High-level erythroid-specific gene expression in primary human and murine hematopoietic cells with self-inactivating lentiviral vectors
Bibliographic record
Abstract
Use of oncoretroviral vectors in gene therapy for hemoglobinopathies has been impeded by low titer vectors, genetic instability, and poor expression. Fifteen self- inactivating (SIN) lentiviral vectors using 4 erythroid promoters in combination with 4 erythroid enhancers with or without the woodchuck hepatitis virus postregulatory element (WPRE) were generated using the enhanced green fluorescent protein as a reporter gene. Vectors with high erythroid-specific expression in cell lines were tested in primary human CD34(+) cells and in vivo in the murine bone marrow (BM) transplantation model. Vectors containing the ankyrin-1 promoter showed high-level expression and stable proviral transmission. Two vectors containing the ankyrin-1 promoter and 2 erythroid enhancers (HS-40 plus GATA-1 or HS-40 plus 5-aminolevulinate synthase intron 8 [I8] enhancers) and WPRE expressed at levels higher than the HS2/beta-promoter vector in bulk unilineage erythroid cultures and individual erythroid blast-forming units derived from human BM CD34(+) cells. Sca1(+)/lineage(-) Ly5.1 mouse hematopoietic cells, transduced with these 2 ankyrin-1 promoter vectors, were injected into lethally irradiated Ly5.2 recipients. Eleven weeks after transplantation, high-level expression was seen from both vectors in blood (63%-89% of red blood cells) and erythroid cells in BM (70%-86% engraftment), compared with negligible expression in myeloid and lymphoid lineages in blood, BM, spleen, and thymus (0%-4%). The I8/HS-40-containing vector encoding a hybrid human beta/gamma-globin gene led to 43% to 113% human gamma-globin expression/copy of the mouse alpha-globin gene. Thus, modular use of erythroid-specific enhancers/promoters and WPRE in SIN-lentiviral vectors led to identification of high-titer, stably transmitted vectors with high-level erythroid-specific expression for gene therapy of red cell diseases.
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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 | 0.001 | 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 | 0.001 | 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".