydrate metabolism, gluconeogenesis, and lipid biosynthesis. The latter include synthesis of the phospholipids, which are the major lipid components of cellular membranes. In addition, the smooth ER harbours most of the cytochrome P450 enzymes that are involved in metabolism of a variety of endogenous and exogenous toxic compounds (Neve EP et al. (2010)). Moreover, the ER lumen is one of the major storage sites of intracellular calcium ions and maintains the Ca2+ homeostasis by a controlled release and uptake of the ions.

Gene Ontology (GO)-based enrichment analysis of genes encoding proteins that localize to the ER highlight several functions associated with this organelle. The most highly enriched terms for the GO domain Biological Process are related to protein translation, mRNA degradation, biosynthesis of lipids and metabolic processes (Figure 5a). For the GO domain Molecular Function, there is an enrichment of ubiquitin-specific protease activity, which points to the function of the ER in protein degradation, RNA binding, transferase activity and certain enzymatic activities (Figure 5b).

Figure 5a. Gene Ontology-based enrichment analysis for the endoplasmic reticulum 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 endoplasmic reticulum 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.

Endoplasmic reticulum-associated proteins with multiple locations

In the Cell Atlas, approximately 52% (n=250) of the annotated ER proteins also localize to other compartments in the cell. The network plot (Figure 6) shows an overrepresentation for proteins localized to the ER together with vesicles and/or the cytosol. This likely reflects the close connection of the ER and vesicles in the secretory pathway. Similarly, proteins that localize to the cytosol, can interact with the ER as part of certain functions, the most prominent example being the recruitment of ribosomal proteins to the ER during translation of certain groups of proteins. Examples of multilocalizing proteins within the ER proteome can be seen in Figure 7.

Figure 6. Interactive network plot of ER proteins with multiple localizations. The numbers in the connecting nodes show the proteins that are localized to the ER and to one or more additional locations. Only connecting nodes containing more than one protein and at least 0.5% of proteins in the ER 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.

CREB3L2 - U-2 OS
LPCAT2 - A-431
RPL28 - MCF7

Figure 7. Examples for multilocalizing proteins in the endoplasmic reticulum proteome. CREB3L2 is an ER membrane protein, whose cytosolic N-terminal domain is translocated to the nucleus upon ER-stress (detected in U-2 OS cells). LPCAT2 was found in both the ER and lipid droplets. The ER has a direct role in the emergence and regression of lipid droplets and many RPL28 encodes a component of ribosomes and is required for protein biosynthesis in both ER and cytosol (detected in U-2 OS cells).

Expression levels of endoplasmic reticulum proteins in tissue

Transcriptome analysis and classification of genes into tissue distribution categories (Figure 8) shows that genes encoding ER-associated proteins are more likely to be detected in all tissues, and less likely to be detected in a single tissue, compared to all genes presented in the Cell Atlas. This indicates that a large fraction of the ER-associated proteins are likely to fulfill housekeeping functions needed in all tissue types.

Figure 8. Bar plot showing the percentage of genes in different tissue distribution categories for endoplasmic reticulum-associated protein-coding genes, compared to all genes in the Cell Atlas. 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

Parikh K et al., Colonic epithelial cell diversity in health and inflammatory bowel disease. Nature. (2019)
PubMed: 30814735 DOI: 10.1038/s41586-019-0992-y

Menon M et al., Single-cell transcriptomic atlas of the human retina identifies cell types associated with age-related macular degeneration. Nat Commun. (2019)
PubMed: 31653841 DOI: 10.1038/s41467-019-12780-8

Wang L et al., Single-cell reconstruction of the adult human heart during heart failure and recovery reveals the cellular landscape underlying cardiac function. Nat Cell Biol. (2020)
PubMed: 31915373 DOI: 10.1038/s41556-019-0446-7

Wang Y et al., Single-cell transcriptome analysis reveals differential nutrient absorption functions in human intestine. J Exp Med. (2020)
PubMed: 31753849 DOI: 10.1084/jem.20191130

