Cytosol
The cytosol is a semi-fluid substance filling the interior of the cell and embedding the other organelles and subcellular compartments (Clegg JS. (1984)). The cytosol itself is enclosed by the cell membrane and the membranes of different organelles, thus making up a separate cellular compartment. Together, the cytosol and all organelles, except for the nucleus, make up the cytoplasm. Example images of proteins localized to the cytosol can be seen in Figure 1.
In the subcellular section, 4957 genes (25% of all protein-coding human genes) have been shown to encode proteins that localize to the cytosol and its substructures (Figure 2). A Gene Ontology (GO)-based functional enrichment analysis of genes encoding cytosolic proteins shows enrichment of genes associated with bological processes related to protein modifications, mRNA degradation, metabolic processes, signal transduction, and cell death. About 79% (n=3937) of the cytosolic proteins localize to other cellular compartments in addition to the cytosol. The most common additional locations are the nucleus and the plasma membrane.
G3BP1 - U-251MG
QARS1 - U2OS
MTHFS - U2OS
Figure 1. Examples of proteins localized to the cytosol. G3BP1 is an enzyme localized in the cytosol and plays a role in signal transduction (detected in U-251 MG cells). QARS1 catalyzes the aminoacylation of tRNA by their associated amino acid (detected in U2OS cells). MTHFS is an enzyme involved in metabolic processes (detected in U2OS cells).
- 25% (4957 proteins) of all human proteins have been experimentally detected in the cytosol by the Human Protein Atlas.
- 1786 proteins in the cytosol are supported by experimental evidence and out of these 319 proteins are enhanced by the Human Protein Atlas.
- 3937 proteins in the cytosol have multiple locations.
- 694 proteins in the cytosol show single cell variation.
- Cytosolic proteins are mainly involved in protein modification, mRNA degradation, metabolic processes, signal transduction, and cell death.
Figure 2. 25% of all human protein-coding genes encode proteins localized to the cytosol. Each bar is clickable and gives a search result of proteins that belong to the selected category.
Composition of the cytosol
Substructures
- Aggresome: 19
- Cytosol: 4883
- Cytoplasmic bodies: 73
- Rods & Rings: 20
The cytosol makes up about 70% of the total volume of human cells, and is highly crowded and complex (
Luby-Phelps K. (2013)). The cytosol is mainly composed of water (approximately 70% of the volume) and proteins (20-30% of the volume) (
Luby-Phelps K. (2000);
Ellis RJ. (2001)). Rather than a liquid, it is often described as a hydrophilic jelly-like matrix that allows for free movement of ions, hydrophilic molecules and proteins, but also larger structures such as protein complexes and vesicles, across the cell. Ions such as potassium, sodium, bicarbonate, chloride, calcium, magnesium and amino acids are also important constitues of the cytosol. The differences in concentration of these ions between the cytosol and the extracellular fluid or cytoplamic organelles are essential for many cellular functions, for example to enable cell-to-cell communication at the synapses of nerve cells. The cytosolic pH of human cells ranges between 7.0 - 7.4 and is usually higher if the cell is growing (
Bright GR et al. (1987)).
Example images of the protein coded by MTHFD1 stained in 3 different cell lines can be seen in Figure 3.
MTHFD1 - A-431
MTHFD1 - U-251MG
MTHFD1 - U2OS
Figure 3. Examples of the morphology of the cytosol in different cell lines, represented by immunofluorescent staining of protein MTHFD1 in A-431, U-251 MG and U2OS cells.
The cytosol also contains different non-membrane bound structures, including cytoplasmic inclusions, such as glycogen-, pigment- and crystalline inclusions, and cytoplasmic bodies, such as P-bodies and stress granules. Aggresomes are large inclusion bodies formed upon active retrograde transport of misfolded proteins along microtubules (Kopito RR. (2000)). This sequestration of aggregated proteins that fail to be cleared by proteosomal degradation has a cytoprotective function. P-bodies are non-membrane bound foci of mRNA and proteins that function in RNA turnover, translational repression, RNA-mediated silencing, and RNA storage (Aizer A et al. (2008)). A rare, and rather recently discovered structure that can appear in the cytosol are Rods and Rings (RRs). These are filament-like structures containing proteins involved in the biosynthesis of nucleotides, originally discovered by the use of human autoantibodies, but little is known about their biological function (Carcamo WC et al. (2014)).
A selection of proteins suitable to be used as markers for the cytosol is listed in Table 1.
Table 1. Selection of proteins suitable as markers for the cytosol.
Gene |
Description |
Substructure |
ADSL
|
Adenylosuccinate lyase |
Cytosol |
ATXN2
|
Ataxin 2 |
Cytosol |
G3BP2
|
G3BP stress granule assembly factor 2 |
Cytosol |
AIMP1
|
Aminoacyl tRNA synthetase complex interacting multifunctional protein 1 |
Cytosol |
SERBP1
|
SERPINE1 mRNA binding protein 1 |
Cytosol |
CCDC43
|
Coiled-coil domain containing 43 |
Cytosol |
ATXN2L
|
Ataxin 2 like |
Cytosol |
AMPD2
|
Adenosine monophosphate deaminase 2 |
Cytosol |
RABGAP1
|
RAB GTPase activating protein 1 |
Cytosol |
Function of the cytosol
The cytosol has an important role in providing structural support for other organelles and in allowing transport of molecules across the cell. For example, metabolites often need to be transported across the cytosol from the area of their production to the site where they are needed, and various signals need to be transduced from the cell membrane to target compartments. Moreover, many important cellular processes and reactions, especially of metabolic character, occur in the cytosol. These processes include protein synthesis through translation, the first stage of cellular respiration through glycolysis, and cell division through mitosis and meiosis. The cytosol also plays a pivotal role in maintaining gradients across the membranes, which is important for cell signaling, osmosis and cellular excitability (Lang F. (2007)).
