ReviewViruses2014
Viruses and tetraspanins: lessons from single molecule approaches.
Review in Viruses, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 19 citations in OpenAlex.
- Article
- Mosquito Exosomal Tetraspanin CD151 Facilitates Flaviviral Transmission and Interacts with ZIKV and DENV2 Viral Proteins.International journal of molecular sciences · 2025Article
- Mechanism and complex roles of HSC70/HSPA8 in viral entry.Virus research · 2024Review
- CD82 and Gangliosides Tune CD81 Membrane Behavior.International journal of molecular sciences · 2021Article
- In silico selection of functionally important proteins from the mialome of Ornithodoros erraticus ticks and assessment of their protective efficacy as vaccine targets.Parasites & vectors · 2019Article
- Biogenesis of Extracellular Vesicles during Herpes Simplex Virus 1 Infection: Role of the CD63 Tetraspanin.Journal of virology · 2019Article
- Uroplakins play conserved roles in egg fertilization and acquired additional urothelial functions during mammalian divergence.Molecular biology of the cell · 2018Article
- Virus Entry: Looking Back and Moving Forward.Journal of molecular biology · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tetraspanins are four-span membrane proteins that are widely distributed in multi-cellular organisms and involved in several infectious diseases. They have the unique property to form a network of protein-protein interaction within the plasma membrane, due to the lateral associations with one another and with other membrane proteins. Tracking tetraspanins at the single molecule level using fluorescence microscopy has revealed the membrane behavior of the tetraspanins CD9 and CD81 in epithelial cell lines, providing a first dynamic view of this network. Single molecule tracking highlighted that these 2 proteins can freely diffuse within the plasma membrane but can also be trapped, permanently or transiently, in tetraspanin-enriched areas. More recently, a similar strategy has been used to investigate tetraspanin membrane behavior in the context of human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) infection. In this review we summarize the main results emphasizing the relationship in terms of membrane partitioning between tetraspanins, some of their partners such as Claudin-1 and EWI-2, and viral proteins during infection. These results will be analyzed in the context of other membrane microdomains, stressing the difference between raft and tetraspanin-enriched microdomains, but also in comparison with virus diffusion at the cell surface. New advanced single molecule techniques that could help to further explore tetraspanin assemblies will be also discussed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.