Liao J et al., Single-cell RNA sequencing of human kidney. Sci Data. (2020)
PubMed: 31896769 DOI: 10.1038/s41597-019-0351-8

MacParland SA et al., Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat Commun. (2018)
PubMed: 30348985 DOI: 10.1038/s41467-018-06318-7

Vieira Braga FA et al., A cellular census of human lungs identifies novel cell states in health and in asthma. Nat Med. (2019)
PubMed: 31209336 DOI: 10.1038/s41591-019-0468-5

Vento-Tormo R et al., Single-cell reconstruction of the early maternal-fetal interface in humans. Nature. (2018)
PubMed: 30429548 DOI: 10.1038/s41586-018-0698-6

Qadir MMF et al., Single-cell resolution analysis of the human pancreatic ductal progenitor cell niche. Proc Natl Acad Sci U S A. (2020)
PubMed: 32354994 DOI: 10.1073/pnas.1918314117

Solé-Boldo L et al., Single-cell transcriptomes of the human skin reveal age-related loss of fibroblast priming. Commun Biol. (2020)
PubMed: 32327715 DOI: 10.1038/s42003-020-0922-4

Henry GH et al., A Cellular Anatomy of the Normal Adult Human Prostate and Prostatic Urethra. Cell Rep. (2018)
PubMed: 30566875 DOI: 10.1016/j.celrep.2018.11.086

Chen J et al., PBMC fixation and processing for Chromium single-cell RNA sequencing. J Transl Med. (2018)
PubMed: 30016977 DOI: 10.1186/s12967-018-1578-4

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

Uhlen M et al., A proposal for validation of antibodies. Nat Methods. (2016)
PubMed: 27595404 DOI: 10.1038/nmeth.3995

Stadler C et al., Systematic validation of antibody binding and protein subcellular localization using siRNA and confocal microscopy. J Proteomics. (2012)
PubMed: 22361696 DOI: 10.1016/j.jprot.2012.01.030

Poser I et al., BAC TransgeneOmics: a high-throughput method for exploration of protein function in mammals. Nat Methods. (2008)
PubMed: 18391959 DOI: 10.1038/nmeth.1199

Skogs M et al., Antibody Validation in Bioimaging Applications Based on Endogenous Expression of Tagged Proteins. J Proteome Res. (2017)
PubMed: 27723985 DOI: 10.1021/acs.jproteome.6b00821

Takahashi H et al., 5' end-centered expression profiling using cap-analysis gene expression and next-generation sequencing. Nat Protoc. (2012)
PubMed: 22362160 DOI: 10.1038/nprot.2012.005

Lein ES et al., Genome-wide atlas of gene expression in the adult mouse brain. Nature. (2007)
PubMed: 17151600 DOI: 10.1038/nature05453

Kircher M et al., Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res. (2012)
PubMed: 22021376 DOI: 10.1093/nar/gkr771

Pollard TD et al., Actin, a central player in cell shape and movement. Science. (2009)
PubMed: 19965462 DOI: 10.1126/science.1175862

Mitchison TJ et al., Actin-based cell motility and cell locomotion. Cell. (1996)
PubMed: 8608590 

Pollard TD et al., Molecular Mechanism of Cytokinesis. Annu Rev Biochem. (2019)
PubMed: 30649923 DOI: 10.1146/annurev-biochem-062917-012530

dos Remedios CG et al., Actin binding proteins: regulation of cytoskeletal microfilaments. Physiol Rev. (2003)
PubMed: 12663865 DOI: 10.1152/physrev.00026.2002

Campellone KG et al., A nucleator arms race: cellular control of actin assembly. Nat Rev Mol Cell Biol. (2010)
PubMed: 20237478 DOI: 10.1038/nrm2867

Rottner K et al., Actin assembly mechanisms at a glance. J Cell Sci. (2017)
PubMed: 29032357 DOI: 10.1242/jcs.206433