A list of highly expressed cytosolic proteins is summarized in Table 2. Gene Ontology (GO)-based analysis of the cytosolic proteome shows enrichment of terms that are well in-line with the known functions of the cytosol. The most highly enriched terms for the GO domain Biological Process are related to translation, post-translational modifications, metabolic pathways, signaling pathways, and apoptosis (Figure 4a). Enrichment analysis of the GO domain Molecular Function also shows significant enrichment for terms related to translation, protein metabolism and protein interactions (Figure 4b).
Figure 4a. Gene Ontology-based enrichment analysis for the cytosol 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 4b. Gene Ontology-based enrichment analysis for the cytosol 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.
Table 2. Highly expressed single localizing cytosolic proteins across different cell lines.
Gene |
Description |
Average nTPM |
RPS18
|
Ribosomal protein S18 |
5997 |
TPT1
|
Tumor protein, translationally-controlled 1 |
3949 |
RPL23
|
Ribosomal protein L23 |
2658 |
LGALS1
|
Galectin 1 |
2035 |
PKM
|
Pyruvate kinase M1/2 |
1703 |
HSP90AB1
|
Heat shock protein 90 alpha family class B member 1 |
1534 |
LDHB
|
Lactate dehydrogenase B |
1389 |
HSP90AA1
|
Heat shock protein 90 alpha family class A member 1 |
1260 |
BTF3
|
Basic transcription factor 3 |
1062 |
RPL36
|
Ribosomal protein L36 |
1060 |
Cytosolic proteins with multiple locations
Approximately 79% (n=3937) of the cytosolic proteins detected in the subcellular section also localize to other cellular compartments (Figure 5). The network plot shows that the most common compartments sharing proteins with the cytosol are the nucleus and the plasma membrane, and that these dual localizations are overrepresented. Indeed, there are many proteins known to be transported, or to continuously shuttle, between the cytosol and these compartments, including transcription factors, ribosomal proteins and signaling molecules. Examples of multilocalizing proteins within the cytosolic proteome can be seen in Figure 6.
Figure 5. Interactive network plot of the cytosol proteins with multiple localizations. The numbers in the connecting nodes show the proteins that are localized to the cytosol and to one or more additional locations. Only connecting nodes containing more than one protein and at least 0.7% of proteins in the cytosolic 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.
RPL10A - U2OS
STAT5A - A-431
DDX55 - A-431
Figure 6. Examples of multilocalizing proteins in the cytosolic proteome. RPL10A is a known ribosomal protein, which is required for formation of the 60S ribosomal subunits. It has been shown to localize both to the nucleoli and the cytosol (detected in U2OS cells). STAT5A belongs to the family of STAT transcription factors. It translocates from the cytosol into the nucleus in response to phosphorylation (detected in A-431 cells). DDX55 is a member of DEAD box protein family implicated in several cellular processes involving alteration of RNA secondary structure. It has been shown to localize to the nucleus, nucleoli and cytosol (detected in A-431 cells).
Expression levels of cytosol proteins in tissue
Transcriptome analysis and classification of genes into tissue distribution categories (Figure 8) shows that genes encoding proteins localizing to the cytosol and its substructures have a similar distribution as all genes in the subcellular section, but with a slightly larger fraction of genes expressed in all tissues, and a slightly smaller fraction of genes expressed in many or some tissues.
Figure 7. Bar plot showing the percentage of genes in different tissue distribution categories for cytosol-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
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
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
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 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
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
Ulrich ND et al., Cellular heterogeneity of human fallopian tubes in normal and hydrosalpinx disease states identified using scRNA-seq. Dev Cell. (2022)
PubMed: 35320732 DOI: 10.1016/j.devcel.2022.02.017
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
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
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
Wagner M et al., Single-cell analysis of human ovarian cortex identifies distinct cell populations but no oogonial stem cells. Nat Commun. (2020)
PubMed: 32123174 DOI: 10.1038/s41467-020-14936-3
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
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
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
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
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
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
Guo J et al., The adult human testis transcriptional cell atlas. Cell Res. (2018)
PubMed: 30315278 DOI: 10.1038/s41422-018-0099-2
Agaton C et al., Affinity proteomics for systematic protein profiling of chromosome 21 gene products in human tissues. Mol Cell Proteomics. (2003)
PubMed: 12796447 DOI: 10.1074/mcp.M300022-MCP200
Lindskog M et al., Selection of protein epitopes for antibody production Biotechniques (2005)
PubMed: 15945371
Larsson M et al., High-throughput protein expression of cDNA products as a tool in functional genomics. J Biotechnol. (2000)
PubMed: 10908795 DOI: 10.1016/s0168-1656(00)00258-3
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
Fagerberg L et al., Prediction of the human membrane proteome. Proteomics. (2010)
PubMed: 20175080 DOI: 10.1002/pmic.200900258
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
Gilvesy A et al., Spatiotemporal characterization of cellular tau pathology in the human locus coeruleus-pericoerulear complex by three-dimensional imaging. Acta Neuropathol. (2022)
PubMed: 36040521 DOI: 10.1007/s00401-022-02477-6
Jin H et al., Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation. Nat Commun. (2023)
PubMed: 37669926 DOI: 10.1038/s41467-023-41132-w
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
Álvez MB et al., Next generation pan-cancer blood proteome profiling using proximity extension assay. Nat Commun. (2023)
PubMed: 37463882 DOI: 10.1038/s41467-023-39765-y
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
Orchard S et al., The MIntAct project--IntAct as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res. (2014)
PubMed: 24234451 DOI: 10.1093/nar/gkt1115
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
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
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