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PXD073836
PXD073836 is an original dataset announced via ProteomeXchange.
Dataset Summary
| Title | A multi-omics approach reveals specific oncogenic and inflammatory potential of viral oncoproteins Tax from neglected HTLV-1b and -1c genotypes |
| Description | Over the recent years, there has been a renewed interest in the genetic variability of the human oncogenic retrovirus HTLV-1 (Human T-cell Leukemia Virus type 1), following reports of high prevalences of infection with HTLV-1 genotype c in remote aboriginal populations in Central Australia, and acknowledgment of the remarkably high genetic diversity of HTLV-1 in Central Africa. While clinical and epidemiological studies suggest that HTLV-1 genotypes might be associated with varying risks of pathological manifestations, molecular comparisons of the viral determinants among genotypes remain scarce. In this study, we provide the first comprehensive comparative analysis of the major oncoprotein Tax1 from genotypes a (Japanese), b (African) and c (Australo-Melanesia). Using unbiased analysis of image cytometry data from Tax1-expressing Jurkat T-cells, combined with proximity interactomics, we first show that Tax1 variants exhibit distinct subcellular localization in T-cells. Indeed, in contrast to Tax1a that assembles a NF-kB-activating signalosome at the surface of the Golgi apparatus, Tax1c lacks any significant association with this cell compartment. Surprisingly however, Tax1c does not show any general defect in NF-kB activation compared to Tax1a and Tax1b. Instead, transcriptomics analysis combined with pathway inference indicate that the quality of the NF-kB signature induced by Tax1c differs from that of Tax1a, and that the transcriptional landscape of Tax1c-expressing cells is biased towards T-cell activation and inflammation, an observation that is consistent with the kinome profiling of Tax1c-expressing cells. Analysis of Tax1b-induced transcriptional modulation revealed that it closely parallels that of Tax1a, but with an overall higher magnitude. In addition, distinct modulation of cell cycle-related kinase activity by Tax1b compared to Tax1a was correlated with a specific modulation of the cell cycle. Consistently, functional cell transformation assays demonstrated that Tax1b presents a higher oncogenic potential compared to Tax1a, while Tax1c harbours a decreased transforming activity. Altogether, we provide evidence of functional divergence among Tax1 from different genotypes that may have pathophysiological and clinical implications. |
| HostingRepository | MassIVE |
| AnnounceDate | 2026-08-16 |
| AnnouncementXML | Submission_2026-08-16_23:53:43.944.xml |
| DigitalObjectIdentifier | |
| ReviewLevel | Non peer-reviewed dataset |
| DatasetOrigin | Original dataset |
| RepositorySupport | Supported dataset by repository |
| PrimarySubmitter | Page |
| SpeciesList | scientific name: Homo sapiens; common name: human; NCBI TaxID: 9606; scientific name: HTLV-1 subtype A; NCBI TaxID: 402042; scientific name: HTLV-1 subtype B; NCBI TaxID: 402043; scientific name: HTLV-1 subtype C; NCBI TaxID: 402044; |
| ModificationList | Oxidation; Biotin |
| Instrument | Q Exactive HF |
Dataset History
| Revision | Datetime | Status | ChangeLog Entry |
|---|---|---|---|
| 0 | 2026-01-30 02:01:21 | ID requested | |
| ⏵ 1 | 2026-08-16 23:53:44 | announced |
Publication List
| no publication |
Keyword List
| submitter keyword: HTLV, Tax, BioID2, proximity interactomics, DatasetType:Proteomics |
Contact List
| Chloe Journo | |
|---|---|
| contact affiliation | ENS de Lyon |
| contact email | chloe.journo@ens-lyon.fr |
| lab head | |
| Page | |
| contact affiliation | CNRS |
| contact email | adeline.page@ibcp.fr |
| dataset submitter | |
Full Dataset Link List
| MassIVE dataset URI |
| Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://massive-ftp.ucsd.edu/v12/MSV000100656/ |