Bird RP., Observation and quantification of aberrant crypts in the murine colon treated with a colon carcinogen: preliminary findings. Cancer Lett. (1987)
PubMed: 3677050 DOI: 10.1016/0304-3835(87)90157-1

HUXLEY AF et al., Structural changes in muscle during contraction; interference microscopy of living muscle fibres. Nature. (1954)
PubMed: 13165697 

HUXLEY H et al., Changes in the cross-striations of muscle during contraction and stretch and their structural interpretation. Nature. (1954)
PubMed: 13165698 

Svitkina T., The Actin Cytoskeleton and Actin-Based Motility. Cold Spring Harb Perspect Biol. (2018)
PubMed: 29295889 DOI: 10.1101/cshperspect.a018267

Kelpsch DJ et al., Nuclear Actin: From Discovery to Function. Anat Rec (Hoboken). (2018)
PubMed: 30312531 DOI: 10.1002/ar.23959

Malumbres M et al., Cell cycle, CDKs and cancer: a changing paradigm. Nat Rev Cancer. (2009)
PubMed: 19238148 DOI: 10.1038/nrc2602

Massagué J., G1 cell-cycle control and cancer. Nature. (2004)
PubMed: 15549091 DOI: 10.1038/nature03094

Hartwell LH et al., Cell cycle control and cancer. Science. (1994)
PubMed: 7997877 DOI: 10.1126/science.7997877

Barnum KJ et al., Cell cycle regulation by checkpoints. Methods Mol Biol. (2014)
PubMed: 24906307 DOI: 10.1007/978-1-4939-0888-2_2

Weinberg RA., The retinoblastoma protein and cell cycle control. Cell. (1995)
PubMed: 7736585 DOI: 10.1016/0092-8674(95)90385-2

Morgan DO., Principles of CDK regulation. Nature. (1995)
PubMed: 7877684 DOI: 10.1038/374131a0

Teixeira LK et al., Ubiquitin ligases and cell cycle control. Annu Rev Biochem. (2013)
PubMed: 23495935 DOI: 10.1146/annurev-biochem-060410-105307

King RW et al., How proteolysis drives the cell cycle. Science. (1996)
PubMed: 8939846 DOI: 10.1126/science.274.5293.1652

Cho RJ et al., Transcriptional regulation and function during the human cell cycle. Nat Genet. (2001)
PubMed: 11137997 DOI: 10.1038/83751

Whitfield ML et al., Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol Biol Cell. (2002)
PubMed: 12058064 DOI: 10.1091/mbc.02-02-0030.

Boström J et al., Comparative cell cycle transcriptomics reveals synchronization of developmental transcription factor networks in cancer cells. PLoS One. (2017)
PubMed: 29228002 DOI: 10.1371/journal.pone.0188772

Lane KR et al., Cell cycle-regulated protein abundance changes in synchronously proliferating HeLa cells include regulation of pre-mRNA splicing proteins. PLoS One. (2013)
PubMed: 23520512 DOI: 10.1371/journal.pone.0058456

Ohta S et al., The protein composition of mitotic chromosomes determined using multiclassifier combinatorial proteomics. Cell. (2010)
PubMed: 20813266 DOI: 10.1016/j.cell.2010.07.047

Ly T et al., A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells. Elife. (2014)
PubMed: 24596151 DOI: 10.7554/eLife.01630

Pagliuca FW et al., Quantitative proteomics reveals the basis for the biochemical specificity of the cell-cycle machinery. Mol Cell. (2011)
PubMed: 21816347 DOI: 10.1016/j.molcel.2011.05.031

Ly T et al., Proteomic analysis of the response to cell cycle arrests in human myeloid leukemia cells. Elife. (2015)
PubMed: 25555159 DOI: 10.7554/eLife.04534

Dueck H et al., Variation is function: Are single cell differences functionally important?: Testing the hypothesis that single cell variation is required for aggregate function. Bioessays. (2016)
PubMed: 26625861 DOI: 10.1002/bies.201500124

