c-SRC protein tyrosine kinase regulates early HIV-1 infection post-entry
Bibliographic record
Abstract
OBJECTIVE: We investigated whether HIV-1 inhibition by SRC-family kinase inhibitors is through the non-receptor tyrosine kinase pp60 (c-SRC) and its binding partner, protein tyrosine kinase 2 beta (PTK2B). DESIGN: CD4 T-lymphocytes were infected with R5 (JR-FL) or X4 (HXB2) HIV-1. We used SRC-family kinase inhibitors or targeted siRNA knockdown of c-SRC and PTK2B, then monitored effects on the early HIV-1 lifecycle. METHODS: Four SRC-family kinase inhibitors or targeted siRNA knockdown were used to reduce c-SRC or PTK2B protein expression. Activated CD4 T-lymphocytes were infected with recombinant, nef-deficient, or replication-competent infectious viruses. Knockdown experiments examined early infection by monitoring: luciferase activity, expression of host surface receptors, reverse transcriptase activity, p24 levels and qPCR of reverse transcripts, integrated HIV-1, and two-long terminal repeat (2-LTR) circles. RESULTS: All SRC-family kinase inhibitors inhibited R5 and X4 HIV-1 infection. Neither c-SRC nor PTK2B siRNA knockdown had an effect on cell surface receptors (CD4, CXCR4, and CCR5) nor on reverse transcriptase activity. However, using JR-FL both decreased luciferase activity while increasing late reverse transcripts (16-fold) and 2-LTR circles (eight-fold) while also decreasing viral integration (four-fold). With HXB2, c-SRC but not PTK2B siRNA knockdown produced similar results. CONCLUSIONS: Our results suggest c-SRC tyrosine kinase is a major regulator of HIV-1 infection, participating in multiple stages of infection post-entry: Reduced proviral integration with increased 2-LTR circles is reminiscent of integrase inhibitors used in combination antiretroviral therapy. Decreasing c-SRC expression and/or activity provides a new target for antiviral intervention and the potential for repurposing existing FDA-approved kinase inhibitors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".