HTLV-1 HBZ protein inhibits IRF3-mediated innate immune responses
Bibliographic record
Abstract
The bZIP factor (HBZ) is an HTLV-1 regulatory protein encoded by anti-sense transcription of the HTLV-1 genome. HBZ mRNA expression correlates with clinical disability in HAM/TSP patients – and can be reversed by interferon (IFN) therapy. Sporadic evidence suggests that HBZ may have a negative role on interferon signalling. Activation of IRF3-dependent IFN signalling – either direct induction of IFNβ, viral restriction factors or interferon stimulated genes (ISGs) – is crucial for TLR and RLR mediated antiviral response. Thus, we sought to determine whether HBZ can impair IRF3-mediated innate immune responses. Over-expression of active forms of RIG-I, MAVS, TBK1, IKKe or IRF3 alone drive an antiviral response – however, in the presence of an HBZ expression vector, IFNβ responses were abrogated by 50-70%. In contrast, HBZ enhanced IRF7-dependent responses. In confirmation, both PBMC and human astrocytes transfected with HBZ and subsequently stimulated with IFN-triggering ligands (LPS, PolyI:C, VSV, Sendai virus and HTLV-1 virions), exhibited impaired IRF3-dependent signalling as compared with controls. As IRF3 is known to bind other bZIP proteins, further studies are underway to delineate the nature of IRF-HBZ interactions. Identifying such a mechanism may explain an enhanced risk of neurologic infection, as we show that chronically HTLV-1 infected astrocytes gradually increase and maintain long-term HBZ expression. Defining the immunomodulatory properties of HTLV-1 HBZ protein will provide a vital contribution toward understanding clinical outcome and risk of opportunistic infection associated with HTLV-1 infection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".