Transient Replication of Hepatitis C Virus Sub-Genomic RNA in Murine Cell Lines Is Enabled by miR-122 and Varies with Cell Passage
Bibliographic record
Abstract
Hepatitis C Virus (HCV) is a serious global health problem, infecting almost 3% of the world's population. The lack of model systems for studying this virus limit research options in vaccine and therapeutic development, as well as for studying the pathogenesis of chronic HCV infection. Herein we make use of the liver-specific microRNA miR-122 to render mouse cell lines permissive to HCV replication in an attempt to develop additional model systems for the identification of new features of the virus and its life cycle. We have determined that some wild-type and knockout mouse cell lines--NCoA6 and PKR knockout embryonic fibroblasts--can be rendered permissive to transient HCV sub-genomic RNA replication upon addition of miR-122, but we did not observe replication of full-length HCV RNA in these cells. However, other wild-type and knockout cell lines cannot be rendered permissive to HCV replication by addition of miR-122, and in fact, different NCoA6 and PKR knockout cell line passages and isolates from the same mice demonstrated varying permissiveness phenotypes and eventually complete loss of permissiveness. When we tested knockdown of NCoA6 and PKR in Huh7.5 cells, we saw no substantial impact in sub-genomic HCV replication, which we would expect if these genes were inhibitory to the virus' life cycle. This leads us to conclude that along with the influence of specific gene knockouts there are additional factors within the cell lines that affect their permissiveness for HCV replication; we suggest that these may be epigenetically regulated, or modulated by cell line immortalization and transformation.
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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".