Snijder B et al., Origins of regulated cell-to-cell variability. Nat Rev Mol Cell Biol. (2011)
PubMed: 21224886 DOI: 10.1038/nrm3044

Thul PJ et al., A subcellular map of the human proteome. Science. (2017)
PubMed: 28495876 DOI: 10.1126/science.aal3321

Cooper S et al., Membrane-elution analysis of content of cyclins A, B1, and E during the unperturbed mammalian cell cycle. Cell Div. (2007)
PubMed: 17892542 DOI: 10.1186/1747-1028-2-28

Davis PK et al., Biological methods for cell-cycle synchronization of mammalian cells. Biotechniques. (2001)
PubMed: 11414226 DOI: 10.2144/01306rv01

Domenighetti G et al., Effect of information campaign by the mass media on hysterectomy rates. Lancet. (1988)
PubMed: 2904581 DOI: 10.1016/s0140-6736(88)90943-9

Scialdone A et al., Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods. (2015)
PubMed: 26142758 DOI: 10.1016/j.ymeth.2015.06.021

Sakaue-Sawano A et al., Visualizing spatiotemporal dynamics of multicellular cell-cycle progression. Cell. (2008)
PubMed: 18267078 DOI: 10.1016/j.cell.2007.12.033

Grant GD et al., Identification of cell cycle-regulated genes periodically expressed in U2OS cells and their regulation by FOXM1 and E2F transcription factors. Mol Biol Cell. (2013)
PubMed: 24109597 DOI: 10.1091/mbc.E13-05-0264

Semple JW et al., An essential role for Orc6 in DNA replication through maintenance of pre-replicative complexes. EMBO J. (2006)
PubMed: 17053779 DOI: 10.1038/sj.emboj.7601391

Kilfoil ML et al., Stochastic variation: from single cells to superorganisms. HFSP J. (2009)
PubMed: 20514130 DOI: 10.2976/1.3223356

Ansel J et al., Cell-to-cell stochastic variation in gene expression is a complex genetic trait. PLoS Genet. (2008)
PubMed: 18404214 DOI: 10.1371/journal.pgen.1000049

Colman-Lerner A et al., Regulated cell-to-cell variation in a cell-fate decision system. Nature. (2005)
PubMed: 16170311 DOI: 10.1038/nature03998

Liberali P et al., Single-cell and multivariate approaches in genetic perturbation screens. Nat Rev Genet. (2015)
PubMed: 25446316 DOI: 10.1038/nrg3768

Elowitz MB et al., Stochastic gene expression in a single cell. Science. (2002)
PubMed: 12183631 DOI: 10.1126/science.1070919

Kaern M et al., Stochasticity in gene expression: from theories to phenotypes. Nat Rev Genet. (2005)
PubMed: 15883588 DOI: 10.1038/nrg1615

Bianconi E et al., An estimation of the number of cells in the human body. Ann Hum Biol. (2013)
PubMed: 23829164 DOI: 10.3109/03014460.2013.807878

Malumbres M., Cyclin-dependent kinases. Genome Biol. (2014)
PubMed: 25180339 

Collins K et al., The cell cycle and cancer. Proc Natl Acad Sci U S A. (1997)
PubMed: 9096291 

Zhivotovsky B et al., Cell cycle and cell death in disease: past, present and future. J Intern Med. (2010)
PubMed: 20964732 DOI: 10.1111/j.1365-2796.2010.02282.x

Cho RJ et al., A genome-wide transcriptional analysis of the mitotic cell cycle. Mol Cell. (1998)
PubMed: 9702192 

Spellman PT et al., Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol Biol Cell. (1998)
PubMed: 9843569 

Orlando DA et al., Global control of cell-cycle transcription by coupled CDK and network oscillators. Nature. (2008)
PubMed: 18463633 DOI: 10.1038/nature06955

Rustici G et al., Periodic gene expression program of the fission yeast cell cycle. Nat Genet. (2004)
PubMed: 15195092 DOI: 10.1038/ng1377

