Opposing roles of CLK SR kinases in controlling HIV-1 gene expression and latency
Bibliographic record
Abstract
Abstract Background The generation of over 69 spliced HIV-1 mRNAs from one primary transcript by alternative RNA splicing emphasizes the central role that RNA processing plays in HIV-1 replication. Control is mediated in part through the action of host SR proteins whose activity is regulated by multiple SR kinases (CLK1-4, SRPKs). Methods Both shRNA depletion and small molecule inhibitors of host SR kinases were used in T cell lines and primary cells to evaluate the role of these factors in the regulation of HIV-1 gene expression. Effects on virus expression were assessed using western blotting, RT-qPCR, and immunofluorescence. Results The studies demonstrate that SR kinases play distinct roles; depletion of CLK1 enhanced HIV-1 gene expression, reduction of CLK2 or SRPK1 suppressed it, whereas CLK3 depletion had a modest impact. The opposing effects of CLK1 vs. CLK2 depletion were due to action at distinct steps; reduction of CLK1 increased HIV-1 promoter activity while depletion of CLK2 affected steps after transcript initiation. Reduced CLK1 expression also enhanced the response to several latency reversing agents, in part, by increasing the frequency of responding cells, consistent with a role in regulating provirus latency. To determine whether small molecule modulation of SR kinase function could be used to control HIV-1 replication, we screened a GSK library of protein kinase inhibitors (PKIS) and identified several pyrazolo[1,5-b] pyridazine derivatives that suppress HIV-1 gene expression/replication with an EC 50 ~ 50 nM. The compounds suppressed HIV-1 protein and viral RNA accumulation with minimal impact on cell viability, inhibiting CLK1 and CLK2 but not CLK3 function, thereby selectively altering the abundance of individual CLK and SR proteins in cells. Conclusions These findings demonstrate the unique roles played by individual SR kinases in regulating HIV-1 gene expression, validating the targeting of these functions to either enhance latency reversal, essential for “Kick-and-Kill” strategies, or to silence HIV protein expression for “Block-and-Lock” strategies.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; a candidate call from one teacher head, not a consensus.
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".