Dominant negative effect of wild-type NS5A on NS5A-adapted subgenomic hepatitis C virus RNA replicon is a research paper published in Journal of General Virology (2004). On theSindex it has a DataRank of 1.1. It has been cited 12 times, with 12 citing works in its 1-hop citation network.
An efficient model is currently used to study hepatitis C virus (HCV) replication in cell culture. It involves transfection in Huh7, a hepatoma-derived cell line, of an antibiotic (neomycin) selectable HCV subgenomic replicon encoding the non-structural (NS) proteins from NS3 to NS5B. However, strong and sustained replication is achieved only on the appearance of adaptive mutations in viral proteins. The most effective of these adaptive mutations are concentrated mainly in NS5A, not only into the original Con1 but also in the recently established HCV-BK and HCV-H77 isolate-derived replicons. This suggests that the expression of wild-type (wt) NS5A may not allow efficient HCV RNA replication in cell culture. With the use of a β-lactamase reporter gene as a marker for HCV replication and TaqMan RNA analysis, the replication of different HCV replicons in cotransfection experiments was investigated. Comparing wt with NS5A-adapted replicons, the strong evidence accumulated showed that the expression of wt NS5A was actually able to inhibit the replication of NS5A-adapted replicons. This feature was characterized as a dominant negative effect. Interestingly, an NS5B (R2884G)-adapted replicon, containing a wt NS5A, was dominant negative on an NS5A-adapted replicon but was not inhibited by the original Con1 replicon. In conclusion, these studies revealed that the original wt Con1 replicon is not only incompetent for replication in cell culture, but is also able to interfere with NS5A-adapted replicons.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.385
From this paper's citation signal
Citation Network Contribution
0.740
From 12 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 34% comes from its base citations and 66% from the citation network (12 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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