Uhlén M et al., Tissue-based map of the human proteome. Science (2015)
PubMed: 25613900 DOI: 10.1126/science.1260419

Nigg EA et al., The centrosome cycle: Centriole biogenesis, duplication and inherent asymmetries. Nat Cell Biol. (2011)
PubMed: 21968988 DOI: 10.1038/ncb2345

Doxsey S., Re-evaluating centrosome function. Nat Rev Mol Cell Biol. (2001)
PubMed: 11533726 DOI: 10.1038/35089575

Bornens M., Centrosome composition and microtubule anchoring mechanisms. Curr Opin Cell Biol. (2002)
PubMed: 11792541 

Conduit PT et al., Centrosome function and assembly in animal cells. Nat Rev Mol Cell Biol. (2015)
PubMed: 26373263 DOI: 10.1038/nrm4062

Tollenaere MA et al., Centriolar satellites: key mediators of centrosome functions. Cell Mol Life Sci. (2015)
PubMed: 25173771 DOI: 10.1007/s00018-014-1711-3

Prosser SL et al., Centriolar satellite biogenesis and function in vertebrate cells. J Cell Sci. (2020)
PubMed: 31896603 DOI: 10.1242/jcs.239566

Rieder CL et al., The centrosome in vertebrates: more than a microtubule-organizing center. Trends Cell Biol. (2001)
PubMed: 11567874 

Badano JL et al., The centrosome in human genetic disease. Nat Rev Genet. (2005)
PubMed: 15738963 DOI: 10.1038/nrg1557

Clegg JS., Properties and metabolism of the aqueous cytoplasm and its boundaries. Am J Physiol. (1984)
PubMed: 6364846 

Luby-Phelps K., The physical chemistry of cytoplasm and its influence on cell function: an update. Mol Biol Cell. (2013)
PubMed: 23989722 DOI: 10.1091/mbc.E12-08-0617

Luby-Phelps K., Cytoarchitecture and physical properties of cytoplasm: volume, viscosity, diffusion, intracellular surface area. Int Rev Cytol. (2000)
PubMed: 10553280 

Ellis RJ., Macromolecular crowding: obvious but underappreciated. Trends Biochem Sci. (2001)
PubMed: 11590012 

Bright GR et al., Fluorescence ratio imaging microscopy: temporal and spatial measurements of cytoplasmic pH. J Cell Biol. (1987)
PubMed: 3558476 

Kopito RR., Aggresomes, inclusion bodies and protein aggregation. Trends Cell Biol. (2000)
PubMed: 11121744 

Aizer A et al., Intracellular trafficking and dynamics of P bodies. Prion. (2008)
PubMed: 19242093 

Carcamo WC et al., Molecular cell biology and immunobiology of mammalian rod/ring structures. Int Rev Cell Mol Biol. (2014)
PubMed: 24411169 DOI: 10.1016/B978-0-12-800097-7.00002-6

Lang F., Mechanisms and significance of cell volume regulation. J Am Coll Nutr. (2007)
PubMed: 17921474 

Schwarz DS et al., The endoplasmic reticulum: structure, function and response to cellular signaling. Cell Mol Life Sci. (2016)
PubMed: 26433683 DOI: 10.1007/s00018-015-2052-6

Friedman JR et al., The ER in 3D: a multifunctional dynamic membrane network. Trends Cell Biol. (2011)
PubMed: 21900009 DOI: 10.1016/j.tcb.2011.07.004

Travers KJ et al., Functional and genomic analyses reveal an essential coordination between the unfolded protein response and ER-associated degradation. Cell. (2000)
PubMed: 10847680 

Roussel BD et al., Endoplasmic reticulum dysfunction in neurological disease. Lancet Neurol. (2013)
PubMed: 23237905 DOI: 10.1016/S1474-4422(12)70238-7

Neve EP et al., Cytochrome P450 proteins: retention and distribution from the endoplasmic reticulum. Curr Opin Drug Discov Devel. (2010)
PubMed: 20047148